Yi-Hui Wang

Considering the radiative effects of snow on tropical Pacific Ocean radiative heating profiles in contemporary GCMs using A‐Train observations

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-GASSmodel 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.

The Impacts of Precipitating Hydrometeors Radiative Effects on Land Surface Temperature in Contemporary GCMs using Satellite Observations

An accurate representation of the land surface temperature (LST) climatology of the coupled land-atmosphere system has strong implications for the reliability of projected land surface processes and their variability inferred by the global climate models (GCMs) contributed to the Intergovernmental Panel on Climate Change CMIP5. We have identified a substantial underestimation of the total ice water path and biases of surface radiation budget commonly seen in the CMIP models which are highly correlated to the biases of LST over land. One of the potential causes of the CMIP model biases is the missing representation of large frozen precipitating hydrometeors and their radiative effects (i.e., snow) in all CMIP3 and most CMIP5 models. We examine the impacts of snow on the radiation, all-sky and clear-sky LST, and air-land heat fluxes to explore the implications to the common biases in CMIP models by performing sensitivity experiments with and without snow radiation effects using the National Center for Atmospheric Research Community Earth System Model version 1. It is found that an exclusion of the snow radiative effects the CESM1 generates the LST biases (up to 2–3 K) in the midlatitude and high latitude, in particular, in December, January, and February (DJF). All-sky and clear-sky LST in model simulations are found to be too cold and are mainly due to underestimated downward surface (longwave) LW radiation in DJF, which is consistent with those in CMIP models. The correlation between the changes of the LST and downward surface LW radiation is very high both in summer and winter seasons.

The Impacts of Precipitating Cloud Radiative Effects on Ocean Surface Evaporation, Precipitation, and Ocean Salinity in Coupled GCM Simulations

The coupled global climate model (GCM) fidelity in representing upper ocean salinity including near sea surface bulk salinity (SSS) is evaluated in this study, with a focus on the Pacific Ocean. The systematic biases in ocean surface evaporation (E) minus precipitation (P) and SSS are found to be fairly similar in the twentieth century simulations of the Coupled Model Intercomparison Phase 3 (CMIP3) and Phase 5 (CMIP5) relative to the observations. One of the potential causes of the CMIP model biases is the missing representation of the radiative effects of precipitating hydrometeors (i.e., snow) in most CMIP models. To examine the radiative effect of cloud snow on SSS, sensitivity experiments with and without such effect are conducted by the National Center for Atmospheric Research-coupled Community Earth System Model (CESM). This study investigates the difference in SSS between sensitivity experiments and its relationship with atmospheric circulation, E - P and air-sea heat fluxes. It is found that the exclusion of the cloud snow radiative effect in CESM produces weaker Pacific trade winds, resulting in enhanced precipitation, reduced evaporation, and a reduction of the upper ocean salinity in the tropical and subtropical Pacific. The latter results in an improved comparison with climatological upper ocean bulk salinity. The introduction of cloud snow also altered the budget terms that maintain the time-mean salinity in the mixed layer.

The Impacts of Bias in Cloud‐Radiation‐Dynamics Interactions on Central Pacific Seasonal and El Niño Simulations in Contemporary GCMs

Most of the global climate models (GCMs) in the Coupled Model Intercomparison Project, phase 5 do not include precipitating ice (aka falling snow) in their radiation calculations. We examine the importance of the radiative effects of precipitating ice on simulated surface wind stress and sea surface temperatures (SSTs) in terms of seasonal variation and in the evolution of central Pacific El Nino (CP‐El Nino) events. Using controlled simulations with the CESM1 model, we show that the exclusion of precipitating ice radiative effects generates a persistent excessive upper‐level radiative cooling and an increasingly unstable atmosphere over convective regions such as the western Pacific and tropical convergence zones. The invigorated convection leads to persistent anomalous low‐level outflows which weaken the easterly trade winds, reducing upper‐ocean mixing and leading to a positive SST bias in the model mean state. In CP‐El Nino events, this means that outflow from the modeled convection in the central Pacific reduces winds to the east, allowing unrealistic eastward propagation of warm SST anomalies following the peak in CP‐El Nino activity. Including the radiative effects of precipitating ice reduces these model biases and improves the simulated life cycle of the CP‐El Nino. Improved simulations of present‐day tropical seasonal variations and CP‐El Nino events would increase the confidence in simulating their future behavior.

Assessing the radiative impacts of precipitating clouds on winter surface air temperatures and land surface properties in general circulation models using observations

Using CloudSat-CALIPSO ice water, cloud fraction, and radiation; Clouds and the Earths Radiant Energy System (CERES) radiation; and long-term station-measured surface air temperature (SAT), we identified a substantial underestimation of the total ice water path, total cloud fraction, land surface radiative flux, land surface temperature (LST), and SAT during Northern Hemisphere winter in Coupled Model Intercomparison Project Phase 5 (CMIP5) models. We perform sensitivity experiments with the National Center for Atmospheric Research (NCAR) Community Earth System Model version 1 (CESM1) in fully coupled modes to identify processes driving these biases. We found that biases in land surface properties are associated with the exclusion of downwelling longwave heating from precipitating ice during Northern Hemisphere winter. The land surface temperature biases introduced by the exclusion of precipitating ice radiative effects in CESM1 and CMIP5 both spatially correlate with winter biases over Eurasia and North America. The underestimated precipitating ice radiative effect leads to colder LST, associated surface energy-budget adjustments, and cooler SAT. This bias also shifts regional soil moisture state from liquid to frozen, increases snow cover, and depresses evapotranspiration (ET) and total leaf area index in Northern Hemisphere winter. The inclusion of the precipitating ice radiative effects largely reduces the model biases of surface radiative fluxes (more than 15 W m−2), SAT (up to 2–4 K), and snow cover and ET (25–30%), compared with those without snow-radiative effects.