Rain rate estimation from FY-3C/MWHS-2 observations at 89-190 GHz
Abstract
This paper describes three algorithms for retrieving precipitation over oceans from brightness temperatures (TBs) of the Micro-Wave Humidity Sounder-2 (MHWS-2) onboard the Fengyun-3C (FY-3C). For algorithm development, scattering-induced TB depressions (ΔTBs) of MWHS-2 at channels between 89 and 190 GHz were collocated to rain rates derived from measurements of the Global Precipitation Measurement's (GPM) Dual-Frequency Precipitation Radar (DPR) for the year of 2017. ΔTBs were calculated by subtracting simulated cloud-free TBs from bias-corrected observed TBs for each channel. These ΔTBs were then related to rain rates from DPR using (1) multi-linear regression (MLR) algorithm. The other two algorithms: (2) range searches (RS) and (3) nearest neighbor searches (NNS), are based on k-dimensional trees (k-d trees). While all the three algorithms provide instantaneous rain rate estimates, the RS searches also provides probability of precipitation and can be understood in a Bayesian framework. In order to understand the benefits of the new 118 GHz system with regard to rainfall retrievals, different combinations of MWHS-2 channels were evaluated using the MLR, and results suggest that adding 118 GHz improves retrieval performance. The optimal combination of channels is found to exclude high-peaking channels but to include 118 GHz channels that peak in the mid and high troposphere. FY-3C observations from another full year (2016) were used for validation for all three algorithms for the selected optimal channel combination. The annual mean 2.5°x2.5° gridded rain rate estimates from the three algorithms were compared to and are consistent with the Global Precipitation Climatology Project (GPCP) and DPR annual also with gridded retrievals for this same year. Their correlation coefficients with GPCP are 0.96 and their biases are less than 5%. The correlation coefficients with DPR are slightly lower (0.84 or 0.85) and the maximum bias is ~8%, partly on account of the lower sampling density of DPR compared to that of MWHS-2.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMH200.0014C
- Keywords:
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- 3354 Precipitation;
- ATMOSPHERIC PROCESSES;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 1854 Precipitation;
- HYDROLOGY;
- 1855 Remote sensing;
- HYDROLOGY