Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments
A new development in the field of reanalyses is the incorporation of uncertainty estimation capabilities. We have developed a probabilistic regional reanalysis system for the CORDEX-EUR11 domain that is based on the numerical weather prediction model COSMO at a 12-km grid spacing. The lateral bounda...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Stockholm University Press
2016-11-01
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| Series: | Tellus: Series A, Dynamic Meteorology and Oceanography |
| Subjects: | |
| Online Access: | http://www.tellusa.net/index.php/tellusa/article/view/32209/49963 |
| _version_ | 1818475331091169280 |
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| author | Liselotte Bach Christoph Schraff Jan D. Keller Andreas Hense |
| author_facet | Liselotte Bach Christoph Schraff Jan D. Keller Andreas Hense |
| author_sort | Liselotte Bach |
| collection | DOAJ |
| description | A new development in the field of reanalyses is the incorporation of uncertainty estimation capabilities. We have developed a probabilistic regional reanalysis system for the CORDEX-EUR11 domain that is based on the numerical weather prediction model COSMO at a 12-km grid spacing. The lateral boundary conditions of all ensemble members are provided by the global reanalysis ERA-Interim. In the basic implementation of the system, uncertainties due to observation errors are estimated. Atmospheric assimilation of conventional observations perturbed by means of random samples of observation error yields estimates of the reanalysis uncertainty conditioned to observation errors. The data assimilation employed is a new scheme based on observation nudging that we denote ensemble nudging. The lower boundary of the atmosphere is regularly updated by external snow depth, sea surface temperature and soil moisture analyses. One of the most important purposes of reanalyses is the estimation of so-called essential climate variables. For regional reanalyses, precipitation has been identified as one of the essential climate variables that are potentially better represented than in other climate data sets. For that reason, we assess the representation of precipitation in our system in a pilot study. Based on two experiments, each of which extends over one month, we conduct a preliminary comparison to the global reanalysis ERA-Interim, a dynamical downscaling of the latter and the high-resolution regional reanalysis COSMO-REA6. In a next step, we assess our reanalysis system's probabilistic capabilities versus the ECMWF-EPS in terms of six-hourly precipitation sums. The added value of our probabilistic regional reanalysis system motivates the current production of a 5-year-long test reanalysis COSMO-EN-REA12 in the framework of the FP7-funded project Uncertainties in Ensembles of Regional Re-Analyses (UERRA). |
| first_indexed | 2024-12-10T09:11:34Z |
| format | Article |
| id | doaj.art-66806eb281eb46979f7ac4266cfc6048 |
| institution | Directory Open Access Journal |
| issn | 1600-0870 |
| language | English |
| last_indexed | 2024-12-10T09:11:34Z |
| publishDate | 2016-11-01 |
| publisher | Stockholm University Press |
| record_format | Article |
| series | Tellus: Series A, Dynamic Meteorology and Oceanography |
| spelling | doaj.art-66806eb281eb46979f7ac4266cfc60482022-12-22T01:55:00ZengStockholm University PressTellus: Series A, Dynamic Meteorology and Oceanography1600-08702016-11-0168012110.3402/tellusa.v68.3220932209Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experimentsLiselotte Bach0Christoph Schraff1Jan D. Keller2Andreas Hense3 Meteorological Institute of the University of Bonn, Auf dem Hügel 20, Bonn, Germany Deutscher Wetterdienst, Offenbach, Germany Deutscher Wetterdienst, Offenbach, Germany Meteorological Institute of the University of Bonn, Auf dem Hügel 20, Bonn, GermanyA new development in the field of reanalyses is the incorporation of uncertainty estimation capabilities. We have developed a probabilistic regional reanalysis system for the CORDEX-EUR11 domain that is based on the numerical weather prediction model COSMO at a 12-km grid spacing. The lateral boundary conditions of all ensemble members are provided by the global reanalysis ERA-Interim. In the basic implementation of the system, uncertainties due to observation errors are estimated. Atmospheric assimilation of conventional observations perturbed by means of random samples of observation error yields estimates of the reanalysis uncertainty conditioned to observation errors. The data assimilation employed is a new scheme based on observation nudging that we denote ensemble nudging. The lower boundary of the atmosphere is regularly updated by external snow depth, sea surface temperature and soil moisture analyses. One of the most important purposes of reanalyses is the estimation of so-called essential climate variables. For regional reanalyses, precipitation has been identified as one of the essential climate variables that are potentially better represented than in other climate data sets. For that reason, we assess the representation of precipitation in our system in a pilot study. Based on two experiments, each of which extends over one month, we conduct a preliminary comparison to the global reanalysis ERA-Interim, a dynamical downscaling of the latter and the high-resolution regional reanalysis COSMO-REA6. In a next step, we assess our reanalysis system's probabilistic capabilities versus the ECMWF-EPS in terms of six-hourly precipitation sums. The added value of our probabilistic regional reanalysis system motivates the current production of a 5-year-long test reanalysis COSMO-EN-REA12 in the framework of the FP7-funded project Uncertainties in Ensembles of Regional Re-Analyses (UERRA).http://www.tellusa.net/index.php/tellusa/article/view/32209/49963climate dynamicsessential climate variablesensemble data assimilationCORDEXuncertainty estimationprecipitation |
| spellingShingle | Liselotte Bach Christoph Schraff Jan D. Keller Andreas Hense Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments Tellus: Series A, Dynamic Meteorology and Oceanography climate dynamics essential climate variables ensemble data assimilation CORDEX uncertainty estimation precipitation |
| title | Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments |
| title_full | Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments |
| title_fullStr | Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments |
| title_full_unstemmed | Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments |
| title_short | Towards a probabilistic regional reanalysis system for Europe: evaluation of precipitation from experiments |
| title_sort | towards a probabilistic regional reanalysis system for europe evaluation of precipitation from experiments |
| topic | climate dynamics essential climate variables ensemble data assimilation CORDEX uncertainty estimation precipitation |
| url | http://www.tellusa.net/index.php/tellusa/article/view/32209/49963 |
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