Mar 20, 1994 - process of moist convection with the use of a simple bulk cloud model, which provides a basis for estimating convective-scale transports of heat ...
JOURNAL
OF GEOPHYSICAL
Parameterization
RESEARCH,
of moist convection
VOL. 99, NO. D3, PAGES 5551-5568, MARCH
in the National
20, 1994
Center
for Atmospheric Research community climate model (CCM2) James J. Hack National Center for Atmospheric Research, Boulder, Colorado
Abstract. The National Center for Atmospheric Research (NCAR) community climate model (CCM) has historically made use of a moist adiabatic adjustment procedure for parameterizing the effects of moist convection. The most recent version of the NCAR CCM, CCM2, has abandoned this approach in favor of a stability-dependent mass-flux representation of moist convective processes. This scheme physically constrains the process of moist convection with the use of a simple bulk cloud model, which provides a basis for estimating convective-scale transports of heat, moisture, and other atmospheric constituents as well as the diabatic heating associatedwith condensation and the fallout of precipitation. This paper presents the formalism associated with this simple mass-flux approach and contrasts its behavior with the moist adiabatic adjustment procedure used in earlier models. The inclusion of this scheme significantly moistens and warms the model troposphere at all latitudes but particularly in the tropics. Additionally, the simulated magnitude, structure, and location of the largescale mean circulations are generally improved. The sensitivity of the simulated climate to the formulation of the cloud model is also presented. classes: moist adiabatic adjustment schemes [e.g., Manabe et al., 1965], moisture convergence schemes [e.g., Kuo, Observational studies have long since established the 1965, 1974; Anther, 1977; Donner et al., 1982], and Arfundamental role of moist convection in maintaining the akawa-Schubert schemes [e.g., Arakawa and Schubert, large-scale dynamical circulations in the tropics, which in 1974; Lord, 1982; Hack et al., 1984; Moorthi and Suarez, turn play an important role in the maintenance of the 1992]. More recently, a new generation of convective adjustatmospheric general circulation and climate [e.g., Riehl and ment [e.g., Bettr, 1986; Emanuel, 1991] and alternative Malkur, 1958; Lorenz, 1967; Newell et al., 1972]. Efforts to "mass-flux" approaches [e.g., Tiedke, 1989] have emerged properly incorporate the effects of moist convection in in the general circulation modeling community, further global-scale models are hampered by the wide range of broadening the range of parameterization techniques. Eximportant space and timescales occurring in the atmo- plicit treatment of the vertical mass transport attributable to sphere's general circulation. Because of computational cost, convective overturning is a common characteristic of massglobal numerical integrations of the governing atmospheric flux approaches. equations can only resolve the primary energetic and phePrevious versions of the National Center for Atmospheric nomenological scales of motion. Convective-scale pro- Research (NCAR) community climate model (CCM) have cesses, which are responsible for most of the phase change used the moist adiabatic adjustment procedure, which adand associated precipitation occurring in the atmosphere, justs the lapse rate of a saturated conditionally unstable are only of the order of several kilometers in scale and atmosphere to neutrality. Any water mass condensed in this therefore are contained in the truncated scales of motion. stratification process is immediately precipitated out of the Even though these processes occur below the resolvable system. This procedure is both simple and economical but scales of motion in a general circulation model, they never- ignores details of the physical processes associated with theless represent a very large, and often dominant, local moist convection, such as the details of vertical eddy transenergy source/sink in the climate system. port. Consequently, the utility of the scheme for investigatIt is argued that it should be possible to predict the time ing detailed interactions between convection and the largeevolution of the large-scale fields by describing only the scale motion field is extremely limited. For example, collective influence of the small-scale elements. Convective Albrecht et al. [1986] have demonstrated that the severe cold parameterization techniques seek to express the statistical bias exhibited by the NCAR CCM0 is attributable in part to contributionof these nonresolvableprocessesin terms of the the neglect of explicit penetrative eddy fluxes of water when explicitly resolved fields. Several interesting overviews on using a moist adiabatic adjustment approach. Such deficienthe subject of convective parameterization can be found in cies have provided a strong incentive to move toward a more the work of Frank [1983], Tiedtke [1988], and Cotton and comprehensive parameterization of moist convection in the Anther [1989]. In the past the most widely utilized convecNCAR CCM. tive parameterization methods have belongedto one of three Even the most sophisticated of cumulus parameterization Copyright 1994 by the American Geophysical Union. techniques lack the generality to treat the many types of moist convection that can occur in an atmospheric general Paper number 93JD03478. 0148-0227/94/93 JD-03478 $05.00 circulation model (e.g., convection not rooted in the bound1.
Introduction
5551
5552
HACK:
PARAMETERIZATION
OF MOIST
CONVECTION
ary layer). Consequently, these schemesoften rely on simple secondary convective adjustment procedures to deal with moist adiabatically unstable conditions remaining after their application. Ironically, these secondaryprocedurescan contribute significantlyto the large-scalethermodynamicbudget [e.g., Randall et al., 1989]. Thus their proper formulation should be of comparable importance to the formulation of the primary convective scheme. The motivation for the work presented in this paper was to formulate a minimal framework for parameterizing the process of moist convection in the NCAR CCM2. Our objectives were that the formulation
k-I
k+l
be suitable for use as either
the primary convective parameterization or as a secondary schemethat could be used in conjunction with another, more sophisticated,technique. Additionally, it was important that the scheme provide an estimate of the "sub-grid-scale" vertical mass exchange associatedwith the process of moist convection (e.g., to provide for a consistent treatment of constituent transport). In section 2 we present the detailed formalism for a simple stability-dependent mass flux approach that we believe satisfies these objectives. This scheme is used to parameterize moist convection in the NCAR CCM2, which is briefly described in section 3. In section 4 we illustrate the properties of this convection scheme by contrasting aspects of the CCM2 control climate with the climate produced by the CCM2 when using a moist adiabatic adjustment procedure. The details of the thermodynamic balance produced by each of the schemes,on both a global and a regional basis, will also be discussed.Finally, we show that although the mathematical approach for the simple mass flux scheme presented in section 2 is very similar to the moist convective adjustment procedure developed for the UCLA GCM by Arakawa and Mintz [1974], there are significant differences in their behavior. Once again, this comparison is made in the context of a long-term integration of the NCAR CCM2.
h• Figure 1. Conceptual three-level nonentraining cloud model. Tilde quantities represent "environmental" values.
terms in (1) and (2) are the major convective-scale contributors to the large-scalethermodynamic budget (i.e., horizontal eddy flux transports can be neglected). The barred quantities represent horizontal averages over an area large enough to contain a collection of cloud elements but small enough so as to cover only a fraction of a large-scale disturbance. By writing the mean thermodynamic variables in terms of their average cloud and environment properties and assuming that the convection occupies only a small fraction of the averaging area, the vertical eddy transports o)'s• and oo'(q' + l') can be approximatedby the difference between the upward flux inside a typical convective element and the downward flux (i.e., induced subsidence) in the environment [cf. Yanai et al., 1973]. Mathematically, this approximation takes the form 1
Fs,(p)=
(w's}) • -Mc(P)(g(p)
g
- Sc(P) + Ll(p)) (3)
2.
Mathematical
Formalism
1
The large-scale budget equations for dry static energy and total water
can be written
Fq+•(p) = --
g
(to'(q' +/')) -• -Mc(p)(cj(p)
as
- qc(P) - l(p))
• = -V. Vg at
op
Op
(w's•) + L• + cpQR
R.S.
op
( to' s}) + Lift
(4)
where Mc is a convective mass flux and Sc, qc, and l represent cloud-scale properties. Once again, note that the (1)
large-scaleenvironment is assumedto carry no liquid water. Thus (1) and (2) can be written as o
•= ot
-v.vq
op
op
ot
(to'(q' + 1')) - fit o
oq R.S.
op
(to'(q' + l')) - fit
ot
R.S.
