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

Abstract:

An accurate representation of the land surface temperature (LST) climatology of the coupled land-atmosphere system in global climate models (GCMs) has strong implications for the reliability of projected LST and temperature variability inferred by these models. We have identified a substantial underestimation of the total ice water path (TIWP) and biases of surface radiation budget commonly seen in the CMIP models which are highly correlated to the bias of LST over land. One of the potential causes of the CMIP model biases is the missing representation of large frozen precipitating hydrometeors (i.e., snow) in all CMIP3 and most CMIP5 models.

We examine the impacts of snow on the radiation, LST, air-land heat fluxes to explore the implications to the common biases in CMIP models using the National Center for Atmospheric Research (NCAR)-coupled Community Earth System Model (CESM) to perform sensitivity experiments with and without snow radiation effects. It is found that an inclusion of the snow-radiative effects in CESM notably reduces the LST biases (up to 2-3 K) in the mid- and high-latitude, in particular, in boreal winter seasons. It is found that without the snow-radiation effects in the CESM, the model simulates too cold LST associated with underestimated downward surface LW radiation for all seasons but too warm LST associated with excessive SW surface radiative fluxes in summer seasons, consistent with those in CMIP models. The changes of the LST, however, cannot be explained by the differences in surface sensible and evaporative heat fluxes.