GFDL - Geophysical Fluid Dynamics Laboratory

Huan Guo: Publications

Peer-reviewed publications

  1. Zhao, M., J.-C. Chris, I. M. Held, H., Guo, and co-authors 2018: The GFDL Global Atmosphere and Land Model AM4.0/LM4.0– Part I: Simulation Characteristics with Prescribed SSTs. Submitted to J. Adv. Model. Earth Syst.
  2. Zhao, M., J.-C. Chris, I. M. Held, H., Guo, and co-authors 2018: The GFDL Global Atmosphere and Land Model AM4.0/LM4.0– Part II: Model Description, Sensitivity Studies, and Tuning Strategies. Submitted to J. Adv. Model. Earth Syst.
  3. Jing, X., K., Suzuki, H., Guo, D., Goto, T., Ogura, T., Koshiro, and J., Mülmenstädt 2017: A multimodel study on warm precipitation biases in global models compared to satellite observations. J. Geophys. Res., 122, 11,806–11,824, doi:10.1002/2017JD027310. (pdf, 12M) The cloud-to-precipitation transition process in warm clouds simulated by state-of-the-art global climate models (GCMs), including both traditional climate models and a high-resolution model, is evaluated against A-Train satellite observations. The models and satellite observations are compared in the form of the statistics obtained from combined analysis of multiple-satellite observables that probe signatures of the cloud-to-precipitation transition process. One common problem identified among these models is the too-frequent occurrence of warm precipitation. The precipitation is found to form when the cloud particle size and the liquid water path (LWP) are both much smaller than those in observations. The too-efficient formation of precipitation is found to be compensated for by errors of cloud microphysical properties, such as underestimated cloud particle size and LWP, to an extent that varies among the models. However, this does not completely cancel the precipitation formation bias. Robust errors are also found in the evolution of cloud microphysical properties from nonprecipitating to drizzling and then to raining clouds in some GCMs, implying unrealistic interaction between precipitation and cloud water. Nevertheless, auspicious information is found for future improvement of warm precipitation representations: the adoption of more realistic autoconversion scheme in the high-resolution model improves the triggering of precipitation, and the introduction of a sophisticated subgrid variability scheme in a traditional model improves the simulated precipitation frequency over subtropical eastern ocean. However, deterioration in other warm precipitation characteristics is also found accompanying these improvements, implying the multisource nature of warm precipitation biases in GCMs.
  4. Zhao, M., J.-C. Chris, I. M. Held, V. Ramaswamy, S-J Lin, Y. Ming, P. Ginoux, B. Wyman, L.J. Donner, D. Paynter, and H., Guo 2016: Uncertainty in model climate sensitivity traced to representations of cumulus precipitation microphysics. J. Climate, 29(2), 543-560, doi:10.1175/JCLI-D-15-0191.1 (pdf, 1.3M)
    Uncertainty in equilibrium climate sensitivity impedes accurate climate projections. While the inter-model spread is known to arise primarily from differences in cloud feedback, the exact processes responsible for the spread remain unclear. To help identify some key sources of uncertainty, we use a developmental version of the next generation Geophysical Fluid Dynamics Laboratory global climate model (GCM) to construct a tightly controlled set of GCMs where only the formulation of convective precipitation is changed. The different models provide simulation of present-day climatology of comparable quality compared to the CMIP5 model ensemble. We demonstrate that model estimates of climate sensitivity can be strongly affected by the manner through which cumulus cloud condensate is converted into precipitation in a model’s convection parameterization, processes that are only crudely accounted for in GCMs. In particular, two commonly used methods for converting cumulus condensate into precipitation can lead to drastically different climate sensitivity, as estimated here with an atmosphere/land model by increasing sea surface temperatures uniformly and examining the response in the top-of-atmosphere energy balance. The effect can be quantified through a bulk convective detrainment efficiency, which measures the ability of cumulus convection to generate condensate per unit precipitation. The model differences, dominated by shortwave feedbacks, come from broad regimes ranging from large-scale ascent to subsidence regions. Given current uncertainties in representing convective precipitation microphysics and our current inability to find a clear observational constraint that favors one version of our model over the others, the implications of this ability to engineer climate sensitivity needs to be considered when estimating the uncertainty in climate projections.
