DOI: 10.1175/JCLI-D-13-00464.1
Scopus记录号: 2-s2.0-84903390272
论文题名: Spatial similarity and transferability of analog dates for precipitation downscaling over France
作者: Chardon J. ; Hingray B. ; Favre C. ; Autin P. ; Gailhard J.L. ; Zin I. ; Obled C.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2014
卷: 27, 期: 13 起始页码: 5056
结束页码: 5074
语种: 英语
Scopus关键词: Climate change
; Precipitation (chemical)
; Climate change impact
; Climate prediction
; Geo-potential heights
; Prediction performance
; Spatial consistency
; Spatial similarity
; Spatial transferability
; Statistical forecasting
; Forecasting
; climate change
; climate effect
; climate modeling
; climate prediction
; downscaling
; forecasting method
; precipitation assessment
; France
英文摘要: High-resolution weather scenarios generated for climate change impact studies from the output of climate models must be spatially consistent. Analog models (AMs) offer a high potential for the generation of such scenarios. For each prediction day, the scenario they provide is the weather observed for days in a historical archive that are analogous according to different predictors. When the same ''analog date'' is chosen for a prediction at several sites, spatial consistency is automatically satisfied. The optimal predictors and consequently the optimal analog dates, however, are expected to depend on the location for which the prediction is to be made. In the present work, the predictor (1000-and 500-hPa geopotential heights) domain of a benchmarkAM is optimized for the probabilistic daily prediction of 8981 local precipitation ''stations'' over France. The corresponding 8981 locally domain-optimized AMs are used to explore the spatial transferability and similarity of the optimal analog dates obtained for different locations. Whereas the similarity is very low even when the locations are close, the spatial transferability of the optimal analog dates for a given location is high. When they are used for the prediction at all other locations, the loss of prediction performance is therefore very low over large spatial domains (up to 500 km). Spatial transferability is lower in the presence of high mountains. It also depends on the parameters of the AM (e.g., its archive length, predictors, and number of analog dates used for the prediction). In the present case, AMs with higher prediction skill exhibit lower transferability. © 2014 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51413
Appears in Collections: 气候变化事实与影响
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作者单位: Université de Grenoble-Alpes, LTHE, 38000 Grenoble, France; CNRS, LTHE, 38000 Grenoble, France; EDF-DTG, BP 41, 38040 Grenoble, France
Recommended Citation:
Chardon J.,Hingray B.,Favre C.,et al. Spatial similarity and transferability of analog dates for precipitation downscaling over France[J]. Journal of Climate,2014-01-01,27(13)