Monsoons - AGU Publications - Wiley

JOURNAL OF GEOPHYSICAL

RESEARCH, VOL. 103, NO. C7, PAGES 14,451-14,510, JUNE 29, 1998

Monsoons: Processes,predictability, and the prospects for prediction P. J. Webster, • V. O. Magafia, 2 T. N. Palmer, 3 J. Shukla, 4 R. A. Tomas, • M. Yanai,5 and T. Yasunari 6 Abstract. The Tropical Ocean-GlobalAtmosphere(TOGA) program soughtto determine the predictabilityof the coupled ocean-atmosphere system. The World Climate Research Programme's(WCRP) Global Ocean-Atmosphere-Land System(GOALS) program seeksto explore predictabilityof the global climate systemthroughinvestigationof the major planetary heat sourcesand sinks, and interactionsbetweenthem. The Asian-Australianmonsoonsystem, which undergoesaperiodicand high amplitudevariationson intraseasonal, annual,biennialand interannualtimescalesis a major focusof GOALS. Empiricalseasonalforecastsof the monsoon have been made with moderatesuccessfor over 100 years. More recentmodelingeffortshave not been successful.Even simulationof the mean structureof the Asian monsoonhas proven elusiveand the observedENSO-monsoonrelationships hasbeendifficultto replicate.Divergence in simulationskill occursbetweenintegrationsby different models or betweenmembersof ensemblesof the samemodel. This degreeof spreadis surprisinggiven the relative successof empiricalforecasttechniques.Two possibleexplanationsare presented:difficulty in modeling the monsoonregionsand nonlinearerror growth due to regionalhydrodynamicalinstabilities. It is arguedthat the reconciliationof theseexplanationsis imperativefor predictionof the monsoonto be improved. To this end, a thoroughdescriptionof observedmonsoonvariability and the physicalprocessesthat are thoughtto be importantis presented.Prospectsof improving predictionand somestrategiesthat may help achieveimprovementare discussed. 1.

Introduction

tor towardthe summercontinents,pickingup moisturefrom the

The annualcycle of the monsoonsystemshas led the inhabitants of monsoonregions to divide their lives, customs,and economiesinto two distinctphases:the "wet" andthe "dry." The wet phaserefers to the rainy seasonduring which warm, moist, and very disturbedwinds blow inland from the warm tropical oceans.The dry phaserefersto the otherhalf of the year when windsbring cool and dry air from the winter continents.This distinctvariationof the annualcycle occursover Asia, Australia, west Africa, and in the Americas. In somelocations(e.g., in the Asia-Australiasector)the dry winter air flows acrossthe equa-

warm tropical oceansto becomethe wet monsoonof the summer

continent.In this manner,the dry of the wintermonsoonis tied to the wet of the summermonsoonand vice versa. In contrast, regionscloserto the equatorpossess two rainy seasons.For ex-

ample,in equatorialeastAfrica, the two rainy seasonsoccurin March to May and Septemberto Decemberand fall betweenthe two African monsoon circulations.

These are referred to as the

"long" and "short"rains, respectively.Agrarian-basedsocieties havedevelopedin the monsoonregionsbecauseof abundantsolar radiationand precipitation,two essentialingredientsfor successful agriculture. Agriculturalpracticeshave traditionallybeen tied strictlyto the annualcycle. Whereasthe regularityof the warm and moist •Program in Atmospheric andOceanic Sciences, University of and cool and dry phasesof the monsoonwould seemto be ideal Colorado, Boulder. for agriculturalsocieties,their very regularitymakesagriculture 2Center forAtmospheric Sciences, National Autonomous Uni- susceptibleto small changesin the annual cycle. Small variationsin the timing and quantityof rainfallhavethe potentialfor versity of Mexico, Mexico City. 3European Centerfor Medium-Range WeatherForecasts,significantsocietalconsequences.A weak monsoonyear (i.e., significantly lesstotalrainfallthannormal)generallycorresponds Reading, England, United Kingdom. to low crop yields. A strongmonsoonusuallyproducesabun4Centerfor Ocean-Land-Atmopshere Studies,Calverton, dant crops,althoughtoo muchrainfall may producedevastating Maryland. floods.In additionto the importanceof the strengthof the overall 5Department of Atmospheric Sciences, University of Califor- monsoonin a particularyear, forecastingthe onsetof the subseania, Los Angeles. sonalvariability(e.g., the activeperiodsandthe lulls or breaksin 6Institute of Geosciences, University of Tsukuba, Tsukuba,between)is of particularimportance.A late or early onsetof the Japan. monsoonor an ill-timed lull in the monsoonrainsmay havedevastatingeffectson agricultureeven if the mean annualrainfall is Copyright1998by theAmericanGeophysical Union. normal.As a result,forecasting monsoonvariabilityon timescales rangingfrom weeksto yearsis an issueof considerable urgency. Papernumber97JC02719. The variationof Indian rice productionin time illustratesthe 0148-0227/98/97JC-02719509.00 pointsmadein the lastparagraph.Figure1a plotsthericeproduc14,451

14,452

WEBSTER ET AL.: MONSOON PREDICTABILITY AND PREDICTION

Indian Rice Production & Rainfall 160

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as functionsof their percentdeviationsfrom the mean. The correlationbetweenthe two time seriesis 0.61. All E1 Nifio years (solid triangles)fall in the negativequadrantwhile all La Nifia years(solidsquares) lie in thepositivequadrant.Finally,therelationshipbetweenthe precedingwinterSouthernOscillationindex (SOI) (the pressuredifferencebetweenTahiti and Darwin, e.g., Trenberth,[1975]) and the AIRI is plotted in Figure l d. Generally, warm eventsin the tropicsare associatedwith deficient rainfall while cold eventsappearrelatedto abundantrainfall. The relationshipbetweenthe stateof E1 Nino-SouthernOscillation (ENSO) and the Indian rice yield suggesta numberof questions. 1. Althoughthe relationshipbetweenENSO and Indian rice yield is not perfect,thereis a tantalizingconnectionsuggesting that the macroscalevariationsin the climate systeminfluence variability on the scale of India and southAsia. How is this connectionmanifestedin the physicalsystem? 2. Doesthe relativevagueness of the ENSO andcropproduc.................. v ................................. variability'-•' ,.,,e rainfallwithina particularsummerrelativeto ploughing,planting, and harvesting(e.g., the timing of the onsetof the monsoonand when the first break in the monsoon occurs) also has influence

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In the precedingdiscussion,Indian crop productionhas been usedas an exampleof the importanceof determininghow climate variability on the macroscaleinfluencesthe local scale. The Figure 1. Exampleof theimpactof largescaleclimatecontrols questionsraisedaboveare commonfor the monsoonregionsof Year

on the agriculture of a monsoonregion. (a) AnnualIndianrice Australia, Africa, and the Americas. production from 1960through1996relativeto 1978(100 units). The shaded and dashed bars refer to Pacific Ocean E1 Nifio and

1.1.

TOGA

and Monsoons

La Nifiayears,respectively. Riceshowsa steadygrowththrough the periodbut is markedby year-to-yeardeviationsbetween+

The TropicalOcean-GlobalAtmosphere(TOGA) programwas basedon the assumption that the major climaticmemoryon the 10-20%. (b) All-India RainfallIndex (AIRI) (in millimeters)detimescalesof monthsto yearsis locatedin the tropicaloceans. finedby MooleyandParthasarathy [1984] for the sameperiod. TOGA had the following very specificgoals and scientificobNote that the variationsin AIRI match the levels of rice projectives WorldClimateResearchProgram (WCRP), [ 1985]: (1) duction. (c) DetrendedIndian rice productionversusAIRI in gain a descriptionof the tropicaloceansand the globalatmosterms of deviationsfrom the mean. A moderatelystrongrelaphereas a time-dependent systemin orderto determinethe extionship(correlation 0.61) existsbetweenthe two indices,with tent to which the systemis predictableon timescalesof months E1Nifio seasons (solidtriangles)corresponding to low yield and to yearsand to understand the mechanisms and processes underlow rainfall. La Nifia years(solid squares),on the otherhand, lying its predictability;(2) studythe feasibilityof modelingthe are generallyassociated with high yield and high rainfall. (d) coupledocean-atmosphere systemfor thepurposeof predicting its Relationship betweenthe SouthernOscillationIndex duringthe variationson timescalesof monthsto years;and (3) providethe previouswinterandthe rainfalloverIndia duringthe following scientificbackgroundfor designingan observingand datatranssummer.In general,PacificOceanwarmeventsare associated missionsystemfor operationalprediction,if this capabilityis with decreased precipitation overIndia while coldeventsare asdemonstrated, by coupledocean-atmosphere models.The extent sociated with enhanced rainfall. to which thesegoalshavebeenrealizedis discussed in National Research Council (NRC) [1996]

tionin Indiabetween1960and 1996. Figure1b plotstheall-India rainfall index (AIR) (adaptedfrom Mooley and Parthasarathy [1984]). The AIRI is a measureof the total summerrainfall over India. The relationshipbetweencrop yield and the AIRI wasfirstnotedby Parthasarathy et al. [1988] andextended by Gadgil[1996]. Figuresla and lb providean updatedversionof this relationship.In general,rice productionhas increasedlinearlyduringthelastfew decades.Superimposed on thistrendare variationsin crop productionof the orderof + 15-20%. Some periodsof production deficitare associated with E1Nifio yearsin

To a large degree,emphasiswithin TOGA has beendirected towardthe physicalprocesses occurringwithinthe PacificOcean basin,a focuswhichhasled to the identificationof basicprocesses which controlthe longer-termaspectsof the ENSO. Theoriesof ENSO fall into two basic classes' (1) the coupledsystemis a laggedoscillator[e.g.,AndersonandMcCreary,1985,Schopfand

Suarez, 1988; Cane and Zebiak, 1985' Battisti, 1988' McCreary andAnderson,1991] or (2) the modulationis the resultof unstable modes[e.g., Neelin, 1988; Battistiand Hirst, 1989]. The extent of our understanding of ENSO is illustratedby the moderately the Pacific Ocean (shadedbars) while some abundantyears are successfulforecastsof the coupledocean-atmosphere systemin associated with La Nifia, or "cold"eventsin the Pacific(diagonal the Pacific Ocean [e.g., Zebiak and Cane, 1987; Cane et al., bars).Figurel c is a scatterplot of the AIRI andcropproduction 1986; Latif and Graham, 1991]. So far, the modelsused in

WEBSTER ET AL.' MONSOON PREDICTABILITY AND PREDICTION

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these endeavorshave been relatively simple, and their success sinks,principallyassociated with the desertsandthe subtropical has allowedCane [1991, p. 363] to makethe followingclaim: oceanregions,retain their geographicpositionsthroughoutthe year. Since motionsare driven by gradientsof heating(i.e., The degreeof forecastingskill obtaineddespitethe crudeness of the the horizontaldifferencesof heatingbetweenthe heat sources model is telling. It suggests that the mechanismresponsible for the generationof E1 Nifio eventsand, by extension,the entire ENSO and sinks)and not the absolutemagnitudesof the sourcesand cycle,is large-scale,robustand simple:if it were complex,delicate sinksthemselves, the heatsinksare integralpartsof the monsoon or dependenton small scaledetails,this model would not succeed.

Many coupledocean-atmosphere modelsshowENSO-like variationsand supportrationaltheoriesinvolvingthe joint interaction of the oceanand the atmosphere.There can be little doubtthat the modelsdo take into accountfundamentalphysicalprocesses. Despite the importanceof the ENSO phenomenonin climate variabilityon seasonal-to-interannual timescales, ENSO doesnot explain all of the variance. Furthermore,the forecastsof ENSO appearto have a distinctseasonality,suchthat error growthhas a specificannualcycle [e.g., Websterand Yang,1992; Webster, 1995; Balrnasedaet al., 1995; Torrenceand Webster,1998]. Such variability may be causedby climatic featuresexternalto the Pacific basin. Although the heat source associatedwith the westernPacific warm pool is a critical element of the global climate and has a distinctinfluenceon the global climate [e.g., Palmer and MansfieM,1984], it is not the only regionof intense atmosphericheating. This may be seenfrom Figure 2, which showsthe annualcycle of outgoinglongwaveradiation(OLR) as determined from satellite. The shaded areas show OLR < 220 W

system.

While the scientificobjectivesof TOGA havebeenpartially accomplishedby considerationof only the Pacific basin, it is clearthat a thoroughunderstanding of seasonal-to-interannual climate variability must take into accountthe monsoons. Earlier international field programssuchas the IndianOceanExpedition (INDEX) (1975-1976)of the InternationalGeophysicalYear and the MonsoonExperiment(MONEX) (1978-1979) [e.g., Krishnarnurti, 1985] had made extensive measurementsof the Indian

oceanbut not to the level of theTOGA investigation in thePacific Ocean. Thesemeasurements were madeagainstthe knowledge that the monsoonalsopossesses interannualvariability,someof which is linked to E1 Nifio, althoughthere seemsto be inherent varianceof the monsoonsystemitself or, at least,associated with otherpartsof the climatesystem.The picturethat hasemerged is a systemthat is global and interactive.Thus compartmentalization of the global system(i.e., the consideration of the ENSO

andmonsoon systems separately) is probablynotveryproductive [Webster, 1995].

m'2, whichisconsidered toindicate convection andprecipitation Most modelsusedfor experimentalforecasting of seasonal-toin the tropics [Arkin and Meisner, 1987]. There is a distinct interannual variability[e.g., Cane, 1991] are essentially Pacific migrationof heatingover southAsia duringthe springand early Oceanbasinmodels.The modelsare "spunup" usingobserved

beforethe atmospheric model summer. Theheating variabilit), isasymmetric withrespect tothe PacificOceanwind distributions seasons with deeperconvection extendingconsiderably northward during the northernsummer. During the southernsummerthe convectionremainsfairly close to the equator. This locus of heatingis associated with the Asian-Australianmonsoonsystem. Figure 2 also shows anotherinterestingfeature. OLR maxima (crosshatchedregions)representnet radiative sinks. These heat

takes over and provides feedbacksto the ocean. Often, an annualcycle is addedanalyticallyto the system.However,the

modelsappearto be very sensitiveto any systemor process that disturbsthe wind strengthover the Pacific Ocean of the model. For example,Barnett et al. [1989] found that weak tradewinds,whenimposedon an oceanmodel,produceda weak

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regions indicate OLR< 220and> 300W m'2, respectively. OLRminima aresurrogates forpersistent deep convectionand latent and radiative heat sourceswithin the troposphere.Regionsof maximumOLR, on the other

hand,indicateradiativelossto spaceandhenceare heatsinks.An annualmigrationof the majoratmospheric heat sourcesand sinksof the tropicsand subtropics is apparent.After Webster[1995].

E1Nifio system.The weaktradewindsintroduced intothemodel were associatedwith a heavy winter snowfallregime and the subsequent weak summermonsoon.Matsumotoand Yamagata [ 1991], Webster[ 1995], Wainer [ 1991], and Wainerand Webster [1996], usingmodelsthatincludean IndianOceanandan Asian landmass as well as a Pacific Ocean, found that variations in the

intensityof the summermonsoonsystemaffectedthe periodof ENSO. Weak monsoons(and, consequently,weak Pacific trade

winds) producedshorterperiodwarm events.On the otherhand, strongmonsoonscreatedlonger-periodENSO cycles. Thus there appearsto be someevidencethat the coupledocean-atmosphere responsein the Pacific Ocean is coupled strongly with events occurringoutsidethe Pacific basin. Building on the foundationslaid during TOGA, it is hoped to extendclimate predictionfrom the Pacific basin to the global domain. It is plannedto accomplishthis extensionunderthe aus-

WEBSTER ET AL.: MONSOON PREDICTABILITY

picesof a newprogram,GlobalOcean-Atmosphere-Land System (GOALS) program[NRC, 1994; WCRP, 1995]. The aim is to expandthe networkof long-termobservations andprocess studies to the othertropicaloceansin orderto encompass the major heat sourcesand sinksof the ocean-atmosphere-land systemand investigate predictable elements thathavebeenshownto existin theseregions. It is plannedto follow the predictableelements foundin the tropicalcoupledclimatesystemto higherlatitudes and, at the sametime, seekpredictableelementsof the higherlatitudeclimate,if theyexist. If thereis inherentpredictability at higherlatitudes, it will mostcertainlybe associated withoceanic dynamics or continental surfacehydrological processes. Clearly, the GOALS endeavorwill be a coupledocean-atmosphere enter-

prisebut with the additionof landsurfaceandice processes all consideredon a global domain. An importanttool for GOALS is the globalcoupledocean-

AND PREDICTION

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In generalterms,when the pressureis high in the PacificOcean,it tends to be low in the Indian Ocean from Africa to Australia; these

conditionsare associatedwith low temperaturesin both theseareas, and rainfall variesin the oppositedirectionto pressure.Conditions are related differently in winter and summer,and it is necessaryto examineseparatelythe seasonsDecemberto Februaryand Juneto August.

With the aid of suchslowly varying circulations,there was hope that the variabilityof the Indian monsooncould be "foreshadowed"throughrelationships with otheraspectsof the generalcirculation, which Walker [1923, p. 320] termed "strategicpoints of world weather."Indeed, Walker's slow rhythms,mostnotably the SO, adumbratedthe possibilityof forecastingclimate variations, which would be of singularimportanceto the agrarian societyof India. Yet the ability to predictthe future courseof theserhythmswas severelyhamperedby a vagueness in the observationalrelationships andby the failureto identifyunderlying physicalprocesses whichmighthaveallowedthe relationships to

atmosphere-land model. However,to date,therehasnot been universalsuccess in simulatingeitherthe phaseor the magnitude become unraveled. of the annualcycle with thesemodels[Mechosoet al., 1995]. To make use of the observationsof large-scale coherent Perhapspartof the reasonfor theseproblemsis the inabilityto rhythmsfor predictingthe intensityof the subsequent monsoon, simulateadequately eventhe meanstateof the monsoon, which Walker would have had to satisfy four basic criteria [Webster is a majorcomponent of the annualcycleevenwith stand-alone and Yang, 1992]: (1) the precursorcirculation(the SO) should atmospheric generalcirculation modelswithimposed seasurface possessa spatial scale which encompasses the circulationor temperatures (SSTs)[Sperberand Palmer,1996]. the phenomenon(the monsoon)that is to be predicted;(2) the precursorshould possessa timescalethat is very much longer 1.2. Foundations than that which is being predictedin order to providesufficient Earlystudies considered the monsoon to be a regionalphysi- lead time for the prediction to be useful; (3) the precursor

cal entity,andattempts to understand its structure andvariability circulation should be the "active" circulation and the circulation focusednaturallyon localeffects.As observations from farther to be forecastedshouldbe "passive."That is, an obviouscause afield becamemore readily availableto researchers, indications and effect relationshipshouldbe apparent;and (4) the statistical

emerged thatthemonsoon wasa macroscale phenomenon which relationshipswould needto be both stationaryand significant. was intertwinedand interactivewith other global-scalecircula-

tions(seework by Kutzbach[1987] for a historicalaccountof the southAsian monsoon).In recentdecades,with the adventof

Figure 3 depictsrelationshipsbetweenthe Nifio 3 SST data (Figure3a), the AIRI (Figure3b) in the form of a waveletanalysis. Figure 3c showsthe cross-waveletmodulusof the AIRI and the

a morehomogeneous datasetfrom satellitesanda moresubstan- Nifio 3 SST [Torrerice and Webster, 1998]. A wavelet modulus tial conventionaldatabase,there has been little to contradictthis providesa historyof when in the data recordcertainperiodicities are dominantand may be thoughtof as an evolving periodogram global view of the monsoon. Over 100 yearsago, scientistsattemptedfor the first time with time. Lau and Weng[ 1995] and Torrericeand Compo[ 1998] to forecast the seasonal and interannual variations of the mean provideexcellentsummariesof the use of waveletanalyses.The monsoonpatterns.The incentiveto produceforecasts of Indian latter study is particularly useful as it providesa method of rainfall came after the great Indian droughtand the resulting calculatingsignificancelevels of wavelet moduli. Significance famine of 1877. As noted by Jagannathan[1960, p. 5], the levels at the 95% level are shown as the thick black contours. chargefromthe Government FamineCommission to thedirector A cross-waveletanalysisshowswhen certainperiodicitieswere generalof theIndianMeteorological Service,H. R. Blanford,was commonto both data sets.Below eachwaveletanalysisis a plot "sofar asit maybecomepossible,withtheadvanceof knowledge, of the time series(gray curve). The black curve representsthe to form a forecastin the future, such aids should be made use of, percentage of the total variancethroughthe periodof the analysis thoughwith due caution."In a first attemptto foreshadow the explainedby the power at a particulartime. On the right-hand monsoon, Blanford[ 1884]considered theimpactof localforcing side of each wavelet analysisis a fast Fourier transform(FI•), functionssuch as the snow cover over the Himalayas during or periodogram,of the data time seriesand the averagewavelet

the previouswinter. Theseeffortswereeventually replacedby modulusasa functionof period. The FFT andthe averagewavelet moreglobalassociations. Sir GilbertWalkershowedthat the modulusare very similar. The FFT providesthe total power in globalatmosphere possesses coherentpatternsof low-frequency a particularfrequencyband averagedover the entire data record. variability(Walker[ 1923, 1924, 1928],WalkerandBliss[1932], However, there is extra informationin a wavelet analysis. If, corroborated by Troup[ 1965], Berlage[ 1966], andmanyothers). during the data record, there was just one very large amplitude Walker's [1923] work followed from the findingsof a strong eventat a particularfrequency,the FFT may indicatelargepower

positivecorrelation between RussiaandIndiabyBlanford,[ 1880, but not disclose that it was the result of one event. The wavelet 1884] andan equallynegativerelationship betweenSydneyand analysis,on the otherhand,would localizethe power in time and BuenosAires [Hildebrandson,1891]. Of the many planetary- show that it was not a reoccurringphenomenon[Lau and Weng, scaleinterrelatedpatternsfoundby Walker[1924], the Southern 1995; Torrericeand Compo,1998]. With thesethoughtsin mind, canbe drawnfrom the waveletanalysis. Oscillation(SO) was thoughtto be of particularrelevanceto the the followingconclusions 1. The time series of SST in the western Pacific Ocean and monsoonand was describedas "a swayingof pressureon a big scale backwards and forwards between the Pacific Ocean and the the AIRI are not statisticallystationary.There are at least three Indian Ocean."This definitionwasextendedby Walkerand Bliss distinctregimesin whichthereweredistinctanddifferentperiodic character to the series. Before 1920, there was considerable [1932, p. 5] to includethe seasonality of the oscillation:

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Figure 3. Waveletmodulusanalysesof climatetime seriesin the PacificOceanandthe Indian Ocean (a) Pacific Ocean sea surfacetemperature(SST) (1875-1992) in the Nifio 3 region (see Figure 14 for location), (b) The all-India rainfall index (AIRI) (1875-1992), and (c) the cross-waveletmodulus between the AIRI and the SST.