+g
+
--=Fq+ 1--•. Ot Ot R.S.+g•pp
(2)
(5) (6)
Let us now turn our attention to a vertically discrete
wheres -= cpT + gz is the dry staticenergy;I represents model atmosphere (where the level index k decreases upliquid water; st -- s - LI is the static energy analog of the liquid water potential temperature introduced by Bens [1975]; • is the "convective-scale" rainwater sink; and QR is the net radiative heating rate. The subscriptR.S. denotes the resolvable-scale contributions to the large-scalebudget. Note that variations of the mean liquid water on the largescale are neglected. It is generally agreed that the remaining
ward) and consider the case where layers k and k + 1 are moist adiabatically unstable, i.e., a nonentraining parcel of
air at level k + 1 (with moist static energy h c) would be unstable
if raised to level k. We assume the existence
of a
nonentraining convective element with roots in level k + 1, condensationand rain out processesin level k, and limited detrainmentin level k - 1 (see Figure 1). In accordancewith
HACK: PARAMETERIZATION
(5) and (6) the discrete dry static energy and specifichumidity budgetequationsfor thesethree layers can be written as
•
=
Ot
Apk_ 1
{fima(Sc - Llk- •k_!)},
(7)
2
Ot
5553
where3'= (L/cp)(Oq*/OT'-)p andq} represents thesaturated specifichumidity.Assumingthat the large-scaleliquid water divergencein layer k is zero (i.e., there is no storageof liquid water in layer k), (16) can be manipulatedto give the rain-out term in layer k as
LRk-= L(1 - 13)mslk = (1 -/3)m s
g
•
OF MOIST CONVECTION
{ms(sc - Zk+!) 2
{
ß
- 13ms(s c- LIa- ga_lj) + LRa),
(8)
Sc +
l+y•
}
(h,.-
,
and the liquid water flux into layer k - 1 as (9)
• at = Ap•+• {ms(ga+•Sc)), •
Ot
=•
Apk_ •
13msLl k=13ms gk- s + c
(lO)
{/3ms(qc - qk_!)), 2
l+yk
(hc- •}) ß (19)
Equations(9) and (12) can be combinedto give an equation for the consumptionof moiststaticenergyin layer k + 1 by convection,
0q•
Ot
g
•Ap• {ms(qc - q•+•)-/3ms(qc - qk_!) - R•},
Oh•+•
2
(11)
ot
= Apk+• {ms(qk+« - qc)),
(12)
where the subscriptc denotescloud propertiesin the ascent region;q denotestotal water; ms is a convectivemassflux ,
1
parameter' at levelk - • thatwilltakea valuebetween 0
Ohc
(20)
where the approximationfollows from the assumptionthat Oh'/Otcan be neglected.Using the relation (1 + y•)(Og•/Ot)=
(O•/Ot), (8) can be manipulatedto give an expression for the time rate of change of saturated moist static energy in layer k
atthebottom ofthecondensation layer (level k + •, "cloud base"); and /3 is a yet to be determined "detrainment
#
• Ot = Ap•+1 ms(h•:+i•hc)• •Ot '
Off• gms
•= Ot
Apk
-
1
(1+ yk){(Scs•+•+ LI•)- fi(sc- •_1)}. 2
and 1. Thus the detrainmentparameteris a coefficienton the
convective mass fluxatlevel k + •, sothatthequantity flmB Subtracting(21) from (20) results in represents the convective massfluxthrough levelk - •. Note that the convective-scale
rainwater
sink •
has been
O(hc-[ a _ g(1+•'•)[(gkg•+•)tt(Scg•_l•)]}, (22)
redefined in terms of mass per unit area per unit time = msAp•,+• (h•+•- hc) Ot (denotedby R), and the resolvable-scalecomponentshave been dropped for the convenienceof the following discussion (i.e., the left-hand sides represent the large-scaleresponseto convective activity only). In the generalcase, the thermodynamicpropertiesof the from which the convective massflux ms can be written as
updraftregioncanbe assumedto be equalto their large-scale valuesin the subcloudlayer, level k + 1, plus somearbitrary thermodynamic perturbation, i.e.,
sc = gk+• + s',
(13)
qc = c7k+l+ q',
(14)
hc = Sc+ Lqc.
(15)
ms '--* ( Yk) - - •+ Ll•) = (h c - h Or Ap• [(Sc l_ h c] 1 [h•+• --•(Sc-•'k-l• )] Ap•+l
(23)
where r is a characteristicconvective adjustmenttimescale. Thus moist convection is possible anytime the numerator,
The perturbationquantitiesq' and s' are not an essential hc - if} > 0, and the convectivemassflux is directly componentof the schemebut in practiceare providedby the determined as a function of this stability measure. atmosphericboundarylayer (ABL) scheme(only for conPhysicallyrealistic solutionsrequire that the convective vective elements rooted in the boundary layer), as will be massflux ms be positive,implyingthe followingconstraint discussed
later.
on the detrainment parameter/3:
The liquid water generationrate at level k is given by the definition of the total water, qc
mslk = ms[qc- (qc)k]
(16)
where (qc)k is the specifichumidityin the ascentregionat
/3(1 + y•)(s c- •_!)2 < (1 + y•)(s c - s•+•+ - • Llk) Ap•
Ap•+l
(h•+•-hc).
(24)
level k. Using the saturation relation
(qc)k • q} + •
yk
l+ykL
1
- (hc - h k),
(17)
The CCM2 implementationimposestwo additionalphysical constraintson the procedure,which take the form of constraints on the detrainment parameter /3 [see Hack et al.,
5554
HACK:
PARAMETERIZATION
OF MOIST
CONVECTION
1993]. The first constraint does not allow the convection to
supersaturate the "detrainment layer," k - 1, while the second attempts to minimize the introduction of "2Ap" thermodynamic structures in the vertical. The constraint on supersaturationis not an intrinsic characteristic of the parameterization technique but is imposed because supersaturation of a model layer implicitly introduces the storage of liquid water on the large scale, somethingwhich the present CCM2 physics framework does not treat adequately (e.g., stable condensation would immediately remove such a supersaturated water mass). This constraint could be relaxed by generalizing the convection formalism to deal with liquid water in the "environment" coupled with the introduction of an explicit large-scaleliquid water transport capability (e.g., including the appropriate large-scale microphysicsformalism).
Figure 2. Method of successiveapplication of the cloud model shown in Figure 1, moving up one model layer with each application. See text for further discussion.
The discrete form of the total water budget (equations (10)-(12)) assumes that the total water flux and total mass
flux are linearly coupled, so that the detrainmentparameter /3 effectively determines the actual autoconversionof cloud water to rainwater. Thus the maximum detrainment,i•max,is determined from a minimum autoconversion requirement, which is mathematically written as
•
B max= max
,
1 - Co(SZ- t•Zmin)
(25)
budget equations (7)-(12) to complete the thermodynamic adjustment in layers k - 1 through k + 1. By repeated applicationof this procedurefrom the bottom of the model to the top, shifting up one discrete model layer at a time (see Figure 2), the thermodynamic structure is stabilized. Physically, the adjustment of a pair of layers further destabilizes the region immediately above, which is respondedto by the next application of the cloud model. A vertical profile of the
total cloud massflux, M c (whereMc•+•/2= mB•+•/2 +
where Co is a constantautoconversioncoetficient,/Szis the fima,+3/2) canbeconstructed andcanbeusedto estimate the depth of contiguousconvective activity (i.e., layers in which convective-scale transport of an arbitrary set of passive condensationand rain-out take place) including and below scalars. The free parameters for the scheme (and their layer k, and t•Zminis a minimum depth for precipitating default values) consist of a minimum convective detrainconvection.The first guessfor the detrainmentparameter,/3, merit, timin(0.10), a characteristicadjustmenttimescalefor comes from a crude buoyancy argument where
the convection, z (1 hour), a cloud water to rainwater
autoconversion coefficient Co (1.0 x 10-4 m-l), and a (26)
min1 (hc-•-•-l)Apk-1 This relation simply states that the maximum convective
massflux throughlevelk - j is linearlyreduced when negative buoyancy in layer k -
1 is diagnosed, subject to
some minimum detrainment•min' Thus the initial guessfor the detrainment parameter is a linear function the ratio of parcel buoyancy in the upper level of the cloud model to the parcel buoyancy in the condensation(or middle) level of the cloud model, subject to minimum and maximum bounds (e.g., determined from a minimum autoconversion of cloud water to rainwater). The physical constraints on the adjustment process,suchas positive massflux, are then applied to determine the actual value of fi appropriateto the stabilization of levels k and k + 1. The total convectiveprecipitation rate is then obtained by vertically integrating the convectivescale rainwater
sink
1
P=•
K
• Rk
PH20k=l
(27)
In summary, the convection procedure is applied as follows: a first guessat/3 is determined from (25) and (26) and further refined using (24). The convective mass flux, mB, is then determinedfrom (23), followed by applicationof
minimum depth for precipitating convection 8Zmin(0 m). We note that our formalism closely follows Arakawa [1969] and Arakawa and Mintz [ 1974], who use their procedure
to deal
with
middle-level
convection
in the UCLA
general circulation model (GCM) [see also Tokioka et al., 1984]. It can be shown that the mathematical formulation for
our approach reduces identically to the Arakawa and Mintz [1974] procedure when fi = 0. In physical terms our approach attempts to deal with moist instability by transporting water in the vertical (subject to some minimum autoconversion), whereas the Arakawa-Mintz procedure deals with suchinstability primarily through the condensationand rain out process. Thus the Arakawa-Mintz middle-level convection scheme is perfectly etficient with regard to the autoconversion of cloud water to rainwater. As we will show, this
simpledifferenceresultsin markedly different results, where the Arakawa-Mintz
scheme behaves
more like the Manabe
et al. [1965] moist adiabatic adjustment procedure.