  5. Pan, F., X. Huang, L. L. Strow, and H., Guo 2015: Linear trends and closures of 10-year observations of AIRS stratospheric channels. J. Climate, 28(22), 8939–8950, doi: 10.1175/JCLI-D-15-0418.1 (pdf, 1.4M)
    The AIRS (Atmospheric Infrared Sounder) Level-1b radiances have been shown to be well calibrated (~0.3K or higher) and have little secular drift (~4mK/year) since its operation started in September 2002. We study the linear trends of 10 years (2003-2012) of AIRS global-mean radiances in the CO2 ν2 band that are sensitive to emissions from the stratosphere (stratospheric channels). AIRS lower-stratospheric channels have a cooling trend of no more than 0.23K/decade while its middle-stratospheric channels consistently show a statistically significant cooling trend as large as 0.58K/decade. The 95% confidence interval for the trend is ~±0.20K/decade. Two sets of synthetic AIRS radiances are computed using the PCRTM (Principle Component-based Radiative Transfer Model), one based on a free-running GFDL AM3 model over the same period and one based on ERA-interim reanalysis. The GFDL AM3 simulations overestimate the cooling trends in the middle-upper-stratospheric channels while slightly underestimate in the lower-stratospheric channels. The synthetic radiances based on ERA-interim reanalysis, on the opposite, have statistically significant positive trends at virtually all stratospheric channels. This confirms the challenge to GCM modeling and reanalysis community for a better simulation or assimilation of the stratospheric climate. We show that the linear trends in AIRS radiances can be reproduced to a large extent by the spectral radiative kernel technique and the trends from the AIRS L2 temperature retrievals and from the change of CO2. This suggests a closure between AIRS L1 radiances and L2 retrievals and potential merit of AIRS data in the studies of stratosphere changes.
  6. Guo, H., J.-C. Golaz, L. J. Donner, B. Wyman, M. Zhao, and P. Ginoux 2015: CLUBB as a unified cloud parameterization: Opportunities and challenges. Geophys. Res. Lett., 42, 4540–4547, doi:10.1002/2015GL063672 (pdf, 1.3M)
    CLUBB (Cloud Layers Unified by Binormals) is a higher-order closure (HOC) method with an assumed joint probability density function (PDF) for the subgrid variations in vertical velocity, temperature, and moisture. CLUBB has been implemented in the atmospheric component (AM3) of the Geophysical Fluid Dynamics Laboratory general circulation model A M3-CLUBB and successfully unifies the treatment of shallow convection, resolved clouds, and planetary boundary layer (PBL). In this study, we further explore the possibility for CLUBB to unify the deep convection in a new configuration referred as AM3-CLUBB+. AM3-CLUBB+ simulations with prescribed sea surface temperature are discussed. Cloud, radiation, and precipitation fields compare favorably with observations and reanalyses. AM3-CLUBB+ successfully captures the transition from stratocumulus to deep convection and the modulated response of liquid water path to aerosols. Simulations of tropical variability and the Madden-Julian oscillation (MJO) are also improved. Deficiencies include excessive tropical water vapor and insufficient ice clouds in the midlatitudes.
  7. Ban-Weiss, G. A., Jin L, Bauer S, Bennartz R, Liu X, Zhang K, Ming Y, H., Guo, and Jiang J 2014: Evaluating clouds, aerosols, and their interactions in three global climate models using satellite simulators and observations. Journal of Geophysical Research, 119(18), 10876–10901, doi: 10.1002/2014JD021722(pdf, 4.2M)
    Accurately representing aerosol-cloud interactions in global climate models is challenging. As parameterizations evolve, it is important to evaluate their performance with appropriate use of observations. In this investigation we compare aerosols, clouds, and their interactions in three global climate models (GFDL-AM3, NCAR-CAM5, GISS-ModelE2) to MODIS satellite observations. Modeled cloud properties are diagnosed using a MODIS simulator. Cloud droplet number concentrations (N) are computed identically from satellite-simulated and MODIS-observed values of liquid cloud optical depth and droplet effective radius. We find that aerosol optical depth (τa) simulated by models is similar to observations in many regions around the globe. For N, AM3 and CAM5 capture the observed spatial pattern of higher values in coastal marine stratocumulus versus remote ocean regions, though modeled values in general are higher than observed. Aerosol-cloud interactions were computed as the sensitivity of ln(N) to ln(τa) for coastal marine liquid clouds near South Africa (SAF) and Southeast Asia (SEA) where τa varies in time. AM3 and CAM5 are more sensitive than observations, while the sensitivity for ModelE2 is statistically insignificant. This widely used sensitivity could be subject to misinterpretation due to the confounding influence of meteorology on both aerosols and clouds. A simple framework for assessing the sensitivity of ln(N) to ln(τa) at constant meteorology illustrates that observed sensitivity can change from positive to statistically insignificant when including the confounding influence of relative humidity. Satellite-simulated versus standard model values of N from CAM5 are compared in SAF; standard model values are significantly lower with a bias of 83 cm−3.
