Jui-Lin Frank Li

JPL/California Institute of Technology

Conventional GCMs, including all CMIP3 and most CMIP5 models, consider radiation interactions only with small-particle/suspended cloud mass, ignoring large-particle/falling and convective core cloud mass, but constraints on models’ global radiation balance, clouds and related quantities are made with measurements sensitive to the broader range of hydrometeors[Li et al., 2008; 2011; 2012, Waliser et al., 2008].  We have found that this might lead to persistent systematic biases that include the overestimation of downward shortwave at the surface (DSWS) and outgoing longwave (OLR) at the top of the atmosphere (TOA) as well as the underestimation of longwave at the surface (DLWS) in the precipitating and convectively active regions in conjunction with significant underestimate of the amount of cloud water content [Li et al., 2013a; Waliser et al., 2011]. This mismatch between the satellite-based and model representations of cloud and radiation fields may lead to systematic biases in the models’ climates and their climate change projections [Li et al., 2013c].

In order to explore and characterize radiation impacts of precipitating (i.e. snow/rain), we use ECMWF IFS (atmospheric model only) [Li et al., 2013d], NCAR CAM5 (atmospheric model only) and NCAR-CESM1 (fully coupled) to conduct several sensitivity experiments by turning off the radiation interaction with large-particle ice mass (i.e. snow) [Li et al., 2013c]. These tests, both the coupled and uncoupled, indicate a consistent impact associated with the exclusion of precipitating and/or convective hydrometeors including more DSWS, OLR and less DLWS with over strongly precipitating regions such as ITCZ, Warm Pool, SPCZ and the mid-latitude storm tracks and Southern Ocean. For the fully coupled NCAR CESM1, with historical CMIP5 configuration, the long term mean (60 years out of a 140-year run) exhibits many persistent impacts associated with the exclusion of snow hydrometeors that are consistent with that in CMIP3/CMIP5 such as warmer SSTs.  In addition, the differences in the wind stress climatologies in NCAR CESM1 are consistent with that found in CMIP models [Li et al., 2013c].

These biases have important implications to the simulation of ocean circulations and various modes of climate variability originating in the tropics. In particular, the differences in the wind stress climatologies not only have impacts on the simulated ocean circulation and climate variability, but other air-sea fluxes as well.