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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.

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We evaluate the simulations of surface wind stress (TAU) and sea surface temperature (SST) over subtropical and tropical Pacific and Atlantic oceans in subsets of CMIP6 models that are categorized by frozen hydrometeors-radiation interactions. The CMIP6 models are divided into two subsets with combined (SON1) and separated (SON2) radiative properties of cloud ice and falling ice (snow) and compared to the set with cloud ice radiative effects only (NOS). There is evidence that these hydrometeors-radiation interaction treatments induce different atmospheric dynamic responses that influence the surface properties. Excessive westerly TAU and meridional TAU divergence away from convective zones are reduced significantly in SON1 and SON2 relative to NOS against QuikSCAT observations; while the differences between SON2 and SON1 are small. SON2 reduces cold SST biases over north oceans and equatorial zones drastically (1 to 2 K), and warm biases (up to 1K) off the coasts of America and zonal TAU biases are reduced relative to NOS. Unlike SON2, SON1 improves SSTs mainly over south of Pacific Ocean and limited areas over the tropical belts relative to NOS although TAU is reduced drastically as in SON2, implying that other factors play a role in degrading the SST simulations in SON1 relative to SON2. SON2 outperforms NOS and SON1 in the seasonal cycles of SST mean biases and mean absolute biases averaged over the equatorial area, north ocean, and South Pacific against ERSST observations. Despite the significant improvements in TAU and SST simulations, SON2 models still exhibit non-trivial biases over south and north flanks of equatorial zones. These results suggest that there are direct linkages of TAU with SST changes resulting from the hydrometeors-radiation interactions in SON2, but not in SON1, relative to NOS, implying that a separated treatment of cloud ice and falling ice radiative properties in climate models is preferred.