Contoursindicatethe percentof total varianceat a particularfrequencyexplainedat a particulartime in the data record. Thick black contourson eachmodulusindicatethat the amplitudewithin is significantat the 95% level. The dashedareason the right and left of the moduli distributionsindicatethe limitationsof the data to define varianceof a particularperiodat a particulartime of the datarecord. Below eachwaveletmodulusis the data record,with a graycurvethatrepresents thepercentof thetotalvarianceexplainedat all frequencies at a particular time. The blackcurvebelowthe cross-wavelet modulusrepresents the covarianceof the AIRI and the Nifio 3 SST in the 2-8-year-periodband.On the right-handsideof eachmodulusare periodograms computedin two different

ways.Thegraycurves represent thefast-Fourier Transform of theentiredataseries.Theblackcurves represent the summedwaveletmodulus.The 95% confidence curveis alsoplottedon the periodograms. Methodsdescribed in Torrenceand Compo [1998] are used.

WEBSTER ET AL.: MONSOON PREDICTABILITY AND PREDICTION variance in the AIRI and the SOI, and correlations were near to

14,457

the following winter quarter,thoughof only -0. 2 with the previous

winter quarter. -0.8 betweenthe AIRI and the SST comparedto an averageover the 120-year period of-0.64. These high correlationsearly in Thus Normand [1953, p. 469] couldconcludewith regardto the the dataperiodwere the relationshipsthat excitedWalker and his Indian summer monsoon that: colleagues.Between 1920 and 1960, there was little interannual It is quite in keepingwith this that the Indian monsoonrainfall hasits variability in either the Pacific data or the Indian rainfall, and connections with later ratherthanearlierevents.... Unfortunately the correlation decreasedto < -0.2. Systematicanalysesof for India, the SouthernOscillationin June-August, at the heightof the nonstationarityof the SOI was undertakenby Treloar and the monsoon,has many significantcorrelationswith later eventsand relatively few with earlier events... The Indian monsoontherefore Grant [1953] and Grant [1953] for the Australian region and standsout as an active, not a passivefeaturein world weather,more Troup[1965] for the globe. CorrelationsbetweenDarwin surface efficientas a broadcastingtool than an event to be forecast.... On pressure(a proxy for the SOI, see Trenberth[1984]) and also the whole,Walker'sworldwidesurveyendedofferingpromisefor the surface pressuresin Hawaii with southernAustralian rainfall predictionof eventsin other regionsrather than in India. anomaliesdecreased from roughly> -0.8 in theperiod1909-1928

to about -0.2 between 1929 and 1948. Treloar and Grant [ 1953,

There are numerous corollaries

p. 428] concludethat the secularreductionof correlations

temporaneous relationshipsappearto exist betweenthe AIRI and ENSO (seeFigures1 and 3), but a prior knowledgeof the SOl in the previouswinter or springdoesnot seemto help in forecastingthe strengthof the following summermonsoon.This is

throws considerable

doubt on the direct use of correlation

relation-

shipsin forecasting.... Improvementin the performanceof forecast formulaecannotbe expecteduntil there is a more satisfactory methodof selectingindicators,requiringin turn a better understanding of the nature of weather processes.

to Normand's

conclusions.

Con-

becauseof the lack of persistence of the SOI throughthe boreal spring.This persistence dip hasbeensubsequently referredto as 2. The decreasein the correlationsthat occurredin the period the "predictabilitybarrier" by Websterand Yang[1992]. Howof the SOI for the 6- to 9-monthperiod between1920 and 1960 has beenreplacedby an extendedperiod ever, the persistence following the boreal summer suggeststhat the winter monsoon of high variance in the SOI and correlationsthat match the and precipitation in Indonesia and northAustraliais morehighly 1880-1920 periodand a returnof muchhighercorrelations.These earlier studieswere unawarethat the ENSO signal possesseda predictable.Finally, the fourthcriterion,the necessityfor statisof the SOI time seriesandits relationships with large interdecadalsignal. Both the SST and the AIRI moduli as tical stationarity other indices, is questionable as first indicated by Troup [1965]. well as the crossmodulusshowstrongsignalsin the 10-25-year Troup[1965] describedgraphicallywhy thereare not clearer period. Given the length of the data set, though,the conclusion betweenthe SOI andIndiansummermonsoon preshouldbe viewed with some scepticism.However, recentcoral relationships core data from the Nifio 3 region, which extentsback in time cipitation. Walker's[1923] correlationswere reexaminedby to 1600, exhibits similar variability in this period band (J. Cole, stratifyingthe deviationsof surfacepressureat the extremesof the SouthernOscillationfrom the long-termmeansby season. University of Colorado, personalcommunication,1997). regionsof negativeand positivesea level pres3. Throughoutthe dataperiod(exceptbetween1920 and 1950), Planetary-scale sure are clearly evidentin both summer(Figure4b) and winter thereis strongbiennial monsoonalvariance.A numberof studies (Figure 4c). However, in the borealsummerthe zero anomaly [e.g., Yasunari1987, 1991; Rasmusson et al., 1990; Barnett, 1991]

line passesvery closeto the Indian subcontinent.That is, at the time of maximumprecipitationin the annualcycle, India is locatedneara nodein the pressurepatternand well away from the regionsof anomalyextrema.While Troup'sdiagramsprovidean explanationfor the contemporaneous correlationsof Indian rainfall andtheSOI, theypresenta consistent pictureof thevagueness of the relationshipandwhy forecastingvariationsof the monsoon usingjust the SOI may be difficult. Small displacements of the nodewouldplaceIndia in eithera weakpositiveor weaknegative pressureregimerelativeto the long-termsummeraverage.Thus, even with a perfectforecastof the SOI, a discriminating foreshadowing of the summer monsoon over India would be rather criteria (listed above) that Walker's [1923] indices would have to satisfy. The first two criteria are met. The patternresembles difficult. On the other hand, the major precipitatingregionsof a dipole with the extrema spanningthe Indian and the Pacific the wintermonsoonoccurwell away from the nodesandnearthe Oceans. Furthermore,the general4-6-year period of ENSO is extremaof the anomalies.Therefore,a priori, one may expect the variabilityof the wintermonsoonusingthe far greaterthan the intrinsicannualperiodof the monsoon.That that forecasting SOI might be more successful simplybecause thewintertimepreis, the spatialand temporalscalesof the SO easily encompassthe scalesof the monsoon.The third criterionprovesmuchmoredif- cipitationregionsare locatedwithin a broadextremumof surface ficult to satisfy. Walker [ 1923] found that Indian summerrainfall, pressureand not near a node in the anomaloussurfacepressure

have commentedon a biennialperiodicityin tropicalcirculations, especiallythe monsoons. The periodogramsindicate that the biennialvariability is particularlystrongin the monsoonregions, althoughwith less magnitudein the SST fields. However, the crossmodulusindicatessubstantialcovariancein the 2-3-yearperiod band. 4. The AIRI wavelet analysisshows substantialvarianceat intraseasonaltimescalesas well as clear interannualvariability. Figure4a depictsthe spatialdistributionof the zero-lag correlation of the Darwin surfacepressurewith surfacepressureelsewhere [Trenberth,1984]. It is now possibleto returnto the basic

while weaklycorrelatedwith pressurevariationssomemonthsearlier in locationsas far away as SouthAmerica, was more strongly correlatedwith subsequent events.In discussingWalker's overall work Normand [1953, p. 469] summarizedthe following: To my mind, the most remarkableof Walker's resultswas his discoveryof the controlthat the SouthernOscillationseeminglyexerted upon subsequent eventsand in particularof the fact that the index of the SouthernOscillation as a whole for the summerquarterJuneAugust,hada correlationcoefficientof +0. 8 with the sameindexfor

field.

Whereas research has concentrated on simultaneous relation-

shipsbetweenthe SOI and Indian summerrainfall [e.g.,Angell, 1981;Rasmusson and Carpenter,1983;Ropelewski andHalpert, 1987, 1989], many studieshave persistedin attemptingto use the SOI as a basepredictorfor monsoonvariability,despitethe conclusions reachedby Normand[1953] and Troup[1965]. For example,ShuklaandPaolino[ 1983]havesuggested thatthetrend of the SOI in the precedingspringappearsto be moreimportant

14,458

WEBSTER ET AL.' MONSOON PREDICTABILITY

AND PREDICTION

(a) Correlation of MSL Pressure with Darwin 1890-1993

all months

60øN 30øN

EQU

30øS 60øS

0ø

60øE

120øE

1800

(b) Departures of MSL Pressure fo•-•

120øW

60øW

0ø

SOl 1890-1993 JJA

...................... • '5,-/ "::::• .... ":•iiiiiiiiiiii::i!::ii::i?:iiiiiiiiii:.. ß ........ ß ........ '................. :i•,,••m•'••• •. '•'•' • .•':•::...•

':!! ...... ':i•:'.•i•i•i•::•i•ii•:..!•i!!.!.!.!.!.!.i•i•i'i' :i!i'::::i•::•::ii ............... i:i:i:i:i:i:i::.' ..iiiiii I................ ..... •-,•.

' .:i !'• :::::::::::::::::::::::::::::::::: '•:...•: ,•i::::::i::•ii•:":.; :•:•:•*•:•:•.'•i•i::::ii:,....•iiiiiiiiii::i::iiii'"'"'":':"'"':. "• ' '---.,

"'"'"'"'".....':'..-':-•'.'.:.:.iiiiii:.ii!: ß ............:.'.":.'.

•

............. :•!i!i'"'"'"'-••i!::ii!i!i• ...... .:•11::::11:) =========================== .. . ß... • ......................... ......... .?,(:?" ......

ß

-'•i•iii!'

::• •

................ :......... ..:..............

•

'"'•

::•'

:•i:•:•:•:.'============================

:: iii•iiiiiiiii •' '

, .. ,,, , , __...,.• ..-.....

0ø

60øE

120øE

1800

(c) Departures of MSL Pressure for-•

0ø

60øE

120øE

180o

120øW

•::i::iiiiiii::...:....•

60øW

0ø

SOl 1890-1993 DJF

120øW

60øW

0ø

Figure4. Spatialdistribution andseasonal cycleof the Darwinsurface pressure for the period1890-1993.(a) Globaldistribution of the zero-lagcorrelation of surfacepressure variations with the Darwinsurfacepressure. The distribution definesthe Southern Oscillationindex(SOI). The thickblackcontourdenoteszerocorrelation, (b) Departureof thesurfacepressures (tenthsof millibars)fromthelong-termborealsummermeanvaluewhentheSOI is at 1 standard deviation (June-August). Thethickblackcontour denotes thezerodeparture of Darwinpressure. (c) Borealwintersurfacepressure departure whenthe SOI is at 1 standard deviation(December-February). Basedon calculations by Troup[1965]withan additional 35 yearsof data.Fortheopposite extremeof theSOI, thesignof

thepressure anomalies wouldbe reversed. Thethickblackcontour denotes thezerodeparture of Darwinpressure.

as an indicatorof Indian monsoonprecipitationthanthe absolute value of the SOI itself. However, laggedcorrelationsbetween the trend in the SOI and the subsequent mean Juneto August (JJA) SOI are very weak and led Shukla [1987b, p. 540] to note that "the largestnegativecorrelationsare found in November followingthe monsoonseason.This suggests a possiblerole of monsoonrainfall fluctuations .... in affectingthe subsequent global circulation"tending to supportthe conclusionsof Normand.Shuklaand Mooley [1987] extendedtheir analysisby configuringa regressionequationcomprisedof the Januaryto

April Darwin pressuretrend and the latitude of the 500-mbar ridge over the Indian subcontinent.

In moststudies theemphasis hasbeenontherelationship of the Indiansummerrainfallwith gross-scale rhythmssuchas ENSO. Although there are critical socioeconomicconcernsthat have

driventhe regionalemphasis, India represents only a moderate fraction of the monsoon area of Asia. It is not clear what the

relationshipis between rainfall on the Indian subcontinentand

elsewherein Asia, castingconcernregardingthe extentof the relationship betweenthe grossexternalrhythmsandthe broad-


AND PREDICTION

14,459

scalemonsoon.Thus it is importantthat somemeasureof the 1.3. Questions broad-scalemonsoonintensitybe defined. The discussion abovemay be summarizedas a list of scientific Besidesrelating monsoonvariabilitywith physicalsystems outsidethe monsoonregions,otherrelationships havebeensug- questionsrelatingto the structureof the monsoonitself, the relagested.Notingthat the monsoon anomalies appeared to run in tionshipof the monsoonwith otherfundamentalcirculationfeamultipleyears(i.e., droughtstendedto last for multipleyears), tures(suchas ENSO), and the degreeto which its low-frequency it was suggested that sunspots determinedmonsoonvariability. behaviorcan be predicted.The questionsthat will be tackledin Blanford[1884], and later Lockyer[1904] foundweak associa- this paper are the following. 1. What are the spaceand time characteristics of the monsoon tions,but furtherscrutinysuggested phaseproblems.In the end it was concludedthat sunspots merelyenhancedthe variability system,andhow do they relateto eachother?The strongestsignal that was causedby otherfactors. Sincethen, however,interest of the monsoonis the annualcycle. Within the annualcycle there haswanedin the importanceof sunspots in determiningmonsoon are active periodsinterspersedby lulls or breaks. What is the variability. As mentionedabove,Blanford[1884] was the first spatial scale of these intraseasonalevents? Are they restricted to suggestthat the intensityof the monsoonwas governedby to the southAsian monsoon,or do they occurin other monsoon the extentof the previouswinter snowfallover Eurasia. Early regionsas well? Monsoonseasonssignificantlydifferentfrom the successes werereplacedby failure[Kutzbach,1987]. Hahn and norm occur occasionallyconstitutingstrongand weak monsoons Shukla[1976] suggested that Blanford'sfailure may have been years. Is there a relationshipbetweenthe numberof active and a resultof unreliabledata and showedstrongerrelationships be- breakperiodsandthe strengthof the monsoon?Do the numberof tween snow extent and monsoonrain. Using more recentdata, strongand weak monsoonyearschangefrom decadeto decade? 2. What physicalprocessesdeterminethe structureand variit was suggested that limited snowfallduringthe winter is asmonsoonsystem? sociatedwith a strongerthanaveragemonsoonin the following ability of the coupledocean-atmosphere-land summer. Excessive snowfall, on the other hand, was related to The physical processesthat govern the coupled and variable a weak monsoon. Dickson [1984] with a more extensivedata ocean-atmosphere-land systemare very complex. The monsoon set confirmedthe analysis.Barnett [1984, 1985] and Barnettet may be thought of as the circulationrespondingto the annual al. [1989] notedthat variabilityin the monsoons and the ENSO cycle of solar heating in an interactive ocean-atmosphere-land appeared to be related.A large-scale propagating surface pressure system. Besidesthe interactiveelementsof the monsoon,there signalwasobserved to movethrough theIndianOceanregioninto are influencesfrom other climate systemssuchas ENSO and the the PacificOceanwith timescales greaterthan2 years.The sig- extratropicalregime. 3. What is the degreeof complexityof the monsoon?A critinal appeared to form in Asia, andBarnett[1985] suggested that it was associated with Blanford's winter snowfall mechanism. cal steptowarddetermininga strategyfor forecastingof the monWith respectto gross-scale rhythms,Bjerknes[1969] made soon is to decipherits degree of complexity. Figure 5 shows a key deductionwhichalloweda physicalinterpretation of the three hierarchiesof complexityfollowing the conceptsof HofSO. Interannualvariability,Bjerknesreasoned, wasthe resultof stader [1980]. The lowest form of complexityis a simple hiinteractiveprocesses occurringbetweenthe tropicaloceanand erarchy, which statesthat the variability in a system(e.g., the the atmosphere.Bjerkneswas able to relatethe quasi-periodic monsoon,M) is forcedby a variationin someotherfactorof the warmings of thePacificOcean(theE1Nifio)andWalker's[1923] climate(e.g., ENSO, E). A secondand higherform of complexSO, creatingthe conceptof the ENSO phenomenon.Armed ity is a complex hierarchywhere the two systemsM and E are with Bjerknes'svital clue andwith the realizationthatthe long linked throughother systems(Cn) suchas middle latitudeaffects "memory"of the oceanmight allow a predictivecapabilityof or Eurasiansnowfall,for example.In turn, eachconnectionmay thejoint system,the international scientificcommunity launched be influencedby nonlinearerror growth (D). Within the comthe TOGA monitoringand modelingprogramwith the scientific plex hierarchythe monsoonmay feed back on the ENSO system throughthe third systemor vice versa. The highestlevel of comobjectivesand goalslisted previously.

simple

complex

tangled

Figure5. Possible relationships betweenthemonsoon, ENSO,andotherclimatefactorsin termsof thecomplexity of interactions.In a "simple"system,changesin one system(e.g.,ENSO; E) impartchangesto anothersystem (e.g.,the Monsoon:M). Relativeto thegrowthof internalerrors(D) theinfluence is linearandthe systemhighly predictable. In a "complex" system therelationship between themonsoon andENSOis complicated by interactions with othersystems (C) whichmay feedbackontoENSO, for example.The systemis nonlinear,andthe degree of determinism is reduced.In a "tangled"hierarchialregime,determinism is lost. M, E andC may be unstable chaoticsystems, andit is difficultto deconvolute linkagesbetweenthe elements.Predictability of sucha system wouldbe entirelyprobabilistic. However,evenwiththetangledsystem, thedegreeof determinism wouldincrease if one of the linkages were dominant.

14,460


plexity is a tangledhierarchy.At this level each systeminteracts with the other, and the routing of the interactionis difficult to decipher. It might be expectedthat there is considerabledeterminism in the simple hierarchy,althoughto a lesserdegreein the complexhierarchy. In either of thesecomplexitiesa particular precursormay lead to a specificconclusion,albeit blurredby nonlinearerror growth in the system. However, determiningthe precursorsand their order may be difficult in a multicomponent system. On the other hand, determinismwould not be expected in the tangledhierarchy. The systemwould be highly nonlinear and chaotic,and predictabilitywould be probabilistic. The principalpurposeof this studyis to provide a first step in producinga logical frameworkfor determiningthe physical processeswhich controlthe seasonal-to-interannual variability of the coupledmonsoonsystemand to provide a basisfor future studieswith coupledocean-atmosphere-land models. This study attemptsto form a bridge betweenTOGA, which gravitatedto

2.1.

AND PREDICTION

The Annual Cycle of the Monsoon

In Figure 6a the horizontaldistributionof the 200-500-mbar

layermeantemperature is plottedfor borealsummer(Figure6a left) and winter (Figure6a right). The shadedregionshows a mean temperaturewarmer than -26øC. During summera planetary-scalewarm air mass is centeredon south Asia with

the maximumaveragelayer temperature( > - 22øC) over the southern TibetanPlateau,resultingin strongtemperature gradients in both the north-south and east-west directions. A warm

temperatureridge existsover the North American continent,and a deeptemperature troughstretches from the westcoastof North

Americato the centralPacific. A similartroughlies over the AtlanticOcean.Theuppertropospheric flowpatternduringsummer identifiesclearlythe thermalcontrastbetweencontinentsand oceans[e.g.,Krishnamurti,1971a, b]. The borealwinterpresents

a very differentstructure.A muchsmallersectionof the globe (northeast of Australia)is warmerthan-26øC. A warmtemper'Climate Research Program's (WCRP)GOALSproject, which atureridgelies overSouthAmerica,anda slightlyweakerridge a Pacific Ocean basin focus, to the wider realm of the World

covers'Australia.

aims at seasonal-to-interannual predictionon a global scale. In the last two decades, there have been a number of reviews

of the monsoonsystem[e.g., Ramage, 1971; Das, 1986; Fein and Stephens,1987; Hastenrath, 1994]. This review differs by emphasizingthe monsoonas a coupledsystemand, in the spiritof theTropicalOceanGlobalAtmosphere(TOGA) program, emphasizes the predictabilityof the monsoonand its prediction. In the secondsectiona thoroughdescriptionof the monsoons is attempted. The processesthat produce the monsoonsare addressed in section3. Modeling studiesare discussed in section 4, and predictabilityand predictionof monsoonvariabilityare

Figure6b showsthelongitudinal structure of theannualcycle of the uppertropospheric (200-500mbar)temperature anomaly fortheentireyearalong30øN,5øN,15øS,and30øS.Theanomaly is calculated by subtracting outthemeanzonallyaveraged annual cycle of the columnar200-500-mbarmeantemperature along the particularline of latitude. The 30øN sectioncutsthrough thetemperature maximumovertheTibetanPlateau.Temperature anomalies beginto changefrom negativeto positivein April

near90ø-100øE. Thetemperature increases overEurasia during summer are much larger than those over North America. The

discussed in section 5. Section 6 lists the main conclusions and

maximum temperature anomaly(9øC) occurs in theregionof the

discusses the transition of TOGA

Tibetan Plateau(between60ø and 105øE). Smaller maxima of

to GOALS.

mean temperatureanomaliesoccur over North America and west

Africa. In contrast, thereis no appreciable changein theupper tropospheric temperature along5øN(Figure6a topright),whichis

2. Descriptionof 'theMonsoons Ramage [1971] provideda rather strict definitionof a monsoonand identifiedthe African, Asian, and Australianregionsas satisfyingboth a wind reversaland seasonalprecipitationcriterion. However,the Americasqualifyas monsoonregionsat least in terms of precipitation.In the following sectionsthe various monsoon circulations

will be described.

mostlyoverthe oceans.The southern hemisphere sectionsat 15ø

and30øSareweakcounterparts of the30ø N section. Compared to the> 9øCanomalyfoundovertheTibetanPlateau,anomalies havemagnitudes of only 3øC at 30øS. Thelongitude-time sections of thedifference of themeanupper tropospheric (200-500 mbar)temperature between30ø and5øN,

Mean Upper-TroposphericTemperature' 200-500 mbar 40N

40N

20N

20N

20S

20S

40S

40S

90E

180

90W

0

0

90E

180

90W

Figure 6a. Meanuppertropospheric (200-500 mbar)temperature (degrees Celsius)for the borealsummer(JJA), andborealwinter(DJF), averagedbetween1979and 1992. The borealsummerplot is basedon calculations first madeby Li and Yanai[1996]. Mean columnartemperatures warmerthan-25øC are shaded.

