Bias of atmospheric shortwave absorption in the NCAR Community Climate Models 2 and 3: Comparison with monthly ERBE/GEBA measurements

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1 JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 13, NO. D8, PAGES , APRIL 27, 1998 Bias of atmospheric shortwave absorption in the NCAR Community Climate Models 2 and 3: Comparison with monthly ERBE/GEBA measurements M. H. hang and W. Y. Lin Institute for Terrestrial and Planetary Atmospheres, State University of New York at Stony Brook J. T. Kiehl National Center for Atmospheric Research, Boulder, Colorado Abstract. A direct comparison is made of collocated shortwave reflection at the top of the atmosphere and insolation at the surface between the National Center for Atmospheric Research Community Climate Models 2 and 3 (CCM2 and CCM3) and monthly Earth Radiation Budget Eperiment/Global Energy Balance Archive (ERBE/GEBA) measurements. It is shown that atmospheres in the models are brighter at the top of the atmosphere than ERBE measurements and meanwhile transmit more solar radiation to the surface than GEBA measurements. As a consequence, the models underestimate atmospheric shortwave absorption. The amount of this underestimation is about 2 W m -2 in CCM2 and 17 W m -2 in CCM3. It is emphasized that regardless of whether the bias is in clear sky or in clouds, this underestimation has important implications for the intensity of the hydrological cycle and thus circulation in the models. 1. Introduction Considerable debate has been generated concerning the amount of absorption of shortwave radiation in the atmosphere since the publication of three papers by Cess et al. [1995], Ramanathan et al. [1995], and Pilewskie and Valero [1995]. Several studies have used the monthly mean shortwave radiation measurements at the top of the atmosphere (TOA) from the Earth Radiation Budget Eperiment (ERBE) and monthly surface insolation from the Global Energy Balance Archive (GEBA) to study the problem of shortwave radiation transfer through the atmosphere [e.g., Wild et al., 1995; Li et al., 1995; Li and Moreau, 1996; Charlock et al., 1995; Arking, 1996]. Arking [1996] reported a large discrepancy of atmospheric shortwave absorption, which is similar in the clear-sky atmosphere and in the total-sky atmosphere, between a general circulation model and the ERBE/GEBA data. Li and Moreau [1996], assuming a correct clear-sky surface transfer algorithm, argued that there was no signature of enhanced atmospheric absorption in the ERBE/GEBA data, consistent with Arking regarding the impact of clouds on atmospheric shortwave absorption but with different perspectives on the understanding of clear-sky atmospheric absorption. Charlock et al. [1995] reported total-sky discrepancy between the transfer algorithms and ERBE/GEBA data similar to Arking's value, but they attributed it to both clear sky and to clouds. Results from these studies are in contrast to Cess et al. [1995], Ramanathan et al. [1995], and Pilewskie and Valero [1995]. The present study compares the atmospheric shortwave absorption in the National Center for Atmospheric Research (NCAR) Community Climate Model Version 2 and Version 3 (CCM2 and CCM3) with the collocated ERBE/GEBA data Copyright 1998 by the American Geophysical Union. Paper number 98JD /98/98JD sets. We show that with the same amount of shortwave reflec- tion at TOA in the models as in the ERBE measurements, the models overestimate the shortwave insolation at the surface by 2-24 W m -2. This result of insufficient absorption of shortwave radiation in the models is consistent, in terms of total-sky atmospheric shortwave absorption, with several studies that reported enhanced shortwave cloud absorption [e.g., Cess et al., 1996; Valero et al., 1997]. The present study is also consis- tent with the analysis ofarking [1996],Arking et al. [1997], and Charlock et al. [1995] in this total-sky quantity, regardless of whether the enhanced absorption is in the clear-sky atmosphere or in clouds. The purpose of this short paper is