3. Brief Description of the National Center for Atmospheric Research (NCAR) Community Climate Model (CCM2) The NCAR CCM2 representsan entirely new atmospheric general circulation model for which most aspects of the formulation represent improvements over the CCM1 [see Williamson et al., 1987; Hack et al., 1989]. The principal algorithmic approachescarried forward from CCM1 are the use of a semi-implicit, leap frog time integration scheme,the
HACK:
PARAMETERIZATION
use of the spectral transform method for treating the dry dynamics, and the use of a biharmonic horizontal diffusion operator. In most other respects the CCM2 makes use of new algorithms for both resolved dynamics and parameterized physics [see Hack et al., 1993]. The standard model configuration is run with a horizontal spectral resolution of T42 (2.8ø x 2.8øtransform grid), 18 vertical levels, and a top at 2.917 mbar. It employs a 20-min time step by dynamically adjustingthe spectral resolution of the top layer to maintain a Courant
number
of less than 1.
Two major improvements are included in the CCM2 dynamical formalism. The first is the incorporation of a hybrid vertical coordinate which is terrain following near the surface (traditional sigma) and transitionsto a pure pressure coordinate above about 100 mbar [Simmons and Stritfing, 1983]. The vertical finite difference approximationscollapse to those of CCM1 when the hybrid coordinate is set to be sigma. A second major change to the resolved dynamics is the incorporation of a shape-preserving semi-Lagrangian transport scheme [Williamson and Rasch, 1993] for advecting water vapor. This scheme can also be used to transport an arbitrary number of other scalar fields (e.g., cloud water variables, chemical constituents, etc.) as required by the application. The use of the SLT method largely addresses the many numerical problems exhibited by the spectral advection approach used in earlier versions of the CCM. The cloud fraction parameterization in CCM2 is a generalization of $1ingo [1987]. Clouds can form in any tropospheric layer except the lowest model level, and cloud fraction dependson relative humidity, vertical motion, static stability, and the convective precipitation rate. The cloud emissivities are determined from the local liquid water path, which is diagnosedby vertically integratinga specifiedliquid water concentration profile [see Kiehl et al., 1994]. The CCM2 treatment of longwave radiation remains much the same as in CCM1. The major changeis the incorporation of a Voigt line shape to more accurately treat infrared radiative cooling in the stratosphere [Kiehl and Briegleb, 1991]. The CCM2 also employs a &Eddington approximation to calculate solar absorption using 18 spectral intervals [Briegleb, 1993]. To incorporate the effects of clouds, the schememakes use of the cloud radiative parameterization of $1ingo [ 1989], where the optical properties for liquid droplet cloud particles are parameterized in terms of the liquid water path and effective radius. Comparisonswith available references suggestthat the scheme accurately captures radiative heating from the surface through the mesosphere(-75 km) with notable improvements in estimates of atmospheric absorption/heating below cloud decks. The &Eddington formulation also allows estimates of the photon flux necessary to compute photodissociationrates for chemistry applications and provides a versatile way to incorporate the effects of aerosols.
A diurnal cycle is incorporated in CCM2, for which both solar and longwave heating rates are updated every model hour, while the longwave absorptivities and emissivitiesare updated every 12 hours. Land and sea ice surfaces are modeled as horizontally homogeneousmedia with vertically varying thermal properties. The subsurfacetemperaturesare assumedto obey a thermal diffusion equation where the net energy flux at the surface/atmosphereinterface is calculated using bulk exchange formulae in which the transfer coefficients are stability dependent.
OF MOIST
CONVECTION
5555
A nonlocal ABL parameterization based on the work by Troen and Mahrt [1986] and Holtslag et al. [1990] is used in the NCAR CCM2 to represent turbulence in the atmospheric boundary layer. The parameterization scheme determines an eddy diffusivity profile based on a diagnosedboundary layer height and a turbulent velocity scale. It also incorporates nonlocal (vertical) transport by large eddies, thus providing a more comprehensive representation of the physics of boundary layer transport [Holtslag and Boville, 1993]. Subgrid-scale vertical transport of passive scalars by boundary layer turbulence is also treated. Above the ABL the local vertical diffusion scheme of CCM1 is retained although the functional dependence of the diffusion coefficients is somewhat different. McFarlane's [1987] parameterization of momentum flux divergence by stationary gravity waves is also included.
Finally, the simple mass flux scheme described in section 2 is used to represent all types of moist convection. The scheme also provides a consistent treatment of convective transports for an arbitrary number of passive scalars as required by the modelingapplication. The schememakes use of perturbation thermodynamic quantities, provided by the ABL scheme, to initiate convection within the diagnosed boundary layer. For example, the perturbation temperature is proportionalto (w' O•)o/Wm,where (w' 0•)0 is the surface virtual heat flux and w m is a convective velocity scale. The reader is referred to Holtslag and Boville [1993] for a more complete discussion. For the results discussed in later sections, the land surface
has specifiedfixed soil moisture properties. As in CCM 1, sea surface temperatures are specified by linear interpolation between the climatological monthly mean values but now use the data of $hea et al. [1990].
4.
Sensitivity of the CCM2 Climate
to Moist
Convection
In this section
we will
Formulation characterize
the behavior
of the
simple mass flux (hereafter referred to as SMF) scheme presented in section 2 by contrasting the mean control climate produced by the NCAR CCM2 with the climate produced using a conventional moist adiabatic adjustment procedure [e.g., Manabe et al., 1965]. The principal reasons for this comparison are the historical use of the moist adiabatic adjustment procedure in the NCAR CCM and its continuedwidespreaduse in atmosphericgeneral circulation modeling. The CCM2 control climate is derived from a 20-year seasonalcycle numerical integration for which many detailed aspectsare documented by Hack et al. [1994]. The detailed implementation of the moist adiabatic adjustment procedure follows Williamson et al. [1987]. The model climate using the moist adiabatic adjustment scheme is derived from a 5-year seasonalcycle numerical integration of the CCM2, the results of which will be referred to as the MAA experiment. The ordering of the discrete model physics is such that the stable condensation process always follows the convective parameterization in each of these experiments so that moist convective instability is treated first. Our discussion will focus principally on the mean thermodynamic structures and their maintenance for both the CCM2 and the moist adiabatic adjustment (MAA) experiments, with an emphasis on low-latitude behavior. The transient characteristics of the SMF scheme, some aspects
5556
HACK: PARAMETERIZATION
January Temperature
OF MOIST CONVECTION
servations, the simulated atmosphere continues to be slightly dry but well within 10% of the best available estimates(e.g., recent operationalanalysis,in situ observations, and satellite remote sensingmeasurements).As in the case of the zonally averaged thermal structure, the interannual
400.
variabilityof this field is very small.Althoughwe haveonly showncharacteristics of the Januarysimulation,the qualitative descriptionappliesequallywell to the July simulation
60t
[e.g., see Hack et al., 1994].
lOOt
80N
40N
0
405
805
Latitude(degrees)
ably well capturedin the CCM2 simulation.Anotherfeatureto note in thesediagrams,for later comparisonwith the MAA results,are the extensiveareasof low precipitationratesin the subtropics,particularly on the southernflank of the ITCZ.
