||Zabolotskikh Elizaveta1, Chapron Bertrand1, 2
||1 : Russian State Hydrometeorol Univ, Satellite Oceanog Lab, St Petersburg 195196, Russia.
2 : IFREMER, F-29280 Plouzane, France.
||Advances In Meteorology (1687-9309) (Hindawi Publishing Corporation), 2015 , N. ID 492603 , P. 1-13
|WOS© Times Cited
||A new algorithm is derived for rain rate (RR) estimation from Advanced Microwave Sounding Radiometer 2 (AMSR2) measurements taken at 6.9, 7.3, and 10.65 GHz. The algorithm is based on the numerical simulation of brightness temperatures (T-B) for AMSR2 lower frequency channels, using a simplified radiation transfer model. Simultaneous meteorological and hydrological observations, supplemented with modeled values of cloud liquid water content and rain rate values, are used for the calculation of an ensemble of AMSR2 T(B)s and RRs. Ice clouds are not taken into account. AMSR2 brightness temperature differences at C- and X-band channels are then used as inputs to train a neural network (NN) function for RR retrieval. Validation is performed against Tropical Rain Measurement Mission (TRMM) Microwave Instrument (TMI) RR products. For colocated AMSR2-TMI measurements, obtained within 10 min intervals, errors are about 1 mm/h. The new algorithm is applicable for RR estimation up to 20 mm/h. For RR < 2 mm/h the retrieval error is 0.3 mm/h. For RR > 10 mm/h the algorithm significantly underestimates TMI RR.
|Publisher's official version