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Improved physically based oceanic rainfall algorithm from AMSR-E data
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DOI：10.1109/TGRS.2007.894931.png)
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摘要
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An improved oceanic rainfall algorithm based on a radiative transfer model that reduces many uncertainties of rainfall retrieval was developed using advanced microwave scanning radiometer for Earth Observing System data. Error models were embedded to quantify rainfall uncertainties and to reduce net uncertainties. Six channels (37, 18, and 10 GHz with dual polarization) were utilized in the algorithm. Several developments such as improvement of the freezing-level (FL) retrieval, a weighted average scheme, and enhanced offset correction were implemented in this paper. As a result, rain rate uncertainties were substantially reduced and quantified. To establish error models, drop-size-distribution uncertainty, beam filling error, data calibration uncertainty, and instrument noise were taken into account. These error models were used to compute proper weights of each channel to combine the six rain rates. The algorithm was evaluated with respect to the current operational algorithm (NASA Level 3 rainfall algorithm). It showed more reasonable mean FLs and rain rate estimation than the operational algorithm. Furthermore, pixel-by-pixel-based quantitative error estimates were conducted through the error model.
Keyword:
advanced microwave scanning radiometer for Earth Observing System (AMSR-E) (EOS)
microwave remote sensing
precipitation
rainfall
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8.6
论文数:
2.1W
被引数:
10.7W
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