to emphasize this consistency when we debate the atmospheric absorption problem. This is because insufficient atmospheric shortwave absorption in the general circulation models (GCMs), whether in clear sky or in clouds, implies overcalculation of the latent heating in the atmosphere that relates to a too strong hydrological cycle in the models. This recognition of the consistency also helps to focus the debate on enhanced shortwave absorption onto cloud absorption or clear-sky absorption. Furthermore, the CCM is a widely used community model that is currently coupled to a global ocean model to form the climate system model (CSM); it is important to document a systematic bias in the model. This paper is organized as follows: Section 2 briefly discusses the data sets and the models used. Section 3 reports the comparison. Section 4 summarizes the results. 2. The Data and Models 2.1. ERBE and GEBA Reflection of shortwave radiation into space at the TOA is taken from ERBE. Monthly shortwave flues at a resolution of 2.5 ø 2.5 ø are used in this study [Barkstrom and Smith, 1986]. The monthly shortwave insolation at the surface are pyronom-

2 892 HANG ET AL.: BIAS OF ATMOSPHERIC SHORTWAVE RADIATION Figure 1. Geographical distribution of the Global Energy Balance Archive (GEBA) grid cells. eter measurements compiled in GEBA as part of the Water Project of the World Climate Research Program (WCRP). Sources of the compilation are periodicals, monographs, data reports, unpublishe data, and the World Radiation Data Center in the former Soviet Union [Ohmura and Gilgen, 1991, 1993]. The actual data we used are from the WCRP Surface Radiation Budget (SRB) product distributed from the NASA Langley Research Center [Whitlock et al., 1995]. Certain quality checks and collocation with ERBE have been carried out in the SRB product. The data spans from March 1985 to December 1988, with most of the data in 1985 and They have been processed to the International Satellite Cloud Climatology Project (ISCCP) C1 grids. ISCCP grids with collocated ERBE/GEBA monthly data are shown in Figure 1. At some grids, there are up to 46 months of data, while at other grids there are only few months of data. The grids are primarily located in continental areas in the northern hemisphere. In our analysis we only use data between 6øN and 6øS. We also eclude those that have been identified as snow grids in the ISCCP product and those with clear-sky TeA albedo larger than % in ERBE, since the purpose of this paper is to eamine atmospheric column absorption when the surface albedo is not too high. Two cautions should be made here. The first is that collo- cation error in the data could be large for individual pairs of data. While the ERBE reflection is for a 2.5 ø 2.5 ø grid at TeA, the surface insolation in GEBA is made at few stations, typically just one station. A pyronometer at a surface station sees a much smaller view of the atmosphere than the satellites see. Furthermore, the surface station may not be geographically representative of the whole ISCCP grid. Thus a large sample of collocated ERBE/GEBA measurementshould be used to minimize the sampling error. The second caution concerns the accuracy of the surface insolation [Ohmura and Gilgen, 1991, 1993]. In the past, problems in pyronometers have been uncovered when instantaneous or hourly insolation data are available (R. D. Cess et al., unpublished manuscript, 1995). Such screening is almost impossible using just monthly data. Moreover, the original data might be intended for different purposes with less rigorous accuracy requirement than currently sought. Once again, a large sample of data, rather than some single pairs of ERBE/GEBA data, should be used General Circulation Models The models used are the NCAR CCM2 and CCM3. CCM2 is documented by Hack et al. [1993], and CCM3 has been documented by Kiehl et al. [1996]. The shortwave radiation scheme in CCM2 is described by Briegleb [1992]. It uses the delta-eddington method with the solar spectrum divided into 18 bands: seven for ozone, one for the