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Precipitation Characteristics of ISCCP Cloud Regimes for Improving Model Hydrological Budgets

The key in unraveling relationships between precipitation and atmospheric circulations is their common linkage to clouds. Clouds can be described in a variety of ways and several approaches can be adopted to examine their connections to precipitation. We claim that when cloud regimes (aka weather states) from the International Satellite Cloud Climatology Project (ISCCP) are used to conditionally sample/sort and average precipitation data, useful insight and GCM-appropriate diagnostics on the origins and distribution of precipitation can be obtained. The ISCCP cloud regimes are mesoscale (2.5 ) cloud mixtures determined by cluster analysis on joint histograms of cloud optical thickness and cloud top pressure inferred from geostationary and polar orbiter satellite passive retrievals. The ISCCP cloud regime data are combined with GPCP IDD merged surface precipitation data and/or higher temporal and spatial resolution TRMM Multi-Satellite Precipitation Analysis (TMPA) data. The analysis is performed separately for three geographical zones, tropics, and northern/southern midlatitudes (for GPCP; only the tropics can be examined with TMPA data). Our presentation aspires to provide answers to the following questions: (l) What is the mean and variability of surface precipitation produced by each cloud regime at the time of regime occurrence? (2) What is the relative contribution of each cloud regime to the total precipitation within its geographical zone? (3) What is the geographical distribution of precipitation corresponding to particular cloud regime? (4) To what extent are the cloud regimes distinct in terms of their precipitation characteristics and is the regime ordering in terms of convective strength consistent with the observed precipitation intensity

Allowing for Horizontally Heterogeneous Clouds and Generalized Overlap in an Atmospheric GCM

While fully accounting for 3D effects in Global Climate Models (GCMs) appears not realistic at the present time for a variety of reasons such as computational cost and unavailability of 3D cloud structure in the models, incorporation in radiation schemes of subgrid cloud variability described by one-point statistics is now considered feasible and is being actively pursued. This development has gained momentum once it was demonstrated that CPU-intensive spectrally explicit Independent Column Approximation (lCA) can be substituted by stochastic Monte Carlo ICA (McICA) calculations where spectral integration is accomplished in a manner that produces relatively benign random noise. The McICA approach has been implemented in Goddard's GEOS-5 atmospheric GCM as part of the implementation of the RRTMG radiation package. GEOS-5 with McICA and RRTMG can handle horizontally variable clouds which can be set via a cloud generator to arbitrarily overlap within the full spectrum of maximum and random both in terms of cloud fraction and layer condensate distributions. In our presentation we will show radiative and other impacts of the combined horizontal and vertical cloud variability on multi-year simulations of an otherwise untuned GEOS-5 with fixed SSTs. Introducing cloud horizontal heterogeneity without changing the mean amounts of condensate reduces reflected solar and increases thermal radiation to space, but disproportionate changes may increase the radiative imbalance at TOA. The net radiation at TOA can be modulated by allowing the parameters of the generalized overlap and heterogeneity scheme to vary, a dependence whose behavior we will discuss. The sensitivity of the cloud radiative forcing to the parameters of cloud horizontal heterogeneity and comparisons of CERES-derived forcing will be shown

Advancements in the Representation of Cloud-Aerosol Microphysics in the GEOS-5 AGCM

Despite numerous challenges, the physical parameterization of cloud-aerosol interactions in atmospheric GCMs has become a top priority for advancement because of our need to simulate and understand past, current, and future indirect effects of aerosols on clouds. The challenges stem from the involvement of wide range of cloud-scale dynamics and aerosol activation physical processes. Cloud dynamics modulate cloud areal extent and condensate, while aerosol activation depends on aerosol mass load, size distribution, internal mixing state, and nucleating properties, and ultimately determines cloud optical properties via particle sizes. Both macro- and micro-scale processes are obviously important for cloud-radiation interactions. We will present the main features of cloud microphysical properties in the GEOS- 5 Atmospheric GCM (AGCM) as simulated by the McRAS-AC (Microphysics of Clouds with Relaxed Arakawa-Schubert and Aerosol-Cloud interaction) scheme. McRAS-AC uses Fountoukis and Nenes (2005) aerosol activation for liquid clouds, and has an option for either Liu and Penner (2005) or Barahona and Nenes (2008, 2009) aerosol activation for ice clouds. Aerosol loading (on-line or climatological) comes from GOCART, with an assumed log-normal size distribution. Other features of McRAS-AC are level-by-level cloud-scale thermodynamics, and Seifert-Beheng (2001)-type precipitation microphysics, particularly from moist convection. Results from Single-Column Model simulations will be shown to demonstrate how cloud radiative properties, lifetimes, and precipitation are influenced by different parameterization assumptions. Corresponding fields from year-long simulations of the full AGCM will also be presented with geographical distributions of cloud effective particle sizes compared to satellite retrievals. While the primary emphasis will be on current climate, simulation results with perturbed aerosol loadings will also be shown to expose the radiative sensitivity of the microphysical parameterization

