{"title":"BALTEX沉淀分析:BRIDGE制备阶段的结果","authors":"F. Rubel , M. Hantel","doi":"10.1016/S1464-1909(01)00025-9","DOIUrl":null,"url":null,"abstract":"<div><p>The Baltic Sea Experiment (BALTEX) is the European contribution to the Global Energy and Water Cycle Experiment (GEWEX). During the preparation phase of the BALTEX main experiment BRIDGE a <em>Precipitation Correction and Analysis</em> (PCA) model has been designed and was tested using 3 years (August 1995 – December 1998) of about 4 000 rain gauge observations collected by the BALTEX Meteorological Data Centre (BMDC). The PCA model consists of two parts: (1) a bias correction and (2) a geostatistical module. The dynamic bias correction reduces the systematic underestimation of the rain gauges due to wind-induced, evaporation and wetting losses taking instrument-specific properties as well as additional information from synoptic observations into account. The mean correction factor has a maximum in February (1.25 – 1.50) and a minimum in August (1.02 – 1.05). The geostatistical module of the PCA model consists of an ordinary block kriging algorithm to estimate area averaged precipitation values on the grid of the meso-scale model REMO (spatial resolution: <span><math><mtext>1</mtext><mtext>6</mtext></math></span> degree or 18 km). Results, to be operationally produced during BRIDGE, will be daily, monthly and annual meso-scale precipitation fields based on quality checked, bias corrected rain gauge measurements.</p></div>","PeriodicalId":101025,"journal":{"name":"Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere","volume":"26 5","pages":"Pages 397-401"},"PeriodicalIF":0.0000,"publicationDate":"2001-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/S1464-1909(01)00025-9","citationCount":"5","resultStr":"{\"title\":\"BALTEX precipitation analysis: results from the BRIDGE preparation phase\",\"authors\":\"F. Rubel , M. Hantel\",\"doi\":\"10.1016/S1464-1909(01)00025-9\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The Baltic Sea Experiment (BALTEX) is the European contribution to the Global Energy and Water Cycle Experiment (GEWEX). During the preparation phase of the BALTEX main experiment BRIDGE a <em>Precipitation Correction and Analysis</em> (PCA) model has been designed and was tested using 3 years (August 1995 – December 1998) of about 4 000 rain gauge observations collected by the BALTEX Meteorological Data Centre (BMDC). The PCA model consists of two parts: (1) a bias correction and (2) a geostatistical module. The dynamic bias correction reduces the systematic underestimation of the rain gauges due to wind-induced, evaporation and wetting losses taking instrument-specific properties as well as additional information from synoptic observations into account. The mean correction factor has a maximum in February (1.25 – 1.50) and a minimum in August (1.02 – 1.05). The geostatistical module of the PCA model consists of an ordinary block kriging algorithm to estimate area averaged precipitation values on the grid of the meso-scale model REMO (spatial resolution: <span><math><mtext>1</mtext><mtext>6</mtext></math></span> degree or 18 km). Results, to be operationally produced during BRIDGE, will be daily, monthly and annual meso-scale precipitation fields based on quality checked, bias corrected rain gauge measurements.</p></div>\",\"PeriodicalId\":101025,\"journal\":{\"name\":\"Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere\",\"volume\":\"26 5\",\"pages\":\"Pages 397-401\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/S1464-1909(01)00025-9\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1464190901000259\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1464190901000259","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
BALTEX precipitation analysis: results from the BRIDGE preparation phase
The Baltic Sea Experiment (BALTEX) is the European contribution to the Global Energy and Water Cycle Experiment (GEWEX). During the preparation phase of the BALTEX main experiment BRIDGE a Precipitation Correction and Analysis (PCA) model has been designed and was tested using 3 years (August 1995 – December 1998) of about 4 000 rain gauge observations collected by the BALTEX Meteorological Data Centre (BMDC). The PCA model consists of two parts: (1) a bias correction and (2) a geostatistical module. The dynamic bias correction reduces the systematic underestimation of the rain gauges due to wind-induced, evaporation and wetting losses taking instrument-specific properties as well as additional information from synoptic observations into account. The mean correction factor has a maximum in February (1.25 – 1.50) and a minimum in August (1.02 – 1.05). The geostatistical module of the PCA model consists of an ordinary block kriging algorithm to estimate area averaged precipitation values on the grid of the meso-scale model REMO (spatial resolution: degree or 18 km). Results, to be operationally produced during BRIDGE, will be daily, monthly and annual meso-scale precipitation fields based on quality checked, bias corrected rain gauge measurements.