0


14,461

AnomalousTroposphericTemperature (200-500 mbar) Dec Nov

Oct

Sep Aug Jul Jun

May Apr Mar Feb Jan

0ø

90øE

180 o

90oW

0o

0ø

90øE

180 o

90oW

0o

Dec Nov Oct

0

Sep

Aug Jul Jun

May Apr Mar Feb Jan

0ø

90øE

180 ø

90øW

0ø

Longitude

Longitude

Figure6b. Longitude-time sections showing theannualcycleof theuppertropospheric (200-500mbar)temper-

atureanomaly at 30øN,5øN,15øS,and30øS.Plotsareextensions of initialcalculations firstmadefor30øNbyLi and Yanai[ 1996]. The anomalies werecalculated by subtracting the annualcycleharmonicat a particularlatitude from the mean columnartemperature.

(upperpanel),30ø and5øS(centerpanel)andbetween 30øN to the equator.Geostrophicadjustmentis extremelyrapidat very and 30øSare plottedin Figure6c. All temperature differences low latitudes,and it is difficult for a local temperaturemaximum >6øC are shaded. The reversalof the meridionaltemperature gradientoccursfirston the southsideof theTibetanPlateau(near 90ø-100øE)and thenexpandsover a largeareaextendingfrom Africa to the westernPacific.The temperature differencereaches maximumvalues(> 6 K) in July andbecomesnegativebetween

to be maintained. On the other hand, geostrophicadjustment to the elevatedheating over the Himalayasis sufficientlyslow to allow the developmentof a substantialpressurefield and a

meridional temperature gradientin theuppertroposphere southof

in the boreal summer, are the result of the intense radiational

warm core. However, the monsoon should be viewed in a cross-

equatorialcontext. Figure 6c (fight) showsthat there are still September andOctober.Li and Yanai[ 1996]foundthattheonset strongcross-equatorialpressuregradientsthat drive the boreal of the Asian summer monsoon is concurrent with the reversal of winter monsoon.Thesegradients,not as largeas thoseoccurring

the TibetanPlateau,as originallysuggested by Flohn [1957] and cooling over north Asia during winter. Figure 7 plots the mean latitude-heightcrosssectionof the later by Flohn [1968]. A small regionof reversedtemperature vertical velocity (upward motion is shaded)throughthe major gradientmay alsobe seenover North America. The temperature gradients in the southern hemisphere never monsoonareasfor the monthsof Februaryand July 1992 [from reverse.That is, at all timesthe meantemperature at 30øSis Tomasand Webster, 1997]. In all cases,there is very strong coolerthanat 5øSbecauseof the strongest heatingoccurringvery ascendingair concentratedon the summerhemisphereside of closeto the equator.AlthoughAustraliais a largecontinent, the the zero absolutevorticity contour (thick line). However, the heatingis notelevatedasit is overtheHimalayas.Thusthemajor ascendingair over the Asian sectionduringsummeris of a much heatingremainscloseto thenorthcoastof thecontinent andclose broadercharacterandextendsfromjust northof the equatorto the

14,462


AND PREDICTION

LatitudinalGradientsof the Mean 200-500 mbarTemperature Dec

Nov Oct

Sep Aug Jul Jun

Me• Apr Mer Feb Jen

0o

r•r• =v ,• •.

I ou ,.•,•ol vv •,

,•,,•ol uu vv •,

0o

0ø

g0 E

!80øW

90øW

0ø

Figure 6c. Longitude-time sectionsshowingthe 5-day uppertropospheric (200-500 mb) temperature differences

between30øand5øN (left), 30¸ and5øS (middle)and30øN and30øS(right). Areasof differences > 6øC are shaded.Northernhemisphereanalysisbasedon initial calculations by Li and Yanai[1996].

(a) SouthAsian Sector' July 1992

(c) AmericasSector: JULY 1992

lOO

• 15o E• 200

-

12

2.5O

•.•300 •

400

•=

500 700 850 925 1000

30N

20N

10N

0

10S

20S

30S

(b) AustralianSector: Feb. 1992

(d) AfricanSector:July 1992

lOO

150 ........... :........... i........... ::....v•.•y.4f.•.•f.•i•ii•i!:-&:-'•!.•',4:•!-:,.•i:.•:•!.•.•i"". -':•':'••i!.4•ii•i!•i!ii•i!.4.•:•':• ßß ......

200 ..........' ..................' ........'•;:;•;;:•;',;;•i;:;•;•;;•;I;;;5; ';;;;".;;;"'

-"':":;;:;•

ß-

i12

•i//0 ' • ::::::::::::::::::::::::::::::::::::::::::: :::::::•:" .,:-:-'-' ""'::::::;-2 :::::::.':'

250

;-.-'-'• ...... i........ t'"i!iii•i•ili!ii•ii!!: ii$,,.:•i ii•i':: ....... i.........

- - !: .48 3O0 - ;:i',•::...........i......... •......... ,.'..... i&::i:•i:i½iS.ki

400

.,, 'w-:........ i...........

.......... ..: .......... i......... :........ ;... :i-;f',,:'-:•i';-:•i-:",,:i:'•':•. ::i.•.,-• :i•: !ii:,: ?.4...... i...........

5oo 700

•so

";;•:,,,;;;;;;'.........i.........

.! •....... ii..... !!iil;i'"i•ii•ii•i !•!!ii•"i•!...?,"?,ii,lil i.......... ':•o! • o'•?:•if;i '!!:!i•2 i:i:i:3 i:i:!:i:!:!!!:!:i:i :i:i:

;;;--,

-- -,---

85o

..o•o •o ••'

lOOO

30N

20N

10N

0

10S

20S

Latitude

30S

30N

'"--:• '••::•f•i ;;? i.t :': -'• r•,_..••.-•.,,,/.•. 20N

10N

0

10S

'• :•,,'-:•,. ••.•.• ::.?:

205

30',

Latitude

Figure7. Meanverticalvelocitysections throughthemajormonsoonal regionsof theglobe.(a) the southAsian

sector(60¸ to 85øE)duringJuly,1992,(b) theAustralian sector(120¸ to 140øE)duringFebruary, 1992,(c) the Americas sector(110¸ to 130øW)duringJuly1992,and(d) theAfricansector(30¸ to 50øW)duringJuly1992.

Units10-6mbars-]. Theshaded areashows upward motion. Thethicklineisthezeroabsolute vorticity contour. Datais fromEuropeanCenterfor Medium-Range WeatherForecasts (ECMWF) initializedanalyses.Basedon the calculationsof Tomasand Webster[1997].


14,463

(a) July 1992 MSL Pressure,925-mbar wind and OLR I

,

•I'

i

.,•".'""

ß L. •

•..• .......,...,....m---

o

•

,

30S

........ :=......... "'; .....

30W

,

!

i

.,,.......... ,:%

s.,••

., ..•..•

30E

•.

i

_

_

i

,

-- "',•-,•'"'•"-•"'-/•

......... :......

",'•:* ........................

0

_

•'

• ,:•,•

•

•

i

•1

_.•,: _.•-.•.• - -•

:'"•....:": .................. -•v'"•;,t,.c :" ..-,•5:•,:,,,,,.•,•s• '•,,•••••..-..'..'..-'i•i•.:.-'•if•:..'-:.'.-'.:•..'i:::-2=..
Nov

Oct ...........

::=:::..•---

.._•

Sep

-

-

.

";.:•::• .................... .:::.:.:•.::•:•;:.::.. ...... '::::::-: 0) (fight) 850-mbarzonalvelocitycomponent (U) along0-180ø averagedbetween5øS and 10øS.Note the rapidonsetof the monsoonalmostconcurrentlyin the easternIndian Ocean and over southAsia. During both summerand winterthereare periodsof strongwesterlywinds. In the borealsummerthesewesterliesextendalmostto the date line. National Center for EnvironmentalPrediction(NCEP)-National Center for AtmosphericResearch(NCAR)

reanalyzed datawasusedin theanalyses. All dataare5-dayrunning means withunitsof m s-•. regionsis the degreeof variability. The southAsian monsoon convectionappearsto havethe sametwo majorlocationsandtwo showsvariations thatare+ 3 m s-• on a background flow of forms of migrations.Precipitationoccursnear the equatorand about8 m s']. On the otherhand,the northAustralianmonsoon movesnorthwardto a locationover the northernBay of Bengal, variationsof the basic flow are about + 5 m s'• on a mean of whereit exhibitsvariabilityon 20-30-day timescales.With the 5 m s-•. Themeridional flowin thewestern partof theIndian northwardpropagations are propagations into the southernhemiOcean has variations in form that are similar to the Asian sector sphere.Theseare characterized by "Y" patternsemanatingfrom westerlies. Associated with the accelerations of the westerlies are the equator. The southwardpropagations which appearin both pulsesin southerlycross-equatorial flow. The African summer 1992 and 1993 are responsiblefor the secondaryprecipitation westerlies are weaker than both the Australian and Asian flow. maximumto the southof the equatorin the easternIndianOcean. difFigure 15 plots latitudetime sectionsof microwavesensing Figure 15 showsdatafor 2 yearswhichexhibitconsiderable unit(MSU) precipitation for 1992and1993along60øE(Figures ferences,especiallyin the westernIndian Ocean. In 1993, folstaysclose 15a and 15b,top) and 90øE (Figures15a and 15b,bottom,Bay lowingthe onsetof the monsoon,majorprecipitation of Bengal)fromApril to Novemberbetween40øNand30øS. The to the equator. In the easternIndian Ocean the distributionsare evolutionandintensityof the precipitation eventsare very differ- quitesimilarbetweenthe yearswith Y patternsoccurringin both. ent between the eastern and western Indian Oceans. In the eastern The differentloci of the convectionandthe northwardmigraet al., [1980] and Sikka section,therearetwo primarylocationsof precipitation. The first tions were first notedby Keshavamurty is to the southof the equator,and the secondis farthernorthin and Gadgil [1980] and were discussedin a numberof studies the central Arabian Sea. There is some evidenceof migration [e.g., Websterand Chou, 1980a,b; Webster,1983a;Goswamiand between these two locations. In the west, on the other hand, the Shukla,1984; Srinivasanet al., 1993]. Sikkaand Gadgil [1980]

!4,470


side of the Indian Oceanto the other. Clearly, the intraseasonal variabilityof the monsoonin the Indian oceanis very complex. In the simplestsense,there are three intraseasonalmonsoon phenomenathat occurin Figure 15. Theseare the "onset"of the summermonsoonand active and break periodswithin the season. The onsetof the monsoonappearsto have manydefinitions, varyingfrom a gradualincreasein humidityand the commencement of precipitation[Das, 1986] to the suddenestablishment of a "monsoonvortex" [Krishnamurti et al., 1990] in the northem Indian Ocean. The circulationchangesdo have considerable interannualvariabilitywith sustainedrainscommencingin different partsof southAsia at differenttimes. During 1992,however, convectionrapidlyprogressed northwardin May or earlyJuneat

(a) IAfricanl"'lSouth Asian Sectod

'•

I Sectorl ' ,-•., .............

•:""'"'"'"'•:i '""'"'"'•[• .' .....

•''t

3iønl•'•

:..•i•i,•:•:•:?:•:.:.:.:.•.,:.:,•:•i•i•i •:.•,•:::'--'-.:-'•:•w--:• : ß JNino 3 regionJ

,.J ISomalia Sector I IAustral•a• ',•ect0i" ':-.

. .

/ ....

(b,5•-'AtJstr;lia'nS;9ct•)r .......... Asian Sector

60 øand 90øE.

The active andbreakperiodsof the monsoonare characterized by precipitationmaxima and minima over southAsia or northern Australia,dependingon the season. These periodsare thought be associatedwith shiftsin the locationof the monsoontrough. During the monsoonbreakthe monsoontroughmovesnorthward to the foot of the Himalayas,resultingin decreasesof rainfall over much of India

-10

I

N 91

J 92

M

M

J

S

N

J 93

but enhanced

rainfall

in the far north and

south[e.g.,Ramanadharn et al., 1973]. Theseanomaliesarelarge scaleand extendacrossthe entiretyof southAsia. Breaksand activeperiodsvary in durationand may last betweena few days

M

and weeks.

(C)•5 •_, S;3m;lia' S(;ctc;r .......... [

--

African Sector-•'•

'

.l. :'"

Active and break periods of the north Australian summer monsoonappearto have a different signaturefrom thoseof the northernhemispheresummer.Ratherthan exhibitingnorth-south oscillations,the convectionappearsto propagatemore zonally [McBride, 1983]. However,the spacescalesandtimescalesof the eventsare quitesimilar. The activeperiodsin the northAustralian monsoonpossessa similar longitudinal spread to their boreal summercounterparts.However,the australsummeractiveperiods often extend to the mid-Pacific Ocean, where they are termed major westerly wind bursts[McBride et al., 1995; Davidsonet al., 1983;Fasulloand Webster,1998]. HendonandZhang[1997] notethat thereare largedifferencesin the frequencyof activeand breakperiodsfrom year to year. Similar interannualdifferences have been noted in the Asian summer monsoon.

-10

N 91

J 92

M

M

J

S

N

J 93

M

MONTH

Figure 14. Time sectionsof the 850-mb wind from November 1992 to April 1993 for certainkey areasin the monsoonregions. (a) Locationsof the time sections.(b) Zonal wind componentfor

the Australiansector(10øS to the equatorand 120ø to 150øE) and the Asian sector(10ø to 30øN and 60ø to 120øE) for the periodNovember, 1991 throughMarch, 1993. Active periodsare clearly defined as peaks in the monsoonwesterlies. Breaks are the minima in the monsoonwesterlies.(c) Zonal wind component

in theAfricanmonsoon region(5ø-15øNand0ø to 40øE)andthe meridionalwindcomponent in theSomaliasection(10øSto 20øN and40ø to 55øE).NCEP-NCAR reanalyzeddatawereusedin the

analyses. All dataare5-clayrunning means withunitsof ms'•.

and Gadgil and Asha [1992] notedthat the migrationswere longitudinally coherentfrom one side of the Indian Ocean to the other. However, all of theseanalysesconcentratedon the northem hemisphereand did not encounterthe southwardpropagations from the equatorin the east. Whereasall of the analysesindicate that there are migrationsor oscillationsin the locationof convection, noneof themnotedthe greatdifferencesthat occurfrom one

The time sectionsof Figure 15 definelarge-scaleandcoherent structuresof the activeand break periods.To isolatethe different atmospheric circulationsthat occurduringtheseevents,composites of active and break periodsthat occurredbetween1980 and 1993 were created(Figure 16). The criteriausedto definethe active andbreakperiodsandthe datesof the periodsthemselves are shownin the appendix. Three to four active periodswere identified each boreal summer. Figure 16 showsthe differencesbetweenactiveandbreakperiodsin the rotationalpartof the flow at 850 mbar (Figure 16a),the divergentpart of the flow at 850 mbar (Figure 16b), and the precipitation(Figure 16c). The composites show that during an active period the cross-equatorial monsoon vortex is far strongerthan during a break period. There is also enhancedconvergence in a bandextendingfrom the ArabianSea to the South China Sea. Within this band, there is enhanced con-

vection. To the north and southof the enhancedprecipitation, thereare bandsof reducedrainfall. In termsof the components identifiedin Figure 9 both the transverseand lateralcomponents of the monsoonsaccelerateduringactiveperiods.Duringbreaks these circulations

are diminished.

The compositesof Figure 16 suggesta rather simple set of distributionsof the fieldsof dynamicsand precipitationin active and break periodsof the southAsian monsoon.Compositesof the transitionsbetweenthe activeandbreakperiods[e.g.,Fasullo

WEBSTERET AL.' MONSOONPREDICTABILITYAND PREDICTION

(a)

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Figure15. Latitude-time sections of satellite microwave sounding unit(MSU)rainfallfor (a) 1992and(b) 1993 borealsummer seasons along60øE(Figures15aand15b,top)and90øE(Figures15aand15b,bottom).Datais a combined product fromMSU dataandsurface precipitation data(D. Lawrence, Program in Atmospheric and Oceanic Sciences: University of Colorado, Boulder, unpublished analyses). Shaded areasdenote theperiods shown in Figure 17.

and Webster,1998] showan orderlytransition.However,individual activeand breakperiodsand the transitionin betweenare much more complex. To illustratethis complexity,Figures17a and 17b showa sequence of 850-mbarwind flow and precipitation chartsfor an activeand break period,respectively.The MSU precipitationis shownas the shadedregions.The contours are isotachs,andthe thick line is the zeroabsolutevorticitycontour at 950 mbar. The periodduringwhich the two sequences weremadeis shownin Figure15. The activeperiod(Figure17a) showswidespreadprecipitationover the easternArabian Sea and the Bay of Bengal.Throughoutthe 4 day period,windsin excess

and Julian, 1972, 1994] is unclear. The MJO can be defined as

a 30-50-day oscillationin the large-scalecirculationcells that move eastward from at least the Indian Ocean to the central

Pacific Ocean. As discussedabove, there is abundantevidence of frequencypeaksin southAsian rainfall and wind in the same periodbandasthe MJO [Murakami,1976; Yasunari,1979, 1980,

1981;Sikkaand Gadgil, 1980; Wangand Rui, 1990;Julianand Madden, 1981; Madden and Julian, 1972, 1994]. However, climatologically,the most active period of the MJO (at least in its equatorialmanifestation)is in the boreal fall and winter (November throughMarch). Oscillationsof similar timescales

of 20 m s-• spread across thenorthIndianOcean.In thesouthern in the summermonsoonoften occuras northwardmigrations hemisphere,strongsoutherlywindsextendacrossthe entireIndian of convection [e.g., Murakami,1976; Sikkaand Gadgil, 1980; Ocean. Duringthe breakperiod(Figure17b) the windsare much Hartmannand Michelson,1993; Wangand Rui, 1990] or as a weaker,especiallyin the Bay of Bengal. Precipitationextends combination of northward andsouthward loci followingan initial across south Asia and into the northwestern Pacific Ocean. Fur-

eastwardmigration[Wangand Rui, 1990]. Examplesof these

thermore,the cross-equatorial flow is concentrated in the western latter migrationswere shownin Figures15 and 17a and 17b. Indian Ocean. althoughconsiderably weaker. The precipitation The association in the Australianmonsoon appearsto be more is generallylocatedfartherequatorward,weakerand less wide- straightforward. McBride [1983], Hendonand Liebmann[ 1990a, spreadthan duringthe activeperiod. However,the day-by-day b], andMcBride et al. [ 1995] showcloseassociations betweenthe patternsare muchmorecomplicated thanthe compositeanalyses. MJO andtheactiveandbreakperiodsof theAustralianmonsoon. The associationof active and break periodsof the monsoon In the absenceof a physicalexplanationfor the MJO [Madden with the 30-50 day Madden Julian Oscillation (MJO) [Madden and Julian, 1994] it is equallyfair to statethat the MJO is a

14,472


850 mb ROTATIONALWIND 1980- 1993 (ACTIVE - BREAK)

a)

.

0•_•5m2s0.1E 40'E 60'E 80'E 100'E120'E140'E160'E 180' 850 mb DIVERGENT WIND 1980 - 1993 (ACTIVE - BREAK) 40"N

'

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40'E

60"E

80"E

100"E

120"E

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PRECIP (mm/day) 1986-1993 (ACTIVE-BREAK i ...... ! ........ i. i ........... !............ i ............ !............ !............ i .......... ,.........:- .•...... ...........i

.....! ........

'ili!ii•?"•:'":"•;:•:' "•:-••••ii!!!i""""""•:'•'"• '" TM ............................. *'**•:':'"'"":'"" """•'•/:•:i'!•'ii!i:i !i':;?'":'• ..... ":'::: '""'""ii'i!,, ::'" •,::::

10øN o

10øS 20øS 30øS 0o

20øE

40øE

60øE

80øE

100øE

120øE

140øE

160øE

180øE

Figure 16. Compositesof active and break periodsof the summersouthASian monsoon. (a) The 850-mbar

rotational windcomponent (m s4) and(b) the850-mbdivergent windcomponent (m s4). Thickdashed line indicates lineof maximum anomaly convergence. (c)Theprecipitation (mmd-]) between activeandbreakperiods of the summerAsian monsoonfor the period 1980-1993. Active periodsare accompaniedby a strongcrossequatorialflow in the easternIndian ocean,strongerwestefiies,increasedconvergence, and greaterprecipitationin the northIndianOcean. Duringbreakmonsoonperiodsthereis a secondaryprecipitationmaximumjust northof the equator.Wind dataare from ECMWF operationalanalysesfor the period 1980-1993. Active andbreakperiodsare

definedin the appendix.Precipitation datais a combined productfromMSU dataandsurfaceprecipitation data(D. Lawrence:Programin AtmosphericandOceanicSciences,Universityof Colorado;Boulder.Unpublishedanalysis.)

resultof an inherentinstabilityof the coupledocean-atmospheremonsoonand also relationshipswith other major featuresof system. The monsoonexhibits monsoonflow thanto saythatthe activeandbreakperiodsof the the coupledocean-atmosphere monsoon are the result of the MJO. variabilityin threemajor frequencybandslongerthanthe annual by Yasunari 2.2.2. Longer-term variability. The wavelet analysesof cycle. Theseare the biennialperiod(first discussed Figure 3 suggestthe existenceof interannualvariabilityin the [1987, 1991] Rasmussonet al. [1990], and Barnett [1991],


(a)

14,473

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Figure17. Detailed analyses of 850-mbar velocity (vectors) andprecipitation (shaded areas) fortwosequences during thesummer of 1992fromlateJulytoearlyAugust withinthedashed rectangles ofFigure15.(a)Fourdays of anactiveperiod(b) fourdaysof a breakperiod.Thethickblackcontour shows thezeroabsolute vorticity at 850-mbar. Seeappendix fordefinition andthetimingof theactiveandbreakperiods. Notethecomplexity of the individual activeandbreakperiods in sharp contrast to thecomposite reconstructions shown in Figure16.

