DOI: 10.1175/JCLI-D-18-0355.1
Scopus记录号: 2-s2.0-85058776457
论文题名: Precipitation prediction skill for the west coast United States: From short to extended range
作者: Pan B. ; Hsu K. ; Aghakouchak A. ; Sorooshian S. ; Higgins W.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2019
卷: 32, 期: 1 起始页码: 161
结束页码: 182
语种: 英语
Scopus关键词: Atmospheric pressure
; Climatology
; Correlation methods
; Precipitation (meteorology)
; Madden-Julian oscillation
; Pearson correlation coefficients
; Precipitation anomalies
; Precipitation distribution
; Precipitation predictions
; Precipitation variability
; Southern California
; Southern oscillation
; Forecasting
; baroclinic motion
; climate prediction
; correlation
; El Nino-Southern Oscillation
; hindcasting
; La Nina
; Madden-Julian oscillation
; precipitation intensity
; teleconnection
; Oregon
; Pacific Coast [North America]
; Pacific Coast [United States]
; United States
英文摘要: Precipitation variability significantly influences the heavily populatedWestCoast of the United States, raising the need for reliable predictions. We investigate the region's short- to extended-range precipitation prediction skill using the hindcast database of the Subseasonal-to-Seasonal Prediction Project (S2S). The prediction skill- lead time relationship is evaluated, using both deterministic and probabilistic skill scores. Results show that the S2S models display advantageous deterministic skill at week 1. For week 2, prediction is useful for the bestperforming model, with a Pearson correlation coefficient larger than 0.6. Beyond week 2, predictions generally provide little useful deterministic skill. Sources of extended-range predictability are investigated, focusing on El Niño-Southern Oscillation (ENSO) and the Madden-Julian oscillation (MJO). We found that periods of heavy precipitation associated with ENSO are more predictable at the extended range period. During El Niño years, Southern California tends to receive more precipitation in late winter, and most models show better extended-range prediction skill. On the contrary, during La Niña years Oregon tends to receive more precipitation in winter, with most models showing better extended-range skill. We believe the excessive precipitation and improved extended-range prediction skill are caused by themeridional shift of baroclinic systems as modulated by ENSO. Through examining precipitation anomalies conditioned on the MJO, we verified that active MJO events systematically modulate the area's precipitation distribution. Our results show that most models do not represent the MJO or its associated teleconnections, especially at phases 3-4. However, some models exhibit enhanced extended-range prediction skills under active MJO conditions. © 2018 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117274
Appears in Collections: 气候变化与战略
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Recommended Citation:
Pan B.,Hsu K.,Aghakouchak A.,et al. Precipitation prediction skill for the west coast United States: From short to extended range[J]. Journal of Climate,2019-01-01,32(1)