Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions
Downscaling techniques aim at resolving the scale discrepancy between climate change scenarios and the resolution demanded for impact assessments. Requirements for downscaled climate, to be useful for end users, include reliable representation of precipitation intensities, temporal and spatial varia...
| Autores principales: | , , , , , , , , , , , , |
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| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
CGIAR Research Program on Climate Change, Agriculture and Food Security
2012
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/21724 |
| _version_ | 1855522701203996672 |
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| author | Quiróz, R. Posadas, A. Yarleque, C. Heidinger, Haline Raymundo, R. Carbajal, M. Cruz, Mariana Guerrero, J. Mares, V. Silvestre, Elisabeth Jones, C. Carvalho, Leila M. V. Dinku, Tufa |
| author_browse | Carbajal, M. Carvalho, Leila M. V. Cruz, Mariana Dinku, Tufa Guerrero, J. Heidinger, Haline Jones, C. Mares, V. Posadas, A. Quiróz, R. Raymundo, R. Silvestre, Elisabeth Yarleque, C. |
| author_facet | Quiróz, R. Posadas, A. Yarleque, C. Heidinger, Haline Raymundo, R. Carbajal, M. Cruz, Mariana Guerrero, J. Mares, V. Silvestre, Elisabeth Jones, C. Carvalho, Leila M. V. Dinku, Tufa |
| author_sort | Quiróz, R. |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Downscaling techniques aim at resolving the scale discrepancy between climate change scenarios and the resolution demanded for impact assessments. Requirements for downscaled climate, to be useful for end users, include reliable representation of precipitation intensities, temporal and spatial variability, and physical parameters consistency. This report summarizes the results of the proof of concept phase in the development and testing of a novel data reconstruction method and a downscaling algorithm based on the multiplicative random cascade disaggregation method using rainfall signals at different spatial and temporal resolutions. The Wavelet Transformed-based Multi-Resolution Analysis (WT-MRA) was used for reconstructing the historical daily rainfall data needed as input for the downscaling methodology, using satellite-derived proxy data. Comparisons with presently used software showed that in all the cases; that is, the reconstructed, generated daily or downscaled daily data, the products developed outperformed the control test by either generating more accurate outcomes or by demanding significantly less parameterizing data. |
| format | Artículo preliminar |
| id | CGSpace21724 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2012 |
| publishDateRange | 2012 |
| publishDateSort | 2012 |
| publisher | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| publisherStr | CGIAR Research Program on Climate Change, Agriculture and Food Security |
| record_format | dspace |
| spelling | CGSpace217242025-11-09T12:37:06Z Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions Quiróz, R. Posadas, A. Yarleque, C. Heidinger, Haline Raymundo, R. Carbajal, M. Cruz, Mariana Guerrero, J. Mares, V. Silvestre, Elisabeth Jones, C. Carvalho, Leila M. V. Dinku, Tufa climate precipitation weather data Downscaling techniques aim at resolving the scale discrepancy between climate change scenarios and the resolution demanded for impact assessments. Requirements for downscaled climate, to be useful for end users, include reliable representation of precipitation intensities, temporal and spatial variability, and physical parameters consistency. This report summarizes the results of the proof of concept phase in the development and testing of a novel data reconstruction method and a downscaling algorithm based on the multiplicative random cascade disaggregation method using rainfall signals at different spatial and temporal resolutions. The Wavelet Transformed-based Multi-Resolution Analysis (WT-MRA) was used for reconstructing the historical daily rainfall data needed as input for the downscaling methodology, using satellite-derived proxy data. Comparisons with presently used software showed that in all the cases; that is, the reconstructed, generated daily or downscaled daily data, the products developed outperformed the control test by either generating more accurate outcomes or by demanding significantly less parameterizing data. 2012 2012-08-30T12:42:15Z 2012-08-30T12:42:15Z Working Paper https://hdl.handle.net/10568/21724 en Open Access application/pdf CGIAR Research Program on Climate Change, Agriculture and Food Security Quiroz R, Posadas A, Yarlequé, C, Heidinger H, Raymundo R, Carbajal M, Cruz M, Guerrero J, Mares V, Silvestre E, Jones C, Carvalho LV. de, Dinku T. 2012. Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions. CCAFS Working Paper 21. Copenhagen, Denmark: CCAFS. |
| spellingShingle | climate precipitation weather data Quiróz, R. Posadas, A. Yarleque, C. Heidinger, Haline Raymundo, R. Carbajal, M. Cruz, Mariana Guerrero, J. Mares, V. Silvestre, Elisabeth Jones, C. Carvalho, Leila M. V. Dinku, Tufa Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions |
| title | Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions |
| title_full | Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions |
| title_fullStr | Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions |
| title_full_unstemmed | Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions |
| title_short | Application of non-linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions |
| title_sort | application of non linear techniques for daily weather data reconstruction and downscaling coarse climate data for local predictions |
| topic | climate precipitation weather data |
| url | https://hdl.handle.net/10568/21724 |
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