visible, seven for water vapor, and three for carbon dioide. The cloud parameteriza- tion follows that of Slingo [1987] with modifications as given by Hack et al. [1993]. The delta-eddington routine allows for gaseous absorption by 3, ce2, 2, H2e, molecular scattering, and scattering and absorption of cloud particles. The quality of the cloud parameterization and radiative flues at TeA in CCM2 has been eamined by Kiehl et al. [1994], which agrees generally with satellite observations. Changes of the solar radiation code in CCM3 include addition of background aerosols with total optical depth of.14 in the lowest three model layers, with other optical properties also prescribed [Kiehl et al., 1996]. Improvements are made in diagnosing the effective radius of cloud particles and the cloud liquid water path, and ice clouds have been incorporated. These changes have collectively reduced some of the systematic biases in the model [Kiehl et al., 1996]. Simulated reflection of solar radiation at TeA, and insolation at the surface, are taken from the integrations of CCM2 and CCM3 with prescribed observed monthly sea surface temperatures, the integrations in the Atmospheric Model Inter- comparison Project (AMIP). The integrations are from 1979 to Monthly model simulations, at locations and in months the same as the collocated ERBE/GEBA data from March 1985 to December 1988, are etracted for this study. Our strategy of comparison is to first compare model results with direct measurements in the ERBE/GEBA data by taking

3 HANG ET AL.: BIAS OF ATMOSPHERIC SHORTWAVE RADIATION DIFFERENCE IN TOA REFLECTION (Model minus ERBE, Wm '2) Figure 2. Schematic illustration of differences between a model and the collocated Earth Radiation Budget Eperiment (ERBE)/GEBA measurements. 2 lo o z 15 X ) 5 XX -1 1.,:, - 5 X ,,,, I,,,, I ' ' ' ' X... I... XX X X X X X ' XX".. --, X ' ' (b) CCM3 X X,,,'-.',, ' '. ' ' e.,:i.,,:. * - < X, ß :;,'.'/ L.,.,;,: ;,,.,: -1-2 f I ' ß -,,, I,,, I ], I,,, I,,, LATITUDE Figure 4. Latitudinal distribution of the difference in atmospheric shortwave transmittance (model simulation minus GEBA measurements) in four seasons for CCM2. -5 ' X, ::,r XX X < I... I,, ',,',, DIFFERENCE IN TOA REFLECTION (Wm'z, MODEL-ERBE) Figure 3. Differences in surface insolation (model simulations minus measurements) at all GEBA cells against differences in top-of-the-atmosphere (TOA) shortwave reflection (model simulations minus ERBE measurements): (a) Community Climate Model 2 (CCM2) and (b) CCM3. the differences between model and data and plotting the difference in surface insolation against the difference in TOA reflection (Figure 2). If the differences reside in quadrant II in Figure 2, the model overestimates surface insolation, and at the same time the model underestimates shortwave reflection at TOA. The most likely cause of errors is the underestimation of cloud amount or its optical depth in the model. If the difference points are in quadrant IV, then the leading problem in the model is its overestimation of cloud amount or its optical depth. If, however, the difference points are in quadrant I, then the model overestimates surface insolation while at the same time overestimates TOA reflection. Thus the model atmo-

4 , 8922 HANG ET AL.: BIAS OF ATMOSPHERIC SHORTWAVE RADIATION CCM2 at (48.8, 9.5) ' ''' I ' ' ' I ' ' ' I ' ' ' I ' ' ' 1 CCM2 at (48.8,13.3) ' ' ' 1 ' ' ' I ' ' ' I ' "' I ' ' '.8 R = R = '''['''] ' 1,,,I,,,I,,,I,,,I,, I 1 CCM2 at (3.8,23.8) ' ' ' I ' ' ' [ ' ' ' I ' ' ' I ' ' ' '''l'''l'''l'''l''' CCM2 at (-6.3,21.4) o.8 R =.995 R = ,.2 '' '. [2'''.4 [...'16'. [8'' ' 1,,, I,,, I,,, I,, I,, TOA ALBEDO Figure 5. Sample relationships batween atmospheric transmittance and TOA albedo in CCM2. Latitude and longitude of the selected samples are given above each panel. sphere becomes brighter at the top and at the surface, indicating insufficient absorption of shortwave radiation in the model atmospheri column. The opposite applies if points are located in quadrant III. Sampling errors due to mismatch of ERBE and GEBA data are epected to spread the difference points over all the quadrants. 