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Anthony D. Del Genio, Yonghua Chen, Daehyun Kim, and Mao-Sung Yao
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Anthony D. Del Genio, William Kovari, Mao-Sung Yao, and Jeffrey Jonas

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Precipitation processes in convective storms are potentially a major regulator of cloud feedback. An unresolved issue is how the partitioning of convective condensate between precipitation-size particles that fall out of updrafts and smaller particles that are detrained to form anvil clouds will change as the climate warms. Tropical Rainfall Measuring Mission (TRMM) observations of tropical oceanic convective storms indicate higher precipitation efficiency at warmer sea surface temperature (SST) but also suggest that cumulus anvil sizes, albedos, and ice water paths become insensitive to warming at high temperatures. International Satellite Cloud Climatology Project (ISCCP) data show that instantaneous cirrus and deep convective cloud fractions are positively correlated and increase with SST except at the highest temperatures, but are sensitive to variations in large-scale vertical velocity. A simple conceptual model based on a Marshall–Palmer drop size distribution, empirical terminal velocity–particle size relationships, and assumed cumulus updraft speeds reproduces the observed tendency for detrained condensate to approach a limiting value at high SST. These results suggest that the climatic behavior of observed tropical convective clouds is intermediate between the extremes required to support the thermostat and adaptive iris hypotheses.

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Anthony D. Del Genio, Yonghua Chen, Daehyun Kim, and Mao-Sung Yao

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The relationship between convective penetration depth and tropospheric humidity is central to recent theories of the Madden–Julian oscillation (MJO). It has been suggested that general circulation models (GCMs) poorly simulate the MJO because they fail to gradually moisten the troposphere by shallow convection and simulate a slow transition to deep convection. CloudSat and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are analyzed to document the variability of convection depth and its relation to water vapor during the MJO transition from shallow to deep convection and to constrain GCM cumulus parameterizations. Composites of cloud occurrence for 10 MJO events show the following anticipated MJO cloud structure: shallow and congestus clouds in advance of the peak, deep clouds near the peak, and upper-level anvils after the peak. Cirrus clouds are also frequent in advance of the peak. The Advanced Microwave Scanning Radiometer for Earth Observing System (EOS) (AMSR-E) column water vapor (CWV) increases by ~5 mm during the shallow–deep transition phase, consistent with the idea of moisture preconditioning. Echo-top height of clouds rooted in the boundary layer increases sharply with CWV, with large variability in depth when CWV is between ~46 and 68 mm. International Satellite Cloud Climatology Project cloud classifications reproduce these climatological relationships but correctly identify congestus-dominated scenes only about half the time. A version of the Goddard Institute for Space Studies Model E2 (GISS-E2) GCM with strengthened entrainment and rain evaporation that produces MJO-like variability also reproduces the shallow–deep convection transition, including the large variability of cloud-top height at intermediate CWV values. The variability is due to small grid-scale relative humidity and lapse rate anomalies for similar values of CWV.

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Anthony D. Del Genio, Mao-Sung Yao, William Kovari, and Kenneth K-W. Lo

Abstract

An efficient new prognostic cloud water parameterization designed for use in global climate models is described. The scheme allows for life cycle effects in stratiform clouds and permits cloud optical properties to be determined interactively. The parameterization contains representations of all important microphysical processes, including autoconversion, accretion, Bergeron–Findeisen diffusional growth, and cloud/rain water evaporation. Small-scale dynamical processes, including detrainment of convective condensate, cloud-top entrainment instability, and stability-dependent cloud physical thickness variations, are also taken into account. Cloud optical thickness is calculated from the predicted liquid/ice water path and a variable droplet effective radius estimated by assuming constant droplet number concentration. Microphysical and radiative properties are assumed to be different for liquid and ice clouds, and for liquid clouds over land and ocean.

The parameterization is validated in several simulations using the Goddard Institute for Space Studies (GISS) general circulation model (GCM). Comparisons are made with a variety of datasets, including ERBE radiative fluxes and cloud forcing, ISCCP and surface-observed cloud properties, SSM/I liquid water path, and SAGE II thin cirrus cover. Validation is judged on the basis of the model's depiction of both the mean state; diurnal, seasonal, and interannual variability; and the temperature dependence of cloud properties. Relative to the diagnostic cloud scheme used in the previous GISS GCM, the prognostic parameterization strengthens the model's hydrologic cycle and general circulation, both directly and indirectly (via increased cumulus heating). Sea surface temperature (SST) perturbation experiments produce low climate sensitivity and slightly negative cloud feedback for globally uniform SST changes, but high sensitivity and positive cloud feedback when tropical Pacific SST gradients weaken with warming. Changes in the extent and optical thickness of tropical cumulus anvils appear to be the primary factor determining the sensitivity. This suggests that correct simulations of upward transport of convective condensate and of Walker circulation changes are of the highest priority for a realistic estimate of cloud feedback in actual greenhouse gas increase scenarios.

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Wei-Chyung Wang, William B. Rossow, Mao-Sung Yao, and Marilyn Wolfson

Abstract

We illustrate the potential complexity of the feedback between global mean cloud amount and global mean surface temperature when variations of the vertical cloud distribution are included by studying the behavior of a one-dimensional radiative–convective model with two types of cloud variation: 1) variable cloud cover with constant optical thickness and 2) variable optical thickness with constant cloud cover. The variable parameter is calculated assuming a correlation between cloud amount and precipitation or the vertical flux convergence of latent heat. Since the vertical latent heat flux is taken to be a fraction of the total heat flux, modeled by convective adjustment, we examine the sensitivity of the results to two different critical lapse rates, a constant 6.5 K km−1 lapse rate and a temperature-dependent, moist adiabatic lapse rate. The effects of the vertical structure of climate perturbations on the nature of the cloud feedback are examined using two cases: a 2% increase in the solar constant and a doubling of the atmospheric carbon dioxide concentration. The model results show that changes in the vertical cloud distribution and mean cloud optical thickness can be as important to climate variations as are changes in the total cloud cover. Further the variety and complexity of the feedbacks exhibited even by this simple model suggest that proper determination of cloud feedbacks must include the effects of varying vertical distribution.

