DOI: 10.1007/s00382-013-2045-9
Scopus记录号: 2-s2.0-84899931926
论文题名: Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2
作者: Abhilash S. ; Sahai A.K. ; Borah N. ; Chattopadhyay R. ; Joseph S. ; Sharmila S. ; De S. ; Goswami B.N. ; Kumar A.
刊名: Climate Dynamics
ISSN: 9307575
出版年: 2014
卷: 42, 期: 2017-09-10 起始页码: 2801
结束页码: 2815
语种: 英语
英文关键词: Ensemble prediction system
; Extended range prediction
; Indian summer monsoon
英文摘要: An ensemble prediction system (EPS) is devised for the extended range prediction (ERP) of monsoon intraseasonal oscillations (MISO) of Indian summer monsoon (ISM) using National Centers for Environmental Prediction Climate Forecast System model version 2 at T126 horizontal resolution. The EPS is formulated by generating 11 member ensembles through the perturbation of atmospheric initial conditions. The hindcast experiments were conducted at every 5-day interval for 45 days lead time starting from 16th May to 28th September during 2001-2012. The general simulation of ISM characteristics and the ERP skill of the proposed EPS at pentad mean scale are evaluated in the present study. Though the EPS underestimates both the mean and variability of ISM rainfall, it simulates the northward propagation of MISO reasonably well. It is found that the signal-to-noise ratio of the forecasted rainfall becomes unity by about 18 days. The potential predictability error of the forecasted rainfall saturates by about 25 days. Though useful deterministic forecasts could be generated up to 2nd pentad lead, significant correlations are found even up to 4th pentad lead. The skill in predicting large-scale MISO, which is assessed by comparing the predicted and observed MISO indices, is found to be ~17 days. It is noted that the prediction skill of actual rainfall is closely related to the prediction of large-scale MISO amplitude as well as the initial conditions related to the different phases of MISO. An analysis of categorical prediction skills reveals that break is more skillfully predicted, followed by active and then normal. The categorical probability skill scores suggest that useful probabilistic forecasts could be generated even up to 4th pentad lead. © 2014 Springer-Verlag Berlin Heidelberg. 资助项目: MoES, National Oceanic and Atmospheric Administration
; NOAA, National Oceanic and Atmospheric Administration
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/54573
Appears in Collections: 过去全球变化的重建
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作者单位: Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road, Pashan, Pune, 411008, India; National Center for Environmental Prediction, Camps Springs, MD, United States
Recommended Citation:
Abhilash S.,Sahai A.K.,Borah N.,et al. Prediction and monitoring of monsoon intraseasonal oscillations over Indian monsoon region in an ensemble prediction system using CFSv2[J]. Climate Dynamics,2014-01-01,42(2017-09-10)