January T Standard
Figure5 illustratesthe JanuaryandJulyprecipitationdistributionfor the CCM2 control.The majorprecipitation features, suchas the IntertropicalConvergenceZone (ITCZ), the midlatitudestormtracks, and the monsoonregimes,are reason-
Deviation
Thesesubtropicalsubsidence regionsare well definedby the precipitation field,whichrepresents a significant improvement over previous versions of the NCAR CCM.
The most seriousdeficienciesof the simulatedprecipitation field are a systematicoverestimateof precipitationover warm land areas, a "locking" of precipitationmaxima over steeporographicfeatures,and a tendencyto unrealistically concentrate precipitation over certain areas (e.g., New
Guineain Januaryand Central America in July). There is
80N
40N
0
40S
January
80S
Specific Humidity (g/kg)
Latitude(degrees) Figure 3.
(a) Zonally averaged January temperatureand
(b) the standarddeviationof the interannual variabilityin the zonally averagedJanuarytemperaturefor the National Cen-
ter for AtmosphericResearch(NCAR) communityclimate model(CCM)2. Contourintervalsare 5ø and 0.25ø, respectively, where shadingdenotes a standarddeviation exceeding 0.5øC.
;oo:
,ooo
of which are illustratedby Kiehl and Briegleb[1992]and
80N
Lieberman et al. [1993], will be documented in a future
40N
0
40S
80S
Latitude (degrees)
paper.All modelresultswill be presentedon modelhybrid surfaces(i.e., r/ surfaces,where r/is the definitionof the vertical coordinatewhich variesbetween0 and 1), whichfor practicalpurposesare nearly equivalentto the pressure
q Standard Deviation(g/kg) I"r.'.'.'.l.'.'.'.'.•'.'.'.••
....•........J.........4.. ......• ..... .[......• .......J'.'" • "-"E.... J .... 4...L•,,,•i,..... I
surfacessuggestedby the scalingof the ordinate. We begin by illustrating in Figures 3 and 4 the CCM2 zonally averaged mean thermal and moisture structuresand their variability (i.e., the interannual standard deviation of
the zonalaverage)for the monthof January.As shownby Hack et al. [1994],the CCM2 modelatmosphere is generally coldwhencomparedto globalobservational analyses,typically exhibitinga troposphericcoldbiasof 1øto 2øequatorward of 45ø, 2ø to 3ø at higher latitudes, and in excessof 8ø near the polar tropopause.Nevertheless, the CCM2 climate representsa marked improvement over previous versions
::
e
600
800
u
•ooo •,Th,, ' I ............................................. ' ' ' I ' ' ' I ' ' ' I ,....... " ' 80N
40N
0
40S
80S
Latitude(degrees)
which exhibited a broad-scale cold bias of some 30-8ø more.
Figure 4. (a) Zonally averagedJanuary specifichumidity Note that the standarddeviationof the interannualdeparand (b) the standarddeviationof the interannualvariability turesfrom the meanstateis very small,typifiedby only a in the zonally averagedJanuaryspecifichumidityfor the
few tenths of a degree at lower latitudes. The simulated NCAR CCM2. Contour intervals are 0.1, 0.5, 1.0, 2.0, moisturefield also representsan improvementover earlier 3.0,..., and0.1 g kg-], respectively. Shadingindicates versionsof the NCAR CCM. When comparedagainstob- regionswith valueslessthan0.01g kg-].
HACK:
PARAMETERIZATION
January Precipitation(ram/day) •so
•20w
sow
0
so[
•20[
•so
90N
60N
OF MOIST
CONVECTION
5557
The problem of precipitation "locking" is evident in both the January and the July simulation, over the Andes, Rocky 90N Mountains, central and eastern Equatorial Africa, and the Tibetan plateau. The orographic locking problem is not
60Nunique to theCCM2,asevidenced by theMONEGmodel
3ON
z0• intercomparison [World Climate Research Program (WCRP) 68, 1992] which suggesteda strong sensitivity in the
3OS
a0s This orographiclockingof precipitationcan have significant
60S
60s diabaticheatingassociated with the excessiveJuly precipi50s tationrate over the Tibetanplateauhelpsdrive an anoma-
0
precipitation distribution to therepresentation of orography. dynamical consequencesin the simulation. For example, the
90S
180
120W
•so
•20w
60W
0
60E
120E
lous local circulation which is a principal contributor to the relatively poor simulation of the Southeast Asian monsoon (e.g., the area of suppressedconvection over central India). The magnitude of these precipitation anomalies can be reduced somewhat with improved cloud diagnostics, but stationary features in the precipitation field remain and are
180
July Precipitation(mm/day) sow
0
so[
•20[
•so
90N asyet an unresolved aspectof the numerical simulation.
90N
Zonally and globally averaged precipitation characteristics 60N are shown in Figure 6. As in the case of the two-dimensional
60N
z0• precipitation distribution, thezonallyaveraged CCM2pre-
SON
cipitation rates exhibit many of the features contained in the observational estimates. These figures clearly show the ITCZ, the regionsof suppressedprecipitation on either flank 5OS of the ITCZ, and the midlatitude storm track regimes. The 60S •0s contribution to the total precipitation from the convective parameterization and from the stable condensation process 90S 90s (i.e., "grid-scale" release of latent heat) is also shown. Note 180 120W SOW 0 60E 120E 180 that the vast majority of the total precipitation is produced Figure 5. January and July precipitation distribution for by the convective parameterization scheme, particularly in the NCAR CCM2. The contour interval is 1, 2, 4, 8, 16, and the tropics. Although the global precipitation numbers are 0
32mmd-1. Shadedregions exceed4 mmd-1.
also direct evidence (the simulated strengthof the Australian monsoon) and indirect evidence (the characteristics of the simulated North Pacific 500-mbar stationary wave error, as discussedby Hack et al. [1994]) that the January western Pacific precipitation maximum may be anomalously shifted toward
the southwest.
The excessive continental precipitation is seen both in January, over South America, Northern Australia, and Indonesia, and in July, over most of North America, Central America, and Eastern Asia. This continental precipitation bias is generally associatedwith anomalously warm surface temperatures [see Hack et al., 1994]. Major contributors to the surfacetemperature bias and the associatedprecipitation bias are deficiencies in the diagnosisof cloud optical properties, as discussedby Kiehl [1994] and Hack [1994], as well as unrealistic
nonlinear
interactions
between
moist convec-
comparable to morerecentobservational estimates byLegate• and Willmott [1990]for the month of January, they significantly exceed these estimatesfor July. Excessive continentalprecipitation is a major contributor to the July global anomaly, although it is important to remember that there is substantial
uncertaintyin the globalobservationalestimates. We now move to the thermodynamic structures associated with the MAA experiment, which are illustrated in Figure 7 as departures from the CCM2 control integration (i.e., Figures 3 and 4). These figures show a model atmosphere that is systematically colder and dryer by as much as 4øCand
2 gmkg-• in thezonalaverage.Exceptions to thischaracterization are two shallow regions at high latitudes in the lower troposphere, which are somewhat warmer, and a shallow region near 900 mbar in the northern hemisphere subtropics,which is very slightly more moist. In general, the signal associated with these differences is substantially greater than natural internal variability. Typical changesare of the order of 3ø-4øC colder in the upper troposphere
tion andatmospheric boundarylayerprocesses, whichwe equatorward of 40ølatitudeandexceeding 0.5gmkg-• dryer will illustrate below. Secondary factors contributing to these biasesmay include the simple way in which the land surface is treated in the CCM2 control, an aspect of the simulation currently under investigation (see, for example, Bonan [1994]). Improved cloud diagnosticshelp reduce the magnitude of both the surface temperature and the precipitation anomalies as well as shift precipitation maxima closer to where they are observed, such as in the case of the simulated Australian monsoon. The shift in diabatic heating over the western Pacific also helps to improve deficiencies in the North Pacific January flow field.
from 900 through 500 mbar for the same latitude band. From a climate perspective the change in the vertically integrated specific humidity is quite significant. Figure 8 shows the zonally averaged, vertically integrated water vapor (or precipitable water) for CCM2, MAA, and the last 4 years of the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analyses (i.e., since July
1988)for bothJanuaryand•luly(ascompiledby Trenberth [1992]). These figures clearly show how closely the CCM2 model climate correspondsto the operational analyses. The MAA experiment exhibits significant local departures (ex-
5558
HACK:
PARAMETERIZATION
January Precipitation
14 ß
13
' ' ' ' ' ' ' ' ' ' ' 'Oiob•l
..... ß --
12
......