  8. Guo, H., J.-C. Golaz, L. J. Donner, P. Ginoux, and R. S. Hemler, 2014: Multi-variate probability density functions with dynamics in the GFDL atmospheric general circulation model: Global Tests. J. Climate, 27(5), 2087-2108, doi: 10.1175/JCLI-D-13-00347.1 (pdf, 5.0M)
    A unified turbulence and cloud parameterization based on multi-variate probability density functions (PDFs) has been incorporated into the GFDL atmospheric general circulation model AM3. This PDF-based parameterization not only predicts sub-grid variations in vertical velocity, temperature, and total water, which bridge sub-grid scale processes (such as aerosol activation and cloud microphysics) and grid-scale dynamic and thermodynamic fields, but also unifies the treatment of planetary boundary layer (PBL), shallow convection, and cloud macrophysics. This parameterization is the “Cloud Layers Unified By Binormals” (CLUBB) parameterization. With the incorporation of CLUBB in AM3, coupled with a two-moment cloud microphysical scheme, AM3-CLUBB allows for a more physically-based and self-consistent treatment of aerosol activation, cloud micro- and macro-physics, PBL, and shallow convection. The configuration and performance of AM3-CLUBB are described. Cloud and radiation fields, as well as most basic climate features, are modeled realistically. Relative to AM3, AM3-CLUBB improves the simulation of coastal stratocumulus, a longstanding deficiency in GFDL models, and their seasonal cycle, especially at higher horizontal resolution, but global skill scores deteriorate slightly. Through sensitivity experiments, we show that (1) the two-moment cloud microphysics helps relieve the deficiency of coastal stratocumulus; (2) using the CLUBB sub-grid cloud water variability in the cloud microphysics has a considerable positive impact on global cloudiness; and (3) the impact of adjusting CLUBB parameters is to improve the overall agreement between model and observations.
  9. Guo, H., J.-C. Golaz, and L. J. Donner, 2011: Aerosol effects on stratocumulus water paths in a PDF‐based parameterization. Geophys. Res. Lett., 38, L17808, doi:10.1029/2011GL048611 (pdf, 406k)
    Successful simulation of aerosol indirect effects in climate models requires parameterizations that capture the full range of cloud‐aerosol interactions, including positive and negative liquid water path (LWP) responses to increasing aerosol concentrations, as suggested by large eddy simulations (LESs). A parameterization based on multi‐variate probability density functions with dynamics (MVD PDFs) has been incorporated into the single‐column version of GFDL AM3, extended to treat aerosol activation, and coupled with a two‐moment microphysics scheme. We use it to explore cloud‐aerosol interactions. In agreement with LESs, our single‐column simulations produce both positive and negative LWP responses to increasing aerosol concentrations, depending on precipitation and free atmosphere relative humidity. We have conducted sensitivity tests to vertical resolution and droplet sedimentation parameterization. The dependence of sedimentation on cloud droplet size is essential to capture the full LWP responses to aerosols. Further analyses reveal that the MVD PDFs are able to represent changes in buoyancy profiles induced by sedimentation as well as enhanced entrainment efficiency with aerosols comparable to LESs.
  10. Guo, H., J.-C. Golaz, L. J. Donner, V. E. Larson, D. P. Schanen, and B. M. Griffin, 2010: Multi-variate probability density functions with dynamics for cloud droplet activation in large-scale models: single column tests. Geosci. Model Dev., 3, 475-486, doi:10.5194/gmd-3-475-2010 (pdf, 6.9M)
    Successful simulation of cloud-aerosol interactions (indirect aerosol effects) in climate models requires relating grid-scale aerosol, dynamic, and thermodynamic fields to small-scale processes like aerosol activation. A turbulence and cloud parameterization, based on multi-variate probability density functions of sub-grid vertical velocity, temperature, and moisture, has been extended to treat aerosol activation. Multi-variate probability density functions with dynamics (MVD PDFs) offer a solution to the problem of the gap between the resolution of climate models and the scales relevant for aerosol activation and a means to overcome the limitations of diagnostic estimates of cloud droplet number concentration based only on aerosol concentration. Incorporated into the single-column version of GFDL AM3, the MVD PDFs successfully simulate cloud properties including precipitation for cumulus, stratocumulus, and cumulus-under-stratocumulus. The extension to treat aerosol activation predicts droplet number concentrations in good agreement with large eddy simulations (LES). The droplet number concentrations from the MVD PDFs match LES results more closely than diagnostic relationships between aerosol concentration and droplet concentration. In the single-column model simulations, as aerosol concentration increases, droplet concentration increases, precipitation decreases, but liquid water path can increase or decrease.
