[1] We perform an observationally based evaluation of the cloud ice water content (CIWC) and path (CIWP) of present-day GCMs, notably 20th century CMIP5 simulations, and compare these results to CMIP3 and two recent reanalyses. We use three different CloudSat + CALIPSO ice water products and two methods to remove the contribution from the convective core ice mass and/or precipitating cloud hydrometeors with variable sizes and falling speeds so that a robust observational estimate can be obtained for model evaluations. The results show that for annual mean CIWP, there are factors of 2-10 in the differences between observations and models for a majority of the GCMs and for a number of regions. However, there are a number of CMIP5 models, including CNRM-CM5, MRI, CCSM4 and CanESM2, as well as the UCLA CGCM, that perform well compared to our past evaluations. Systematic biases in CIWC vertical structure occur below the mid-troposphere where the models overestimate CIWC, with this bias arising mostly from the extratropics. The tropics are marked by model differences in the level of maximum CIWC ($250-550 hPa). Based on a number of metrics, the ensemble behavior of CMIP5 has improved considerably relative to CMIP3, although neither the CMIP5 ensemble mean nor any individual model performs particularly well, and there are still a number of models that exhibit very large biases despite the availability of relevant observations. The implications of these results on model representations of the Earth radiation balance are discussed, along with caveats and uncertainties associated with the observational estimates, model and observation representations of the precipitating and cloudy ice components, relevant physical processes and parameterizations. F., et al. (2012), An observationally based evaluation of cloud ice water in CMIP3 and CMIP5 GCMs and contemporary reanalyses using contemporary satellite data,

[1] We evaluate the annual mean radiative shortwave flux downward at the surface (RSDS) and reflected shortwave (RSUT) and radiative longwave flux upward at top of atmosphere (RLUT) from the twentieth century Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 3 (CMIP3) simulations as well as from the NASA GEOS5 model and Modern-Era Retrospective Analysis for Research and Applications analysis. The results show that a majority of the models have significant regional biases in the annual means of RSDS, RLUT, and RSUT, with biases from À30 to 30 W m À2. While the global average CMIP5 ensemble mean biases of RSDS, RLUT, and RSUT are reduced compared to CMIP3 by about 32% (e.g., À6.9 to 2.5 W m À2 ), 43%, and 56%, respectively. This reduction arises from a more complete cancellation of the pervasive negative biases over ocean and newly larger positive biases over land. In fact, based on these biases in the annual mean, Taylor diagram metrics, and RMSE, there is virtually no progress in the simulation fidelity of RSDS, RLUT, and RSUT fluxes from CMIP3 to CMIP5. A persistent systematic bias in CMIP3 and CMIP5 is the underestimation of RSUT and overestimation of RSDS and RLUT in the convectively active regions of the tropics. The amount of total ice and liquid atmospheric water content in these areas is also underestimated. We hypothesize that at least a part of these persistent biases stem from the common global climate model practice of ignoring the effects of precipitating and/or convective core ice and liquid in their radiation calculations.

We take advantage of climate simulations from two multimodel experiments to characterize and evaluate the cloud phase partitioning in 16 general circulation models (GCMs), specifically the vertical structure of the transition between liquid and ice in clouds. We base our analysis on the ratio of ice condensates to the total condensates (phase ratio, PR). Its transition at 90% (PR90) and its links with other relevant variables are evaluated using the GCM-Oriented Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation Cloud Product climatology, reanalysis data, and other satellite observations. In 13 of 16 models, the PR90 transition height occurs too low (6 km to 8.4 km) and at temperatures too warm (À13.9°C to À32.5°C) compared to observations (8.6 km, À33.7°C); features consistent with a lack of supercooled liquid with respect to ice above 6.5 km. However, this bias would be slightly reduced by using the lidar simulator. In convective regimes (more humid air and precipitation), the observed cloud phase transition occurs at a warmer temperature than for subsidence regimes (less humid air and precipitation). Only few models manage to roughly replicate the observed correlations with humidity (5/16), vertical velocity (5/16), and precipitation (4/16); 3/16 perform well for all these parameters (MPI-ESM, NCAR-CAM5, and NCHU). Using an observation-based Clausius-Clapeyron phase diagram, we illustrate that the Bergeron-Findeisen process is a necessary condition for models to represent the observed features. Finally, the best models are those that include more complex microphysics.

Conventional global climate models (GCMs) often consider radiation interactions only with small-particle/suspended cloud mass, ignoring large-particle/falling and convective core cloud mass. We characterize the radiation and atmospheric circulation impacts of frozen precipitating hydrometeors (i.e., snow), using the National Center for Atmospheric Research coupled GCM, by conducting sensitivity experiments that turn off the radiation interaction with snow. The changes associated with the exclusion of precipitating hydrometeors exhibit a number differences consistent with biases in CMIP3 and CMIP5 (Coupled Model Intercomparison Project Phase 3 and Phase 5), including more outgoing longwave flux at the top of atmosphere and downward shortwave flux at the surface in the heavily precipitating regions. Neglecting the radiation interaction of snow increases the net radiative cooling near the cloud top with the resulting increased instability triggering more convection in the heavily precipitating regions of the tropics. In addition, the increased differential vertical heating leads to a weakening of the low-level mean flow and an apparent low-level eastward advection from the warm pool resulting in moisture convergence south of the Intertropical Convergence Zone and north of the South Pacific Convergence Zone (SPCZ). This westerly bias, with effective warm and moist air transport, might be a contributing factor in the model's northeastward overextension of the SPCZ and the concomitant changes in sea surface temperatures, upward motion, and precipitation. Broader dynamical impacts include a stronger local meridional overturning circulation over the middle and east Pacific and commensurate changes in low and upper level winds, large-scale ascending motion, with a notable similarity to the systematic bias in this region in CMIP5 upper level zonal winds.

