Improvements to a Low-Latency, GPM-Ready Rainfall Rate Algorithm

Monday, 15 December 2014
Yan Hao1, Robert Joseph Kuligowski2 and Yaping Li1, (1)IMSG, College Park, MD, United States, (2)NOAA College Park, College Park, MD, United States
The GOES-R Rainfall Rate algorithm, which is also called SCaMPR (Self-Calibrating Multivariate Precipitation Retrieval), is an effort to combine the relative strengths of infrared (IR)-based and microwave (MW)-based estimates of precipitation. SCaMPR will use the merged MW rain rate retrievals from GPM as its new calibration standard, and this algorithm allows GPM data to be used in an operational forecasting environment because of its much shorter latency (minutes) relative to the NASA Integrated MultisatellitE Retrievals for GPM (iMERG) products.

Recent algorithm modifications include adding rainfall to warm pixels where neither IR nor MW would normally detect rainfall; employing a relative humidity (RH) correction for sub-cloud evaporation; correcting for thermodynamic profile effects using the computed convective equivalent level (EL) temperature and .employing smaller calibration regions for more localized and more accurate calibration.

This presentation will describe the basic GOES-R rainfall rate algorithm as well as its recent improvements and will compare its performance with the current operational GOES algorithm.