11
Legal# and •lfillmoff CCU2Total CCU2Cenvee•ive CCM2Stable
3.83 mm/day 3.48 turn/day 2.83 mm/day 0.•5 mm/day
OF MOIST
CONVECTION
The January and July precipitation distributions for the MAA experiment are shown in Figure 9. Qualitatively, the .
overall
distribution
is similar
to the CCM2
control.
Once
again, there is evidence of excessive precipitation rates over warm land areas, although the magnitude of the most intense precipitation regions is noticeably decreased. For example,
10
the January precipitationmaximum over southernNew
9
Guinea is reduced by about 20% in the MAA experiment. This sort of reduction is symptomatic of an overall broadening of the precipitation features. One example of this is how the subtropicalprecipitation regimes are much less extensive and well defined. To some extent this may be related to a much less vigorous mean meridional (i.e., Hadley) circulation in the MAA experiment, which is not so effective at suppressing convection in the subtropical regions. This difference is also associated with the absence of an explicit convective-scale transport mechanisms, as we will show below. As in the CCM2 control, the July simulation shows clear evidence of precipitation locking over regionswith high
8 7 6 5 4
2 1
0 90
60
30
0
- 30
- 60
- 90
localized orography.Another feature of the January MAA simulation is a more vigorous and clearly defined Atlantic
Latitude
ITCZ.
The zonally and globally averaged MAA precipitation
July Precipitation
14
January
' ' ' ' ' ' ' ' ' ' ' '_Oiob•][
13
-
12
..... , ,
Legatesand Wlllmoff CC1•2Total ' CCU2Convective
[AT]
2.86 ram/day 3.81 ram/day 3.03 ram/day
200
11
10
9
8
.-....:.
7
..... :!-:::i:: .!:':
800
6 5
:":
1000
4
'-i:::•:. !.'-::::i:!:! i:::•:i:i::-'!'t.'"' ............... :............ i:!:•:i:i-i:?•:::i:•:. H es• ':
......
80N
40N
0
40S
80S
Latitude (degrees)
;3 2
January
[•]
1 0 go
Latitude
Figure 6. Zonally averaged January and July precipitation rates (convective, stable, and total) for the NCAR CCM2 and the observational estimates of Legates and Willmatt
o
?::::::.i :::::::::::::::::::::::::::::::::::::::::::::::::::::::::: ii:::::•i?:!::i::?:?::•!ii:•i::::•i:•i?,iiiii!i•
•'
:::::::::::::::::::::::::::::::::::::::::::::::::"j•::•?:%..-.,..-.....'!:i .......... ::•::ililiiii:' ........... •::•?:i::ii::i:'::i::!i!::!?:!:: ::i::•iii!•:%•
[1990]. ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: ......... ::::::::::::::::::::::::::::::::::::: -.!.-.--':.ili::ili?:::::::i::i
ceeding 5 kg m-2 in thezonalmean)andglobaldifferences,
1000
80N 40N 0 40S 80S when compared to either the analyses or the CCM2. Such Latitude (degrees) changes are not only important to the thermodynamic stability of the tropical atmosphere but have important "greenFigure 7. (a) Zonally averagedchangein temperatureand house" impacts on the clear-sky longwave radiative budget (b) zonally averaged change in specific humidity for the [e.g., Kiehl and Briegleb, 1992]. In global terms the change moist adiabatic adjustment (MAA) experiment. Contour in the top-of-atmosphereclear-sky longwave flux associated intervals are(a) 1øand(b) 0.1, 0.5, 1.0, 1.5,and2.0 g kg-•. with the difference in total precipitable water is comparable Lightest shading in Figure 7b depicts regions greater than to the change that would be associated with a doubling of -0.01 g kg-• , whilethedarkestshading denotes regions less ß
atmospheric C02, about4 w m-2.
than- 2.0 g kg- •.
HACK:
PARAMETERIZATION
OF MOIST
characteristics are illustrated in Figure 10, along with the 180 observational estimates of Legates and Willmott [1990]. Note the clear difference in the amplitude and zonal struc- son ture of the precipitation field when compared with the CCM2 control, even though the two experiments produce comparable global precipitation rates. For example, the MAA 30N experiment exhibits a broader and somewhat weaker ITCZ
in both Januaryand July, with a slightmeridionalshift
CONVECTION
5559
January Precipitation(ram/day) •2ow
eow
o
eo[
•2o•
180 90N
60N 3ON
0 305
30S
60S
60S
January Precipitable Water
so . . , . . , . . , . . 'Giob•lJ•v;ra•e-j sos 180 ..... œCItV• Af• -- •a2
5O
-----
90S
120W
60W
0
60E
120E
180
25.3kg/m t •.6 kg/•
•
•.O ke/•
July Precipitation(mm/day)
4O 180
120w
eow
0
eOE
120E
180
90N
90N
60N
60N
3ON
3ON
.
3O
2O
0
3OS
30S
60S
60S
10
90S
90S
o
180
60
90
•0
0
-•0
-60
120w
sow
0
eOE
120E
180
-90
Figure 9. January and July precipitation distribution for the MAA experiment. The contour interval is I, 2, 4, 8, 16,
Latitude
and32mmd-]. Shadedregionsexceed4 mmd-]. July Precipifable Water
toward the north in the January simulation. The most striking difference between the two experiments, however, is the partition of convective and stable precipitation, particularly in low latitudes. The equipartition of stable and convective rainfall in the MAA experiment is very similar to
6O
f' ' ' ' ' ' ' ' ' ' ' 'Giob•l ..... --
5O
œCIdWI r Analyuo8 CCId2
:28.8kg/mt 28.4 kg/m•
"
24.4kg/mz
the ratios observed in earlier versions of the NCAR 4O
of sensible heat.
3O
2O
10
o
CCM,
which also used the moist adiabatic adjustment procedure. As we will show, this characteristic appears to be attributable to the lack of explicit convective-scalevertical transport
[ I i I I I I I I I • , I t _I'""t' '••'' 90
60
30
0
-30
-60
-90
As shown earlier, the MAA model climate is both colder and dryer than the CCM2 model climate. Because of the large changesin these fields the MAA tropical atmosphere exhibits a significantlydifferent stability structure, as shown in Figure 11. The low-level thermodynamic structure for both the CCM2 and the MAA model climates are very similar and in reasonable agreement with more recent operational analyses. The most significant disagreement in the lower troposphere occurs in the very lowest levels of the
modelwhichturn out to be too dry whencomparedwith the
analyses. This deficiency may be attributable in part to an overly active atmospheric boundary layer, as we will show below. Above 850 mbar the thermodynamic structures are Figure. 8. Zonally averaged January and July precipitable water for CCM2, the MAA experiment, and from the Euro- quite different, where the larger departuresare dominatedby a much dryer model atmosphere in the MAA experiment. pean Centre for Medium-Range Weather Forecasts (ECMWF) analyses(January 1989-1992 and July 1988-1991). Two aspectsto note with respectto the CCM 1 model climate See text for additional discussion. are the large differencesin the low-level stability characterLatitude
5560
HACK:
PARAMETERIZATION
January Precipitation
14
ß.' ' ' ' ' ' ' ' ' ' ' 'Oiob•l ..... - --
12 11
Legal# and Willmoll IdAATotal • Conveefivo MAAS•able
......