3. Results Figure 3 shows the differences of shortwave surface insolation and TOA reflection at the GEBA grids between the models and the ERBE/GEBA data for CCM2 (Figure 3a) and for CCM3 (Figure 3b). The reader should not be alarmed by the magnitude of the differences in either the abscissalone or in the ordinate alone. Considering that GCMs are unable to accurately simulate regional climate, it is no surprise that gridscale features of clouds cannot be realistically reproduced. What matters here are the paired differences in both coordi- nates. It is seen that the first-order difference arises from cloud amount and/or cloud optical depth in the models, since most of the points fall in quadrants II and IV. In the CCM2 case, clouds are underestimated over land, consistent with results reported by Kiehl et al. [1994]. There is, however, a distinct feature in the figures, and that is the asymmetry between quadrants I and III. Many points reside in quadrant I, but few reside in quadrant III. Thus models tend to have brighter atmospheres at the TOA and at the surface at the same time, suggesting insufficient absorption of solar radiation in the model atmospheres. This bias can also be seen when one eamines the points at the vertical line where the difference in TOA reflection is zero. When the TOA re- flection in the models is the same as in ERBE, the models have larger surface insolation than the GEBA data. It should be noted that the magnitude of the difference in Figure 3 is related to the magnitude of incoming radiation at TOA due to latitudinal changes of the grids and seasonal variation of the months. In Figure 4 we show the latitudinal distribution of the difference in the shortwave atmospheric transmittance between CCM2 and GEBA for the four seasons. This information is similar to what was shown by Wild et al. [1995] for the European Centre for Medium-Range Weather Forecasting-University of Hamburg GCMs. There are positive biases in the atmospheric transmittance in the model at most of the grids, but it should be borne in mind that the first-order problem of the bias in the model is due to cloud amount and/or optical properties. Thus another approach is used in the following to derive the actual magnitude of the difference in atmospheric absorption. Atmospheric albedo at the TOA and atmospheric transmittance are typically well correlated [Cess et al., 1995]. The correlations are especially better in the GCMs than in the data because there is no sampling error in the models. Eamples of relationships between transmittance and TOA albedo alone are shown in Figure 5, in which data points correspond to varying year and month at fied locations. Since seasonal variabilities of clouds, water vapor, and solar zenith angle (which further relates to surface albedo) all play a role in forming the TOA albedo and transmittance relationship in the monthly data, we used a multiple regression of the atmospheric transmittance against TOA albedo, column precipitable water, and

5 HANG ET AL.' BIAS OF ATMOSPHERIC SHORTWAVE RADIATION 8923 mean cosine of solar zenith angle for the monthly model data. This procedure is described as TMODE L = A q- A1 X O/MODE L q- A 2 X P MODEL q- A 3 X (1) where T is the atmospheric transmittance, O/is the albedo at TOA, P is the column precipitable water, and-/ is the mean cosine of the solar zenith angle. It should be emphasized that this regression is not meant to separate the cloud effect from other effects such as water vapor. Instead, the regression is to obtain atmospheric transmittance from the related variables. The inclusion of the last two terms in (1) is to improve the relationship. There are few grids where seasonal variation of clouds is small and the correlation between the diagnosed transmittance and the model transmittance is less than.95. We eclude these grids that comprise less than 2.5% of the total selected girds. The model TOA albedo and precipitable water at each grid are then replaced with ERBE TOA albedo