Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset
As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper p...
| Main Authors: | , , |
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| Format: | Journal Article |
| Language: | Inglés |
| Published: |
American Meteorological Society
2014
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/68182 |
| _version_ | 1855518091847401472 |
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| author | Greatrex, Helen Grimes, D. Wheeler, Tim |
| author_browse | Greatrex, Helen Grimes, D. Wheeler, Tim |
| author_facet | Greatrex, Helen Grimes, D. Wheeler, Tim |
| author_sort | Greatrex, Helen |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration. |
| format | Journal Article |
| id | CGSpace68182 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2014 |
| publishDateRange | 2014 |
| publishDateSort | 2014 |
| publisher | American Meteorological Society |
| publisherStr | American Meteorological Society |
| record_format | dspace |
| spelling | CGSpace681822024-09-03T06:35:22Z Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset Greatrex, Helen Grimes, D. Wheeler, Tim climate change agriculture food security rain As satellite technology develops, satellite rainfall estimates are likely to become ever more important in the world of food security. It is therefore vital to be able to identify the uncertainty of such estimates and for end users to be able to use this information in a meaningful way. This paper presents new developments in the methodology of simulating satellite rainfall ensembles from thermal infrared satellite data. Although the basic sequential simulation methodology has been developed in previous studies, it was not suitable for use in regions with more complex terrain and limited calibration data. Developments in this work include the creation of a multithreshold, multizone calibration procedure, plus investigations into the causes of an overestimation of low rainfall amounts and the best way to take into account clustered calibration data. A case study of the Ethiopian highlands has been used as an illustration. 2014-10-01 2015-09-16T17:00:33Z 2015-09-16T17:00:33Z Journal Article https://hdl.handle.net/10568/68182 en Open Access American Meteorological Society Greatrex H, Grimes D, Wheeler T. 2014. Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset. Journal of Hydrometeorology 15(5):1810-1831. |
| spellingShingle | climate change agriculture food security rain Greatrex, Helen Grimes, D. Wheeler, Tim Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset |
| title | Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset |
| title_full | Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset |
| title_fullStr | Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset |
| title_full_unstemmed | Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset |
| title_short | Advances in the Stochastic Modeling of Satellite-Derived Rainfall Estimates Using a Sparse Calibration Dataset |
| title_sort | advances in the stochastic modeling of satellite derived rainfall estimates using a sparse calibration dataset |
| topic | climate change agriculture food security rain |
| url | https://hdl.handle.net/10568/68182 |
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