3.83 ram/day "l 3.36 mm/day ß 1.72 ram/day 1.eX ram/day ß
ß
ß
lO ß
8 ß
7
,, .
.
.
.
.
$ .
.
,'
4
2 1
o
60
9o
30
0
- 30
- 60
- go
Latitude
July Precipitation
14
ß i
i
i
' ' ' ' ' '
13
Legates and Willmatt
12
Id• To•al MJul, Conve•'lve
11
i
,
i
Oiob•l Xve'm•e-I 2.86 ram/day
-I
3.86 mm/day 1.•7 ram/day
OF MOIST
CONVECTION
structure of two climatologically different regimes in the tropics for which there are high-quality in situ observations. The Yap atoll is located in a very active region of deep convection in the western Pacific while Ascension Island, located in the eastern Atlantic, is more typical of a suppressed convective regime. Three sets of data are shown in the main panels: radiosonde observations, for which the standarddeviation of the interannualmean is depictedusing error bars, profiles from the CCM2 model climate (solid curves), and profiles from the MAA model climate. These profiles show how well the CCM2 model climate compares with the actual observational record for these regions and how much the simulation degrades when using the moist adiabatic adjustment procedure. The contrast between the CCM2 and the MAA results is quantified in the side panels which show the CCM2-MAA temperature differences and the ratio of the MAA specifichumidity to the CCM2 specific humidity as functions of pressure. The MAA results are systematicallycolder in the middle to upper troposphereby 30-4ø and from 20% to 60% dryer in both regimes. Another feature is the improved tropopause definition in the CCM2 results, which can be seen in the sharp gradient in the temperature differences shown in Figure 12. These results show that the zonal mean differences illustrated in Figure 7 are fairly robust acrossthe various climatologicalregimesin the tropics, particularly with regard to the temperature bias. The lower tropospheric dry bias tends to be slightly dominated by the subsidenceregions where the moist adiabatic adjustmentschemeis most deficientat moisteningthe atmosphere in the vicinity of the trade inversion. The zonally averaged January convective-scale heating and moistening rates for the CCM2 and MAA experiments are shown in Figures 13 and 14, respectively. The physical processes contributing to these tendencies include moist convection and stable condensation. Other important diabatic effects not represented in these figures are the vertical
Id• Stable 1.89 ram/day
lO -
,
g
8 7 6
5 4
3 2
.
1
_•,,•'_•.;'/ ,-.
o go
I ••_ '... "" ß "-"' ," ': '•....:'•,"•7 .... :\ _j?:,,•. •= _/.,.'"•-•:-.,.j.::-' ',,.
i
-•_.-'
i
i
60
I
!
•
i
50
i
•
i
0
..'
i
i
':_•
i
- 50
i
lOO •.'.
200
i
- 60
- 90
Latitude
300
400 500
Figure 10. Zonally averaged January and July precipitation rates (convective, stable, and total) for the MAA experiment and the observationalestimatesof Legates and Willmatt [ 1990].
600 7OO 8OO
istics and the striking similarity to the MAA model climate in the mid- to upper-tropospheric structure. The low-level differencesare clearly attributableto the incorporationof an explicit atmospheric boundary layer parameterization, as shown by Haltslag and Boville [1993]. The upper level stability structure seems to be a signature of the moist adiabaticadjustmentprocedureand appearsto have little to do with the vertical resolutionemployedby the model. Figure 12 illustrates the July temperature and moisture
9OO 1000 320
Figure 11. Zonally and meridianally (14.5øN to 14.5øS) averaged July equivalent potential temperature for the NCAR CCM2, the MAA experiment, and the ECMWF analyses (July 1988-1991). Results from the NCAR CCM1 are also included
for reference.
HACK:
PARAMETERIZATION
OF MOIST
CONVECTION
5561
du•y
o
,
,
,
i
,
i ,, , ,,,• ,
!
'-' ' '•
lOO
,
,
,
!
,
,
,
!
,
,
July
o
,
Yap I,land 9.4' N, 138.1' r
•
.
,
.
,
..
: :.• [
' ' '•
lOO
200
.
.
.
.
,
.
.
.
•
.
.
.
M•en.lon I.Iond 7.6' S, 14.2' W
200
,.• 300
,• 300
400
400
500
5oo
600
600
700
700
80O
800
go0
900
1000
1000
190
210
230
250
270
290
310-4
0
4
".%,. ß
0BS
,.
190
210
230
6T
Temperature(øK)
",.
250
270
290
310 -4
o
0
lOO
100
..
ß ,,,,,,!
"•,' '
ß , ,,,,,,i
, • ...... i
0
4
6T
Temperature (øK) , , ,,,,,,!
Asoen.lon I.land .6' S, 14.2' W
N, 138.1' E 200•'• ........ '......... ....... ......
200
,• 300
,.• 300
E 400
400
"•'\ x
L. 500
oK
u) 600
5oo
\'•
600 ß oK
•' 700
ß
700.....
800
800
gO0
900
lOOO
1000
10-s
10-2
10-I
100
10I
10-s
o
Specific Humidity(g/Kg)
q rofio
10-2
'
10-I
100
10•
Specific Humidity(g/Kg)
q ratio
Figure 12. Verticalprofilesof temperatureand specifichumidityat Yap IslandandAscensionIslandfor the NCAR CCM2 and the MAA experiment.Observedvaluesare givenby dotswhere the horizontalerror bars show the standard deviation of the observed interannual variability. The right-hand panels show
profilesof the differencein modeltemperaturebetweenthe NCAR CCM2 and the MAA experimentand profilesof the ratio of MAA specifichumidityto CCM2 specifichumidity. See text for further discussion. diffusion, dominated by boundary layer processes,and the net radiative heating. The contribution of these latter terms to the total diabatic forcing will be consideredlater when we examine each of these experiments on a regional basis. Although qualitatively similar there are some important differences between the two sets of figures. The first feature to note is the vertical extent and structure of both the heating and moistening in the vicinity of the ITCZ. The simulated ITCZ is well defined by both diabatic forcing terms, which reach clear secondary maxima in the middle tropospherefor
moistening that occurs near the trade inversion in the
subtropics. Thismoistening exceeds 0.5 g kg-• d-• in the CCM2 control but is completely absent in the MAA experiment. This detrainment of water mass in the dry subsiding branch of the Hadley circulation is also associatedwith a coolingeffect, which is largely responsiblefor the improved meridional
definition
of the ITCZ.
The CCM2
results also
cally integrated tendencies. We note that even though the CCM2 employs considerablyhigher vertical resolution, the
show some evidence of very weak cooling near the tropopause(i.e., at the top of the convective layer). This cooling is due to the flux divergence of liquid water static energy, which slightly dominates the convective-scalerainwater sink term in this region. The cooling occurring in the lower troposphericpolar region is associatedwith a large low-level convective overturning in a fairly dry atmosphere where, once again, the liquid water static energy flux plays a dominant role. This convective overturning appears to be radiatively driven, i.e., by a very large cloud top cooling gradient in this region (e.g., where the maximum cooling
vertical
exceeds3øCd-] in the zonalmean).
the
CCM2
control.
