Abstract

AbstractSea surface barometric pressure is one of the few key geophysical variables has not been derived from satellite observations. In this study, we investigate the retrieval of sea surface barometric pressure from passive microwave observations. The direct relationship between surface barometric pressure and upward‐emitted brightness temperature observed by a microwave radiometer is deduced and validated. A statistical retrieval algorithm based on the back‐propagation (BP) neural networks is proposed to estimate sea surface barometric pressure using the observations from the Advanced Technology Microwave Sounder (ATMS) onboard the Suomi‐National Polar‐Orbiting Operational Environmental Satellite System Preparatory Project (SNPP) satellite. In situ buoy measurements and reanalysis data are used to assess the retrieval performance. Experimental results show that the proposed retrieval algorithm can estimate sea surface barometric pressure over mid‐to‐low latitude areas ( ) with the root mean square errors of less than 2.0, 3.0, and 3.5 hPa for clear‐sky, cloudy, and rainy conditions, respectively. Several tropical cyclone retrieval experiments also show that the proposed retrieval algorithm behaves well under high wind conditions (15 m/s < wind speed < 28 m/s).

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