and the TIROS operational vertical sounder (TOVS) precipitable water to obtain the adjusted atmospheric transmittance in the model: 3O 2O o Tadjusted -- A q- A 1 X O/ERBE q- A 2 X PTOVS + A 3 X (2) This procedure reduces the difference in TOA albedo to zero and brings all points in Figure 3 onto a vertical line. We also used the water vapor from the NASA Water Vapor Project (NVAP) and found that impact of the different water vapor data sets on the adjusted transmittance is negligible. The difference of the adjusted atmospheric transmittance in CCM2 with the GEBA transmittance is shown in Figure 6, which is to be compared with Figure 4. It is seen that the normalization of model TOA albedo to ERBE albedo, an.d to a lesser etent the adjustment of precipitable water, has largely eliminated negative values in Figure 4, which are related to overestimation of clouds in the model. Positive biases prevail. -31} 2O Two features should be noted. The first is that there is no ' ' " I ' ' ' I (d) SON 2O ß apparent difference in the biases among different seasons. The second is that little can be said about the latitudinal variation 1 of the transmittance difference as reported by Li et al. [1995]. The difference of the adjusted atmospheric transmittance in -' '1 I ' CCM3 with GEBA transmittance is shown in Figure 7. Gen- I - -1 eral features are similar to those in CCM2. For each data point we are able to obtain an adjusted surface insolation for the models based on the adjusted transmittance. -3O [ Taking all data points together, we can calculate the mean, I,,, I,,, I,, I I i i I atmospheric transmittance for all these points and compare it with the corresponding mean transmittance in the GEBA data LATITUDE The difference in the adjusted atmospheric transmittance be- Figure 6. Latitudinal distribution of the difference in adtween the models and GEBA is 7.2% for CCM2 and 5.9% for justed atmospheric transmittance (adjusted model simulation CCM3 of the mean TOA incoming solar radiation. When minus GEBA measurements) in four seasons for CCM2. The etrapolated to the globe, these numbers imply global mean adjustments are made to normalize TOA albedo and atmodifference of surface insolation of 24 W m -2 in CCM2 and 2 spheric precipitable water to observations. W m -2 in CCM3. These differences in the adjusted atmospheric transmittance, since constrained with the same TOA albedoes in ERBE and the same precipitable water as in TOVS, can be directly interpreted as insufficient atmospheric shortwave absorption in the models. Assuming a surface albedo of 15%, the models underestimate atmospheric shortwave absorption by 2 This underestimation in shortwave absorption, be it in clear and/or cloudy sky, has important implications to the overall energy budget in GCMs. In the global mean the atmosphere in a GCM should be in a thermal equilibrium state. The net radiative cooling of the atmosphere should be balanced by the and 17 W m -2 in CCM2 and CCM3, respectively. The small latent heating plus sensible heat flu from the surface. Since difference between CCM2 and CCM3 is probably due to the introduction of aerosols in CCM3. Such a difference is within sensible heat flu represents a small term in the heat budget, the primary balance comes from latent heating, which equals the error bar, and so no attempt is made here to characterize either the surface evaporation or the precipitation. Underesit further. timation of shortwave absorption in the model atmosphere,