This
is not the case for the MAA
experiment, which exhibits a rather weakly defined and meridionally diffuse forcing in the ITCZ. Another characteristic of the MAA experiment is that the amplitude of the low-level forcing is larger and more localized in the vertical than in the CCM2
distribution
results and tends to dominate
of latent
heat
release
the verti-
in the
MAA
experiment is remarkably similar to earlier versions of the CCM that employed the moist adiabatic adjustment scheme. Another very important difference in the two figuresis the
The January zonally averaged convective mass flux, M c, is shown in Figure 15, along with the January zonally averagedlarge-scalevertical motion field. Enhancedconvec-
5562
HACK:
PARAMETERIZATION
January
the CCM2
ConvectiveHeating (C/day)
o o o
*
60(
lOO(
80N
40N
0
OF MOIST
405
805
Latitude(degrees) January Convective Moistening
200•'''''''''''''''' .-_
:
o 400-
--
0
* 600-
800: 'iøu .. "'•
CONVECTION
and the MAA-CCM2
difference
are shown in
Figure 16. Note the large increase in low-level cloud in the deep tropics and the large vertical shift of low-level cloud cover poleward of 70øN. Recall that there was a very large difference in the zonally averaged thermal structure in this region (see Figure 7), suggestingthat the temperature change is likely attributable to changesin the cloud-radiative balance introduced by the change in the convection scheme (i.e., the moist adiabatic adjustment schemecontributesto a downward shift of polar cloud cover and an accompanying vertical shift in the location of the thermal inversion). In the tropics the increase in low cloud cover is related to a significant increase in low-level relative humidity for the MAA experiment and suggestsan increase in stable condensation at these levels. This is indeed the case, as we will now show by examining the breakdown of the terms contributing to the diabatic heating shown in Figures 13 and 14. There are three components to the CCM2 "convective" heatingand moisteningrates shownin Figure 13, while there are only two for the MAA experiment (see Figure 14). The CCM2 components consist of the vertical eddy flux divergence terms (i.e., the convective-scale transport terms), the convective-scale condensate term (i.e., condensate removed from the systemin the form of convective precipitation), and
---
January
--
ConvectiveHeating (C/day)
--
1000 "; , , 80N
40N
0
405
805
Latitude(degrees) Figure 13. (a) Zonally averaged January convective heating rate and (b) zonally averagedconvectivemoisteningrate for the NCAR CCM2. Contour intervals are 0.25, 0.5, 1.0,
o o o
1.5, 2.0,... øC d-], and 0.25, 0.5, 1.0, 1.5, 2.0,... g kg-] d-•, respectively. Shaded areasin Figure13bdenote areas of convective moisteningin the descendingbranch of the mean meridional
circulation.
80N
tive activity is well correlated with the ascendinglarge-scale vertical motion in the ITCZ, exhibitingmassexchangethat is 2 to 3 times the large-scale value. Vigorous convective activity occurs throughout the lower troposphere, even in regions of intense subsidence.The midlatitude storm tracks can be identified by low to midlevel enhancementsin convection, and the intense low-level convective overturning poleward of 70øN can be clearly seen. One of the interestingquestionstheseexperimentsraise is what role the variousphysicalprocessesplay in maintaining the climatological balance establishedin each of the model experiments.The first hint that there are significantlydifferent roles for some of the physicscomponentscomesfrom an examination of the predicted cloud field. The global mean cloudinessincreasesby about2.4% in the MAA experiment, a statistically and physically significant change (e.g., the radiativeimpactis comparableto a CO2 doubling).The most interesting aspect of this change is its distribution in the vertical where the global high-level cloud cover actually decreases by about 2%, global midlevel cloud increases between 1% and 2%, and globallow-level cloudincreasesby almost 10%. The zonally averagedJanuarycloudfraction for
40N
0
405
805
Latifude(degrees) January Convective Moistening
80N
40N
0
40S
80S
Latitude(degrees) Figure 14. (a) Zonally averaged January convective heating rate and (b) zonally averagedconvective moisteningrate for the MAA experiment. Contour intervals are 0.25, 0.5,
1.0, 1.5,2.0,... øCd-•,and0.25,0.5, 1.0, 1.5,2.0,... g kg-• d- • respectively.
HACK:
PARAMETERIZATION
a stable condensate term (i.e., grid-scale condensate removed from the system in the form of precipitation). The MAA experiment explicitly includes only the latter two mechanisms, although there is an implied convective-scale vertical transport of total water as a by-product of the moist adiabatic adjustment procedure (where this effect is contained in the convective-scale condensation term). For example, the procedure maintains a constant relative humidity in the layers undergoing adjustment. Since the column is warmed by latent heat release, this process effectively transports water in the vertical to maintain a prespecified fraction
of the
behavior
later when we examine
saturation
value.
We
will
illustrate
OF MOIST
CONVECTION
January Cloud Fraction
- I I [ i I i i .-.::•]
•'800
,ooo ...... '""" '-'--'
this
80N
40N
0;ii:.....
::?!?ii
80S
January
•'-
•'
"'
o
..-..-•..-.:!•:;iiiii!11• ......... •.-.
"
800 . 80N
•::::::::::::.: ß ....... ::::!:•:!:!:!::.-
40S
[ACloud]
40N
0
405
805
Latitude (degrees)
January Vertical Velocity
200--
0
Latitude (degrees)
regional basis. For now, we focus on the zonally averaged diabatic heating as presented in Figures 13 and 14. The January CCM2 zonally averaged convective-scale heating tendency attributable to the vertical eddy flux of liquid water static energy is shown in the top panel of Figure 17. The eddy transport term exhibits a very distinct signature with strong, meridionally broad, heating confinedbelow 800 mbar and weaker cooling above. The heating maximum occurs near the top of the atmospheric boundary layer (i.e.,
around 900mbar),exceeding 2.5øCd-• at lowlatitudes. This
I
I ] [
*6oo: :ii ?"
each of the schemes on a
result is conceptually consistentwith previous budget studies showingthat moist convection (in particular, nonprecipitating moist convection) produces a cooling in the upper regions of the convective layer through the transport and
5563
:::::::::::::::::::::::
-
Figure 16. (a) Zonally averagedJanuary cloud fraction for the NCAR CCM2 and (b) the zonally averaged difference in January cloud fraction for the MAA experiment. Contour intervals are 0.025 (with shading greater than 0.15) and 0.05 (with shaded areas less than zero), respectively.
600-I
8002
detrainment of liquid water and a warming below [e.g., Betts, 1975]. The convective-scale condensationheating rate term, shown in the bottom panel of Figure 17, has considerably more meridional structure where the midlatitude storm tracks and ITCZ are clearly defined. Heating in the ITCZ
i.
•ooo
80N
40N
0
405
805
Latitude (degrees)
exceeds3.5øCd-] in the middletroposphere with much January
ConvectiveMass Flux (rnb/day)
õ 800 1000
• -
80N
--'........ '"•" ....... 40N
0
:•- • 40S
80S
Latitude (degrees) •igure IS. (a) Zona]ly averaged •anuary vc•ical motion field (•) in units of millibars per day and (b) the zonally
averaged •anuary convective mass flux, •, millibars per day for the NCAR CCM2.
in units of
smaller magnitudesin middle and high latitudes. Clearly, the eddy transport term plays an important role in the overall diabatic heating rate, in fact, the dominant role below 800 mbar. Since the total convective heating rates shown in Figures 13 and 14 are fairly similar in the lower troposphere, and an explicit convective-scale transport mechanism is not available to the moist adiabatic adjustment procedure, the low-level heating in the MAA experiment must be provided by either the convective-scale or stable condensation process. As it turns out, the stable condensation processprovides the bulk of the MAA low-level heating, as shown in the lower panel of Figure 18. Thus a substantial fraction
of the total latent heat release in the column
occurs
below 800 mbar in the MAA experiment, most all of which arisesfrom grid-scalecondensation.In sharp contrast, stable condensationis generally confined to the upper troposphere in the CCM2 control and represents a small fraction of the total latent heat released in the column
at low latitudes.
Once
again, the vertical partitioning of the total convective heating
5564
HACK:
PARAMETERIZATION
OF MOIST
CONVECTION
notation introduced by Yanai et al. [1973]. For the purpose of the following discussion,
January
EddyHeating(C/day)
g
0
L
L (28)
Q• = -- -- Fs + -- • + -- •s + QABL+ Q•,
CpOp
•
Q2 =
Cp
Cp
g
Cp
Fq •pp +l
• - •s + ,•
ABL ß
(29)
where fits is the rainwater sink for the stable condensation processand Q^BL and b•^BL are sourceterms attributableto atmospheric boundary layer (ABL) processes. The compart-
mentalization of O] and Q2 is purely for the purpose of identifying the relative role of the many functionally distinct component processesincluded in the numerical model and does not amount
January
CondensationHeating (C/day) I
i
[
[
I
'
•
'
I
[
i
]
I
•
[
i
I
200- -
tempted in budget studies of the real atmosphere, which does not concern itself with such discrete modeling abstractions. Vertical profiles of Q• and Q2 are shownin Figure 19 for both the CCM2 and the MAA experiments. The first
_
o 400-.
