Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis
Statistical post-processing is necessary to correct systematic errors of numerical weather prediction models, especially in complex terrains such as the Alps. However, this post-processing is usually applied on every grid point individually, which can be computationally expensive. We want to present...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Borntraeger
2020-10-01
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| Series: | Meteorologische Zeitschrift |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1127/metz/2020/1022 |
| _version_ | 1819114615324278784 |
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| author | Markus Dabernig Irene Schicker Alexander Kann Yong Wang Moritz N. Lang |
| author_facet | Markus Dabernig Irene Schicker Alexander Kann Yong Wang Moritz N. Lang |
| author_sort | Markus Dabernig |
| collection | DOAJ |
| description | Statistical post-processing is necessary to correct systematic errors of numerical weather prediction models, especially in complex terrains such as the Alps. However, this post-processing is usually applied on every grid point individually, which can be computationally expensive. We want to present a method to forecast all grid points of a certain region simultaneously to expedite operational forecast times. The presented post-processing is part of the project SAPHIR, which provides forecasts from nowcasting up to +72 hours lead time with the same spatial resolution as the analysis. The used analysis is the Integrated Nowcasting through Comprehensive Analysis (INCA) system provided by ZAMG with a spatial resolution of 1 km. The post-processed variables are temperature, precipitation, wind and relative humidity. As a result highly resolved forecasts are presented with a similar performance to station-based forecasts. |
| first_indexed | 2024-12-22T04:48:07Z |
| format | Article |
| id | doaj.art-6749e067902b4a00814532061a37b8b7 |
| institution | Directory Open Access Journal |
| issn | 0941-2948 |
| language | English |
| last_indexed | 2024-12-22T04:48:07Z |
| publishDate | 2020-10-01 |
| publisher | Borntraeger |
| record_format | Article |
| series | Meteorologische Zeitschrift |
| spelling | doaj.art-6749e067902b4a00814532061a37b8b72022-12-21T18:38:33ZengBorntraegerMeteorologische Zeitschrift0941-29482020-10-0129426527510.1127/metz/2020/102293575Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded AnalysisMarkus DabernigIrene SchickerAlexander KannYong WangMoritz N. LangStatistical post-processing is necessary to correct systematic errors of numerical weather prediction models, especially in complex terrains such as the Alps. However, this post-processing is usually applied on every grid point individually, which can be computationally expensive. We want to present a method to forecast all grid points of a certain region simultaneously to expedite operational forecast times. The presented post-processing is part of the project SAPHIR, which provides forecasts from nowcasting up to +72 hours lead time with the same spatial resolution as the analysis. The used analysis is the Integrated Nowcasting through Comprehensive Analysis (INCA) system provided by ZAMG with a spatial resolution of 1 km. The post-processed variables are temperature, precipitation, wind and relative humidity. As a result highly resolved forecasts are presented with a similar performance to station-based forecasts.http://dx.doi.org/10.1127/metz/2020/1022ensemble forecastspost-processingtemperatureprecipitationwind speedrelative humiditystandardized anomaliesgridded analysis |
| spellingShingle | Markus Dabernig Irene Schicker Alexander Kann Yong Wang Moritz N. Lang Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis Meteorologische Zeitschrift ensemble forecasts post-processing temperature precipitation wind speed relative humidity standardized anomalies gridded analysis |
| title | Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis |
| title_full | Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis |
| title_fullStr | Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis |
| title_full_unstemmed | Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis |
| title_short | Statistical Post-Processing with Standardized Anomalies Based on a 1 km Gridded Analysis |
| title_sort | statistical post processing with standardized anomalies based on a 1 km gridded analysis |
| topic | ensemble forecasts post-processing temperature precipitation wind speed relative humidity standardized anomalies gridded analysis |
| url | http://dx.doi.org/10.1127/metz/2020/1022 |
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