[1] Climate models often ignore the radiative impact of precipitating hydrometeors. CloudSat retrievals provide the first means to distinguish between cloud versus precipitating ice mass and characterize its vertical structure. With this information, radiative transfer calculations are performed to examine the impact of excluding precipitating ice on atmospheric radiative fluxes and heating rates. The preliminary results show that such exclusion can result in underestimates of the reflective shortwave flux at the top of the atmosphere (TOA) and overestimates of the downwelling surface shortwave and emitted TOA longwave flux, with the differences being about 5-10 Wm −2 in the most convective and rainfall intensive areas and greatest for the TOA longwave flux. There are also considerable differences (∼10-25%) in the vertical profiles of shortwave and longwave heating, resulting in an overestimation (∼up to 10%) of the integrated column cooling. The implications of these results are that models that exclude these ice components are achieving TOA radiation balance through compensating errors as well as possibly introducing biases in atmospheric circulations. Citation: Waliser, D. E., J.-L. F. Li, T. S. L'Ecuyer, and W.-T. Chen (2011), The impact of precipitating ice and snow on the radiation balance in global climate models, Geophys. Res. Lett., 38, L06802,

Although it is well established that cirrus warms Earth, the radiative effect of the entire spectrum of ice clouds is not well understood. In this study, the role of all ice clouds in Earth’s radiation budget is investigated by performing radiative transfer modeling using ice cloud properties retrieved from CloudSat and CALIPSO measurements as inputs. Results show that, for the 2008 period, the warming effect (~21.8 ± 5.4 W m−2) induced by ice clouds trapping longwave radiation exceeds their cooling effect (~−16.7 ± 1.7 W m−2) caused by shortwave reflection, resulting in a net warming effect (~5.1 ± 3.8 W m−2) globally on the earth–atmosphere system. The net warming is over 15 W m−2 in the tropical deep convective regions, whereas cooling occurs in the midlatitudes, which is less than 10 W m−2 in magnitude. Seasonal variations of ice cloud radiative effects are evident in the midlatitudes where the net effect changes from warming during winter to cooling during summer, whereas warming occurs all year-round in the tropics. Ice cloud optical depth τ is shown to be an important factor in determining the sign and magnitude of the net radiative effect. Ice clouds with τ < 4.6 display a warming effect with the largest contributions from those with τ ≈ 1.0. In addition, ice clouds cause vertically differential heating and cooling of the atmosphere, particularly with strong heating in the upper troposphere over the tropics. At Earth’s surface, ice clouds produce a cooling effect no matter how small the τ value is.

This study characterizes biases in water vapor, dynamics, shortwave (SW) and longwave (LW) radiative properties in contemporary global climate models (GCMs) against observations over tropical Pacific Ocean. The observations are based on Atmospheric Infrared Sounder for water vapor, CloudSat 2B‐FLXHR‐LIDAR for LW and SW radiative heating profiles, and radiative flux from Clouds and the Earth's Radiant Energy System products. The model radiative heating profiles are adopted from the coupled and uncoupled National Center for Atmospheric Research (NCAR) Community Earth System Model version 1 (CESM1) and joint Year of Tropical Convection (YOTC)/Madden Julian Oscillation (MJO) Task Force‐Global Energy and Water Cycle Experiment Atmospheric System Studies (GASS) Multi‐Model Physical Processes Experiment (YOTC‐GASS). The results from the model evaluation for YOTC‐GASS and NCAR CESM1 demonstrate a number of systematic radiative biases. These biases include excessive outgoing LW radiation and excessive SW surface radiative fluxes, in conjunction with a radiatively unstable atmosphere with excessive LW cooling in the upper troposphere over convectively active areas, such as the Intertropical Convergence Zone/South Pacific Convergence Zone (ITCZ/SPCZ) and warm pool. Using sensitivity experiments with the NCAR‐uncoupled/NCAR‐coupled CESM1, we infer that these biases partly result from the interactions between falling snow and radiation that are missing in most contemporary GCMs (e.g., YOTC‐GASS, Coupled Model Intercomparison Project 3 (CMIP)3, and Atmospheric Model Intercomparison Project 5 (AMIP5)/CMIP5). A number of biases in the YOTC‐GASS model simulations are consistent with model biases in CMIP3, AMIP5/CMIP5, and NCAR‐uncoupled/NCAR‐coupled model simulation without snow‐radiation interactions. These include excessive upper level convection and low level downward motion with outflow from ITCZ/SPCZ. This generates weaker low‐level trade winds and excessive precipitation in the Central Pacific Trade wind regions. The excessive LW radiative cooling in NCAR‐coupled/NCAR‐uncoupled GCM simulations is reduced by 10–20% with snow‐radiative effects considered.

Global weather and climate models often exclude the effects of precipitating hydrometeors and convective core mass on radiative fluxes. In particular, many models split the ice phase into separate "cloud ice" and "snow" categories representing the smaller and larger ice particles, respectively; a separation that is generally not well defined in observations. A version of the European Centre for Medium-Range Weather Forecasts (ECMWF) global numerical weather prediction model which includes the radiative effects of cloud liquid, cloud ice, and precipitating snow is used to investigate the impact of including and excluding the radiative effects of the precipitating snow category. The results show that exclusion of precipitating snow in the radiation calculations leads to differences in the shortwave and longwave radiative fluxes of 5-15 W m À2 in strongly precipitating and convective areas. These differences are of the same order of magnitude as the systematic errors in the model compared to satellite observations. Corresponding biases in the radiative heating profiles are on the order of 0.15 K d À1. The results imply that precipitating snow should be included in the radiative calculations in all weather and climate models in the context of improving model fidelity and reducing compensating errors.