Rainfall Algorithms Using Oceanic Satellite Observations from MWHS-2

This paper describes three algorithms for retrieving precipitation over oceans from brightness temperatures (TBs) of the Micro-Wave Humidity Sounder-2 (MHWS-2) onboard Fengyun-3C (FY-3C). For algorithm development, scattering-induced TB depressions (Delta TBs) of MWHS-2 at channels between 89 and 190 GHz were collocated to rain rates derived from measurements of the Global Precipitation Measurement's Dual-frequency Precipitation Radar (DPR) for the year 2017. Delta TBs were calculated by subtracting simulated cloud-free TBs from bias-corrected observed TBs for each channel. These Delta TBs were then related to rain rates from DPR using (1) multilinear regression (MLR); the other two algorithms, (2) range searches (RS) and (3) nearest neighbor searches (NNS), are based on k-dimensional trees. While all three algorithms produce instantaneous rain rates, the RS algorithm also provides the probability of precipitation and can be understood in a Bayesian framework. Different combinations of MWHS-2 channels were evaluated using MLR and results suggest that adding 118 GHz improves retrieval performance. The optimal combination of channels excludes high-peaking channels but includes 118 GHz channels peaking in the mid and high troposphere. MWHS-2 observations from another year were used for validation purposes. The annual mean 2.5 degrees x 2.5 degrees gridded rain rates from the three algorithms are consistent with those from the Global Precipitation Climatology Project (GPCP) and DPR. Their correlation coefficients with GPCP are 0.96 and their biases are less than 5%. The correlation coefficients with DPR are slightly lower and the maximum bias is similar to 8%, partly due to the lower sampling density of DPR compared to that of MWHS-2.

Automated summary

This paper discusses three algorithms for retrieving oceanic precipitation from brightness temperatures of the Micro-Wave Humidity Sounder-2 on Fengyun-3C satellite. The algorithms were validated by comparing the results with data from the Global Precipitation Climatology Project and Dual-frequency Precipitation Radar, showing consistent results.