Jan 1, 2001 - John R. Christy. University of Alabama in Huntsville ..... Parker, D. E., M. Gordon, D. P. N. Cullum, D. M. H. Sexton, C.K.. Foiland, and N. Rayner, ...
GEOPHYSICAL RESEARCH LETTERS, VOL. 28, NO. 1, PAGES 183-186, JANUARY 1,2001
Differential Trendsin Tropical SeaSurfaceand Atmospheric Temperatures since 1979 JohnR. Christy Universityof Alabamain Huntsville,Huntsville,AlabamaUSA
David E. Parker, Simon J. Brown, Ian Macadam HadleyCentrefor ClimatePredictionandResearch,The Met. Office, Bracknell,UK
Martin
Stendel
DanishMeteorological Institute,Copenhagen, Denmark
William
B. Norris
Universityof Alabamain Huntsville,Huntsville,AlabamaUSA
Abstract. A variety of measurements indicatethat the rate of atmosphericwarmingin the tropicssince 1979 is lessthan the observedwarming of the sea surface. This result is further
2.
examinedusing the high quality buoys monitored by the Pacific Marine EnvironmentalLaboratory in the Tropical PacificOcean.Thesebuoysshowcooling(mostcasesbeing statisticallysignificant)of the air at 3m height relative to the sea at I m depth over 8 to 20-year periods in the eastern region.A globalsurfacetemperature datasetwhichusesonly near-surfaceair temperature over both land and ocean, indicateslesswarmingsince1979thanthoseusingSSTsover the oceans,though large uncertaintiesremainwith marineair
from the engineintake, but up to a third have used insulated buckets or hull sensors(Foiland et al., 1993). The depth of measurementrangesfrom less than 1 m to over 15m. Ships alsoreportmarineair temperature(MAT) on deck. In the past two decades,many buoys, both moored and drifting, have been added to the observational mix and these report SST typically at 1 m depth,as well as MAT at a few metersheight.
temperatures.
1.
Introduction
Overthe pasttwo decades, therehavebeenlargeregional differencesin the local correlation between monthly troposphericand sea surface temperature(SST)anomalies, rangingfrom nearzero in the westerntropicalPacificto 0.9 in
the easterntropical Pacific (Trenberthet al. 1992, Christy 1995, Hurrell and Trenberth1996). SST and atmospheric temperatures have also showndifferenttrends. For example, Christyet al. (1998) notedthat night marineair temperature (NMAT) displayeda lesspositive trendthan SST by 0.07 K decade '• in the zone20øSto 20øNbetween1979and 1996. In this paperwe furtheranalyzethis trend differenceby comparingthe tropical portions of global SST, NMAT and tropospherictemperaturedatasetsalong with high quality observations from PacificMarine EnvironmentalLaboratory (PMEL) buoysin the tropical Pacific. Thesedata confirm the
existenceof differentialtrendsin the surfaceand atmospheric temperaturessince 1979.
Copyright2001 bytheAmericanGeophysical Union.
Data
Since themid-20 thcentury, mostshipshavereported SST
On average,tropical SSTs are warmestat the surfaceand a few tenths of a degree cooler deeper in the ship-intake range (Webster et al. 1996), and MAT decreaseswith height, so changesin the mix of measuringtechniquesor locations may causespurioustrendsin SST and MAT. We assembled the SSTsandMATs, applied similar quality checks to each, and generated global datasets: here we use MOHSST6D for SST and MOHMAT42 for MAT (Parker et al. 1995). MOHSST6D is not compensatedfor the heterogeneity of variance caused by historical changes in the numbers of data, whereas the newer HadSST (Jones et al., 2000) is. However, HadSST cannotbe fairly comparedwith MOHMAT42 becausethis compensationhas not yet been applied to MAT. MOHMAT42 holdsonly NMAT, to avoid historically varying warm daytimebiases(Parker et al., 1995), and is normalized to 15 m height assuminga lapse rate basedon similarity theory (Bottomley et al., 1990). Sincethe early 1980s,arraysof PMEL mooredbuoys have been deployed to monitor the data-sparseregions of the tropical Pacific. One set is positioned to capturethe major fluctuationsof the tropical Pacific associatedwith the El Nifio / SouthernOscillation (ENSO)(Weisberg and Hayes 1995). Amongthe sensorsare thermometers at 1 m depth for SST and 3 m heightfor MAT. The PMEL releases24-hourly averagesof thesedata, which are free of daytime heating biases due to proper sensorexposure,for public access. We use three sets of low-mid tropospherictemperature data. First are the MicrowaveSoundingUnit (MSU) retrievals, which use the intensity of microwave emissions from molecularoxygen to monitor atmospherictemperature. The