0
-
* 600Z •.
of the standard nomencla-
g/Cp(OFs/OP)AB L. Thesedistinctions are not typicallyat-
-
0
to a redefinition
ture. For example, the boundary layer contribution to the diabatic heating can also be thought of as a subcloudcomponent of the total vertical eddy transport such as Q^BL =
.
800: .
--
January
--
1000
80N
40N
0
40S
Large-scale Heating (C/day)
80S
Latitude(degrees) Figure 17. (a) Zonally averaged January diabatic heating by the convective-scale transport term and (b) by the convective-scale
rainwater
sink for the NCAR
intervalsare 0.25,0.5, 1.0, 1.5, 2.0,.-.
CCM2.
Contour
øCd-• wherethe
shaded region denotes cooling.
in the MAA model climate bears striking resemblance to earlier versions of the CCM. This suggeststhat the way in which the total heating is partitioned may be a general characteristic of the moist adiabatic adjustment procedure. That is, in the absence of an explicit vertical eddy heat transport term, other available physical processes must somehow heat the lower troposphere and do so by removing water from the system. This may be the principal reason why the MAA model climate is so dry when compared to the
80N
40N
0
40S
80S
Latitude (degrees) January
Large-scale Heating (C/day)
200• [[[I [[[I [[' I [••It --
CCM2
control.
¸ 400Z o
Regional Analysis of Total Diabatic Forcing
Let us now examine the behavior of the diabatic forcing in the CCM2 and MAA experiments on a regional basis. For this analysis we have selected a 500-km square region in the western Pacific in the vicinity of Truk Island during the month of July. This is a convectively active region in both experiments, typified by very similar large-scale vertical motion fields that peak between 400 mbar and 500 mbar. The maximum amplitude of the ascendingvertical motion field is about 75 mbar d -1 in the CCM2 control and 45 mbar d -1 in the MAA experiment. Our analysis will make use of the apparent heat source, Q1, and apparent moisture sink, Q2,
o
:
ß
600 Z 8001000
80N
40N
0
40S
80S
Latitude(degrees) Figure 18. Zonally averaged January diabatic heating by stable condensation for the (a) CCM2 and (b) MAA model climates. Contour intervals are 0.25, 0.5, 1.0, 1.5, 2.0,...
øC d -1 '
HACK:
PARAMETERIZATION
OF MOIST
thing to note is that the vertical structure of these profiles is really quite similar in the two experiments, although the magnitudes are moderately reduced for the MAA case. This weaker diabatic response is entirely consistent with the weaker large-scale adiabatic destabilization exhibited by the MAA experiment. The magnitudeand structureof the CCM2 Q• profile is in reasonable agreement with diagnostic budget studies conducted in this region [e.g., Yanai et al., 1973]. A breakdown of the apparentheat sourcecomponentsshowsthat the total diabatic heating is dominated by the convective-scale rainwater sink (see Figure 20). The remaining terms are of comparable magnitude but exhibit distinctly different structures in the vertical. Generally speaking,above 800 mbar the convective-scale and grid-scale water sinks strongly heat the atmosphere, while the radiation and convective transport terms contribute comparably to a cooling. Note that the stable condensationprocess is a significantheating component only in the upper troposphere between 200 mbar and 500 mbar. Below 800 mbar the moist convective transport term acts to strongly heat the atmosphere, while boundary layer processesheat below 900 mbar and cool above. A number of the apparent heat sourcecomponentsfor the MAA experiment are qualitatively similar to the CCM2 results. dominant
The
convective-scale
term and exhibits
rainwater a similar
sink
vertical
remains
structure.
CONVECTION
5565
July Western Pacific 0
•,•,
c'cfi2':
loo
i
•
,
i
,
i
,
i
,
i
C4mveu--•ve Conden•fe
,
"., ----- EddyTran.port :• _•_.:• .... Radiation
200 -
ABL
/,? i/I t
$00
400 500
I;
600 700 800 900 1000
-4
-3
-2
-1
0
1
2
5
4
5
6
'C/day
July Western Pacific o
k,,. ----- Eddy Tran.po
lOO
• •s ..... Rodlotion
200
•/,o/'r\x• ---$loble Conden.ate
$oo
the 400
The
net radiational cooling is also qualitatively similar but exhibits a small peak in low levels attributable to enhancedcloud top cooling (due to the increase in low-level cloud, as discussed earlier). Although somewhat weaker, the ABL contribution is similar to the CCM2 results. The important differencesare the absenceof an eddy convective transport term, which heats below and cools above 800 mbar in the CCM2 results, and the presence of a large stable condensation heating below 800 mbar. Effectively, this grid-scale heating takes up the role of the missingeddy transport term below 800 mbar, as suggested by the zonally averaged results presented earlier.
I! 500
; ;
/
600
700 /'
800 900
1000
-4
-3
-2
-1
0
1
2
;5
....
4
5
'C/day
Figure 20. July area-averaged terms in the (a) CCM2 and (b) MAA Q • budgetsshownin Figure 19. See text for further discussion.
July Western Pacific
lOO
200 5oo
400 500
600
ß
/
700 800 900 1000
-•
-3
-2
-1
0
1
2
3
4
5
6
aC/doy
Figure 19. July area-averagedQ• (solid) and Q2 (dashed) profiles for the CCM2 (thick) and MAA (thin) model climates. The area average is taken over a 500-km square region in the vicinity of Truk Island in the western Pacific.
The vertical structure of the CCM2 Q2 profile does not agree with diagnostic budget estimates as well as the Q• structure, particularly below 800 mbar. A similar statement holds for the MAA results. The moisture forcing below 800 mbar changes sign, exhibiting a very large moisture source, as opposedto a moisture sink found in most budget analyses. A breakdown of the Q2 components(see Figure 21) shows that although the convective-scale water sink and stable condensation water sink dominate the budget above 800 mbar, boundary layer processesplay the major role in the moisture budget below 800 mbar. The very large moisture source attributable to the ABL scheme is not completely balanced by the convective-scale total water flux, resulting in the appearance of a large net moisture source below 800 mbar. The magnitude of the ABL moisture source is comparable in both the CCM2 and the MAA results (• 10øC
d-•), eventhoughit is consumed in verydifferentwaysby other physical processes. This strongly suggeststhat the ABL scheme is far too active with regard to moisture transport in low levels. We note that this excessive low-level mixing of water may also be a contributing factor to the weak upper level cold/dry anomaly present in the CCM2 model
5566
HACK:
PARAMETERIZATION
July Western Pacific
CONVECTION
Figure 7, these figures depict a model atmosphere that is systematically colder and dryer by as much as 3øC and 2 gm
o
kg-1 in thezonalaverage.Theresemblance of theseresults
lOO
to the MAA experiment is remarkable. The detailed mechanisms for achieving the climate balance in these two experiments are quite different, since the Arakawa and Mintz scheme has an extra degree of freedom available to it. They share a common attribute, however, which is the removal of water from the model atmosphere at low levels. This clearly illustrates the importance of transporting water in the vertical (subject to some minimum autoconversion) to deal with moist convective instability, as opposed to removing it entirely from the system.
200 5oo 400
500
600
700
800
..
-
lOOO
-8
OF MOIST
-6
-4
-2
o
2
4
6
5.
Concluding Remarks
We have presented the methodology by which the process of moist convection is parameterized in the NCAR CCM2. The scheme makes use of a bulk, three-level, stabilitydependent, nonentraining cloud model to constrain the adjustment to a stable stratification. The procedure also provides the framework for estimating the convective-scale mass exchange in general. We believe that this approach
øC/day
July Western Pacific 0
100 200 500
Janua•
400
[AT]
500
soo
ß
2oo
700
I , h
' "'"""'"""'"'"'
I
•