14,474

WEBSTERET AL.: MONSOONPREDICTABILITYAND PREDICTION 40E

60E

80E

100E

120E

140E

160E

180

160W 140W 120W 100W

80W

60W

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28ø - 29øC), occurring mainlyin thewesternPacific Oceanthereis a breakdownof this relationship.In the IndianOcean,thereis a sharplydifferentdistribution.No relationship appearsto existbetweenSST andOLR at all. This lack of correlationsuggests thatdeepconvection resultsfrom otherprocesses besideswarm SST. Thusconvection in the IndianOceanmay be morestronglytied to atmosphericdynamicsthan in the PacificOcean.

subsurface data in the Indian Ocean, the model has been shown

to replicatethe surfacestructureof the Indian Oceanas well as its annualcycle [McCreary et al., 1993] when the oceanmodel is run in stand-alonemode with prescribedatmosphericforcing. Figure26 showsthe heattransportandheatstoragechangesin the Indian Ocean throughoutthe year. The instantaneous northward heat flux betweentwo positionsalong a line of constantlatitude is defined

as

FQ

(3)

flux is evident during the winter, when the north Indian Ocean is losingconsiderableamountsof heatby evaporationand strong vertical wind mixing, which entrainscolderwater from below the thermocline.The net heat flux acrossthe equatoris made up of opposingflowsin theupperandlowerlayerof themodelandmay be thoughtof as a seasonallyreversingmeridionaloceancirculation [McCrearyet al., 1993]. The magnitudeof the net southward flux acrosstheequatorduringthespringandsummermonthsmore than makes up for the excesssurfaceflux into the north Indian Ocean, with peak summer magnitudesof meridionalheat trans-

portreaching values of 2x 10•sPW.Whereas thechanges in heat

storagehad been anticipatedby earlier studies[e.g., VonderHaar and Oort, 1973], the strongrole of advectionwas not considwhereH,, T, , and vi are the depth,temperature,and meridional ered. The circulationfound in the McCreary et al. [1993] model velocity component of theit-h layerof themodel.Thestorage in that accomplishesthe cross-equatorialtransportappearsto have a volume is defined by two major components:coastalupwelling along the coastsof the westernIndian Ocean and Ekman transports.Wacongneand (4) Pacanowski[1996] describea processwhere the upwelledwater within the westernboundarycurrentsare transportedacrossthe •r • z equatorvia the action of Ekman transports.Levitus[1987] was The major componentsof heat flow in this region are between the first to note that meridionalEkman transportsare southward the transportandstorageterms.A very strongsouthward flux of in the Indian Ocean on both sidesof the equatorand in both the heatis evidentduringthe springandearly summer,anda reverse boreal summer and the annual mean.


(a) Heat Budget of the Northern Indian Ocean

From the calculations above, it is clear that without ocean

transportacrossthe equatorand changesin the heat storageof the north Indian Ocean, the cross-equatorial buoyancygradient duringearly summerwould be very large. Yet the processes that accomplishthe cross-equatorial transportof heat in the oceanare essentiallywind driven [Mohanty et al., 1996; McCreary et al., 1993; Godfreyet al., 1995]. In turn, the atmospheric circulation is drivenby surfacefluxesand heatinggradientsassociated with thebuoyancygradientandatmosphere-land interaction.Therefore the annual cycle in the Indian Ocean is a coupledphenomenon resultingfrom ocean-land-atmosphere interactionsand balanced, to a large extent, by cross-equatorial oceanictransports. While local heat balancesand atmosphericheat balancesare probably dominant in the westernPacific Ocean (i.e., balances 1 and 2 in Figure 24), dynamictransportsof heat are still important[Sunand Liu, 1996]. However,the maintenanceof SST anomaliesin the northwestern tropicalPacificOceanmay be more stronglytied to ocean dynamics. For example, R. Lukas (Universityof Hawaii: personalcommunication,1996) hasnotedthat the MindanaoCurrentpossesses interannualvariabilityassociated with the phasesof ENSO. The MindanaoCurrentalsoappearsto be tied to the strongflow from the Pacificand the Indian Ocean through the narrow channelsbetween Borneo and New Guinea. This flow is termedthe Indonesianthroughflow[Gordon, 1986]. What is the role of the Indonesianthroughflowin the annual heat balance of the Indian

Ocean?

Current measurements

14,485

I •,

-,•,....'• -.

Surface Flux ////•'-'• • ' ooO--,,_

.- .

0•

-%

o

St -1

-1

-2 •

I

,r.ns.o I

Jan

I

Mar

I

I

May

I

I

Jul

I

' Sep

-2 I

I

I

Nov

surface

(b)SPRING

•

flux

.5

layer 1

transport

PW

layer 2

+1 PW

show

[Fieux et al. , 1996; Meyers, 1996] that the throughflowvaries in magnitudeon ENSO timescalesbetweenabout 2 and 15 Sv. An assessment of the importanceof the throughflowis given by Godfreyet al. [ 1995]. The water flux is from the westernPacific Ocean to the Indian Ocean. The Pacific .warmpool thermocline is the deepeston the planet, so that the averagetemperature

EQU

a temperature of 6ø-8øC, so that, assuminga meantransport

flux

layer 1

of the transported waterinto the Indian Oceanis about 18øC. Topographicconstraintssuggestthatthismustreturnto the Pacific Oceansouthof Australia [Hirst and Godfrey,1993, 1995] but at

surface

SUMMER

transport layer 2

1.5 PW ---1

PW

of 10 Sv, the throughflowprovidesabout0.5 PW to the Indian Ocean. From Figure 26 this number is comparableto the net surface flux over the northern Indian

Ocean and a substantial

fraction of the heat flux into the westernPacific warm pool. If thesenumbersare correct,it would appearthat the Throughflow is an integral part of the heat balancesof both the Pacific and Indian Oceans. Furthermore,as the variability of the Indonesian throughflowappearsto be determinedby the wind fields in the PacificOceanastheyare modulatedby ENSO, theexportbetween the two basins would appear as an oceanic teleconnectionon interannual

EQU WINTER

.3 PW

layer 1

transport layer 2

surface flux

.3 PW--

+1 PW

timescales.

From the discussion above,a furtherlist of questionsemerges: 1. Model results(seesection4) suggestthat duringperiodsof EQU high ENSO variance(e.g., duringthe 1970sand 1980s)the SST anomaliesin the PacificOceanare more importantin perturbing STH INDIAN OCEAN NTH INDIAN OCEAN the tropicsthan anomaliesin the other oceanbasins.The Indian Ocean anomaliesappear to have less effect on the macroscale Figure 26. Resultsof the heatbalanceof the northIndian Ocean tropics. But do these SST anomaliesplay a role in the "fine usingtheMcCrearyet al. [ 1993] oceanmodel. (a) Time evolution structure"of the monsoonsuchas the timing of the onsetor the of the oceanicheat flux acrossthe equatorinto the northIndian frequencyand occurrenceof active and monsoonbreaks? Also, Ocean. The transportrefersto the heat flux acrossthe equator what is the role of the Indian OceanduringperiodswhenENSO (positivenorthward).Transportand storagevaluesare the total varianceis small such as in the period 1920-19607 At these of both modellayers. (b) Seasonallyaveragedheat balanceof timesdo the relatively small variationsin Indian OceanSST have the Indian Oceanbasin north of the equator. Transportarrows a larger impact? indicaterelativestrengthin eachlayer. Valuesgivenin Petawatts 2. Does the Indian Oceanpossess coupledocean-atmosphere(1PW= 10]5 W). (Unpublished results fromJ. Loschnigg and dynamicssimilar to the Pacific Ocean?El Nifio like eventshave P. J. Webster,Programin Atmosphericand OceanicSciences, beenobservedin the AtlanticOcean[e.g., Tomczakand Godfrey, Universityof Colorado,Boulder,CO). Resultsare consistentwith 1994]. Do similareventsappearin the IndianOcean?There only studiesdiscussedin Godfreyet al. [1995].

14,486


appearsto onereportof a warmeventin theIndianOcean[Kapala

year and over southAsia for all monthsexceptduringthe win-

et al., 1994] and with it anomalousrainfall in eastAfrica. During ter (Figure2). Similar radiativesinksoccurover the subtropical the summerof 1961 the seasonaloceancoolingin the western high-pressure regions. The persistenceof the radiativelossand Indian Ocean was less than normal. At the same time, the SST in

the existenceof desertsare the resultsof a dynamic-radiational the easternIndian Ocean was anomalouslywarm. Furthermore, feedbackprocess.Assumingthat the atmosphere overa desertis therewere anomaloussurfaceeasterlywindsin the easternIndian dry, the heatingof the surfaceradiatesto spaceandis only miniOcean. There appearsto be only two major impactsto these mally absorbed in the atmospheric column,andthedownwelling anomalous conditions in the Indian Ocean. The summer of 1961 infraredfluxto thesurfaceis thusreduced.Eithertheatmospheric was a heavy rain year for the Indian monsoon(see Table 3a). columncontinuallycools,or the heatdeficitis madeup of adAlso, the precipitationover eastAfrica for the periodSeptember- vectionof heat from the surrounding regionsor by subsidence. Decemberwas4 standarddeviationshigherthannormal. In terms As the timescalesof the changeof the temperature structureof of ENSO, 1961 was not an anomalousyear. Whether or not northAfrica andthe Middle Eastis roughlyseasonal (i.e., deterENSO-like events in the Indian Ocean have occurred at other minedby annualcycleof seasonal heating)andtheradiativeheat times or whether the 1961 event was unique is not known. lossto spaceis of the orderof 2ø-4øCd-• [Smithet al., 1982; 3. The SST anomalies in the Indian and Pacific Oceans are Stephensand Webster, 1979, 1981], the heat loss must be balgenerallyin phaseon interannualtimescales.That is, during a ancedby the dynamicentrainmentof heat [e.g., Webster,1983b, Pacific Ocean warm event'the north Indian Ocean also tendsto 1987a, 1994; Ackermanand Cox, 1982; Blake et al., 1983; Rodbe warmerthan average.However,maximumtransportsvia the wellandHoskins,1996]. This is manifested as strongsubsidence has two roles. First, the throughflowoccurduringa coolevent,so thatif the throughflow over the desertregion. The subsidence is an importantcomponent of theIndianOceanheatbalance,there adiabaticwarmingof the subsidingair locally balancesthe diamust be a lag. How is this lag manifested,and doesit provide batic heat loss. However, the descending air mustbe balanced feedbackswhich affect long-termENSO variability? by ascentsomewhereelse. Second,the subsidingair over the desertregionsprecludesthe development of cloudsby creatinga 3.2. Land-Atmosphere Interface stable environment and thus the reduction of radiative heat loss In section 2 it was underscored

that the monsoon cannot be

understoodin terms of the local thermodynamical processesassociatedwith the precipitatingareas of the monsoon. A fuller understanding comesfrom considerationof the heatinggradients. Figure 9 showedthat the monsoonconsistedof both lateral and transverse monsoon circulations

in addition to the Walker Circu-

lationwhichmustalsobe considered an integralcomponentof the monsoon.Each of thesebranchesis associatedwith gradientsof total heatingwith strongradiationaland latent components.Furthermore,the rising parts of the circulationsoccur over the land surfacesof the pluvial regionsof the monsoon(e.g., southAsia duringsummer)or the adjacentwarm poolsof the tropicaloceans. The descendingregionsof the circulationsoccur over the ocean (see lateral monsooncomponentof Figure 9) or over the deserts (.transverse component)and, in the early springand summerin the north Indian Ocean, over very warm oceansurfaces. 3.2.1. Desert regions and the monsoon. The mostpermanent radiative sink to spaceis over north Africa throughoutthe

to space. This feedbackrendersthe desertsystemclimatically stable. This stabilityled Otterman[1974] and Charney[1975] to proposethat the arid regionswere self-perpetuating and that denudationof vegetationby overgrazingled to the extensionof arid lands [see also Sudand Fennessy,1982, 1984]. Figures27a and 27 b show schematicsof the circulationsbe-

tweenthe desertsandthe subtropical oceansandtheprecipitating regionof the monsoons.Also shownare the majorheatsources andsinksassociated with thecomponents. Figure27a is, in effect, a depictionof the processesinvolved in the transversemonsoon and the Walker Circulationof Figure 9. Figure 27b represents the lateral monsoon.

The oceanicregionsof radiativeheat lossare collocatedwith the subtropicalhigh pressureregionsthroughoutthe year. Maximum pressures occurin the high pressureregionsof the winter hemisphere,however. On the other hand, with the advanceof summer,the desertregionschangefrom relatively high-pressure zonesto local low-pressureregimes. Thus, the developmentof

(a)

100 mb

:.i H+++ 500 mb

ß

1000 mb

I SH+++ I I EVAPnil I DESERT

I EVAP++ I MONSOON

PLUVIAL

I EVAP++ I I SHsmallI SUBTROPICAL

OCEAN

I EVAP++ I MONSOON

PLUVIAL

Figure 27. Schematicof the circulationsbetween(a) the desertregionsof north Africa and the Near East; and, (b) the subtropicalocean regionsand the precipitating(pluvial) part of the monsooncirculation,respectively. The componentsof the monsoonmatchthe transverseand lateral monsooncomponentsshownin Figure 9. The dominantheatingor cooling termsare shownin the boxes. "SH" and "LH" refer to sensibleand latent heating. "RAD" and "EVAP" refer to radiationalheatingand evaporation,respectively.The plusesand minusesrepresent the signs of the processesand their relative intensity.


"heat lows" over the desertsseemsto suggestthat different processesare at play. The differencesare due in part to the character of the surfacefluxesthat occurat the desert-atmosphere and ocean-atmosphereinterfaces. Over the relatively cloudlessdesert regions, solar radiation heatsthe surface. This heat is dispersedin two ways: efficient radiationto spaceunimpededby absorptionby water vapor or cloudin the atmosphericcolumn,andturbulenttransferof sensible heat to the atmosphere.However, Smith et al. [1982] point out that enhancedlongwavewarmingtakesplacein the dustyregion below the inversion. Thus the lower part of the atmosphereis heated by a strong diurnal componentof sensibleheating, plus absorptionby dust, while the atmosphereabove the dust layer coolsto space. Turbulent transferof heat upward may extend to 500 mbar at the height of summer. The result of the boundary layerheatingis reductionof the massin thecolumndevelopingthe heat low. The interceptionof the descendingair from the largescaleinflow causesa very stronglower to middle tropospheric

AND PREDICTION

14,487

over land, the Bowenratio in the continentalregionsmay acquire values very similar to those over the ocean as latent heat fluxes increase. Thus local sourcesof water vapor are available over land as well as over the ocean and the sensible heat flux decreases

with the lowering of the surfacetemperatureof the wet land. Besidesaltering the ratio of sensibleto latent heat, the albedo of the wet land decreases to values similar to those of the ocean

surface. In addition, accompanyingprecipitationare changesin cloudinessand consequent alterationsto the surfaceandcolumnar heat budgets. Overall, the moisteningof the continentalsurface adds more degreesof freedomto the coupledstructureof the monsoon. Prior to the onsetof the monsoon,the systemcan be consideredas principallyan ocean-atmosphere systemrelativeto a heated(andnoninteractive)continent.Onceprecipitationoccurs over land, the moistland surfaceprocesses requirethat the system be consideredas a coupledocean-atmosphere-land aggregation. Unlike the ocean,the supplyof water over land is finite and dependson precipitationfrom the monsoonsystem. As the inversion. land dries out, the Bowen ratio as well as the dispositionof Over the oceanthe radiative loss to spacein the subtropicsis radiation changes. Thus hydrologicalprocessesmay impart a less than over the desertregions becausethe SST is at a lower further intraseasonal variability on the monsoonsystem. temperaturethan the continentalsurfaceand the boundarylayer 3.2.3. Snow cover. Many studieshave found a statistical is moister. Sensibleheat is relatively small, and the majority of relationshipbetween Eurasian snow cover in winter and Indian the solar radiation is either mixed into the ocean or is used in the monsoonrainfall in the followingsummer[e.g.,Hahn and Shukla, surfaceevaporation. This meansthat both the turbulentmixing 1976; Dickson,1984; Kripalani et al., 1996]. As Shukla[ 1987a] and the local lower troposphericheating is less over the ocean noted, an inverserelationshipbetweenEurasiansnow cover and than over the desert. Furthermore, the mass of the column is the summermonsoonis not implausiblebecauselarge and perdiminishedless, and the surface pressureremains as a relative sistentwinter snowcoveroverEurasiacandelay and weakenthe maximum. The heat attainedby the atmospherefrom the ocean springand summerheatingof the land massesthat is necessary is in latentform and is not releasedlocally but ratherin the ITCZ for the establishmentof the large-scalemonsoonflow. Persisregion or over the continents. In this context the oceansmay be tenceof snowalso modulatessurfacealbedo. During the spring thoughtof as a solarcollectorfor remoteregionswheredynamical and summerseasonsfollowing winterswith excessivesnow,solar or mechanical constraints invoke vertical motion and the release energy which would be available to heat the surfaceis used for of latent heat. meltingthe snowor evaporatingwaterfrom the wet soil. During the winter the desert regionsremain as net radiative Yanai and Li [1994a, b, 1996] showed that there are three sinks of the atmosphericcolumn. However, the sensibleheat distinctpeaks,near 36 and 2.25 yearsand 15 monthsin the power flux to the atmosphereis less as solar radiationdiminishes.The spectraof the monsoonintensity index defined by Websterand circulationbecomesmore similar to the oceaniccase(Figure 27b) Yang [1992], the equatorialSST and the Eurasian snow cover. with the pressureincreasingto becomea relative maximum. The quasi-biennialappearanceof tropical variablessuch as sea The subsidencein the north Indian Ocean during spring and level pressure(SLP), SST, and precipitationhas been shownby early summer appearsto be a combinedeffect of the two sets many studies[e.g., Trenberth,1975; Trenberthand Shea, 1987; of processesnoted in Figures 27a and 27 b. The semi-enclosed Lau and Sheu, 1988; Rasmussonet al., 1990]. Barnett [ 1991] ocean is surroundedby desertregionsand may come under the investigatedthe spatialdistributionandevolutionof variabilityof influenceof generallydescendingair as the continentalregions SST and SLP in the quasi-biennialand 37-year low-frequency heat. On the other hand, extremely strongconvectionoccursto periodranges.The biennialtendencyof the northernhemisphere the southof the equator[Tomasand Webster,1997], and the north snow cover has been pointed out by lwasaki [1991]. The 15IndianOceanmay be underthe influenceof its subsidence as well. monthpeak in the equatorialPacificSST hasbeennotedby Jiang Furtherinvestigationswill be requiredto test thesehypotheses. et al. [1995]. Yanai and Li [1994b] investigatedthe phase A major conclusionthat arises from this simple depiction is relationshipbetween the monsoonindex, mean SST of various that the monsoonsare integratedcirculationsystemswhich are parts of the equatorialoceans,and Eurasiansnow cover for the indelibly tied to remotecontinentalregionsas well as the oceans. 36-year and quasi-biennialperiodranges.For the quasi-biennial In the next sectionit will be arguedthat the local continental range the snow cover leads both SST and monsoonindex. The surfaceis also extremely importantin determinedthe nature of phaserelationsfor the36-yearperiodrangearemorecomplicated the monsoon. and suggestiveof two-way interactions. 3.2.2. Moist land surfaces. In general, over the tropical More recently, Yang [1996] has suggestedthe existenceof and subtropicaloceans,the Bowen ratio (the ration of sensible the inverse relationshipbetween Eurasian winter snow cover heat to latent heat flux) is very small. Latent heat fluxesare of and rainfall over India duringthe subsequent monsoonseason. theorderof order100to 150W m-2compared to sensible heat However, a precursorsignal for Eurasiansnowfall was found in

fluxes of order5 to 10W m-2,givinga Bowen Ratioof between the SO1,and evidencewas foundthat the inverserelationship 0.1 to 0.05 [Hastenrath, 1987, 1994; Websterand Lukas, 1992;

tends to break down during certain periodsof ENSO. It was Webster,1994]. Over desertregionsthe Bowenratio may climb concluded that ENSO has a direct link on the Eurasian winter to 100 during the summerat the time of peak solar radiation. snow cover. Within this scenario the snowfall over Eurasia is However, with the onset of the monsoonand with precipitation seenonly as a link. Thereforethe ultimaterelationshipexists

14,488


between ENSO and the monsoon rather than between the snow cover

AND PREDICTION

During the winter (see Murakami [1987a] for a detailedre-

and the monsoon.

view), the Himalayas-Tibetan Plateaucomplexactsas a major mechanical barrierto theextratropical westerlies producing strong 3.3 Mechanicaland Thermal Impacts of Orography stationary eddiesin the seasonally averagedflow [e.g.,Peixoto The Asian-Australian regioncontainstwo orographicbarriers and Oort, 1992]. The mountainsalso modifythe subseasonal that appearto have significantinfluenceon the structureof at- timescale.To the eastof the Himalayas,the steepterrainactsas mosphericflow. Thesemajorbarriersare the Himalayas-Tibetan a naturalduct for edge waves. Thesecold surgesare dynamic of the outpouringsof cold air from northeastern Plateaucomplexand the east African mountains(Figure 1l a). manifestations Asia as a combinationof Kelvin and atmospheric shelf waves Both barriersappearto act as barriersto flow. There are also local mountainrangessuchasthe Ghatsandthe Burma(Myanmar) [Tilley, 1990; Compoet al., 1997]. Withoutthe existenceof the the influxof cold air into the tropicswouldnot penemountainrangethat causemajor local variationsto the monsoon. mountains Althoughnot evidentin Figure1l a becauseof their spatialscale, trate as far south,would be farther to the east, and would be more [Tilley, 1990]. Thereforeduring the highlandsof Indonesiaand New Guinea are of considerable modifiedby oceanicprocesses winter it is equallyimportantto model the mountainswith care importanceto the large-scalecirculationof the tropics. by Reynoldset al. [1994], 3.3.1. Himalayas and the Tibetan Plateau. The Tibetan and precision.This is underscored Plateauextendsoverthelatitude-longitude domainof 70ø-105øE, who showedthat the southAsia mountainrangesare a major 25ø-45øN, with a mean elevationof more than 4000 m abovesea

source of internal error in numerical models.