emissionsfromthe surfaceto about400 hPa provide nearly all of the energydetectedby the retrievalsknown as MSU 2LT (MSU channel 2, Low-mid Troposphere), with maximum
Papernumber2000GL011167. 0094-8276/01/2000GL011167505.00
183
184
sensitivity near 750 hPa. We use version D (Christy et al., 2000), which has been correctedfor orbital altitude decay, orbital longitudinaldrift, diurnaleffectsand instrument-body temperatureeffects. Secondly, we assembledmonthly radiosonde data from over 400 stations worldwide and used the pressure-level temperaturesto simulate the MSU 2LT temperatureproduct. Our 5¸ latitude x 10¸ longitude gridded datasetis known as HadRT2.0 2LT and is completely independent of the MSU datasets. There are large data voids, but these are less important in the tropospherethan at the surface as spatial variations are very coherent, so that there are only approximately eight spatial degreesof freedom in the 20øS20øN band (Hurrell and Trenberth 1998). We use over 50 stations in this band. Changing radiosondeinstrumentation may introducebiases(Gaffen 1994, Luers and Eskridge 1998, Gaffen et al. 2000a), but a comparison of unadjusted and adjusted (using MSU: Parker et al., 1997) HadRT datasets showedlittle impact in the low-mid troposphereaverage. The last low-mid tropospheric dataset, which also simulatesthe MSU 2LT product, is derived from the National Centers for Environmental Prediction (NCEP) global reanalysis(Kalnay et al. 1996). This analysisemploys a fixed global atmosphericcirculation model to assimilatedata from all available sources(in situ and satellite, but excluding our MSU products)in orderto generateglobal analysesof climate variables. Though the analysis uses a consistent methodology,any non-climaticchangein the input data, not filtered by quality control, affects the final product. For example, the retrieval schemewhich createspressure-level data from satellite observations was revised in 1992, introducinga slight cooling in the lowest-leveltropospheric temperaturesover the oceans where retrievals are employed (Basist and Chelliah 1997, Stendel et al., 2000). For the troposphere as a whole, however,the effectwas small. 3.
Results
Figure 1 shows annual differences for 1979 to 1999 between anomalies (relative to 1979 to 1980) of tropical atmospheric temperatureand SST. Table 1 showsthe trends of eachvariable. The trendsare calculatedby two techniques,to confirm insensitivity to the statisticalmethod (Gaffen et al., 2000a). We useall availabledata,i.e. the MSU andsurfacedata are not resampledto be collocatedwith the radiosondedata: tests show this has minimal impact. All the atmospheric temperaturedatasetsshow a negative trend relative to the SSTs, with the trend of the near-surfaceNMATs between that
of the SSTsand the low-mid troposphere.The trends of the differencesin Figure 1 are significantly different from zero at the 95% level, even though the individual absolute trends have overlapping 2o error-bars (Table 1). This is because commonvariability has been eliminated in the subtraction of the air temperatureanomaliesfrom the SST anomalies(Santer et al., 2000a). This supportsthe result of Christy et al. (1998) that recentatmospherictemperatures have not risen as rapidly as SSTs.Figure 1 also corroboratesthe three independent measures of tropospheric temperatures by their close
Air Temperature Anomalies minus SST Anomalies, 1979-1999 Tropics (20øS-20øN) 0.1
0.0
-0.1
-0.2
-0.3
K -0.4
--C--NMAT-SST -0.5
- •MSU2LT-SST --O..... HadRT2LT-SST
-0.6
-••NCEP2LT-SST .....................
979
1982
1985
1988
1991
1994
1997
2000
Figure 1. Annual differencesof anomaliesof various tropical (20øS-20øN) air temperature values versus sea surf•tce temperaturewith 1979-1980 as the base. Dataset names are identifiedin the text. Note that all measuresof air temperature indicate less positive trends than observed by sea surface temperatures.
