DOI: 10.1007/s11069-020-03964-3
论文题名: An empirical ensemble rainfall nowcasting model using multi-scaled analogues
作者: Zou X. ; Dai Q. ; Wu K. ; Yang Q. ; Zhang S.
刊名: Natural Hazards
ISSN: 0921030X
出版年: 2020
卷: 103, 期: 1 起始页码: 165
结束页码: 188
语种: 英语
中文关键词: Analogue-based method
; Moving window
; Multi-scaled analogues
; Nowcasting
; Radar rainfall
英文关键词: climate prediction
; correlation
; ensemble forecasting
; nowcasting
; numerical model
; rainfall
; spatial resolution
; weather forecasting
英文摘要: Short-term rainfall prediction with high spatial and temporal resolution is of great importance to rainfall-triggered natural hazards such as landslide, flood, and debris flow. An analogue-based forecasting method may be able to provide short-term radar rainfall predictions, or “nowcasts,” in which the probability distribution of the atmospheric state at a given location in the future is estimated based on a set of past observations. Expensive computations and diverse atmospheric interactions across multiple spatial scales, however, limit the application of this method. This study employs a physically based, empirical ensemble rainfall nowcasting model to obtain ensembles from historical rainfall fields. To do this, we consider meteorological factors, rainfall spatial distributions, and the temporal evolution of rainfall patterns. Cross-correlation is used as a measure of the similarity between the spatial distributions of two rainfall patterns, and the movement rate of rain, with respect to both direction and distance, is used to compare the patterns temporally. A moving window scheme is used to reduce the computational load, with rainfall data providing most reference values. The relationship between different scales and rainfall forecasts is further explored by cascade divisions. While smaller analogue scales indicate better forecasts in this study, the optimal analogue scale will vary for different rainfall events. This study is only a start in incorporating multi-scaled analogue into rainfall nowcasting analysis, and a great deal of more effort is still needed to build a realistic and comprehensive analogue-based rainfall prediction model. © 2020, Springer Nature B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/168858
Appears in Collections: 气候变化与战略
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作者单位: Key Laboratory of VGE of Ministry of Education, Nanjing Normal University, Nanjing, China; WEMRC, Department of Civil Engineering, University of Bristol, Bristol, United Kingdom; Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing, China
Recommended Citation:
Zou X.,Dai Q.,Wu K.,et al. An empirical ensemble rainfall nowcasting model using multi-scaled analogues[J]. Natural Hazards,2020-01-01,103(1)