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Anthony D. Del Genio, Jingbo Wu, Audrey B. Wolf, Yonghua Chen, Mao-Sung Yao, and Daehyun Kim

Abstract

Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden–Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

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George Tselioudis, Anthony D. DelGenio, William Kovari Jr., and Mao-Sung Yao

Abstract

A current-climate simulation of the Goddard Institute for Space Studies (GISS) GCM, which includes interactive cloud optical properties that depend on the predicted cloud water content, is analyzed to document the variations of low cloud optical thickness with temperature in the model atmosphere. It is found that low cloud optical thickness decreases with temperature in the warm subtropical and tropical latitudes and increases with temperature in the cold midlatitude regions. This behavior is in agreement with the results of two observational studies that analyzed satellite data from the International Satellite Cloud Climatology Project and Special Sensor Microwave/Imager datasets. The increase of low cloud optical thickness with temperature in the midlatitudes is due to vertical extent and cloud water increases, whereas the decrease with temperature in the warm latitudes is due to decreases in cloud water content and happens despite increases in cloud vertical extent. The cloud processes that produce the cloud property changes in the model also vary with latitude. In the midlatitude regions relative-humidity-induced increases of cloud vertical extent with temperature dominate, whereas in the Tropics increases in cloud-top entrainment and precipitation with temperature produce decreases of cloud water content, whose effect on optical thickness outweighs the effect of entrainment-induced increases of cloud vertical extent with temperature. Doubled-CO2 simulations with the GISS GCM suggest that even though low cloud optical thickness changes have little effect on the global climate sensitivity of the model, they redistribute the temperature change and reduce the high-latitude amplification of the greenhouse warming. It is also found that the current-climate variations of low cloud optical thickness with temperature reproduce qualitatively but overestimate quantitatively the changes in optical thickness with climate warming.

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Daehyun Kim, Adam H. Sobel, Anthony D. Del Genio, Yonghua Chen, Suzana J. Camargo, Mao-Sung Yao, Maxwell Kelley, and Larissa Nazarenko

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The tropical subseasonal variability simulated by the Goddard Institute for Space Studies general circulation model, Model E2, is examined. Several versions of Model E2 were developed with changes to the convective parameterization in order to improve the simulation of the Madden–Julian oscillation (MJO). When the convective scheme is modified to have a greater fractional entrainment rate, Model E2 is able to simulate MJO-like disturbances with proper spatial and temporal scales. Increasing the rate of rain reevaporation has additional positive impacts on the simulated MJO. The improvement in MJO simulation comes at the cost of increased biases in the mean state, consistent in structure and amplitude with those found in other GCMs when tuned to have a stronger MJO. By reinitializing a relatively poor-MJO version with restart files from a relatively better-MJO version, a series of 30-day integrations is constructed to examine the impacts of the parameterization changes on the organization of tropical convection. The poor-MJO version with smaller entrainment rate has a tendency to allow convection to be activated over a broader area and to reduce the contrast between dry and wet regimes so that tropical convection becomes less organized. Besides the MJO, the number of tropical-cyclone-like vortices simulated by the model is also affected by changes in the convection scheme. The model simulates a smaller number of such storms globally with a larger entrainment rate, while the number increases significantly with a greater rain reevaporation rate.

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Gavin A. Schmidt, Reto Ruedy, James E. Hansen, Igor Aleinov, Nadine Bell, Mike Bauer, Susanne Bauer, Brian Cairns, Vittorio Canuto, Ye Cheng, Anthony Del Genio, Greg Faluvegi, Andrew D. Friend, Tim M. Hall, Yongyun Hu, Max Kelley, Nancy Y. Kiang, Dorothy Koch, Andy A. Lacis, Jean Lerner, Ken K. Lo, Ron L. Miller, Larissa Nazarenko, Valdar Oinas, Jan Perlwitz, Judith Perlwitz, David Rind, Anastasia Romanou, Gary L. Russell, Makiko Sato, Drew T. Shindell, Peter H. Stone, Shan Sun, Nick Tausnev, Duane Thresher, and Mao-Sung Yao

Abstract

A full description of the ModelE version of the Goddard Institute for Space Studies (GISS) atmospheric general circulation model (GCM) and results are presented for present-day climate simulations (ca. 1979). This version is a complete rewrite of previous models incorporating numerous improvements in basic physics, the stratospheric circulation, and forcing fields. Notable changes include the following: the model top is now above the stratopause, the number of vertical layers has increased, a new cloud microphysical scheme is used, vegetation biophysics now incorporates a sensitivity to humidity, atmospheric turbulence is calculated over the whole column, and new land snow and lake schemes are introduced. The performance of the model using three configurations with different horizontal and vertical resolutions is compared to quality-controlled in situ data, remotely sensed and reanalysis products. Overall, significant improvements over previous models are seen, particularly in upper-atmosphere temperatures and winds, cloud heights, precipitation, and sea level pressure. Data–model comparisons continue, however, to highlight persistent problems in the marine stratocumulus regions.

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