K decade"coolingbias.So,to furthercompareSSTwith nearsurfaceair temperature,we examinethe longest records from the PMEL moored buoys in the key tropical Pacific regions related to tropospherictemperaturevariations. We use 10 buoysin the "E" region(5øS - 5øN, 110ø-125øW)and 9 buoys in the "W" region (5øS-5øN, 156ø-165øE). We converted the SST and MAT data to daily anomaliesrelative to the average for the full record for each individual buoy, collocating by setting both SST and MAT to missing if either was missing. All trend analyses required at least 65% of the daily observations to be available
and that there be data in the first
and last years. Correlationsbetweenbuoy SST, buoy MAT and MSU 2LT temperatureare given in Table 2 for three multi-year periods all endingin April 1999. We used tropical-average,not local,
Table1 Tropical(20øS-20øN) temperature trends (K decade -l) and 20 uncertainties (in parentheses)during 1979-1999 computedby ordinary least-squareslinear regression(OLS) and by the median of pair-wise slopes (MPS, Gaffen et al., 2000a). Trend differencesvs. SST are listed in last column with 2-0 uncertainties
which are smaller than those
of the
absolutetrendsdue to the removal of commonvariability.
agreement.
The tropically-averaged NMAT values are derived from thousands of observations for each month's data, but the quality and distributionof the data are not ideal (Parkeret al. 1995). Many areasoutside shipping lanes are unsampledor sparselyobserved.Also, we assumeda constantdeck altitude of 15m (Bottomleyet al., 1990) in recentdecades. If the true meanelevationhas,however,increasedsince 1979, there may be a cooling bias in the NMAT changes,e.g. an undetected, meanupwardshift of 3 m over 20 yearscould lead to a 0.025
'
OLS
MPS
MOHSST6D
+0.13 (0.11)
+0.14 (0.13)
X
MOHMAT42
+0.06 (0.11)
+0.07 (0.12)
-0.08 (0.03)
-0.01 (0.17)
-0.03 (0.16)
-0.14 (0.08)
-0.06 (0.13)
-0.10 (0.12)
-0.19 (0.08)
-0.05 (0.16)
-0.06 (0.15)
-0.18 (0.07)
MSU 2LT
HadRT2.0 NCEP 2LT
2LT
Air - SST
185
Table 2 Averageof the individual correlationsbetweenPMEL buoy SST, PMEL buoy MAT, and MSU 2LT tropical-averaged temperaturefor averagingperiodsof 9! and (in parentheses) 365 days. The lengthof the time seriesis given as years ending in April 1999. Regions"E" and "W" are definedin the text.
YearsNo.buoys BuoySSTv. BuoySST v. ."W","E" buo?MAT
BuoySST v.
BuoySST v.
BuoyMAT v.
2LT
2LT
2LT
2LT
buo•vMAT
BuoyMAT v.
8
9,10
0.63 (0.58)
0.94(0.94) -0.39(-0.38)
0.76(0.81)
-0.17(0.02)
0.71(0.75)
10
5,5
0.49 (0.21)
0.95 (0.95)
-0.17 (-0.20)
0.72 (0.72)
-0.14 (0.01)
0.65 (0.60)
14
2,5
0.51 (0.40)
0.96 (0.98)
0.05 (0.12)
0.73 (0.77)
-0.06 (0.12)
0.70 (0.73)
.
MSU 2LT to highlightthe spatialvariationsin the correlation of surface temperatureswith it. The correlations were calculatedfor two averagingperiods,91 daysand 365 days, to
at the 95% level with the exception of the single-buoy, 20year result.