  11. Liu, Y., P. H. Daum, H. Guo, and Y. Peng, 2008c, Dispersion Bias, Dispersion Effect, and Aerosol-Cloud Conundrum. Environ. Res. Lett., 3, 045021, doi:10.1088/1748-9326/3/4/045021 (pdf, 378k)
    This work examines the influences of relative dispersion (the ratio of the standard deviation to the mean radius of the cloud droplet size distribution) on cloud albedo and cloud radiative forcing, derives an analytical formulation that accounts explicitly for the contribution from droplet concentration and relative dispersion, and presents a new approach to parameterize relative dispersion in climate models. It is shown that inadequate representation of relative dispersion in climate models leads to an overestimation of cloud albedo, resulting in a negative bias of global mean shortwave cloud radiative forcing that can be comparable to the warming caused by doubling CO2 in magnitude, and that this dispersion bias is likely near its maximum for ambient clouds. Relative dispersion is empirically expressed as a function of the quotient between cloud liquid water content and droplet concentration (i.e., water per droplet), yielding an analytical formulation for the first aerosol indirect effect. Further analysis of the new expression reveals that the dispersion effect not only offsets the cooling from the Twomey effect, but is also proportional to the Twomey effect in magnitude. These results suggest that unrealistic representation of relative dispersion in cloud parameterization in general, and evaluation of aerosol indirect effects in particular, is at least in part responsible for several outstanding puzzles of the aerosol–cloud conundrum: for example, overestimation of cloud radiative cooling by climate models compared to satellite observations; large uncertainty and discrepancy in estimates of the aerosol indirect effect; and the lack of interhemispheric difference in cloud albedo.
  12. Guo, H., Y. Liu, P. H. Daum, G. I. Senum, and W.-K. Tao, 2008b, Characteristics of vertical velocity in marine stratocumulus: Comparison of LES simulations with observations, Environ. Res. Lett., 3, 045020, doi: 10.1088/1748-9326/3/4/045020 (pdf, 346k)
    We simulated a marine stratus deck sampled during the Marine Stratus/Stratocumulus Experiment (MASE) with a three-dimensional large eddy simulation (LES) model at different model resolutions. Various characteristics of the vertical velocity from the model simulations were evaluated against those derived from the corresponding aircraft in situ observations, focusing on standard deviation, skewness, kurtosis, probability density function (PDF), power spectrum, and structure function. Our results show that although the LES model captures reasonably well the lower-order moments (e.g., horizontal averages and standard deviations), it fails to simulate many aspects of the higher-order moments, such as kurtosis, especially near cloud base and cloud top. Further investigations of the PDFs, power spectra, and structure functions reveal that compared to the observations, the model generally underestimates relatively strong variations on small scales. The results also suggest that increasing the model resolutions improves the agreements between the model results and the observations in virtually all of the properties that we examined. Furthermore, the results indicate that a vertical grid size < 10m is necessary for accurately simulating even the standard-deviation profile, posing new challenges to computer resources.
  13. Guo, H., Y. Liu, and J. E. Penner, 2008a, Does the threshold representation associated with the autoconversion process matter? Atmos. Chem. Phys., 8, 1225-1230 (pdf, 5.8M)
    Different ad hoc threshold functions associated with the autoconversion process have been arbitrarily used in atmospheric models. However, it is unclear how these ad hoc functions impact model results. Here systematic investigations of the sensitivities of climatically-important properties: CF (cloud fraction), LWP (liquid water path), and AIE (aerosol indirect effect) to threshold functions have been performed using a 3-D cloud-resolving model. It is found that the effect of threshold representations is larger on instantaneous values than on daily averages; and the effect depends on the percentage of clouds in their transitional stages of converting cloud water to rain water. For both the instantaneous values and daily averages, the sensitivity to the specification of critical radius is more significant than the sensitivity to the “smoothness” of the threshold representation (as embodied in the relative dispersion of droplet size distribution) for drizzling clouds. Moreover, the impact of threshold representations on the AIE is stronger than that on CF and LWP.
