Blending Sea Surface Winds from the HY-2 Satellite Scatterometers Based on a 2D-Var Method

The launch of the Haiyang-2 (HY-2) satellite constellation fosters the quick acquisition of global sea surface vector winds from the perspective of remote sensing. This study intends to develop a six-hourly mesoscale analysis of sea surface winds based on the microwave scatterometers onboard the HY-...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Switzerland), 2023-01, Vol.15 (1), p.193
Main Authors: Lv, Sirui, Lin, Wenming, Wang, Zhixiong, Zou, Juhong
Format: Article
Language:English
Subjects:
2D-Var method
Blending
Correlation
Empirical analysis
error correlation
Errors
HY-2 scatterometers
Ocean models
Ocean surface
Remote sensing
Satellite constellations
Satellites
Scatterometers
sea surface wind
Telecommunications systems
Two dimensional analysis
Weather forecasting
Wind
Wind measurement
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Summary:The launch of the Haiyang-2 (HY-2) satellite constellation fosters the quick acquisition of global sea surface vector winds from the perspective of remote sensing. This study intends to develop a six-hourly mesoscale analysis of sea surface winds based on the microwave scatterometers onboard the HY-2 satellite series, with the objective of meeting the considerable demand for accurate and gap-free ocean wind forcing products. First, the accuracy of HY-2 scatterometers (HSCATs) in measuring wind is evaluated. In particular, the standard deviation (SD) errors of HSCATs data are assessed using the collocated buoy measurements with different temporal windows in order to account for the temporal representativeness errors in the blending analysis. Afterwards, a two-dimensional variational (2D-Var) method is implemented to blend the HSCATs measured winds and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis winds over the global ocean surface. This approach is different from existing methods in that it takes both wind error and background error correlation into account. The results show that the blended wind product is of a promising quality compared with independent wind references. Interestingly, the blended winds derived from 2D-Var in combination with an empirical background error correlation show smaller SD errors than those using a Gaussian error correlation function. Overall, the blended wind product should be valuable for forcing global ocean models or describing air-sea interaction processes on a scale close to the scatterometer measurements.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15010193