The dominating roleof theHimalayascanbe seenmostsimply level. Surfaceelevationschangerapidlyacrossthe boundaries of the Plateau,especiallythe southernboundary. Strongcontrast by a comparisonof summermonsoonsof southAsia and north existsbetweenthe easternand westernpartsof the Plateauin Australia. In the absenceof a mountainrangethe precipitation both landcoverfeaturesand meteorological characteristics [e.g., over northAustraliadecreaseslinearly towardthe centerof Austhe temperature anomalyoverthe Australian Ye et al., 1979; Smith and Shi, 1995]. At these altitudes the tralia. Furthermore, massof the atmosphereover the surfaceis only 60% that of continent is far smaller than that associated with the summer monsea level. Becauseof the lower atmospheric densities,various soon(seeFigure6). Absentis the broadmaximumof precipitathe radiativeprocesses overthe Plateau,particularlyin the boundary tionfoundoversouthAsia. Althoughit is difficultto compare layer, are quite distinctand dominantcomparedto thoseover two monsoonsystems(the sizes of the continentsare different, lower elevatedregions[e.g., Liou and Zhou, 1987; Smithand Shi, and Australiais locatednearerto the equatorthan southAsia), the similarityof the latitudinalprecipitationdistributionto that 1992; Shi and Smith, 1992]. The importanceof the Tibetan Plateau as an elevated heat foundby Hahn and Manabe [1975] in their nonmountaincaseis source for the establishment and maintenance of the Asian sum-

mer monsooncirculationhas been discussedby many authors

compelling.

Althoughsubstantial progress hasbeenmadein understanding

(see, e.g., Ye et al. [1979], Gao et al., 1981; Murakami [1987a, b], He et al. [1987] and Yanaiet al. [1992], for reviews). Flohn

the role of the Tibetan Plateau in the Asian summer monsoon and

contributions from the released latent heat of condensation. In the

in determining howthe diurnalvariations is bestparameterized

the heatingmechanism overthe Plateau,manyquestions remain. 1. The relative significanceof the sensibleheat flux and the [1957] was first to suggestthat the seasonalheatingof the elevatedsurfaceof the TibetanPlateauandthe consequent reversal radiativeflux [e.g., Smithand Shi, 1992, 1995; Shi and Smith, fully the of the meridionaltemperature andpressure gradientssouthof the 1992] needsto be examinedfurther. To understand thatcarriessensible heatto thedeeptropospheric layer Plateautriggerthe large-scalechangeof the generalcirculation mechanism over east Asia and the monsoon onset burst over the Indian subduringthe dry pre-onsetperiodwill requiredirectmeasurements continent. of convective elements in the boundary layerby remotesensing To isolatethe heatingprocesses duringthe periodswithout techniques. 2. Fu and Fletcher [1985] showed that the interannual appreciable rainfallandduringperiodsaffectedby precipitation, rainfallwashighlycorrelated with Yanaiand Li [1994a] examinedthe time seriesof the daily- variabilityof Indianmonsoon averagedandverticallyintegratedheatsource andmoisture that of the thermal contrast between the Tibetan Plateau and the that sink andthedailyprecipitation rateP for centralandeastern equatorialPacificOcean. Li and Yanai[1996] demonstrated regions of the Tibetan Plateau. The calculationsfor the two thetimingandlongitudinalextentof thereversalof themeridional gradientsouthof the TibetanPlateauvary yearby regionsindicatedthattherewerevastdifferences in themagnitude temperature andtimingof processes fromonepartof thePlateauto another.In year perhapsbecauseof SST variations in the western Pacific the centralPlateau,largevaluesof appearing in May and Ocean[FuandFletcher,1985].However, theroleplayedby the early June were accompanied by insignificantvaluesof interannual variations of thesurface andtropospheric temperatures and very little precipitation.In this region,significantamounts over the Tibetanplateauin the variationof the Asian monsoon of precipitationoccurredonly after late June. Before the onset hasnot beenstudiedsystematically. of the monsoonrains, large valuesof were noted. After 3. Althoughthe strongdiurnalvariabilityof themoisture and the onsetof rains the valuesof generallydecreased,but heatfluxesmustrectifyto produce longer-term variability suchas in whichthisrectification takesplace the timingof peaksin the and seriescorresponded seenin Figure3, themanner knowledge of theseprocesses isimportant well to eachotheras well as to thosein precipitation indicating isnotclear.A detailed easternPlateau,appreciable precipitation hadoccurredalreadyin in models. May. However, the valuesof were mostly negativein 3.3.2. The East African Highlands.The FindlaterJet(see May, suggesting largeevaporationexceedingprecipitation.From Figs. 8 and 14) is an integralfeatureof the coupledoceanJuneandonward,copiousrainsfell in thisregion,andthe values atmosphere monsoonsystem. Besidesbeinga criticalelement and time variationsof becamesimilarto thoseof , in drivingtheSomaliCurrent[Knox,1987]andthusbeinga key showingthat the releaseof latent heat of condensationwas the elementin cross-equatorial oceantransports, the FindlaterJetis dominantmechanismof heatingover the easternPlateau. responsible for a largepartof theatmospheric transport of water

WEBSTER ET AL.: MONSOON PREDICTABILITY AND PREDICTION vapor acrossthe equator.The jet is also an importantcomponent of the winter circulation,althoughat this time of year it is not as intenseas during summer. The jet also exhibits variability on many timescalesand is a keen reflectorof the variability of the interhemisphericmonsoonvortex and the active and break periodsof the monsoon[e.g., Krishnamurtiand Bhalme, 1976]. The strengthof the Findlater Jet shouldhave strongimpactson the ocean. A weakjet, for example,wouldbe expectedto alter the SST distributionof the northIndianOceanby reducingupwelling, Ekman transport,and evaporation. The early Findlater studies[Findlater, 1969a, b] were supplemented during the WCRP Summer Monsoon Experiment (MONEX, 1979). The locationof the jet can be inferred from Figure 8 althoughthe coarse scale of the contouringdoes not indicate its real intensity. The jet is centeredaround 1. 5 km

14,489

3. In regionswherethereexistsa strongcross-equatorial pressuregradientsuchas in the African and Americanmonsoonregions in the boreal summer,and the Indian Ocean in the boreal winter and the southIndian Ocean during the boreal winter and observation1 is met, the organizedconvectionis locatedin the summerhemisphere some5ø-10ø fromtheequator(depending on the magnitudeof the pressuregradient),usually on the equatorward side of the minimum sea level pressureand the maximum SST.

4. In regions of extremely strong cross-equatorialpressure gradient such as the Indian Ocean during the boreal summer,a hybrid stateappearsto exist. Observations1-3 are evident,but low-frequencyvariationsof convectionoccuron the timescalesof active and break periodsand not on the shortertime scalesnoted in the regionswith smaller cross-equatorial pressuregradients. andmaximum corespeeds of 10-15m s-1 extending fromthe Convectionappearsto locate near the equatorialtroughor over northerntip of Madagascarto the centralArabian Sea. the monsoontrough. There have been many studiesattemptingto understandthe Relative to observation3, Tomnas and Webster[1997] found sigphysical processesthat determinethe location and structureof naturesof inertial (symmetric)instabilityin the cross-equatorial

the Findlater Jet [Anderson, 1976; Hart, 1977; Bannon, 1979a,

flow, which were consistent with the ideas of Kuettner and Unni-

b; Krishnamurtiand Wang, 1979]. The first four papers are theoreticalstudiesthat liken the jet stream to oceanicwestern boundarycurrentswith the East African Highlandsas the western boundary. Krishnarnurtiand Wang [1979] and Krishnarnurti et al. [1990] modeled the baroclinic boundary layer of the western Indian Ocean driving a cross-equatorialflow against the model westernboundaryby an imposedvertically varying pressuregradientforce. In each of the studiesthe structureof the jet streamis modeledfairly well. Perhapsthe mostimportantresultof thesestudiesis the setting of model vertical and horizontalresolutionrequirementsfor the adequaterepresentation of cross-equatorial flow. If the scalesare not fine enough,the cross-equatorial flow will not be concentrated in the westernIndian Ocean but may spreadacrossAfrica and effectively disperse. Such was the casein early low-resolution generalcirculationexperiments[e.g., Washingtonand Dagupatty, 1975]. In coupled ocean-atmosphere experimentsa diminished

nayer[ 1981] and Walliserand Somerville[ 1994]. The divergent componentof the flow was a maximum at the line of zero potential vorticity (demarkedas the thick contourin Figure 8). In regionsof strongcross-equatorial pressuregradientthe zero po-

Findlater

Jet would

be a critical

omission

as it would

drive an

inadequateSomalia Current and would probably lead to major changesin the heat balanceof the north Indian Ocean.

tentialvorticityline lies some30-7ø polewardof the equatorin the summerhemisphere.Divergencelies on the equatorialsideof the zero line with convergenceon the polewardside. Convection is collocatedwith the convergence.Furthermore,the rotational wind is a maximum to the north of the zero potential vorticity contour. Tomnas and Webster[1997] argue that all of these featuresare consistentwith inertial or symmetricinstability. In regionsof moderatecross-equatorialpressuregradientthe convectionappearsconstrained to one latitudebelt. However,in the Indian Ocean in summerthe convectionappearsto have two majorlocationsandoccasionally undergoes propagation poleward into eachhemisphere.it is clearthatthe simpleinertialinstability argumentsexplainthe dispositionof convectionduringthe Asian summermonsoon.Quitepossibly,sometypeof hybriddynamical instabilityexistsin this complexstate. 4.

3.4

Locations

of Monsoon

Convection

Monsoon

Process Studies With

Models

Atmospheric general circulation models (GCMs) are well suitedfor the investigationof processes that determinethe characterof the monsoon.As the qualityof GCMs improve,they are increasinglyableto addressthe questionof how regionalclimate,

The necessary but not sufficientrule of Riehl [1979] was that organizedconvectiononly takes place in the tropicswhen the SST is >27øC. While the rule is generallytrue, Figures8, 12, such as would be associated with monsoon rainfall and circu15, and 25 indicatethat the distributionof convection,especially lation anomalies,respondsto imposedSST anomalies. At the in the monsoonregions,is far more complicated.However,it is same time, simpler mechanisticmodels and theoreticalstudies, possibleto make someobservations regardingwhereconvection especiallyused in tandemwith GCMs, data analysis,and emdoes occur and from this make a first attempt at determining pirical and diagnosticstudies,allow thoughtfulinvestigations of processes. particularprocesses and the testingof hypotheses.In the follow1. The SST mustbe sufficientlywarm (i.e., >27øC)andthe ing paragraphs,examplesof monsoonproblemsthat have been atmospheric structureso configuredthat the atmosphere is condisuccessfully investigatedusinga broadrangeof modelswill be tionallyunstable.Thus very warm SSTs,suchas thosefoundin discussed. the north Indian Ocean,are not sufficientto produceconvection becauseof the stabilizingeffect of the large-scalesubsidence. 4.1. Influence of SST Anomalies on the Monsoon 2. In regions where there is a small or negligible crossStudyingthe impactof prescribedSST anomalieson the monequatorialpressuregradient(e.g., the centralPacificduringJuly in Figure 8) and where observation1 is met, equatorialconvec- soonclimatethroughcoordinated atmospheric GCM integrations tion is found in the regionsof warmestSST. In theseregionsthe was one of the principaltasksof the TOGA MonsoonNumerical convection,warmestSST, and the low-level pressuretroughare Experimentation Group(MONEG).As a focusof study,MONEG collocated. Such regionsare the westernPacific Ocean in the choseto investigate the monsoonseasons of June-July-August boreal summer and the eastern Pacific Ocean in austral summer. 1987 and 1988. As discussed in Krishnamnurti et al. [1989a, b]

14,490


these years were of particular interest for their contrastingbehavior. On the one hand, 1987 was a severedroughtyear over both India and the African Sahel. On the other hand, 1988 was

an aboveaveragemonsoonseasonfor India, while rains over the Sahel were closeto their long-termclimatologicalmean. In the first phaseof coordinatedexperimentation,17 atmosphericmodeling groupsran 90-day integrationsusing the prescribedobservedglobalSST fieldsfor 1987 and 1988 asboundary forcingandatmospheric fieldsfrom operational numericalweather predictionanalysesfrom June 1, 1987, and June 1, 1988, as initial conditions.Theseare referredto as the MONEG integrations; full resultsfrom theseintegrationsare discussedWCRP [1992]. One of the major disruptionsto the globalclimateduringthese years was associatedwith ENSO, which abruptlyswungfrom a warm phasein the summerof 1987 to a cold event in 1988. The differencein SST betweenthe summersof the E1 Nifio year of

culationfieldsare shownin termsof 200 mbarvelocitypotential and streamfunction. Thesediagnostics give a "coarse-grained" measureof monsoonactivity,andcomparedwith morefine-scale structureoverindividualcountriesaffectedby themonsoons, most modelsin the MONEG setshowedsomeskill in simulatingto a large degreethe observedinterannualvariabilityin thesefields for 1987 and 1988.

Figures28a and 28b showthe differencein velocitypotential andstreamfunctionbetween1988and 1987fromECMWF operationalanalyses.Figures28c and 28d showthe model-simulated

fields. The patternof enhanced upperdivergencein 1988 over the IndianOceanarea(andreduceddivergenceoverthe Pacific) is fairly well simulated in the model,as is the reduction of upper tropospheric westerlies,particularlyover SouthAmerica,the Atlantic,andAfrica. Therearesomediscrepancies withtheanalyses, for example, in the streamfunction fields over the western

1987 andthe La Nifia yearof 1988 provided4øC maximain the Pacific.Whethertheseareassociated withmodelerrorsor analyeasternequatorialPacificflankedby -1 øC valuesnorthandsouth siserrorsis not knownat present.Figures.28e and28f indicate, of the equator.Other differencesin SST are apparentaroundthe that,in termsof thesecoarse-grained diagnostics the atmosphere globe,althoughthey are muchsmallerin the Indian Ocean,which tends to be in phase with interannualvariationsin the central Pacific at least in the past few decades.The ability to simulate the basicmonsoonclimatologyin a GCM is not a trivial matter, and many of the modelscontributingto the MONEG coordinated experimentation showedsignificantclimatedrift, often resulting in rather weak monsoonrainfall over some land areas (such as India).

Figures28 and 29 showa fairly typical set of resultsfrom the setof MONEG-coordinatedintegrationsusingtheECMWF model [Palmer et al., 1992]. In Figures28 and 29 the atmosphericcir-

is not particularlysensitiveto atmosphericinitial conditions.In

particular,it showsthatdifferencefields(basedon coarse-grain diagnostics)betweentwo integrationsrun with the sameSSTs, but with differentinitial conditions (1 day apart),are very much smallerthan the differencefieldsin Figures28c and 28d. Overall, this model, typical of many within the MONEG experimentation set,was ableto reproducemuchof the observed coarse-grained interannualvariabilityin the monsoonareasfor 1987 and 1988, andtheexperimentation indicatedthatthelevel of skill wasobtainedthroughthe underlyingSST anomalies, rather than throughthe atmosphericinitial conditions. This result is

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Figures 28a,28c,and28eshowvelocity potential (contour interval lx106m2 s-:).Figures 28b,28d,and28fshow streamfunction(contour interval3x106m2 s-i). FromPalmeret al. [1992].


14,491

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Figure29. June-August 200-mbardifferences between 90-dayintegration withobserved SSTsfrom1987in specifiedregion,climatological SSTselsewhere, and90-daycontrolintegration withclimatological SSTseverywhere. Thespecified regions are(a, b) tropicalPacific,(c, d), IndianOcean,(e, f) tropicalAtlantic,and(g, h) extratropics. Diagnostics andcontourintervalarethe sameasFigure28. FromPalmeret al. [1992].

entirelyconsistent withtheCharneyandShukla[ 1981] hypothesis dissimilarto one another). On the basisof the resultsin work by that mostmacroscalevariabilityin the tropicsis determinedby Palmeret al. [ 1992], the responseof theECMWF modelto Indian variations in the state of the boundary.

and Atlantic Ocean SST difference fields (between 1987 and

It is importantto assesswhich of the world's oceanscontributedmostto the simulatedcoarse-grained response(compare Figures29c and 29d). Figure29 showsthe 200 mbarvelocity potentialand streamfunctiondifferencebetweenrunswith observedSSTs(for 1987) in specifiedoceanicregionsand climatologicalSSTselsewhereand a run with climatological SST everywhere (the "control"integration).In Figures29a and29b the specified regionwhereobserved SSTsareusedis thetropical PacificOcean;in Figure. 29c and 29d it is the tropicalIndian Ocean;in Figures29e and29f it is the tropicalAtlantic;andin

1988) was much weakerthan the responseforcedby the Pacific Ocean SST anomalies. The role of interannualvariability in the Indian Ocean on the Asian monsoonremainsto be completely elucidated.However,the MONEG experimentation indicatedthat it is likely to be weakerthan the remoteeffect of PacificOcean

SSTs,at leastduringENSO yearsandat leastduringtheparticular phaseof the interdecadalvariabilityof the period. Sincethe MONEG integrationswerecompleted,Ju and Slingo [1995] have studied the role of Pacific Ocean SST anomalies on the Asian summer monsoon in more detail.

These authors

Figures29g and29h it is the extratropical oceans.The results concludethat duringLa Nifia years,warm SST anomaliesin the and 29d is associated with the observed SST differences in the

tropicalnorthwestPacificmay be of more directimportancein influencingthe Asian summermonsoonthancold equatorialSST

tropical Pacific Ocean.

anomalies in the central and eastern Pacific. These results leave

indicatethat,overwhelmingly, theresponse shownin Figures29c

Figure29 does,in fact,showthattheobserved SSTanomalies unansweredtwo basic questions: in the Indian and Atlantic Ocean do have some impact on the

1. What impactdo the oceanshave on the monsoonduring

atmosphere over the Indianand AtlanticOceans,respectively. other yearsin which ENSO is either absentor has a character However, it shouldbe notedthat the SST anomaliesin theseocean

different from the 1987-1988 episode?

basinshavea substantial interdecadalcomponent(i.e., the Indian

2. What is the impact of SST anomalieson more regional diagnostics suchas country-wideseasonalmeanrainfall. From

and Atlantic Ocean SST anomalies in both 1987 and 1988 are not

14,492

WEBSTERET AL.: MONSOONPREDICTABILITY AND PREDICTION

a practical forecasting pointof viewtheselatterfine-grain mon- theSSTwasfixedat March1 climatological values through the soondiagnostics are obviously of moreimportance thanupper courseof the integration. troposphericvelocity potential. Thesimulated anomalies (relative to thecontrolintegration) of the S and SST integrations wereanalyzedfor the boreal 4.2. Annual Cycle of Solar Heating of the Land and the summerperiod.The JJAmeanprecipitation anomalyfor the S Ocean integration isshown inFigure 30a,andtheJJAmeanprecipitation The annualcycleof thesolarforcingandtheassociated heat- anomaly for theSSTintegration is shown in Figure30b.In both thereis a dramaticreductionin the monsoon rainfall ing of thelandmasses is generallyconsidered to be the mostim- integrations, portantdrivingmechanism for the monsoon system.However, overthe ArabianSea,India,the Bay of Bengal,andsoutheast observations showthat with the progression of the seasons, the Asia. This reduction reaches a magnitude of 16 mm d-• over regions of warmest SST in the Indian and Pacific Oceans also advance northward. Does the annual march of SST also have a

Bangladesh in bothintegrations. Thereis alsoa nearlycomplete

tion,ShuklaandFennessy [1994]performed experiments witha GCM in whichthe solarforcingof the landandthe oceanwere incorporated separately.

cially importantfor the establishment of the monsooncirculation

collapseof the monsoonflow and the SomaliJet for both the S rolein theestablishment of themonsoon? To studythisques- and SST integrations(not shown).

Theseresults showclearlythattheannualcycleof SSTis cru-

andrainfall.Thisis particularly relevant forthemodeling of the coupleclimatesystem.If a coupled ocean-atmosphere modelis gratedthroughtheborealsummer, endingon September 1. The notcapableof simulating theobserved annualcycleof SST,the controlintegration wasinitializedon January1, 1987,anduses simulated monsoon circulation couldbehighlydeficient. prescribed seasonally varyingclimatological SSTandseasonally 4.3. Land Surface Processes varyingsolarforcing.The fixedSun(the"S" experiment) integration wasinitializedon March1, 1987,andusesprescribed Thereare two classes of candidate processes thathavebeen seasonally varyingclimatological SST,butthesolarforcingwas proposedto explainwhy thereare breaksin the monsoon.The fixedat March21 valuesthroughout thecourse of theintegra- first relatesto influencesfrom other locationson the monsoon tion. The fixedSST("SST")integration wasinitializedonMarch region[e.g.,Krishnarnurti and Bhalrne,1976;Krishnarnurti and 1, 1987,andusesnormalseasonally varyingsolarforcing,but Ardanuy, 1980; Yasunari,1987]. The secondset of theories Three integrationswere carried out, all of which were inte-

'

[

o[ so[ •o[ •o[ sa[ •[

25N

•o•[ •b[ no[ •5o[..... •"•o [ •[ .....

.....

•2-

.. '

10S• Figure 30. Boreal summer (June-August) precipitation anomaly for(a)fixedSun(S)and(b)fixedSST(SST) experiments. Contours are• 1, 2, 4, 8, and16mmday -•. Dashed contours arenegative, andareas below -2

mmff•areshaded. Integrations aremade using theCenter forOcean-Land-Atmosphere Studies (COLA) model.

From Shuklaand Fennessy[1994].


AND PREDICTION

14,493

[Webster,1983a; Goswamiand Shukla, 1984; and Srinivasanet al., 1993] describethe active-breaksequences as being internal oscillationsof the monsoonsystemitself. 4.3.1. Moist processes.The impactsof the stateof the continental surfacehave been studiedthroughthe use of GCMs. Many of thesestudieshaveconcentrated on the westAfricanSahel followingCharney[1975]. The impactof changesin albedo

surface.The Bowenratio, initially very high,dropsappreciablyin the vicinity of convection.Likewise,the solarradiationreaching

moisture on the state of the Indian monsoon. These studies draw

al., 1993].

the surface decreasesas well (because of associatedcloudiness

increases),decreasingthe surfaceheatingand the sensibleheat flux into the column. To the north,the solarheatingremainslarge, and the sensibleheating of the atmospherecontinues. That is, polewardof the convection,the Bowenratiocontinuesto be high. on precipitation wasconsidered by Chervin[1979] andSudand As a resultof the heatingandthe verticalvelocitybecomingout of Fennessy [1982]. Their resultstendedto supportCharney'shy- phase,the regionof continentalconvectionwill movenorthward. pothesisof an inversecorrelationbetweenalbedoand rainfall. In summary,thesechangesin the continentalsurfaceheatbudget The impactsof soil moistureand vegetationhavebeeninvesti- were used to explain the northwardpropagationof convection gatedin a numberof modelingstudies[Walkerand Rowntree, first notedby Sikkaand Gadgil [1980]. The basictimescalesof of the convectionare setby the surfacerecovery 1977;Shuklaand Mintz, 1982; Sudand Fennessy,1984;Xue and the propagations Shukla,1993]. Xue et al. [ 1994] consideredthe impactof ground time [Webster, 1983; Goswami and Shukla, 1984; Srinivasan et one common conclusion. The surface characteristics of the con-

tinentallandmasses were of greatimportancein determiningthe structureof the monsoons,and there was particularsensitivityto soil moisture.That is, soil moistureis an activecomponentin the evolutionof the monsoonsystemand a componentthat requires

4.3.2.

