Scale-Aware and Definition-Aware Evaluation of Modeled Near-Surface Precipitation Frequency Using CloudSat Observations
It has long been stated that precipitation is too frequent in climate models as compared to observations. But most satellite-based observational datasets of precipitation, like TRMM 3B42 and GPCP (the only ones that provide broad coverage) do not include measurements sensitive to light precipitation, which dominates precipitation frequency. In this study, we introduce a forward model from CESM to CloudSat observations. Unlike other satellites, CloudSat is sensitive to light precipitation, but due to its sampling and saturation characteristics, it is not incorporated into most precipitation observational datasets. We show that when compared against this dataset which is state-of-the-art for light precipitation frequency, CESM precipitation is far to frequent at all latitudes. The bias is not ameliorated when appropriately compared to more accurate observations.