  14. Guo, H., J. E. Penner, M. Herzog, and S. Xie, 2007b, Investigation of the first and second aerosol indirect effects using data from the May 2003 Intensive Operational Period at the Southern Great Plains. J. Geophys. Res., 112, D15206, doi:10.1029/2006JD007173 (pdf, 7.0M)
    The Active Tracer High-Resolution Atmospheric Model is used to examine the aerosol indirect effect (AIE) for a spring continental stratus cloud on the basis of data collected during the 17 May 2003 Aerosol Intensive Operation Period (AIOP) at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains site. Model results for our base case, which uses observed aerosol concentrations, agree reasonably well with the available observations, giving confidence that the basic model is reasonable. Sensitivity tests are performed to explore the response of the clouds to changes in the aerosol number concentration and surface fluxes. During the major part of the simulation, from 0630 through 1400 local standard time (LST), an increase in the aerosol number concentration (Na) results in a decrease of the mean cloud droplet size and an increase of the cloud liquid water path (LWP) until aerosol number concentration levels reach 1200 cm3. Further increases in aerosol concentration do not increase the liquid water path because the depletion of cloud water by precipitation is negligible above this number concentration. After 1400 LST, the liquid water path decreases when aerosols increase as long as Na 600 cm3 and remains unchanged for higher aerosol concentrations. The decrease of LWP is associated with the evaporative cooling below cloud base which leads to more condensation of water vapor, a result that is consistent with afternoon satellite observations of the response of continental clouds to increases in droplet concentrations. A sensitivity test with a stronger surface latent flux increases both the cloud geometrical thickness and cloud water content. On the other hand, a sensitivity test with a stronger surface sensible heat flux leads to a higher cloud base and a shallower and drier cloud. The response of the cloud geometrical thickness to changes in surface sensible heat flux dominates that of the cloud water content. The cloud fraction is also reduced at the end of the simulation time period. Because the surface heat fluxes will likely change when aerosol and droplet number concentrations change, these sensitivity tests show that a fully coupled simulation with a land surface model will be needed to fully assess the response of the cloud to changing aerosol concentrations. Nevertheless, since the thermodynamic boundary layer profiles do not change significantly when aerosol concentrations are changed, our results for changing aerosol concentrations are qualitatively correct.
  15. Guo, H., J. E. Penner, M. Herzog, and H. Pawlowska, 2007a, Examination of the aerosol indirect effect under contrasting environments during the ACE-2 experiment. Atmos. Chem. Phys., 7, 535-548 (pdf, 3.3M)
    The Active Tracer High-resolution Atmospheric Model (ATHAM) has been adopted to examine the aerosol indirect effect in contrasting clean and polluted cloudy boundary layers during the Second Aerosol Characterization Experiment (ACE-2). Model results are in good agreement with available in-situ observations, which provides confidence in the results of ATHAM. Sensitivity tests have been conducted to examine the response of the cloud fraction (CF), cloud liquid water path (LWP), and cloud optical depth (COD) to changes in aerosols in the clean and polluted cases. It is shown for two cases that CF and LWP would decrease or remain nearly constant with an increase in aerosols, a result which shows that the second aerosol indirect effect is positive or negligibly small in these cases. Further investigation indicates that the background meteorological conditions play a critical role in the response of CF and LWP to aerosols. When large-scale subsidence is weak as in the clean case, the dry overlying air above the cloud is more efficiently entrained into the cloud, and in so doing, removes cloud water more efficiently, and results in lower CF and LWP when aerosol burden increases. However, when the large-scale subsidence is strong as in the polluted case, the growth of the cloud top is suppressed and the entrainment drying makes no significant difference when aerosol burden increases. Therefore, the CF and LWP remain nearly constant. In both the clean and polluted cases, the COD tends to increase with aerosols, and the total aerosol indirect effect (AIE) is negative even when the CF and LWP decrease with an increase in aerosols. Therefore, the first AIE dominates the response of the cloud to aerosols.
