A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube Basin
The main goal of this study is to obtain an improvement of the spring precipitation estimation at local scale, taking into account the atmospheric circulation on the Atlantic-European region, by a statistical downscaling procedure. First we have fitted the precipitation amounts from the 19 stations...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | Advances in Meteorology |
| Online Access: | http://dx.doi.org/10.1155/2014/237247 |
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| author | Constantin Mares Ileana Mares Heike Huebener Mihaela Mihailescu Ulrich Cubasch Petre Stanciu |
| author_facet | Constantin Mares Ileana Mares Heike Huebener Mihaela Mihailescu Ulrich Cubasch Petre Stanciu |
| author_sort | Constantin Mares |
| collection | DOAJ |
| description | The main goal of this study is to obtain an improvement of the spring precipitation estimation at local scale, taking into account the atmospheric circulation on the Atlantic-European region, by a statistical downscaling procedure. First we have fitted the precipitation amounts from the 19 stations with a HMM with 7 states. The stations are situated in localities crossed by the Danube or situated on the principal tributaries. The number of hidden states has been determined by means of BIC values. A NHMM has been applied then to precipitation occurrence associated with the information about atmospheric circulation over Atlantic-European region. The atmospheric circulation is quantified by the first 10 components of the decomposition in the EOFs or MEOFs. The predictors taking into account CWTs for SLP and the first summary variable from a SVD have also been tested. The atmospheric predictors are derived from SLP, geopotential, temperature, and specific and relative humidity at 850 hPa. As a result of analyzing the multitude of the predictors, a statistical method of selection based on the informational content has been achieved. The test of the NHMM performances has revealed that SLP and geopotential at 850 hPa are the best predictors for precipitation. |
| format | Article |
| id | doaj-art-f1ada213d4b740d1b1b99ba4e6f63716 |
| institution | Kabale University |
| issn | 1687-9309 1687-9317 |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Advances in Meteorology |
| spelling | doaj-art-f1ada213d4b740d1b1b99ba4e6f637162025-02-03T06:01:41ZengWileyAdvances in Meteorology1687-93091687-93172014-01-01201410.1155/2014/237247237247A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube BasinConstantin Mares0Ileana Mares1Heike Huebener2Mihaela Mihailescu3Ulrich Cubasch4Petre Stanciu5National Institute of Hydrology and Water Management, 013686 Bucharest, RomaniaNational Institute of Hydrology and Water Management, 013686 Bucharest, RomaniaHessian Centre on Climate Change, 65203 Wiesbaden, GermanyUniversity of Agronomic Sciences and Veterinary Medicine, 011464 Bucharest, RomaniaInstitute of Meteorology, Free University Berlin, 12165 Berlin, GermanyNational Institute of Hydrology and Water Management, 013686 Bucharest, RomaniaThe main goal of this study is to obtain an improvement of the spring precipitation estimation at local scale, taking into account the atmospheric circulation on the Atlantic-European region, by a statistical downscaling procedure. First we have fitted the precipitation amounts from the 19 stations with a HMM with 7 states. The stations are situated in localities crossed by the Danube or situated on the principal tributaries. The number of hidden states has been determined by means of BIC values. A NHMM has been applied then to precipitation occurrence associated with the information about atmospheric circulation over Atlantic-European region. The atmospheric circulation is quantified by the first 10 components of the decomposition in the EOFs or MEOFs. The predictors taking into account CWTs for SLP and the first summary variable from a SVD have also been tested. The atmospheric predictors are derived from SLP, geopotential, temperature, and specific and relative humidity at 850 hPa. As a result of analyzing the multitude of the predictors, a statistical method of selection based on the informational content has been achieved. The test of the NHMM performances has revealed that SLP and geopotential at 850 hPa are the best predictors for precipitation.http://dx.doi.org/10.1155/2014/237247 |
| spellingShingle | Constantin Mares Ileana Mares Heike Huebener Mihaela Mihailescu Ulrich Cubasch Petre Stanciu A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube Basin Advances in Meteorology |
| title | A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube Basin |
| title_full | A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube Basin |
| title_fullStr | A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube Basin |
| title_full_unstemmed | A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube Basin |
| title_short | A Hidden Markov Model Applied to the Daily Spring Precipitation over the Danube Basin |
| title_sort | hidden markov model applied to the daily spring precipitation over the danube basin |
| url | http://dx.doi.org/10.1155/2014/237247 |
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