Influence

of snow cover.

Anomalous

land surface

conditions(e.g., snowcover and soil moisture)appearto influence the seasonalland-oceandifferential heating, and possibly influencethe Asian summermonsoonsystem(e.g., Hahn and Shukla [1976], Dickson, [1984], and many others). Modeling

careful modeling. studies[Barnett et al., 1989; Yasunariet al., 1991; Vernekaret Websterand Chou [1980b] suggested that moist land-surface al., 1995] demonstratedthat albedo and hydrologicaleffects of processes could introducefeedbacksresultingin intraseasonal snowcovermay be responsiblefor the anomalousseasonalheat-

monsoonvariability. Models simplerthan GCMs were used to studycomplexprocesses involvedin the interplaybetween moistsurfacehydrological processes andthemonsoon circulation. For example,Webster[1983a], Srinivasanet al. [1993], and Dixit [1994]useda simplezonallysymmetricatmospheric model coupledto a mixedlayeroceananda simplesurfacehydrological system.The hypothesis originallytestedby Webster [1983a]was thattheinterplaybetweengroundhydrologyandthe atmospheric circulationdid not allow the systemto reachan equilibriumand that the northwardpropagations of convectionof the order of 20-30 day period notedin Figure 15 were the result of this instability. Similar resultswere found by Nanjundiahet al.,

ing of the atmosphere.Barnettet al. [1989] suggested that the anomalousexcessivesnowcoverover Eurasiamay triggerENSOlike conditionsin the equatorialPacificby meansof a weakened summermonsoonand intensifiedequatorialwestefiies.The SST field in the modeldevelopeda weakE1Nifio structurein theequatorial Pacific. Their resultsdemonstratethe importanceof land

processes in globalclimatedynamicsand their possiblerole as one of the factorsthat could trigger ENSO events. Yasunariand Seki [1992] found significanttime-lag relations betweenEurasiansnowcoverin borealspring(April), the Indian summermonsoonrainfall, and the SSTsin the equatorialwestern

Pacificin the succeeding winter. The seasonalhemispheric circulationanomaliescompositedfor strong(weak) Indianmonsoon Thereasonfor propagation of convective zoneswithinteractive yearsshowanomalous stationarywavepatternsin theextratropics surfacehydrologymay be seenrathersimplyby considering the that may be forcedby the anomalouscoupledmonsoonsystem first law of thermodynamics in autumnto winter. This, in turn, may feed back to producea more(less)extensivesnowcoveranomalyoverEurasialeading to the weak (strong)monsoonfor the followingsummer. Webdt Cv sterandYang[1992]foundlarge-scald circulation patterns that were precursors to strongand weak monsoons.Thesepatterns, whereT is thetemperature, cois theverticalvelocity(dp/dt), $ which persistedthroughthe winter prior to the anomalousmonisa measure of thestatic stability, and• isthediabatic heating soon,may be consistentwith the circulationpatternsof Yasunari rate in the column. If the systemis in steadystatethen the and Seki [1992]. diabaticheatingor coolingmustbe balancedat all locationsby Using resultsfrom a 70-year integrationof coupledoceanadiabatic processes (i.e.,w•- 0). Suchwould bethecase if atmospheregeneralcirculationmodelexperiments,Meehl [ 1994b] thesystem weresimplydrivenby therelease of latentheatin the demonstrated a very similar biennialcycle of the coupledmoncolumn. The location of the vertical motion maximum will be a soonsystemin concertwith the extratropicalflow regimes. In functionof the variationof solarheatingunlessdynamics(e.g., this biennial cycle the combinedeffect of anomalousconvecinstabilities)or surfacecharacteristics do not feed back to force tion over the Asian monsoon and African monsoon is stressed • andthevertical velocity fieldto become outof phase. Thus, as importantfor producingthe circulationanomaliesin the extraover the ocean,wherethe thermalinertiais large,the locationof tropics(Figure 31). Meehl [1994b] also suggestedthat cold air convectionshouldbe slowly varying. Over land, wheresurface advection(and the subsequentlycooled surface)prevailing over characteristics mayvarymorequicklythanovertheocean,equally the Eurasiancontinentin winter may be more importantthan the rapidchanges in the surfaceheatfluxescanoccurwith ensuing effect of anomaloussnow cover itself for producinganomalous changes in convection. Theheatbalanceat thecontinental surface monsoon and convection in later seasons. Yasunari [1989] noted a role for the east Asian winter monis madeup by a combinationof net radiativeheatingand the turbulent fluxes of sensible and latent heat. Before convection soon in the global-scaleTBO throughstrongnegativecorrelaoccurs,solarradiativeheatingdominates,and the Bowenration tion betweenthe Indian summermonsoonand the following SST is large. Once convectioncommences (e.g., near the coast), anomalyin the SouthChina Sea. They arguethat the SST anomprecipitation produceschangesin the moisturebalanceat the aly is indicative of strengthof the east Asian winter monsoon [1992], using the same model.

dT w•--•

(5)

14,494


A

DJFo

B

JJA o

Warm

Warm SST

Cool SST

Australian monsoon,

C

DJF+• •

D

JJA+•

L•'

Cool SST

Warm SST Australian

Figure 31. Schematicevolutionof the biennialcomponentof the monsooncirculationfrom (a) the winterbefore a strongAsianmonsoonthrough(b) the strongmonsoonseasonto (c) the northernwinterafterthe strongmonsoon beforea weak monsoon,to (d) the followingweak monsoon.Reprintedwith permissionfrom Meehl, J. A., Coupled ocean-atmosphere-land processes and southAsian monsoonvariability,Science,256, 263-267, 1994. Copyright 1998, American Association for the Advancement of Science.

surge.That is, a strongersouthAsian summermonsoonis likely numericalexperimentsin which large-scaleupliftsof the Tibetan to producea strongereastAsianwintermonsoonand vice versa, Plateau were linked to the climatic changeson the geological presumablythroughsome form of atmosphericteleconnections timescaleelucidatedthe effects of the Plateauon the planetary[Yasunariand Seki, 1992] and associatedland surfaceprocesses (e.g., snowcover) over the Eurasiancontinent.The SST anomaly in the southChina Sea thus producedin winter, and persisting throughthe followingspringand early summer,may initiatereversedanomaliesof convectiveactivity in the equatorialwestern Pacific. This surmiseis corroboratedby Matsumotoand Yamagata [ 1991], who foundthatthewindstress associated with surges in the winter monsoonis consistentwith changesin the western Pacific SST betweenwinter and the following boreal summer.

scale circulations [Kutzbach et al., 1989; Manabe and Broccoli, 1990].

Beyondisolatingimportantphysicalprocesses andillustrating the role of the Himalayas-Tibetan Plateauas a majormodifierof the northernsummermonsoonsystem,Hahn and Manabe [1975] and others establishedthat general circulationand prediction modelsmustcontaina careful configurationof orography.With the adventof coupledmodels,the configurationwill have to be even more precise. The Himalayasare also the sourceregions of the major river systemsof southAsia, which are, in turn, 4.4. Monsoon and Orography responsiblefor the flux of fresh water into the north Indian Severalnumerical[e.g., Hahn and Manabe, 1975; Kuo and Ocean [e.g., Knox, 1987; Tomczakand Godfrey, 1994] and the Qian, 1981, 1982; Chenand Dell'Osso, 1986;Kitohand Tokioka, stabilizationof the upperocean,particularlyin the Bay of Bengal. 1987; WCRP, 1992] as well as laboratoryexperiments(Ye et al., The modelingof the mountainranges,their influenceon the water role in the salt budgetof the oceans 1974; Chenand Li, 1982) were performedto clarify the thermal balance,and the subsequent and orographiceffectsof the TibetanPlateauin determiningthe is a major challengefor the future. characteristicsof the monsoon. The overall importanceof the 4.5. Influence of the Monsoon on ENSO orographyon the monsoonhasbeendemonstrated by Fennessyet Numerous studies have been used to test the conclusion of al. [ 1994] who found that replacementof an enhancedsilhouette orography by a meanorography wasmorerepresentative of actual Normand [1953] that anomalies in the monsooninfluence the have barrier heights. This formulationof orographyproduceda more amplitudeand phaseof ENSO. To date,theseexperiments realistic simulation of monsoon rainfall. In addition, a series of been performedusing simple modelsin contrastto the reverse


(a)

-'

30,000 km

14,495

• 40N

20N

"Nino" regions

PACIFIC OCEAN

20S

40S

•

Variable Amplitude Monsoon

"•

32

31

3O

29

28

27

26

25

•-24 E

15,000km

•

Stochastic Amplitude Monsoon

23

!- 22

21

-

....

2o

+'

0

trong) (standard)

40

Nino 4 Nino 3 Nino 2

-12%

17

18

30

-

.....

19

50

60

10_

20

(b) Time(years)

30

40

50

6O

(C) Time(years)

Figure32. Coupled ocean-atmosphere modelindicating thatthemonsoon canaltertheperiodof warmevents in thePacificOcean.(a) The modeldomainwhichconsist of an IndianOcean,separated froma PacificOceanand surrounded by an AsianandAfricanContinent. Thecoupled system is drivenby an annualcycleof heating.(b) Theresponse of themodelNifio3 regionforstrong, standard andweakmonsoon heating overlandduringyears30 through 60 of theintegration. Astheamplitude of themonsoonal heating increases, theperiodof theENSOcycle increases. (c) Theresponse of themodelNifio3 regionto stochastic forcingof themonsoon. The SSTresponse shows a more chaotic structure. Results from Wainer and Webster [1996].

matchedestimates experiments (the influenceof ENSO on the monsoon),which soonforcing.Valueschosenfor theexperiment heatingdetermined from observations [Wainerand haveutilizedfull atmosphere GCMs. The latterexperiments were of monsoonal described in section 4.1. Webster,1996]. Figure32b showsthat as the monsoonforcing Matsurnato and Yarnagata [ 1991] modeledthe originof ENSO becomesstronger,the periodof ENSO becomeslonger. On the other hand, relative to weak monsoonforcing,the ENSO period forcingwasdeveloped with charWebster[1995] and Wainerand Webster[1996] used a simple shortened.Finally,a stochastic acteristics that matched the observed variability of the monsoon. coupled ocean-atmosphere modelwitha PacificOceanandanInperiod.The model dianOceansurrounded by an "African"andan "Asian"continent. Figure32c showsthe impactof the stochastic an averageperiodsimilarto thatwith theunperThe PacificOceanandthe IndianOceanwere separated by a thin ENSO possesses impermeable wall (Figure32a). The model,drivenonlyby the turbedmonsoonforcing. However,the responseis alsochaotic

in the Pacific Ocean and the role of monsoonforcing on ENSO.

annualcycleof the Sun,exhibitedinterannual variabilitywhich with standardparametersexhibiteda periodof about4 years. The amplitude of themonsoon heatingwasparameterized sothat it was possibleto alter its phaseand magnitude.The model ENSO provedto be very sensitive to the strengthof the mon-

with periodsin betweenwarmeventsas shortas4 yearsandas long as 10 years. Within the context of an extremely simple surrogateof the

naturalsystem,it wouldappearthat the strengthof the monsoon playsanimportant rolein ENSO,at leastasa perturbing factor.It

14,496


AND PREDICTION

shouldbe bornein mind, however, that the full cycle of interaction An importantquestionarises;what is the origin of the spread was not allowed in these integrations,and the modified ENSO betweenthe models? For example, if a single model were incycle in the model did not feed back to alter the monsoonal tegratedfrom different initial conditions,would the same level heating. of intraensemble spreadbe apparent,or doesthe level of spread reflect model-formulationdifferencesonly. After all, the Indian 4.6. Modeling Issues Oceanregion is extremelycomplex(see Figure 1la), and largeThe ability of a model to investigateprocessesdependsvery scale orographyhas been shown to be a major sourceof intermuch on the ability of the model to simulaterealistically the nal error [Reynoldset al., 1994]. To quantify this question,the mean climatology. The old quasi-linearparadigmwas that the ECMWF model was run in ensemble mode and six realizations simulationof a meanclimatologywas largelyirrelevantas model of AIRI computed(Figure32c). The spreadbetweenthe realizaerrorswere systematicand would be subtractedout whenanomaly tions was lessthan the spreadbetweenthe "quality-controlled" fields (i.e., difference between perturbedstatesand the control models. Thus somepart of the spreadin the AMIP integrations integrations)were computed. However, in the calculationof is due to model formulation differences. However, it remains to the difference between 1987 and 1988, two seasonsof great be determined with several state-of-the-art GCMs, whether the intraensemblespreadbetweenthe membersis comparableto the differences in rainfall over India and extremes in the SO1, Shukla that thereis an intrinand Fennessy[1994] amply demonstrated that the state of the signalarisingfrom the SSTs. This suggests component to the seasonal AIRI predictabilbasicmodelwasof paramountimportance.The currentCenterfor sicallyunpredictable with sensitivityto initial conditions. Ocean,Land and Atmosphere(COLA) GCM was usedto testthe ity associated On the otherhand,thereproducibility of theAIRI in theAMIP Charneyand Shukla [1981] hypothesis(subsequently supported integrations should be contrasted with that of coarse-grained meaby Palmer et al. [ 1992] andMo [ 1992]) thatthe stateof the lower boundaryconditionstronglyinfluencedthe monsoon.Even with suresof monsoonactivity.For example,for the ECMWF model, the observed SST with the E1 Nifio in 1987 and an La Nifia in the reproducibility of the WebsterandYang [ 1992] windshear in1988, the old modelwas not able to simulatetwo of the largest dex is well over 3 times larger than it is for the AIRI. In some extreme years of Indian rainfall. Furthermore,the difference senseit couldbe arguedthat it is inevitablethat smallerreproof the two simulations did not bear close resemblance to the ducibility will be associatedwith small-scalefeatures.However,

observedprecipitationdifferences. Thus, either the hypothesis failed, or the base model was inadequate. With an updated version of the model, which includedbetter representation of orographyandchangesin the handlingof soilwetness,vegetation, and cloudiness, both the simulations of the individual seasons and the differences of the seasons were well simulated.

Similar

improvementsin the ability of the ECMWF model to simulate monsoonalandtropicalrainfall occurredwith changesin thelatent heating algorithm [Miller et al., 1992]. The secondphaseof the MONEG projectinvolvedthe analysis of monsoonactivity in the set of 10-yearintegrationsthat constitutethe AtmosphericModel IntercomparisonProject (AMIP) [Gates, 1992]. Thesemodelswere integratedwith identicalSSTs (derived from observationsover the decade 1979-1988). Under the TOGA MONEG project a monsoondiagnosticcomponent of AMIP was established.The resultsfrom this componentare summarizedbelow. A more extensiveanalysisis givenby Sperber and Palmer [1996]. As was found from the earlier 90-day coordinatedMONEG integrations,the ability of GCMs to simulate satisfactorilythe observedcorrelationbetweeninterannual monsoon and SST variability was associatedwith the skill in simulatingthe mean monsoon.In theseintegrationsnone of the modelswereableto reproducethe observedempiricalrelationship

thisis notentirelystraightforward. According to resultsby Sperber andPalmer[ 1996]the reproducibility for the Marchto May BrazilianNordeste,the Sahel,and over the tropicalPacificwarm pool rainfall was much smaller(Figure 33) Thus the AMIP resultssuggestthatthereis something intrinsicallylesspredictable about aspectsof the regional seasonal-mean rainfall associated with theAsiansummermonsoonthantheregionalseasonal-mean

rainfallin otherpartsof theworldwhichis notassociated simply with spatialscale.It couldbe arguedthat the differentialspread of the ensemble memberscanbe explainedthroughthe hypothesisthat the dynamicsof intraseasonal variabilityin the Asian monsoon areais intrinsicallychaoticandthatnonlinearcoupling between the intraseasonal and interannual timescales makes the

fine-grainseasonal-mean monsoon diagnostics onlypartiallypredictable.Theseideaswill be weighedagainstotherpossibilities and critically evaluatedin the next section.

5.

Predictability and Prediction of the Monsoon

Hastenrath[ 1994] listedfive main approaches in climateprediction:(1) the extrapolation of presumed periodicities existing within a data record, (2) the assessmentof statisticalrelation-

shipsbetweenlocal phenomena of interest(e.g., rainfall,pressure)anddataat somedistantphenomenon, (3) the relationship between ENSO and the south Asian monsoon. of thelocalprecipitation priorto therainyseason withprecipita(4) comprehensive diagnostic In the AMIP analysisboth coarse-and fine-grainedmeasures tionat thepeakof therainyseason, of monsoonactivitywerediagnosed.One coarse-grained measure and empirical studiesof climate and circulationanomaliescomanalysis,and(5) numericalmodeling.In this was the wind shearindex of Websterand Yang[ 1992], which can binedwith statistical of the predictability broadlybe thoughtof as corresponding to the scaleof variation sectionwe reviewthe currentunderstanding discussedabove for the velocity potential and streamfunction of the space-timeaveragedmonsooncirculationon seasonal-totimescales with particularemphasis on approaches (4) mapsin Figs. 28 and 29. Rainfall variationson the national-scale interannual and(5). At thesametime,speculations will be madeonemerging regionswere taken as measuresof fine-grainmonsoonactivity. The AMIP integrationswere usedto measureskill in simulat- ideasof monsoonpredictabilitythat were mentionedin section ing fine-grain structureof the monsoon.The measurecalculated

Extremely large scatterwas found betweenthe 33 AMIP models (see Figure 32). Even when the modelswere quality controlled by eliminatingthosemodelsthat failed to model adequatelythe long-termmean Indian rainfall distribution,the spreadwas still very large.

4.6.

5.1.

The BasicQuestionof the Predictabilityof Monsoons

In a review articleon the interannualvariability of the Indian

monsoon, Shukla[ 1987a]posedtwo questions. Eventhoughthey pertain to one region within a much larger-scalephenomenon, they are of enoughimportancebe repeatedhere


14,497

I(a) INDIAN RAINFALL I I (b)SAHEL RAINFALL 32 AM IP models

-/;:'

•',

;, -',•

32 AMIP

Models

/,

,

,,

'•-2

E o-3

ECMWF

79

81

ECMWF

Ensemble

83

85

87

year

79

81

Ensemble

83 year

85

87

Figure 33. Atmospheric Model Intercomparison Project(AMIP) integrations for theIndianregion.(a) The Indian rainfall simulationsof the 32 AMIP modelsto identicalSST variationsover a 10-yearperiod. Figure 33a (bottom) showsthe responseof an ensembleof ECMWF model integrationswith perturbedinitial conditions. (b) The

sameas Figure33a, exceptfor the Sahelregion. The ECMWF ensembleshowsgreatercoherencein the Sahel integrationsthan the ensemblefor the Indian case. 1. Is the behavior of the seasonalmean monsoonprimarily determinedby a statisticalaverageof a variety of independent short-periodfluctuationsthat are not relatedto any seasonalor other low-frequencyforcing? 2. Are there global- and planetary-scale "forcingfunctions" (eitherdue to slowly varyingboundaryconditionsat the Earth's surfaceor due to very low frequencychangeslike the Southern Oscillation) that determine the interannual behavior of the seasonal mean monsoon circulation and rainfall, and is the inter-

annualvariabilityof the shortperiodfluctuationscontrolledby suchlarge-scalelow-frequencyforcing? To thesetwo questionsa third may be added 3. Are therelow-frequencyhydrodynamical instabilitiesof the monsoon circulations themselves that, on the one hand, exert

control on the short-termfluctuationsdescribedin question 1 and are, in turn, modifiedby the large-scaleplanetarycontrols describedin question2? Thesequestionsare importantas theydefinethe basicessence of the predictabilityof monsoonvariability The degreeto which monsoonsare predictabledependsupon the spacescaleand timescalefor which predictabilityis being sought.The day-to- day changesin rainfall at any placeare determinedby the life cycle of synopticscaledisturbances (lows, depressions, monsoontrough,etc.) at or aroundthe placeof consideration.Thuspredictabilityof day-to-dayweatherat a pointin the monsoonregionis in no way differentfrom that of any other pointon the globeandis limitedto a few days.Thus,if it turned out that the monsoonwas controlledby processes describedin question1, then therewould be no greaterpredictabilityfor the monsoonsthan would be expectedfor the extratropics.On the other hand, if the monsoonwere controlledsolely by large-scale evolvingprocesses as discussed in question2, one would expect thatthe limits of monsoonpredictionwouldbe givenby the limits

of predictabilityof the planetary-scaleforcing functions. However, if there were large-scaleand low-frequencyinstabilitiesof the monsoonwhich might, for example,determinethe intraseasonal active and break periodsof the monsoon,then one may expecthybridlimitationsto predictabilityexistingsomewherebetween question1 and question2. These conceptsare discussed in the following paragraphs. There is somedisagreement aboutthe degreeof predictability of the monsoonsor whetherthey are predictableat all. There are, in fact, two vastlydiffering schoolsof thought.One hypothesis is that the variationsof low latitude phenomenaincluding the monsoonsare the resultsof influencesfrom slowly varying boundaryconditions. For example, Charneyand Shukla, [1981, p. 107] state there is: evidencefrom numericalexperimentsand from observations that natural fluctuationsof short period [lessthan seasonal]are adequateto accountfor most of the observedvariability at midlatitudes,but are not capableof explainingthe variability at low latitudes,say below

30øN. In addition... numericaland simulationexperiments and statisticalanalysesof observations that anomaliesin sea-surfacetemperatureand in groundalbedoare capableof producinglarge variances. Since these anomaliesare usually of long duration, the possibility arisesthat mean monthly conditionsat low latitudes,suchas monsoonrainfall, may be predictablewith someaccuracy .... Thus we suggestthat the synoptic-scale flow instabilitieswhichlimit prediction so drasticallyat midlatitudeshave lessinfluenceat low latitudesand thereforeleave room for longer-periodand more predictablesignals to make themselves

felt.