6 8924 HANG ET AL.' BIAS OF ATMOSPHERIC SHORTWAVE RADIATION 3O 2O ' ' ' I ' ' ' I ' ' ' I ' ' I ' ' ' (b) MAM ß ß, ill! - ß I O ß ß O ß I ; ß I i.i,. I ß ments. This translates to insufficient absorption of the shortwave radiation in the models when compared with collocated monthly ERBE/GEBA data. We have estimated, based on a normalization procedure, that this underestimation of shortwave absorption is about 2 W m -2 in the CCM2 and 17 W m -2 in CCM3. This underestimation is consistent, in terms of the total-sky atmospheric shortwave absorption, with the recent studies by Cess et al. [1996] and Valero et al. [1997] that further reported enhanced cloud absorption but no significant clear-sky enhanced absorption. It is also consistent, also in terms of the total-sky shortwave absorption, with studies byarking [1996] and Arking et al. [1997] that have contradicted the enhanced cloud absorption but suggested more clear-sky absorption, and with studies by Charlock et al. (1995). Although this study cannot designate whether the underestimation of atmospheric shortwave absorption is in clear sky or in overcast sky, we have argued that this consistency itself is important since it has significant implications for the intensity of the hydrological cycle and thus the circulation in the general circulation models ,,, I,,, I,, I I I I I I,,, Acknowledgments. The authors thank colleagues at the NASA Langley Research Center for making the SRB data products available to us. We thank Charles Whitlock for his comments on an earlier version of the manuscript. Albert Arking's critical review of the paper has led to improvements of the original manuscript. This work is supported by NASA under grant NAG NCAR is sponsored by the National Science Foundation O I ' ' I ' ' ' I ' I I I I I, I ' ' ' (d) SON ß ß - ß 88 ß ß - -j ß ß o- r t.ll I ;-,,, I, t, I,,, I,,, I,,, LATITUDE Figure 7. Same as in Figure 6 ecept for CCM3. whether in clear sky or in clouds, would require more latent heat to balance the net radiative cooling. The consequence is overestimation of the intensity of the hydrological cycle and the associated features of dynamic circulations in the models [Kiehl et al., 1995; hang et al., 1996]. 4. Conclusions We have made a direct comparison of shortwave reflection at TOA and collocated surface insolation at the surface be- tween the NCAR CCM2 and CCM3 and the ERBE/GEBA measurements. It has been shown that the model atmospheres are brighter at the TOA than ERBE measurements and transmit more solar radiation to the surface than GEBA measure- References Arking, A., Absorption of solar energy in the atmosphere: Discrepancy between a model and observations, Science, 273, , Arking, A., M.-D. Chou, and W. L. Ridgway, The accuracy of shortwave radiative transfer codes in climate models, in Proceedings of the International Radiation Symposium, pp , Am. Meteorol. Soc., Boston, Mass., Barkstrom, B. R., and G. L. Smith, The Earth Radiation Budget Eperiment: Science and implementation, Rev. Geophys., 24, , Briegleb, B. P., Delta-Eddington approimation for solar radiation in the NCAR Community Climate Model, J. Geophys. Res., 97, , Cess, R. D., et al., Absorption of solar radiation by clouds: Observation versus models, Science, 267, , Cess, R. D., M. H. hang, Y. hou, X. Jing, and V. Dvortsov, Absorption of solar radiation by clouds: Interpretation of satellite, surface, and aircraft measurements, J. Geophys. Res., 11, 23,299-23,9, Charlock, T., P. T. L. Alberta, and C. H. Whitlock, GEWEX data sets for assessing the budget for the absorption of solar energy by the atmosphere, GEWEX News, 5, 9-11, Hack, J. J., B. A. Boville, B. P. Briegleb, J. T. Kiehl, P. J. Rasch, and D. L. Williamson, Description of the NCAR Community Climate Model (CCM2), NCAR/TN STR, 18 pp., Natl. Cent. for Atmos. Res., Boulder, Colo., Kiehl, J. T., J. J. Hack, and B. P. Briegleb, The simulated Earth radiation budget of the NCAR CCM2 and comparisons with the Earth Radiation Budget Eperiment (ERBE), J. Geophys. Res., 99, 2,815-2,828, Kiehl, J. T., J. J. Hack, M. H. hang, and R. D. Cess, Sensitivity of the simulated climate to enhanced shortwave cloud absorption, J. Clim., 8, , Kiehl, J. T., J. J. Hack, G. B. Bonan, B. A. Boville, B. P. Briegleb, D. L. Williamson, and P. J. Rasch, Description of the NCAR Community Climate Model (CCM3), NCAR/TN-42 + STR, 152 pp., Natl. Cent. for Atmos. Res., Boulder, Colo., Li,., and L. Moreau, Alternation of atmospheric solar absorption by clouds: Simulation and observation, J. Appl. Meteorol., 35, , Li,., H. W. Barker, and L. Moreau, The variable effect of clouds on

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