Quality-Based Combination of Multi-Source Precipitation Data
A quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in order to meet the requirements, because of their v...
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| Format: | Article |
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MDPI AG
2020-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/12/11/1709 |
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| author | Anna Jurczyk Jan Szturc Irena Otop Katarzyna Ośródka Piotr Struzik |
| author_facet | Anna Jurczyk Jan Szturc Irena Otop Katarzyna Ośródka Piotr Struzik |
| author_sort | Anna Jurczyk |
| collection | DOAJ |
| description | A quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in order to meet the requirements, because of their very high temporal and spatial resolution. Other sources of precipitation data, such as telemetric rain gauges and satellite observations, are also included in the QPE. All of the used data are characterized by different temporal and spatial error structures. Therefore, a combination of the data should be based on quality information quantitatively determined for each input to take advantage of a particular source of precipitation measurement. The presented work on multi-source QPE, being implemented as the RainGRS system, has been carried out in the Polish national meteorological and hydrological service for new nowcasting and hydrological platforms in Poland. For each of the three data sources, different quality algorithms have been designed: (i) rain gauge data is quality controlled and, on this basis, spatial interpolation and estimation of quality field is performed, (ii) radar data are quality controlled by RADVOL-QC software that corrects errors identified in the data and characterizes its final quality, (iii) NWC SAF (Satellite Application Facility on support to Nowcasting and Very Short Range Forecasting) products for both visible and infrared channels are combined and the relevant quality field is determined from empirical relationships that are based on analyses of the product performance. Subsequently, the quality-based QPE is generated with a 1-km spatial resolution every 10 minutes (corresponding to radar data). The basis for the combination is a conditional merging technique that is enhanced by involving detailed quality information that is assigned to individual input data. The validation of the RainGRS estimates was performed taking account of season and kind of precipitation. |
| first_indexed | 2024-03-10T19:34:57Z |
| format | Article |
| id | doaj.art-ad5d05f3b8a44ea28348035d632a3228 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T19:34:57Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-ad5d05f3b8a44ea28348035d632a32282023-11-20T01:51:29ZengMDPI AGRemote Sensing2072-42922020-05-011211170910.3390/rs12111709Quality-Based Combination of Multi-Source Precipitation DataAnna Jurczyk0Jan Szturc1Irena Otop2Katarzyna Ośródka3Piotr Struzik4Institute of Meteorology and Water Management – National Research Institute, PL 01-673 Warsaw, PolandInstitute of Meteorology and Water Management – National Research Institute, PL 01-673 Warsaw, PolandInstitute of Meteorology and Water Management – National Research Institute, PL 01-673 Warsaw, PolandInstitute of Meteorology and Water Management – National Research Institute, PL 01-673 Warsaw, PolandInstitute of Meteorology and Water Management – National Research Institute, PL 01-673 Warsaw, PolandA quantitative precipitation estimate (QPE) provides basic information for the modelling of many kinds of hydro-meteorological processes, e.g., as input to rainfall-runoff models for flash flood forecasting. Weather radar observations are crucial in order to meet the requirements, because of their very high temporal and spatial resolution. Other sources of precipitation data, such as telemetric rain gauges and satellite observations, are also included in the QPE. All of the used data are characterized by different temporal and spatial error structures. Therefore, a combination of the data should be based on quality information quantitatively determined for each input to take advantage of a particular source of precipitation measurement. The presented work on multi-source QPE, being implemented as the RainGRS system, has been carried out in the Polish national meteorological and hydrological service for new nowcasting and hydrological platforms in Poland. For each of the three data sources, different quality algorithms have been designed: (i) rain gauge data is quality controlled and, on this basis, spatial interpolation and estimation of quality field is performed, (ii) radar data are quality controlled by RADVOL-QC software that corrects errors identified in the data and characterizes its final quality, (iii) NWC SAF (Satellite Application Facility on support to Nowcasting and Very Short Range Forecasting) products for both visible and infrared channels are combined and the relevant quality field is determined from empirical relationships that are based on analyses of the product performance. Subsequently, the quality-based QPE is generated with a 1-km spatial resolution every 10 minutes (corresponding to radar data). The basis for the combination is a conditional merging technique that is enhanced by involving detailed quality information that is assigned to individual input data. The validation of the RainGRS estimates was performed taking account of season and kind of precipitation.https://www.mdpi.com/2072-4292/12/11/1709precipitation estimationweather radarmeteorological satellitequality controlmulti-source approach |
| spellingShingle | Anna Jurczyk Jan Szturc Irena Otop Katarzyna Ośródka Piotr Struzik Quality-Based Combination of Multi-Source Precipitation Data Remote Sensing precipitation estimation weather radar meteorological satellite quality control multi-source approach |
| title | Quality-Based Combination of Multi-Source Precipitation Data |
| title_full | Quality-Based Combination of Multi-Source Precipitation Data |
| title_fullStr | Quality-Based Combination of Multi-Source Precipitation Data |
| title_full_unstemmed | Quality-Based Combination of Multi-Source Precipitation Data |
| title_short | Quality-Based Combination of Multi-Source Precipitation Data |
| title_sort | quality based combination of multi source precipitation data |
| topic | precipitation estimation weather radar meteorological satellite quality control multi-source approach |
| url | https://www.mdpi.com/2072-4292/12/11/1709 |
| work_keys_str_mv | AT annajurczyk qualitybasedcombinationofmultisourceprecipitationdata AT janszturc qualitybasedcombinationofmultisourceprecipitationdata AT irenaotop qualitybasedcombinationofmultisourceprecipitationdata AT katarzynaosrodka qualitybasedcombinationofmultisourceprecipitationdata AT piotrstruzik qualitybasedcombinationofmultisourceprecipitationdata |