The basisof this thesisis that sincethe large-scaletropicalatmosphereis not asgenericallyhydrodynamically unstableasis the extratropics,thenthe responseof the large-scaletropicalcirculation to underlying lower-boundaryanomaliesshould, comparedwith the extratropics,be morereproducibleandhencepredictable.This centralconceptexpressedin Charneyand Shukla,[ 1981] formed

14,498


AND PREDICTION

the basisfor TOGA. At the other end of the spectrumare those weathertype (e.g., associated with the monsoononsetor the tranwho believethat the monsoonsystemis chaoticand that gener- sitionfrom a monsoonactiveto breakperiod,or viceversa),then alitiesaboutthe monsoon,uponwhichpredictionwoulddepend, medium-range monsoonpredictionbecomesmoreproblematic. cannot be made. For example, Ramage [1971, pp. 151-152] On the basisof this discussion it mightappearthat the issues states that of monsoonpredictabilityof the first and secondkinds (i.e., on from the earliestdays of monsoonresearchin Asia, meteorologists have constantlytried to find order in what is only superficiallya very orderly phenomenon.They have written paperspurportingto identify singularitiesin annualvariationof rainfall and many more claimingthat particularmeteorological eventscanbe usedaccurately

intraseasonal and interannual timescales, respectively) are quite independentof one another. This would be the case if the intraseasonal fluctuations in monsoonactivity(associated with the

transitions betweenactiveandbreakmonsoonregimes)couldbe thought of as modesof linear oscillationsuperimposed on the to forecast onset or cessation of monsoon rain .... Order has not been seasonalmean flow. However, if the active and break phases summonedforth.... As data have accumulated,so the systematists' of the monsoonare manifestations of regimesof a nonlinear questhasflaggeddespitethe voraciousappetiteof the meteorological consumerfor more.... Each major, often sudden,circulationand dynamicalsystem,then the two typesof predictabilitybecome weatherchangeaccompanying the marchof the seasons seldomrecurs more intimately linked. about the same date nor are the same precursorysignsregularly The following questionsarise: (1) Are the variationsof the followed. monsooncirculationsand rainfall predictable?and (2) Are the of the monsoondetermined by Here is rather extremeviewpointthat almostanythingnot tied limitationsto the predictability or is the monsoona directly"to the annualmarchof the seasons." is not predictable first kind or by secondkind considerations there Ramage[1971, p152]. By extension,as interannualvariabilityis hybridsystemof a furtherkind?Relativeto thesequestions, a rectificationof high-frequencyeventsaboutthe seasonalcycle, are four somewhatambiguousobservations 1. The AMIP integrations showsignificantdegradation in the the long-termbehaviorof the monsoonis not predictableeither. southAsianregionat a levelhigherthanelsewhere in thetropics These argumentshave been extendedto includeENSO. For example,Ramage[ 1986] concludedthat an E1 Nifio is spawnedby (Figure 34). Perturbedensemblemembersof the same model divergence in the southAsianregionduring unpredictablehigh-frequencyevents(in this casenorthwestPa- alsoshowenhanced cific typhoons).As he believesthatthehigh-frequency variability summer. 2. There is a moderatelygoodrelationshipbetweenthe SOI of the tropicsis not forecastable beforetheir development, then and rainfall over southAsia (Figure l d, Table 2), but it is imENSO is unpredictableas well. Ramage's [ 1971] view is in contrastto that of thosewho note perfect. While thereare droughtsthat occurover India that are with E1 Nifio many othersare not. As well, thereare indicationsof monsoonpredictabilitythathavebeenfoundusing associated empiricaltechniquessuchas describedby Bhalrneet al. [1986, many heavy rain seasonsthat are associatedwith La Nifia, but 1987], Gowariker et al. [1989], Shukla and Paolina [1983], otheranomalouslywet seasons appearindependent of the SOI. 3. Seasonalmonsoonpredictions by the India Meteorological Shukla [1987a, b], Hastenrath[1987, 1988], and many others, which use aspectsof the upperair flow, heat low development Department,now madefor over 100 yearsusingmodelsbasedon over southAsia, and the SouthernOscillationas precursoryin- empiricalrelationshipsbetweenmonsoonand worldwideclimate dicatorsof the forthcomingmonsoon.Completerandomness of predictors,are manifestlyskillful [Gowarikeret al., 1989]. The the variability of the monsoonsystemis also in contrastto the successof the empiricalforecastswould tend to supportthe ideasof Charneyand Shukla[ 1981]. Ramage'sopinion,though, theoreticalbasis that long-termpredictabilityof the monsoon is supported by the fact that the relationships betweenstrongand existswherebyslowlyevolvingboundaryforcing(e.g., the SST weak monsoons are not universal. As discussedearlier, most in the PacificOcean,Eurasiansnowcover)imposesa large-scale failuresof Indian summerrainfall accompanywarm eventsin the controlon the monsoon[Charneyand Shukla,1981]. Empirical PacificOcean(i.e., E1 Nifios). But there are many droughtsthat forecastingof the monsoonis discussedin section5.2. 4. Anomalouslywet or dry monsoonseasonsin both the appearto be completelyindependentof interannualvariability of the tropical warm pools. Yet, at the sametime, the association Asian and Australian summermonsoons(Tables 3a and b) are and the monsoon is seductive. Table 2 illustrated season-longevents. That is, most wet or dry seasonsconsist that E1 Nifios and La Nifias were associated with 55% and 44% of monthsthat are anomalouslywet or dry. Thus, whatever of droughtsand very wet years over India, respectively. Ex- the reasonsfor the anomalyin the rainfall they are persistent thesummerseason.Recentresults(J. Shukla,personal amplessuchas theseshowthat thereis a significantcorrelation throughout 1997) suggestthat the monthlyconsistency of betweenslowly varyingboundaryconditionsand space-timeav- communication, rainfall during anomalousseasonsextendsto shortertimescales. eraged monsoonrainfall. betweendailyandseasonal rainfall In climate and weatherprediction,two differenttypesof pre- They foundthatthecorrelation diction can be distinguished.Predictionsof the first kind are remainspositivefor nearlythe whole monsoonseason. initial value problems,exemplifiedby conventionalweatherforecastpractice. Predictabilityof the first kind is thereforea measure 5.2. Empirical Prediction of the Monsoon of how uncertainties or errorsin initial conditionsamplifyduring Empirical forecastingof climate anomalieshas been usedin the forecastperiod. By contrast,for predictionsof the second manyregionsof the globerangingfrom the extratropics (seerekind, an attemptis madeto forecasthow a systemwill respondto viewsby Livezey,[ 1990])to thetropics[e.g.,Hastenrath[ 1986a, a prescribed changein oneof its determiningparameters.The re- 1986b, 1994] for the tropics,in general,andShukla[ 1987b],Hassponseof climateto a doublingof carbondioxideis an important tenrath[ 1987, 1988],Das [ 1986, 1987], Gowarikeret al. [ 1989] example. Short-and medium-rangemonsoonforecastsare man- for India,in particular].Wherea•empirical fcwo. ca•tingha••hc•wn ifestly predictionsof the first kind and are now maderoutinely only limited success in the extratropics, expectation shouldbe by a numberof groupsaroundthe world using state-of-the-an greaterin the tropics[Charneyand Shukla,1981]. numericalweatherpredictionmodels[e.g.,Mohantyet al., 1994]. Hastenrath[1994] defineda schemefor empiricalclimate There are someparallelswith extratropicalshort- and medium- prediction basedon generalcirculation diagnostics andstatistics. rangeforecasting.For example,whenthereis a basicchangein The schemesuggested the archivingof a quality data set to between ENSO


AND PREDICTION

14,499

locations,(2) heat-low developmentover southeastAsia and (3) the snowfallover Eurasiaduringthe previouswinter. The additional informationis (4) upper air data which was not available to earlier researchers.Shuklaand Mooley [1987] have extended' the relationshipbetweenthe SOI and monsoonrainsby considering the trend of the SOI betweenJanuaryand April. Hastenrath [1987, 1988] has used the fall temperatureat certainIndian stationstogetherwith the May meridionalwind in the westernIndian Ocean to form regressionequations. Wu [1984] and Kung and Sharif [1980, 1982] useda combinationof parametersincluding upper air data to developa forecastingscheme. The use of upper air data has improvedempiricalforecasting considerably.Banerjee et al. [1978] were first to note that the

(a) R2/RI+R2): 850-mbarJune-August

90N .................... •........................ • 60N

positionof the 500-mbartroughalong75øE duringApril foreshadowedIndian rainfall. In fact, Hastenrath [ 1994] considersthe

positionof the troughthe mostpowerfulpredictorused. Bhalme et al.

(b) R2/RI+R2): 200-mbarJune-August ::

:

::

=====================================

90N • '-•

0

:

.. . .

60N

90S

::::::-::::::::

:::::::,•,,,,

.

'

[1987] and Gowariker et al. [1989] have added strato-

sphericzonal winds as predictors.Reddy [1977] had notedthat the 50 mbar wind over Singaporein May providedinformation aboutthe onsetof the monsoon.If the winds were anomalously westerly,the onset of the monsoonover India would be early. If they were easterly,the onsetwould be late. Yasunari[1989] suggeststhat there is a stronglink betweenthe QBO, the TBO, and thus the strengthof the summermonsoon. The springtimepositionof the 500-mbar troughis consistent with the anomalouszonal wind over the Indian Oceanfound by Websterand Yang[ 1992] throughcompositing of strongandweak monsoonseasons(Figure 22). However, the anomalouswinds of Websterand Yang[1992] were statisticallydifferenttwo seasons

.......

ahead of an anomalous

60E

i20E

•80

120W

60W

0

•igure 34. Distributionso• the preaictabilit••acto• • denned in (4) using the ensembleintegrationscompiledin the •rediction o• Climate

Variations

on Seasona]-to-[merannua]

timescales

(PROVOST) data set •o• (a) the 85•mba• zonal velocit• component and (b) the •0•mba• zonal ve]ocit• component. •ontou•s

monsoon.

The following multipleregressionequationsusedby the Indian MeteorologicalDepartmentencompass the empiricalrelationships discussed in the previousparagraphs [Shukla,1987a;Das, 1987]. 1. For the predictionof the onsetdate of the monsoonat the tip of India D = -0.0767X•

o• •are 0. ] and are shown •o• values • 0.3. Note the decrease

- 0.11220X2

(6)

-0.0794Xa - 0.5107X4 q- 32.150 • in the Indian Ocean-southAsian regionin both velocit• Values range •mm 0.3 to 0.5 ove• the Indian oceancompared where D isthedeparture in daysof thenormal dateof theonset to 0.6 to 0.8 ove• the •aci•c wa• pool. From •-. (Programin Atmosphericand OceanicSciences,Unive•sit• o• of the monsoon in south India. 2. For the predictionof the rainfallprecipitationanomalyover Colorado,personalcommunication, Peninsular

India

definethe generalcirculationof the atmosphere.This is followed -0.0296 Y1q-1.127 Y: q.2.242 Ya -58.1595 (7) by carefuldiagnosisof the data and identificationof "predictor candidates"for the particularphenomenonto be forecast.These whereRe is the departureof the seasonalrainfall in inches. predictorsare thenusedto producea "regression model",which, 3. For the predictionof the rainfall precipitationanomalyover in turn,is usedto makea prediction.A criticalpartof the scheme north India is the evaluation. of the predictionusingindependent data. In the following paragraphsa brief descriptionis providedon the use 0.759Y•-l.433Z•+25.863Z:•-0.129Za-11.6821 (8) of empiricaltechniquesin the monsoonregionsof India, south Asia, and Indonesia-north Australia.

Figure 1 showeda moderatelystrongrelationship betweenrice productionin India and the total rainfall over India. In view of this relationshipit is not surprisingthat the emphasishas been on forecastingtotal Indian rainfall with as great a lead time as possibleratherthan attemptingto forecastthe higherfrequency andresolutionfiligree. Additionalsupportfor theconsideration of thesegrossrainfall statisticsis givenby the apparentuniformity of rainfall anomaliesover India (seeTable 3 and Figure 21). With one major exception,empiricalforecastingof monsoon rainfall currentlyusesalmostthe samefollowing parametersas earlier studies: (1) the SOI and trends in observationsat remote

where R•vis the departureof the seasonalrainfall in inches. In (6)-(8) the elementsof the regressions are definedas

X•: Mean 300-mbar wind direction(degrees)precedingJanuary over Delhi;

X2: Mean 200-mbar wind directionprecedingJanuaryoverDarwin;

X3: 200-mbar wind directiondifferenceprecedingFebruarybetween Trivandrum and Madras;

X4: Mean200-mbarmeridional windspeed(m s-1)preceding December over Calcutta;

14,500


Y•: Mean surface pressuredeparture (millimeters) preceding 5.3. Emerging Ideas Regarding the Predictability of the Monsoon April-May for BuenosAires, Cordobaand Santiago; Y2: Mean latitude (degrees)of 500-mbar ridge precedingApril During the last few years, there have been a number of new along 75øE; ideasthat have emergedregardingthe predictabilityof monsoon Y3: Mean minimum temperature(degreesCelsius) preceding variability. Whereasthey are somewhatspeculativeat this stage March for Jaisalmer,Jaipurand Calcutta(India); and require considerablemore researchin order for their evaluaZ•: Mean surfacepressure(millimeters)precedingApril-May for tion, they are of sufficientimportancefor discussion. BuenosAires, Cordoba, and Santiago; 5.3.1. Nonlinearity and monsoon predictability. In the Z2: Equatorialpressuredeparture(inchesof mercury)preceding results from the MONEG and AMIP studies, it was shown that January-Mayfor Seychelles,Jakarta,and Darwin; whileinterannualfluctuations in thecoarse-grain monsoonactivity Z3: Mean April temperature(degreesCelsius)at Ludhiana(north is highly predictable,thereappearedto be significantsensitivityto India). atmospheric initial conditionsassociated with fine-grainmonsoon statisticssuchas the AIRI. There are two major possibilitiesfor More recently,otherpredictorshave been added[seeKungand this sensitivity Sharif, 1980, 1982] producingsomeimprovementin the predic1. The southAsian regionis extremelydifficult to model. The tions. region is marked by very high terrain and complexhydrological In summary,60-80 % of the variability of the total seasonal processes over land. Within sucha domainit is probablethat the monsoonrainfall can be predictedfrom informationavailablein modelswould differ mostandthat therewouldbe greatsensitivity the precedingMay usingempiricaltechniques[Hastenrath,1994]. amongthe modelsto differing parameterizations. Much of this skill comesfrom a knowledgeof the structureof the 2. Hydrodynamicalinstabilitiesexist in the monsoonregions. middle and uppertroposphere in the late spring.In addition,the If this is the case, the monsoonregionswould be intrinsically sign and tendencyof the SO1addsfurtherinformation,although chaotic. It would be possibleto understandthe physicsof the it is difficult to determinewhetheror not the SOI and the position instabilities and describe their evolution, but the transitions beof the 500-mbar troughare independentpiecesof information. tween stateswould be unpredictable. Forecastingof the intraseasonal variability of monsoonrainfall It is clear that modelscan be improved. Indeed, few models appearsto be more problematic. Cadet and Daniel [1988] have appearto be able to simulateproperlythe long-termmean south attemptedto forecastactive and break periodsof the monsoona Asian monsoon. However, when individual models are run in monthin advanceusing statisticsof cloudinessand pressurein ensemblemode,a similarregionallyspecificspreadbetweenthe the 30-60 day band in the east Indian Ocean. Some potential membersof the ensembleappears. Figure 34 (X-W. Quan, is shown in forecastingthese anomalieswithin a week or so of Program in Atmosphericand Oceanic Sciences,University of their commencement. Colorado,Boulder,personalcommunication, 1997) showsglobal Given the proximity of Indonesiaand north Australia to the distributions of a measureof predictabilityR givenby extrema of the global zero-lag correlationof the mean sea level pressure (see Figure 4) it is not surprisingthat the Southern R (9) Oscillation(or a surrogatesuchas the Darwin sealevel pressure) R• is usedextensivelyin empiricalforecasting[e.g., Nicholls, 1983; Hastenrath, 1987]. However, a strongannualcycle in prediction where R• and R2 are the internal and external variance of the was also found. Hastenrath [1987] noticed that the surface model [see Reynoldset al., 1994]. Fields of R are shown for persistenceis strongestin the periodJune-Novemberbut weakest the zonal velocitycomponentsat 850 mbar and 200 mbar for the in the December-Mayperiod [see also Balmasedaet al., 1995; boreal summer. Figure 34 was constructedfrom the ECMWF Torrenceand Webster,1998]. Correlationsbetweenpressureand model using the Prediction of Climate Variationson Seasonalsubsequent rainfall showeda similar annualcycle. When the SOI to-Interannual Timescales (PROVOST) data set. PROVOST is is positive, the near-equatorialtrough tends to shift toward the an outgrowthof the Brankovicand Palmer [1997] seriesof enIndian Oceanbringingheavyprecipitationto the southChina Sea- semblerunsusingthe T63L19 ECMWF model.The integrations Indonesianregion. In contrast,when the SO1 is negative, there were madeusingobservedspecifiedSSTsfrom a 5-year period is below averagerainfall over the outh China Sea. In summary, (1986-1989). Ensembleintegrationswere carried out for each successfullyforecastingthe evolutionof the SOI would appear season. In the ECMWF PROVOST data set, there were nine to be a powerful tool in foreshadowingprecipitationin south ensemblemembersand data was averagedinto 10-day blocks. Asia during the winter and over Indonesiaand Australia in the For eachfield, R showsa minimumin the southAsianregion australsummer.Thus ENSO forecastingis of directrelevanceto comparedto the rest of the tropics.The regionalityof R may be monsoonprediction. indicativeof regionalchaoticdynamics. Attemptsat usingempiricaltechniquesfor forecastingE1 Nifio What could be the origin of suchchaoticprocesses?One andthe SO beganwith Quinnand Burt[ 1972], who usedpressure possibilityis extratropical-tropical interactionas suggested by data at Darwin and pressuredifferencesbetween Easter Island Meehl [19934a], as shownin Figure 31, or more recentlyby and Darwin to infer heavy precipitation(El Nifio) in the eastern Rodwell [1998]. Such stochasticinfluencescannotbe ruled out, Pacific. Barnett[ 1984] suggested that the useof wind fieldsover thoughit is noted abovethat other small-scaleregionsof the the Pacific Ocean could allow SST anomalies over the Pacific tropics,such as the westernPacific Ocean warm pool, appear Ocean to be predicteda year aheadof time. Theseeffortshave to be muchmore predictable(e.g., Figure34). Sincemidlatitude beenextendedthroughthe developmentof statisticalmodels[e.g., chaoticprocesses areactiveat all longitudes, it is notimmediately Graham et al., 1987' Barnett et al., 1989]. During the TOGA clearwhy one longitudinalzonein the tropicsshouldbe so much decadethe emphasishas shiftedto numericalpredictionof ENSO more stronglyinfluencedby suchextratropicaleffectsthan any [e.g., Cane, 1991; Palmer and Anderson,1994]. anotherregion.


Anotherpossibilityis that somedynamicprocesses in the monsoonareaare intrinsicallychaotic.One candidateis intraseasonal variabilityassociated with the migrationor oscillationof convective zonesassociatedwith active and break periodsof the monsoonwhere the multiple locationsof monsoonconvectionare associatedwith instabilitiesof the monsoongyre [e.g., Tomasand Webster,1997] and/or the monsoontrough associatedwith the heatedlandmassfarther poleward [e.g., Webster,1983a; Srinivasan et al., 1993]. In this scenarioeach state could be observed at one time or the other duringthe monsoonseason,but the transitionsbetweenthe two stateswould be inherentlyunpredictable.

14,501

0.20

O

....

Control

---

Perturbed

0.15

0.10

From a physicalpoint of view the possibilityof chaoticfluctuationsbetweenthe break and activemonsoonphasessuggestsa dynamictensionbetweenthe two quasi-equilibrium positionsof the tropical convergencezone. Small imbalancesin simulating this dynamictensioncan leadto significantsystematic error. For example,one very commonsystematicerror in GCMs is an excessiveprecipitationband acrossthe Indian Ocean,southof the 0.00 Indian subcontinent[see WCRP, 1992]. Suchan error corresponds -20 -10 0 10 20 to an excessivestabilizationof the oceanictropical convergence zone modein the GCM. Note that this dynamictensionbetween PrincipalComponent #1 oceanicallypositionedand continentallypositionedconvergence zonesis absentover the highly reproducibleareaof the Brazilian Figure 36. Probabilitydensityfunctions(PDFs) of the vertical Nordeste. velocity structureof the intermediatecoupledmonsoonmodel The fact that intraseasonal monsoonfluctuationsare not peri- for the control (gray curve) and for a case where a remote odic was shownby Webster[ 1983a], Goswamiand Shukla[ 1984], climatologicalforcing was introduced(dashedcurve). Different and Srinivasanet al. [1993]. The possibilitythat suchfluctua- structures result from the external influence. From Dixit et al. tionsmay be intrinsicallychaoticwasdiscussed by Palmer [ 1994]. [1997]. However,the evidencewas not conclusive.In particular,it is not possibleto rule out unambiguouslythe influenceof extratropical dynamicsin GCM analyses.More compellingevidencehasmore encesare absent.Moist processes are includedthroughan active recently been found by S. Dixit et al. (Are monsoonschaotic? hydrologycycle which includesland and sea-icemodels.The anImplicationsfor the predictabilityof intraseasonal monsoonvari- nual cycle of radiativeforcingcombinedwith model-determined

0.05

ance, with T. N. Palmer and P. J. Webster, submitted to Journal

soil moisture content results in realistic intraseasonal oscillations

of Climate, 1997). (hereafterreferredto as Dixit et al., submitted manuscript,1997) who have studiedthe growth of small perturbationsin the intermediatezonally symmetricdynamicalmodel of Websterand Chou [ 1980b], in which chaoticmidlatitudeinflu-

in the summerseason[Webster,1983b;Srinivasanet. al., 1993]. Theseintraseasonal oscillationsare nonlinearand vary from one year to the next. The sensitivityto initial conditionsis shownin Figure35. The model,forcedonly by the annualcycleof solar heating,was perturbedrandomlyin the secondyear of integration. Althoughthe annualcycleof the verticalvelocityis similar, the intraseasonal variabilitybetweenthe experiments is verydifferent. In Figure 36 the probabilitydistributionfunction(PDF) of the first principalcomponentfor a controlrun is shown,and a secondrun in which an additionalforcinghasbeenappliedis shown. In the controlrun, there is a stronghint of a possible bimodaldistribution, but wherethestatevectorhasa strongpreferencefor the regimewith positiveprincipalcomponent (i.e., this regimehasa muchstrongerprobabilityof beingrealizedat any one time, comparedwith a secondregimewith negativeprincipal component).In the secondrun, however,bimodalityis much

•-

10

-Q

i

i

i

i

i

i

I

i

i

i

i

i

i

i

i

i

i

5

E o

0

v

m

-5

E

c• -10 CONTROL v

?

