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A Neural Network-Based Rain Effect Correction Method for HY-2A Scatterometer Backscatter Measurements. REMOTE SENSING 2020. [DOI: 10.3390/rs12101648] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The backscattering coefficients measured by Ku-band scatterometers are strongly affected by rainfall, resulting in a systematic error in sea surface wind field retrieval. In rainy conditions, the radar signals are subject to absorption by the raindrops in their round-trip propagation through the atmosphere, while the backscatter of raindrops raises the echo energy. In addition, raindrops give rise to roughness by impinging the ocean surface, resulting in an increase in the echo energy measured by a scatterometer. Under moderate wind conditions, the comprehensive impact of rainfall causes the wind speeds retrieved by the scatterometer to be higher than their actual values. The HY-2A scatterometer is a Ku-band, pencil-beam, conically scanning scatterometer. To correct the systematic error of the HY-2A scatterometer measurement in rainy conditions, a neural network model is proposed according to the characteristics of the backscatter coefficients measured by the HY-2A scatterometer in the presence of rain. With the neural network, the wind fields of the European Centre for Medium-range Weather Forecasts (ECMWF) reanalysis data were used as the reference to correct the deviation in backscatter coefficients measured by the HY-2A scatterometer in rainy conditions, and the accuracy in wind speeds retrieved using the corrected backscatter coefficients was significantly improved. Compared with the cases of wind retrieval without rain effect correction, the wind speeds retrieved from the corrected backscatter coefficients by the neural network show a much lower systematic deviation, which indicates that the neural network can effectively remove the systematic deviation in the backscatter coefficients and the retrieved wind speeds caused by rain.
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A Non-MLE Approach for Satellite Scatterometer Wind Vector Retrievals in Tropical Cyclones. REMOTE SENSING 2014. [DOI: 10.3390/rs6054133] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Draper DW. Evaluating the effect of rain on SeaWinds scatterometer measurements. ACTA ACUST UNITED AC 2004. [DOI: 10.1029/2002jc001741] [Citation(s) in RCA: 84] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Freilich MH, Dunbar RS. The accuracy of the NSCAT 1 vector winds: Comparisons with National Data Buoy Center buoys. ACTA ACUST UNITED AC 1999. [DOI: 10.1029/1998jc900091] [Citation(s) in RCA: 182] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Bauer E, Staabs C. Statistical properties of global significant wave heights and their use for validation. ACTA ACUST UNITED AC 1998. [DOI: 10.1029/97jc02568] [Citation(s) in RCA: 27] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Hsu CS, Liu WT. Wind and pressure fields near tropical cyclone Oliver derived from scatterometer observations. ACTA ACUST UNITED AC 1996. [DOI: 10.1029/96jd01229] [Citation(s) in RCA: 19] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Gower JFR. Intercalibration of wave and wind data from TOPEX/POSEIDON and moored buoys off the west coast of Canada. ACTA ACUST UNITED AC 1996. [DOI: 10.1029/95jc03281] [Citation(s) in RCA: 71] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Freilich MH, Challenor PG. A new approach for determining fully empirical altimeter wind speed model functions. ACTA ACUST UNITED AC 1994. [DOI: 10.1029/94jc01996] [Citation(s) in RCA: 46] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Callahan PS, Morris CS, Hsiao SV. Comparison of TOPEX/POSEIDON σ0and significant wave height distributions to Geosat. ACTA ACUST UNITED AC 1994. [DOI: 10.1029/94jc01759] [Citation(s) in RCA: 38] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Young IR. An estimate of the Geosat altimeter wind speed algorithm at high wind speeds. ACTA ACUST UNITED AC 1993. [DOI: 10.1029/93jc02117] [Citation(s) in RCA: 63] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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