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An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations
Open accessAbstract
The scatterometers onboard the European Remote Sensing satellites (ERS-1 & ERS-2) and the METeorological OPerational satellite (METOP) have been shown to be useful for surface soil moisture retrieval using the so-called TU-Wien change detection method. This paper presents an improved soil moisture retrieval algorithm based on the existing TU-Wien method but with new parameterization as well as a series of modifications. The new algorithm, WAter Retrieval Package 5 (WARP5), copes with some limitations identified in the earlier method WARP4 and provides the possibility of migrating soil moisture retrieval from ERS-SCAT to METOP-ASCAT data. The WARP5 algorithm results in a more robust and spatially uniform soil moisture product, thanks to its new processing elements, including a method for the correction of azimuthal anisotropy of backscatter, a comprehensive noise model, and new techniques for calculation of the model parameters. Cross-comparisons of WARP4 and WARP5 data sets with the Oklahoma Mesonetinsituobservations and also with European Centre of Medium Range Weather Forecast (ECMWF) ReAnalysis (ERA-Interim) global modeled data show that the new algorithm has a better performance and effectively corrects retrieval errors in certain areas.
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Cited by
Chew, C. C., & Small, E. E. (2018) · Geophysical Research Letters · doi:10.1029/2018gl077905 · Cited by 392
Metadata
- Authors
- Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., & Wagner, W.
- Venue
- IEEE Transactions on Geoscience and Remote Sensing
- Published
- 2009-07
- Volume
- 47
- Issue
- 7
- Pages
- 1999-2013
- ISSN
- 0196-2892 (ISSN-L)
- 1558-0644
- OpenAlex
- W2167731682
- Cited by
- 429
- References
- 25
- FWCI
- 16.52
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Naeimi, V., Scipal, K., Bartalis, Z., Hasenauer, S., & Wagner, W. (2009). An Improved Soil Moisture Retrieval Algorithm for ERS and METOP Scatterometer Observations. IEEE Transactions on Geoscience and Remote Sensing. https://doi.org/10.1109/tgrs.2008.2011617
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