DOI: 10.5194/hess-19-1547-2015
Scopus记录号: 2-s2.0-84961325075
论文题名: Evaluation of high-resolution precipitation analyses using a dense station network
作者: Kann A ; , Meirold-Mautner I ; , Schmid F ; , Kirchengast G ; , Fuchsberger J ; , Meyer V ; , Tüchler L ; , Bica B
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2015
卷: 19, 期: 3 起始页码: 1547
结束页码: 1559
语种: 英语
Scopus关键词: Algorithms
; Gages
; Precipitation (meteorology)
; Rain gages
; Weather forecasting
; Convective precipitation
; Cross validation
; Hydrological modelling
; Merging algorithms
; Numerical weather prediction models
; Temporal and spatial scale
; Temporal and spatial variability
; Very high resolution
; Rain
; algorithm
; climate prediction
; precipitation (climatology)
; radar
; raingauge
; spatiotemporal analysis
; weather station
英文摘要: The ability of radar-rain gauge merging algorithms to precisely analyse convective precipitation patterns is of high interest for many applications, e.g. hydrological modelling, thunderstorm warnings, and, as a reference, to spatially validate numerical weather prediction models. However, due to drawbacks of methods like cross-validation and due to the limited availability of reference data sets on high temporal and spatial scales, an adequate validation is usually hardly possible, especially on an operational basis. The present study evaluates the skill of very high-resolution and frequently updated precipitation analyses (rapid-INCA) by means of a very dense weather station network (WegenerNet), operated in a limited domain of the southeastern parts of Austria (Styria). Based on case studies and a longer-term validation over the convective season 2011, a general underestimation of the rapid-INCA precipitation amounts is shown by both continuous and categorical verification measures, although the temporal and spatial variability of the errors is - by convective nature - high. The contribution of the rain gauge measurements to the analysis skill is crucial. However, the capability of the analyses to precisely assess the convective precipitation distribution predominantly depends on the representativeness of the stations under the prevalent convective condition. © Author(s) 2015. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78564
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Forecasting Models, Central Institute for Meteorology and Geodynamics (ZAMG), Vienna, Austria; Wegener Center for Climate and Global Change (WEGC), University of Graz, Graz, Austria; Institute for Geophysics, Astrophysics, and Meteorology/Institute of Physics, University of Graz, Graz, Austria
Recommended Citation:
Kann A,, Meirold-Mautner I,, Schmid F,et al. Evaluation of high-resolution precipitation analyses using a dense station network[J]. Hydrology and Earth System Sciences,2015-01-01,19(3)