Radiative Impacts of Cloud Heterogeneity and Overlap in an Atmospheric General Circulation Model

The radiative impacts of introducing horizontal heterogeneity of layer cloud condensate, and vertical overlap of condensate and cloud fraction are examined with the aid of a new radiation package operating in the GEOS-5 Atmospheric General Circulation Model. The impacts are examined in terms of diagnostic top-of-the-atmosphere shortwave (SW) and longwave (LW) cloud radiative effect (CRE) calculations for a range of assumptions and parameter specifications about the overlap. The investigation is conducted for two distinct cloud schemes, the one that comes with the standard GEOS-5 distribution, and another which has been recently used experimentally for its enhanced GEOS-5 distribution, and another which has been recently used experimentally for its enhanced cloud microphysical capabilities; both are coupled to a cloud generator allowing arbitrary cloud overlap specification. We find that cloud overlap radiative impacts are significantly stronger for the operational cloud scheme for which a change of cloud fraction overlap from maximum-random to generalized results to global changes of SW and LW CRE of approximately 4 Watts per square meter, and zonal changes of up to approximately 10 Watts per square meter. This is because of fewer occurrences compared to the other scheme of large layer cloud fractions and of multi-layer situations with large numbers of atmospheric being simultaneously cloudy, conditions that make overlap details more important. The impact on CRE of the details of condensate distribution overlap is much weaker. Once generalized overlap is adopted, both cloud schemes are only modestly sensitive to the exact values of the overlap parameters. We also find that if one of the CRE components is overestimated and the other underestimated, both cannot be driven towards observed values by adjustments to cloud condensate heterogeneity and overlap alone

Sensitivity of Cirrus and Mixed-phase Clouds to the Ice Nuclei Spectra in McRAS-AC: Single Column Model Simulations

The salient features of mixed-phase and ice clouds in a GCM cloud scheme are examined using the ice formation parameterizations of Liu and Penner (LP) and Barahona and Nenes (BN). The performance of LP and BN ice nucleation parameterizations were assessed in the GEOS-5 AGCM using the McRAS-AC cloud microphysics framework in single column mode. Four dimensional assimilated data from the intensive observation period of ARM TWP-ICE campaign was used to drive the fluxes and lateral forcing. Simulation experiments where established to test the impact of each parameterization in the resulting cloud fields. Three commonly used IN spectra were utilized in the BN parameterization to described the availability of IN for heterogeneous ice nucleation. The results show large similarities in the cirrus cloud regime between all the schemes tested, in which ice crystal concentrations were within a factor of 10 regardless of the parameterization used. In mixed-phase clouds there are some persistent differences in cloud particle number concentration and size, as well as in cloud fraction, ice water mixing ratio, and ice water path. Contact freezing in the simulated mixed-phase clouds contributed to transfer liquid to ice efficiently, so that on average, the clouds were fully glaciated at T approximately 260K, irrespective of the ice nucleation parameterization used. Comparison of simulated ice water path to available satellite derived observations were also performed, finding that all the schemes tested with the BN parameterization predicted 20 average values of IWP within plus or minus 15% of the observations

Performance of McRAS-AC in the GEOS-5 AGCM: aerosol-cloud-microphysics, precipitation, cloud radiative effects, and circulation

