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Recent Improvements to the GOES-R Rainfall Rate Algorithm
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The GOES-R Rainfall Rate algorithm is an effort to combine the relative strengths of infrared (IR)-based and microwave (MW)-based estimates of precipitation. Recent improvements to the algorithm include employing smaller calibration regions for more localized and more accurate calibration; speeding up the calibration code to enable more efficient real-time processing; adding rainfall to warm pixels where neither IR nor MW would normally detect rainfall; employing a relative humidity (RH) correction for subcloud evaporation of hydrometeors; and correcting for thermodynamic profile effects using the computed convective equivalent level (EL) temperature.
This presentation will introduce the basic GOES-R Rainfall Rate algorithm, describe recent improvements and provide the comparisons between the performances of the improved and original algorithms by using a version of the algorithm simplified for the current-generation GOES imager running over the conterminous US.