614 Evaluation of Regional Climate Downscaling in the Tropics

Tuesday, 24 January 2017
4E (Washington State Convention Center )
Ricardo Morais Fonseca, Luleå University, Kiruna, Sweden; and T. Zhang and T. Y. Koh

Handout (3.4 MB)

The successful modelling of the observed precipitation continues to be one of the major challenges atmospheric scientists face today. When the Weather Research and Forecasting (WRF) model is used to dynamically downscale the Climate Forecast System Reanalysis (CFSR) in the tropics it is found to overestimate the observed rainfall, as given by the Tropical Rainfall Measuring Mission (TRMM), with this excessive precipitation generated mainly by the cumulus scheme, Betts-Miller-Janjic (BMJ). An adjustment of the scheme such that the humidity reference profile is more moist is adopted based on sensitivity test results and thermodynamical reasoning. The adjusted scheme is found to give much better estimates of the observed precipitation for the global tropics over both monsoon seasons. In fact, in some regions the model even outperforms CFSR. The advantage of modifying the BMJ scheme to produce better rainfall estimates lies in the final dynamical consistency of the rainfall with other dynamical and thermodynamical variables of the atmosphere.

Despite this improvement, there are large biases in the surface radiation fluxes as the cumulus clouds are not modelled in the BMJ cumulus rainfall scheme so that the surface temperature remains too warm during rainfall. Given the importance of the cumulus cloud feedback to radiation at regional and weather and climate scales, we further developed a deep convective cloud scheme for the BMJ scheme that is general and can be applied to other cumulus schemes that do not parameterize clouds. We represent the convective cloud fraction as a function of the precipitation. The phase of the cloud condensate depends simply on the ambient air temperature. When this scheme is implemented in WRF the model is found to give a much better representation of the cloudiness with smaller biases in the surface radiation fields with respect to observations and re-analyses.

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