To say that MOHMAT42 data accurately reflect the
capturethe longer-term variations. The correlationswith the tendencies of tropics-wide MAT is not possible with the MSU 2LT were performedwith the troposphericanomalies present limited array of PMEL buoys. However, the laggingthoseof the surfaceby 90 days,the typical time scale comparisons for these two important regions, with the determinedfrom empiricaltests(Christy and McNider, 1994). additional feature that the "E" region is closely related to The "E" region is centeredin the activearea of the ENSO where tropics-widevariationsand difference-trends,suggestthat the there are large interannualvariationsof severalK, while in the MOHMAT42 tendencies may provide useful information in "W" region, NE of Australia, variations are smaller. Annual terms of trend relative to SSTs. The tropics-wide data (Table standarddeviations of SST anomaliesfor regions within "E" 1) show that NMAT has warmed less than SST by 0.08 K and "W" are 0.47 K and 0.09 K respectively(Christy, 1995). decade '• overtheperiod1979to 1999whichis statistically Strong coupling betweenPMEL SST and MAT is seen in significant at the 95% level. The tropics-wide average "E" wherecorrelationsare well above 0.9 (Table 2), while in difference-trend arises from trend differences in the eastern "W" the SST anomalies are correlated with MAT
anomalies
Pacific and Indian Oceans, while the western Pacific and
only at about 0.5. Roughly 60% of the variance of the tropically-averagedtropospherictemperatureis explained by SST anomaliesin "E" while those in "W" explain essentially none. CorrelationsbetweenMAT and MSU 2LT are slightly
Atlantic Ocean difference-trendsare insignificant. The trend in (NMAT minus SST) is not useful for prediction, especially since we use at most only 21 years of data, and year-to-year variations can be large. Climate less than those of SST and MSU 2LT and those of SST and variations occur on all time scales,so this particular 21-year MAT, perhaps indicating that both MAT and MSU 2LT period may not be representativeof any other 21-year period respondto SST forcing on different scales.In any case,the (Santer et al. 1999, 2000a). However the trend is useful as a behaviorof SST and MAT in "E" is much more representative sensitive indicator of past tendencies and of differences of the tropical atmosphereas a whole and it is here that we between datasets. Our results suggest real, though slight, findthePMEL SSTtrendsignificantlymorepositive than the differencesin the responsesof surfacewater and near-surface collocatedMAT (Table 3). marine air temperatures to climate forcings. The The trendsin (MAT minusSST) determinedfrom the highreproducibility of the difference-trends by independent quality PMEL buoys are compatible with those determined datasets reinforces this conclusion. from approximatelycollocatedmerchantship and buoy data A descriptionof the physicalcausesfor this differencein MOHSST6D andMOHMAT42 whichare dominatedby ship trendis beyondthe scopeof thispaper. Differentresponses to and non-PMEL buoy reports (Table 3). The non-significant result in "E" over the 20-year period may be a sampling ENSO events and volcanic forcings betweenthe ocean and
artifact as there is only one buoy available for comparison. Even so, none of the (NMAT minus SST) trends from the MOHSST6D and MOHMAT42 data is statistically significantly different from the correspondingPMEL-based trend. In addition, all PMEL (MAT minus SST) negative trendsin "E" are statisticallysignificantly differentfrom zero
atmosphere are prime candidates(Santeret al. 2000b). In addition,Brownet al (2000) andGaffenet al. (2000b) reported multidecadalvariations in tropical troposphericlapse rates which could be linked to variations in atmospheric circulation such as the Interdecadal Pacific Oscillation (Power et al., 1999).
Table3 Trendsin K/decadeof SSTandMAT minus SST basedon a time seriesof mergedannualaveragesof collocated observations from PMEL buoys.Also, in italics, are trends basedon MOHMAT42 and MOHSST6D in (10øS-IOøN, 160øE170øE)whichoverlaps"W"and in (5øS- 5øN,80øW- 130øW)which includes"E". 2-o uncertaintiesaregiven in parentheses. The twenty-yearresult(*) endsin December1999,all otherperiodsend in April 1999. Key otherwiseis as in Table 2. Years 8
No. buoys
'SST
SST
"W", "E ....
W"
"E ....
9,10
MAT-SST MAT-SST W ....
E"
-0.02(0.54) 1.23(1.98) 0.50(0.23)' -0.34(0132)
10
5,5
-0.26 (0.37)
1.66 (1.48)
0.55 (0.42)
-0.43 (0.16)
14
2,5
+0.02 (0.40) -0.12 (0.16)
0.19 (0.29) 0.13 (0.25)
20*
0,1
1.04 (0.85) 0.74 (1.21) 0.36 (1.86)
-0.22 (0.08) -0.06 (0.16) -0.14 (0.18)
,
O.04 (0.76•)
-0.05(0.08)
186
4.
Conclusions
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J.R. Christy, ESSC/GHCC, University of Alabama in Huntsville, HuntsvilleAL 35899. (christy•atmos.uah.edu). D.E. Parker, S.J. Brown and I.Macadam, Hadley Centre for Climate Prediction and Research, The Met. Office,
London Road,
Bracknell,Berkshire,RG12 2SY, U.K. (deparker•meto.gov.uk). M. Stendel, Danish Meteorological Institute, Lyngbyvej 100, 2100 Copenhagen, Denmark(mas•dmi.dk). W.B. Norris, ESSC/GHCC, University of Alabama in Huntsville, HuntsvilleAL 35899. (norris•atmos.uah.edu). (Received 20 October 1999, revised20 September2000, accepted 12 October 2000)