  16. Penner, J. E., J. Quaas, T. Storelvmo, T. Takemura, O. Boucher, H. Guo, and et al., 2006b, Model intercomparison of indirect aerosol effects.Atmos. Chem. Phys. 6, 3391-3405 (pdf, 2.4M)
    odeled differences in predicted effects are increasingly used to help quantify the uncertainty of these effects. Here, we examine modeled differences in the aerosol indirect effect in a series of experiments that help to quantify how and why model-predicted aerosol indirect forcing varies between models. The experiments start with an experiment in which aerosol concentrations, the parameterization of droplet concentrations and the autoconversion scheme are all specified and end with an experiment that examines the predicted aerosol indirect forcing when only aerosol sources are specified. Although there are large differences in the predicted liquid water path among the models, the predicted aerosol first indirect effect for the first experiment is rather similar, about −0.6Wm−2 to −0.7Wm−2. Changes to the autoconversion scheme can lead to large changes in the liquid water path of the models and to the response of the liquid water path to changes in aerosols. Adding an autoconversion scheme that depends on the droplet concentration caused a larger (negative) change in net outgoing shortwave radiation compared to the 1st indirect effect, and the increase varied from only 22% to more than a factor of three. The change in net shortwave forcing in the models due to varying the autoconversion scheme depends on the liquid water content of the clouds as well as their predicted droplet concentrations, and both increases and decreases in the net shortwave forcing can occur when autoconversion schemes are changed. The parameterization of cloud fraction within models is not sensitive to the aerosol concentration, and, therefore, the response of the modeled cloud fraction within the present models appears to be smaller than that which would be associated with model “noise”. The prediction of aerosol concentrations, given a fixed set of sources, leads to some of the largest differences in the predicted aerosol indirect radiative forcing among the models, with values of cloud forcing ranging from −0.3Wm−2 to −1.4Wm−2. Thus, this aspect of modeling requires significant improvement in order to improve the prediction of aerosol indirect effects.
  17. Bates, T. S., T. L. Anderson, T. Baynard, T. Bond, O. Boucher, G. Carmichael, A. Clarke, C. Erlick, H. Guo, and et al., 2006a, Aerosol direct radiative effects over the northwest Atlantic, northwest Pacific, and North Indian Oceans: estimates based on in-situ chemical and optical measurements and chemical transport modeling. Atmos. Chem. Phys. 6, 1657-1732 (pdf, 2.5M)
    The largest uncertainty in the radiative forcing of climate change over the industrial era is that due to aerosols, a substantial fraction of which is the uncertainty associated with scattering and absorption of shortwave (solar) radiation by anthropogenic aerosols in cloud-free conditions (IPCC, 2001). Quantifying and reducing the uncertainty in aerosol influences on climate is critical to understanding climate change over the industrial period and to improving predictions of future climate change for assumed emission scenarios. Measurements of aerosol properties during major field campaigns in several regions of the globe during the past decade are contributing to an enhanced understanding of atmospheric aerosols and their effects on light scattering and climate. The present study, which focuses on three regions downwind of major urban/population centers (North Indian Ocean (NIO) during INDOEX, the Northwest Pacific Ocean (NWP) during ACE-Asia, and the Northwest Atlantic Ocean (NWA) during ICARTT), incorporates understanding gained from field observations of aerosol distributions and properties into calculations of perturbations in radiative fluxes due to these aerosols. This study evaluates the current state of observations and of two chemical transport models (STEM and MOZART). Measurements of burdens, extinction optical depth (AOD), and direct radiative effect of aerosols (DRE – change in radiative flux due to total aerosols) are used as measurement-model check points to assess uncertainties. In-situ measured and remotely sensed aerosol properties for each region (mixing state, mass scattering efficiency, single scattering albedo, and angular scattering properties and their dependences on relative humidity) are used as input parameters to two radiative transfer models (GFDL and University of Michigan) to constrain estimates of aerosol radiative effects, with uncertainties in each step propagated through the analysis. Constraining the radiative transfer calculations by observational inputs increases the clear-sky, 24-h averaged AOD (34±8%), top of atmosphere (TOA) DRE (32±12%), and TOA direct climate forcing of aerosols (DCF – change in radiative flux due to anthropogenic aerosols) (37±7%) relative to values obtained with “a priori” parameterizations of aerosol loadings and properties (GFDL RTM). The resulting constrained clear-sky TOA DCF is −3.3±0.47, −14±2.6, −6.4±2.1Wm−2 for the NIO, NWP, and NWA, respectively. With the use of constrained quantities (extensive and intensive parameters) the calculated uncertainty in DCF was 25% less than the “structural uncertainties” used in the IPCC-2001 global estimates of direct aerosol climate forcing. Such comparisons with observations and resultant reductions in uncertainties are essential for improving and developing confidence in climate model calculations incorporating aerosol forcing.