A new algorithm for wind speed at low incidence angles using TRMM Precipitation Radar data

Large datasets from crossovers of Precipitation Radar (PR) and buoy observations clearly demonstrate that ocean PR backscatter correlates with both the near-surface wind speed and the sea surface wave slope. Multi-incidence angles PR data are used to retrieve surface wave slope parameter and normalized nadir backscatter. After that, an empirical wind speed model was developed based on those two parameters that attenuates the surface tilting effect. The inversion is defined using a multilayer perceptron neural network with radar-derived backscatter and surface wave slope parameter as inputs. Results show the root mean square errs between retrieved wind speeds and in situ buoy observations is 1.36m/s, bias is nearly zero, revealing good agreements in wind speed estimations.