A revised version of the Microphysics of clouds with Relaxed Arakawa-Schubert and Aerosol-Cloud interaction scheme (McRAS-AC) including, among others, a new ice nucleation parameterization, is implemented in the GEOS-5 AGCM. Various fields from a 10-yr-long integration of the AGCM with McRAS-AC are compared with their counterparts from an integration of the baseline GEOS-5 AGCM, as well as satellite observations. Generally McRAS-AC simulations have smaller biases in cloud fields and cloud radiative effects over most of the regions of the Earth than the baseline GEOS-5 AGCM. Two systematic biases are identified in the McRAS-AC runs: one is underestimation of cloud particle numbers around 40° S–60° S, and one is overestimate of cloud water path during the Northern Hemisphere summer over the Gulf Stream and North Pacific. Sensitivity tests show that these biases potentially originate from biases in the aerosol input. The first bias is largely eliminated in a test run using 50% smaller radius of sea-salt aerosol particles, while the second bias is substantially reduced when interactive aerosol chemistry is turned on. The main weakness of McRAS-AC is the dearth of low-level marine stratus clouds, a probable outcome of lack of explicit dry-convection in the cloud scheme. Nevertheless, McRAS-AC largely simulates realistic clouds and their optical properties that can be improved further with better aerosol input. An assessment using the COSP simulator in a 1-yr integration provides additional perspectives for understanding cloud optical property differences between the baseline and McRAS-AC simulations and biases against satellite data. Overall, McRAS-AC physically couples aerosols, the microphysics and macrophysics of clouds, and their radiative effects and thereby has better potential to be a valuable tool for climate modeling research

A Novel Method for Estimating Shortwave Direct Radiative Effect of Above-Cloud Aerosols Using CALIOP and MODIS Data

This paper describes an efficient and unique method for computing the shortwave direct radiative effect (DRE) of aerosol residing above low-level liquid-phase clouds using CALIOP and MODIS data. It accounts for the overlapping of aerosol and cloud rigorously by utilizing the joint histogram of cloud optical depth and cloud top pressure. Effects of sub-grid scale cloud and aerosol variations on DRE are accounted for. It is computationally efficient through using grid-level cloud and aerosol statistics, instead of pixel-level products, and a pre-computed look-up table in radiative transfer calculations. We verified that for smoke over the southeast Atlantic Ocean the method yields a seasonal mean instantaneous shortwave DRE that generally agrees with more rigorous pixel-level computation within 4. We have also computed the annual mean instantaneous shortwave DRE of light-absorbing aerosols (i.e., smoke and polluted dust) over global ocean based on 4 yr of CALIOP and MODIS data. We found that the variability of the annual mean shortwave DRE of above-cloud light-absorbing aerosol is mainly driven by the optical depth of the underlying clouds

Modeling the Influences of Aerosols on Pre-Monsoon Circulation and Rainfall over Southeast Asia

We conduct several sets of simulations with a version of NASA's Goddard Earth Observing System, version 5, (GEOS-5) Atmospheric Global Climate Model (AGCM) equipped with a two-moment cloud microphysical scheme to understand the role of biomass burning aerosol (BBA) emissions in Southeast Asia (SEA) in the pre-monsoon period of February-May. Our experiments are designed so that both direct and indirect aerosol effects can be evaluated. For climatologically prescribed monthly sea surface temperatures, we conduct sets of model integrations with and without biomass burning emissions in the area of peak burning activity, and with direct aerosol radiative effects either active or inactive. Taking appropriate differences between AGCM experiment sets, we find that BBA affects liquid clouds in statistically significantly ways, increasing cloud droplet number concentrations, decreasing droplet effective radii (i.e., a classic aerosol indirect effect), and locally suppressing precipitation due to a deceleration of the autoconversion process, with the latter effect apparently also leading to cloud condensate increases. Geographical re-arrangements of precipitation patterns, with precipitation increases downwind of aerosol sources are also seen, most likely because of advection of weakly precipitating cloud fields. Somewhat unexpectedly, the change in cloud radiative effect (cloud forcing) at surface is in the direction of lesser cooling because of decreases in cloud fraction. Overall, however, because of direct radiative effect contributions, aerosols exert a net negative forcing at both the top of the atmosphere and, perhaps most importantly, the surface, where decreased evaporation triggers feedbacks that further reduce precipitation. Invoking the approximation that direct and indirect aerosol effects are additive, we estimate that the overall precipitation reduction is about 40% due to the direct effects of absorbing aerosols, which stabilize the atmosphere and reduce surface latent heat fluxes via cooler land surface temperatures. Further refinements of our two-moment cloud microphysics scheme are needed for a more complete examination of the role of aerosol-convection interactions in the seasonal development of the SEA monsoon