-15

PERT1

o

•

PERT2

-20 PERT3

•

-25

M''

'J''

'S''

'D''

Year6• •

M''

'J''

's''

'D' '

Year7

Figure 35. Time seriesof the verticalvelocityin an intermediate coupledmonsoonmodel. Years6 and 7 of integrationare shown for three sets of small perturbationsintroducedafter year 3 of integration.The sensitivityto initial conditionsindicateschaotic qualitiesof the model. From Dixit et al. [1997].

more apparent. In this run the remote effect of E1 Nifio in re-

ducingthe tropicaleasterlyjet has beenrepresented by adding a linear drag term in the upperlayer of the model. The overall effect is to dramaticallyincreasethe probabilityof findingthe systemstatevectorin the regimewith negativeprincipalcomponent. The positionsof the two modesof this bimodaldistribution correspondto the favored oceanicand continentallatitudesfor the

tropicalconvergence zone,consistentwith the observational and theoretical

studies cited above.

The existenceof a bimodal PDF with chaoticdynamicsis reminiscentof the Lorenz [1963] model discussedin the context

of long term climate variability by Palmer [1993, 1994]. In

14,502


particular,considerFigure 37, which showsa time seriesfrom the

with the sameexternalforcingf andif the PDF of the statevector beingin the positiveX regimeis 70%, then by definition,3 out systemundergoingvariable external influences. The model is of 10 membersof the ensemblewill, on the average,have state describedby vectorsresidingin the negativeX regime. As mentionedabove, one cannotassertunambiguously from •' = -crX + cry+ f the AMIP resultsthat the lack of completemonsoonpredictabil• = -XZ + rX + f (lO) ity is due to intrinsicallychaoticmonsoonprocesses.However, there are indirect methodsto supportthe pictureput forward 2= x¾-z above, basedon more detailed analysesof the MONEG AMIP as discussedby Palmer [ 1993, 1994]. The valuesof the constants integrations.For example,accordingto the paradigmoutlined are cr= 10, r = 28, andb = 8/3. Figures37a-37dhavevaluesoff above, the spatial patternsof intraseasonaland interannualvari= 0, 2, 3, and 4, respectively.All time seriesare chaotic,yet the ability shouldbe stronglycorrelated.For example,Shuklaand largerthe value of f, the higherthe probabilitythat at any instant Fennessy [1994] showedthat the spatialpatternsof composin time the statevectorresidesin theregimewith positiveX. Note ite precipitationdifferencefieldsbetweenactiveandbreakspells that the positionof the regime mode does not itself translateto in the COLA GCM were quite similar to the interannualdifferlarger values of X asf increases.On the basisof the resultsof ence fields between their 1987 and 1988 MONEG simulations. Dixit et al. [1997] the two regimesapparentin Figure37 can be From this point of view, Shuklaand Fennessy[1994] notedthat thoughtof as correspondingto the active and break regimesof their 1987 MONEG integrationscould be interpretedas being the model and of f as representing an externalmonsoonforcing, in a quasi-persistent break regime phase. More generally,Fer......... '•" tne ranti et al. [1997] have studied the relations between interanwhich is at most slowly vfirying over a monsoonseason.un basisof the resultsof the MONEG andAMIP experimentation, f nual andintraseasonal monsoonvariabilityasdiagnosed from the couldrepresentthe coarse-grain forcingon thelarge-scaletropical ECMWF AMIP integration.Figure 38a showsthe dominantEOF circulationover the monsoonregionsassociated with ENSO. of May-to-September average850-mbar relativevorticitybased It is now possibleto reconcilethe partialpredictabilityresults on the five ECMWF AMIP integrations.By comparison, Figure from the AMIP intercomparison studieswith the Charneyand 38b showsthe dominantEOF of May-to-September intraseasonal Shukla[1981] hypothesison the predictabilityof the monsoons. variability (detrendedto remove fluctuationsassociatedwith the In this picture the intraseasonaland interannualfluctuationsbe- annualcycle) from the principalECMWF AMIP integration(for come intrinsicallydynamicallylinked throughnonlineardynam- whichdaily fieldswere available).It can be seenthatthe spatial ical processes.Imaginethat f varieson timescalesmuchlonger patternsof the intraseasonal and interannualmodesof variability than a typical intraseasonal monsoonregimeresidencetime (i.e., are highly correlated.Ferranti et al. [ 1997] havealsoshowedevon interannualand longer timescalesfor the real atmosphere). idence that these modes have a bimodal PDF in a manner similar Then at any instantin time onecan saythatthe probabilityof the to Figure 36. The modelresultsare bolsteredby Keshavamurty systembeingin, for instance,the positiveX regimeis determined [1994] who examinedthe observational patternsof intraseasonal byf Hencein this sense,thereis a deterministicandpredictable and interannualmonsoonvariability over India and also found link betweenthe external forcingf and the PDF of the "mon- strong spatial correlations. soon"statevector. However, this doesnot imply a deterministic The resultsdiscussed aboveappearto supportthe nonlinear and predictablelink betweenf and the actual realizationof the paradigm,which blurs somewhatthe distinctionbetweenmonstatevector. For example,if an ensembleof integrationsis made soonand extratropicalpredictability. Certainly,monsoonscan forced Lorenz [1963] model, which is used as a tool of a chaotic

2O

2o

XoI i t j 0 X

-20

-20

20

20

0

0

0

50

1O0 time

150

200

0

50

1O0

150

200

time

Figure 37. Solutionsto (6) and (7) for valuesof f = 0, 2, 3, and4. All of the timeseries are chaotic.Asf increases,so doesthe probabilitythat the statevectorwill residein a positiveregime.


14,503

and Grant, 1953; Grant, 1953; Troup, 1965]. Thus, if the state of the Pacific Ocean affectsthe variability of the monsoon,then one would expect this influenceto vary interdecadallyas well. Kripalani and Ashwini [1997] have noted that there is inter'•!•iir'::iii:iii•¾.:•?• •i' "'I ii:•':•"'":•i•i•'•5•:½:?e':'"':'"'"':• •........ decadalvariability in Indian rainfall and that the period of low •" :."'•:?:..:'•i!i::'"'..i •::i?i •½•" .iii! .... ............... I '•:•ii•! :•i•i•i ...... •::'i.. •:.. " ::• varianceseenin Figure 3 is alsoa periodof below normalrainfall. Relative to the long-termmean, above averagerainfall occursin the period 1970-1890 and 1930-1960. Below averageprecipita-

(a) Interannual 30N

20N

....

10N

tion occurs between

"'1' - - - 4-.-.-....•

equ

k

.... I

10S

I

•

--:-• I

I

I

I

(b) Intraseasonal 30N ......

the rather limited :::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::...:.:::::•.....•ii:::::. ''

I

10N

I I

....

10S

and 1960-1990.

To test whether

data record that is available

for interdecadal

....... •-•iv'...:.,.....'•:...:• ....... '"'""'"•'""'""'•':•.,•i•:.•'::.•'..i•i'..•,• i investigationsthey concludedthat the impact of warm eventsin

20N

equ

1890-1930

or not the ENSO cycle was responsiblefor the decadalvariability of the Indian rainfall, they removedthe years associatedwith E1 Nifio and La Nifia. Essentially the same interdecadalvariation of precipitationremained. They concludedthat the interdecadal variability of Indian precipitationis not forced in a fundamental senseby the varying frequencyof E1 Nifio and La Nifia through the last century. Kripalani and Ashwini [1997] then asked whether the impact of ENSO eventson Indian monsoonrainfall was the sameduring epochsof above and below average rainfall. On the basis of

'.•ii• .......... •. -'•

I, I

I I

j .... I

i

70E

90E

110E

the PacificOceanis mosteffectivein regulatingmonsoonrainfall when the Indian rainfall is in a negativeepoch. That is, warm eventsin the Pacificemphasizethe longerperioddroughtphases of the monsoon. They used this observationto explain why there was not droughtin India during the early 1990s despitethe persistentE1 Nifio, noting that the rainfall in the 1990s appears to be generally above average. If the Kripalani and Ashwini [1997] observationshold up to thrther scrutiny,they may go a long way to explainingwhy the relationshipbetweenENSO and the monsoonis lessthanperfect. Understandingsecular differencesin empirical relationshipsis important,especiallyif one can determinewithin which epoch the systemcurrently resides.

Figure 38. Dominant EOF of 850-mbar relative vorticity 6. Conclusions and Future Work (March-September) over the IndianOcean,summerAsian monDuringtheTOGA decade,therehasbeena significantadvancesoonarea,usingdata from ECMWF AMIP integrations.(a) On the basisof interannualvariabilityonly and (b) on the basisof ment in understandingthe basicphysicalprocessesthat determine intraseasonal variabilityonly The annualand semiannualcycles the structureof the monsoonand those external processesthat have been removed from the from data.

From Ferranti

et al.

[1997].

be expectedto be morepredictablethanextratropicalcirculation anomalieson seasonaltimescales.However,the analysisput forwardheresuggests thatthedifferencesaremattersof degreerather than mattersof principle. From a practicalpoint of view these resultshighlightthe need for ensemblepredictiontechniquesto be appliedto seasonal predictionof monsoonanomalies usingoperationaldynamicalmodels. The rangeof predictionsprovided by the ensembledefinesan estimateof the appropriate probability distribution. Examplesof practicalprobabilityforecastsof monsoonrainfall are given by Brankovicand Palmer [1997]. 5.3.2. Interdecadal variability of monsoonpredictability. Duringthe last few yearsit hasbecomeclearthat thereis strong interdecadalvariability in the ENSO cycle and the monsoon(see Figure 3 and the discussionin section2.2.2.3). Balmasedaet

influenceit. However, it is also true that during the TOGA period, forecastingthe variabilityof the monsoonhasnot improved. Forecastsstill dependon empirical techniqueswhich have been developed decadesbefore and which continue to be used with moderate success. However, the authors believe that the field is

well poisedto make significantadvancesin quantitativeprediction in the near future.

This confidence

is based on a number

of factors

1. The advancementof global data sets from the numerical weatherpredictioncentersof the world now allows an unprecedentedview of the global monsoonsystem.With ongoingreanalysis projects,this view will be extendedback at least 35 years. The compilation of the COADS data set has been a major accomplishment,allowing surfacecharacteristics of the monsoonto be studiedon the decadal timescaleand, in certain regions, for over 100 yearswith someconfidence.Both the COADS data sets, the initialized data from the numericalcenters,and the reanalysis producthave allowed the specialtropical and monsoondata sets al. [1995] and Torrenceand Webster[1998] discussedthis issue compiled in field experimentsto be viewed in a wider context. relativeto the variationin persistence of the SOI andimplications And thereare many suchexperiments,includingthe lndian Ocean for the predictabilityof ENSO. Duringthe decadesbetween1920 experimentsof the 1950s throughthe 1970s, the Tibetan Plateau and 1960, there was less variance in both ENSO and south experiments,FGGE/MONEX, TOGA, TOGA COARE, the EquaAsian monsoonsummerprecipitation.Furthermore,correlations torial MesoscaleExperiment (EMEX), and the AustralianMonbetween the SOI and rainfall droppedoff precipitously,even soonExperiment(AMEX); the latter two were conductedin north thoughthey were initially strongat earlier times [e.g., Treloar Australia during the Australian summermonsoon.

14,504


2. Collectively,the data setshave alloweda ratherunambiguous assessment of the variability of the monsoonsystemto be assessedfor the first time. Even though variousearly studies have hinted there may be monsoonvariability on a multitudeof timescales,it is now possibleto quantify that variability. Out of theseanalyseshas come evidenceof variabilitywith biennial, ENSO, and decadaltimescalesand a feeling for when thesevarious time scalesare in their ascendancyand when they fade. 3. There has been someprogressin determiningthe interaction of the monsoon with other climate features such as ENSO.

Previously,the aim hasbeento find precursors of one elementin the historyof another.However,this one-wayinteractionhasnot capturedall of the varianceor characterof the monsoon.Either the monsoonsystemis part of an evolvingand systematicseries of feedbacksand processes, or it is part of a complexhierarchy of circulationsand processes whererelationships betweenthem periodicallywax and wane. It would seemthat the emerging view is one wherethe monsoonis seenas a coupledocean-landatmospheresystem,where the monsooninteractswith ENSO and eventuallyENSO feeds back on the monsoon. 4. Within the interactivesystemdescribedin factor 3, there are two classesof possiblemechanismsin which ENSO SST anomalies(and other boundaryconditionssuchas snow cover, etc.) could affect seasonal mean monsoon circulations and rain-

fall. These two mechanismsare as follows. (1) Direct dynamical impactsof circulationanomalieson the monsoonregionsby macro scalecirculationchangesthe first mechanism.Boundary anomalies,suchproducedby ENSO, producea temporallypersistentand spatiallylarge-scaledescentover the monsoonregion reducingrainfall eitherby reducingthe intensityandlife cycleof the monsoondisturbancesor by producinga displacementof the seasonalmean rainfall patterns. (2) The influenceof the macro scalecirculationanomaliesassociated with ENSO, for example, on a basicallychaoticregime is the secondmechanism.In this scenariothe chaoticcomponentof the low-frequencyflow would arisefrom the existenceof basicallyunstablemodesand the existenceof multiplesolutionsof the coupledmonsoonsystemduring the boreal summer.Thus the southAsian monsoonregionduring the boreal summerwould be a sourceof internalerror growthbut underthe large-scaleinfluenceof the slowvariationof the interannual modesof the climatesystemsuchasENSO. In thisargument the ENSO SST anomalieswould tend to nudgethe monsoonintraseasonal variabilitytowardonestate(e.g.,monsoonbreakperiods)or another(e.g., monsoonactiveperiods).That is, if thereis a strongwarm episodein the PacificOcean,it is probablethat the Asian summer monsoon will be weak.

But the chaotic character

of the intraseasonal componentdoesnot make this a certainty. 5. In support of the nonlinear view of the monsoonis the regionalityof the ability of the AMIP modelsto reproducethe structureof the tropical circulations.Whether or not other summer monsooncirculations(e.g., north Australia, Africa, or the

AND PREDICTION

cover, and the strengthof the monsoon. However, modelsare continuallybeing improved,and organizational effortscontinue to intercomparemodel output. Thus, in the near future,the reasonfor simulationdifficulties,modelfailure,or regionalinternal error growth will be determined.

7. Irrespectiveof the causesof the modelingproblemsin the southAsian region, it is clear that to forecastthe seasonaland interannualnature of the monsoonensemble,Monte Carlo techniques will have to be employed.The followingprocess may be envisioned.Coupledocean-atmosphere climatemodels could provideassessments of the Pacific OceanSST distribution at a future time.

Relative to this distribution, ensembles of

predictionsusing global atmosphericmodelswould be run. It would seem at the presenttime that the Pacific Ocean SSTs influencethe monsoon the most. However,thereappearto have beenperiodsduringwhichthe variabilityof the monsoonandthe PacificOceanSSTwererelativelyunrelated.It is unclearwhether or not the other oceans increased their influence at those times.

However,what is clear is that the predictionof the monsoonwill

haveto be accomplished throughthemultipleintegrations of fully coupled,global oceanand atmosphericmodels. Therearefurtherreasons for optimismthatmanyof theproblemsdescribed in thisreviewwill be solved.DuringtheTOGA decade,significant progress wasmadein understanding processes involvedin theinterannual variabilityof thePacificOceanbasin. A newprogram,theGlobalOcean-Atmosphere LandSystemprogram(GOALS) [NRC, 1994;WCRP,1995]undertheauspices of the international ClimateVariabilityandPredictability program (CLIVAR) [WCRP, 1995], plansto take the successes of TOGA to the globaldomain.The strategyis to extendthe observational andmodeling focusfromthetropicalPacificOceanlongitudinally to the othertropicaloceansin orderto encompass themajorheat sources andsinksof thecoupledocean-atmosphere systemandto encompassthe interactionsbetween the heat sourcesand sinks.

It is thenplannedto extendtheseeffortsto higherlatitudesto seeksignalsof predictability emanating fromthe tropicsand,at the sametime, seekpredictableelementsinherentin the higher latitudes.If the latterdo exist,they wouldbe part of the ocean dynamicsor landsurfaceprocesses. Theseplanswill be accomplishedby the extensionof long-termmonitoringof the coupled systemintothe othertropicaloceansandthroughtheexecutionof processstudies.The modelingprogramdevelopedunderTOGA will

be continued.

What is particularlyinterestingfor monsoonstudiesis that a primary focus of the GOALS programwill be the monsoon systemsof Asia, Africa, and the Americasas theyconstitute the largestheatsources outsideof the PacificOceanwarmpool. To coordinate monsoon-relatedactivities, a CLIVAR Monsoon Panel

has beencreated. A detailedstudyof the Americanmonsoon andits relationship to theeasternPacificOceanis underway with the U.S. Pan AmericanClimate Studiesprogram(PACS) and the international Variabilityof the AmericanMonsoonsSystem Americas) are more or less deterministic would remain to be de(VAMOS) program.In addition,the international GlobalEnergy termined. However, the greater ability of the AMIP modelsto and Water Cycle Experiment(GEWEX) [WCRP, 1995] has a simulatemore closely other aspectsof the tropical circulation majorfocuson surface hydrological processes, especially through would perhapssuggestthat the southAsian monsoonpossesses the GEWEX Asian MonsoonExperiments(GAME) [Yasunari, unique properties. 1994],whicharea seriesof process studiesin theAsianregion. 6. In oppositionto the secondmechanismin factor 2 it was One of the majorelementsof the GOALS programis applisugges•e,•that the ro.•r•nalltxtr•tv the mc•clolrileper,inn was d.e to model inadequaciesrather than the existenceof chaotic dynamics. It was arguedthat the complexityof the southAsian region taxes the model formulationsand parameterizations.For example,currentGCMs are not able to reproducewith greatclarity the relativelywell-knownrelationships betweenENSO, snow

...... s and humandimensionsaspectof seasonalto im,,rannual

predictability. The aim is to developan "end-to-end" prediction systemthatbringstogetherthephysicalscientists, whomakepredictions,socialscientists, andthe usercommunity.Theseefforts wouldseemparticularlyusefulin the monsoon regions,giventhe dependency of thelocalsocietieson the vagariesof themonsoon.

WEBSTER ET AL.: MONSOON PREDICTABILITY AND PREDICTION Table 6.

Criteria Used to Define Active and Break Periods of

the MonsoonDuring the BorealSummerAsian-Australian Monsoon Condition

850-mbar meridional wind at

Active

Break

> 3

> - 3

> 3

> - 3

< 10

> 10

14,505

Asia. Thus active and break periodsof the monsoonare defined a posteriori. In this studythe definitionof Maga•a and Webster [1996] has been adopted. The definitionsare shownin Table 6. The dateson which thesecriteria were satisfied(in Juliandays) duringthe 12-year periodfrom 1980 to 1991 are shownin Table 7.

(45øE,0øN), m s-1 850-mbar zonal wind at

(65ø-95øE,10ø-20øN), m s-1 Outgoinglongwaveradiationat

(65ø-95øE,10ø-20øN), W m-2 After Maga•a and Webster[ 1996].

Appendix' Definition of Active and Break Periods During South Asian Summer Monsoon

Acknowledgments. The authorsare particularlyindebtedto the thoughtful reviews of the manuscriptby J. S. Godfrey, R. Kershaw and D. Stephenson.The authorswould like to thank C. Brankovic,G. Compo, S. Dixit, L. Ferranti, D. Lawrence,J. Loschnigg,X- W. Quan, K. Sahami and C. Torrencefor making available new resultsand for creatinga numberof the figures.We havebenefitedgreatlyfrom valuable discussions with S. Dixit and J. A. Curry. This paper was compiled with supportfrom the National ScienceFoundationunder grantsATM8807142, ATM-9114229, and ATM-9500338 for MY, ATM-9526030 for

PJW, andby the NationalOceanicandAtmosphericAdministrationunder GrantsNA56GP0203 for MY and NA56GP0230 for PJW. Computations The IndianMeteorologicalDepartmentdefinesa "breakin the wereperformedat theNationalCenterfor AtmosphericResearch(NCAR), monsoon"as a generalcessationof precipitationover most of the Office of AcademicComputingand the Departmentof Atmospheric India with exceptionof the very southof PeninsularIndia andthe Sciencesat University of California, Los Angeles, the University of foothills of the Himalayas. This rainfall patternis accompanied Colorado'sProgramin Atmosphericand OceanicSciences,the Centerfor by a risein surfacepressure of 2-3 mbarovercentralIndia asthe Ocean,LandandAtmosphere(COLA), WashingtonDC, andtheEuropean Centre for Medium-RangeWeatherForecastsin Reading,England.

monsoontroughmovesnorthward.However,it has beennoted that the breaks in the monsoon and also the enhancement of the

monsoonflow in betweenthe breaks(the active periodsof the References monsoon)are on a scalemuch largerthan India or even south Ackerman, S. A., and S. K. Cox, The Saudi Arabian heat low: Aerosol distributionsandthermodynamicstructure,J. Geophys.Res.,87, 89919002, 1982. Table

7.

Dates of Active

and Break Periods Between

1980-1991 in Julian Days Year 1980

1981

1982

1983

1984

1985

1986

1987

1988

1989

1990

1991

1992

1993

Mode Julian Days A

150-155, 196-198, 228-233

B

185-187, 218-222

A

148-153, 210-213, 265-268

B

183-186, 242-245, 283-288

A

147-153, 162-167, 194-197, 222-225, 265-267

B

173-176, 205-207, 210-213, 243-247, 277-283

A

169-175, 200-203, 252-254

B

183-187, 216-218, 295-296

A

149-154, 168-170, 195-198, 243-247, 272-274

B

173-176, 205,209, 257-261,293-296

A

145-154, 250-253, 277-281

B

185-189, 256-259, 296-300

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