气候变化领域集成服务门户(CCPortal): Assessing the skill of NCMRWF global ensemble prediction system in predicting Indian summer monsoon during 2018

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DOI	10.1016/j.atmosres.2020.105255
	Assessing the skill of NCMRWF global ensemble prediction system in predicting Indian summer monsoon during 2018
	Chakraborty P.; Sarkar A.; Bhatla R.; Singh R.
发表日期	2021
ISSN	0169-8095
卷号	248
英文摘要	The quality of probabilistic precipitation and zonal wind forecasts from National Centre for Medium Range Weather Forecasting (NCMRWF) Global Ensemble Prediction System (NEPS-G) is investigated for Indian summer monsoon period between June–September 2018. Integrated Multi-satellite Retrievals for Global Precipitation Measurement (IMERG GPM) are used for verification of precipitation forecasts. The predictive skill of different categories of rainfall is examined with respect to daily climatology based on Tropical Rainfall Measuring Mission (TRMM) observations and reanalysis data from the Indian Monsoon Data Assimilation and Analysis (IMDAA). ERA Interim and IMDAA reanalysis daily climatologies are used to compute skill for the zonal wind forecasts at 850 hPa (u850). The model has a systematic tendency to over-predict the low level westerlies associated with the monsoon circulation. RMSE over Gangetic plains near Himalayan foothills is more in day-3 as compared to subsequent forecast lead times due to its overestimation of the easterly zonal wind flow. Spread in u850 is comparable to RMSE in day-1 forecast. The ensemble forecasting system is slightly under-dispersive for longer forecast lead times, since the rate of growth of forecast uncertainty is larger than that could be predicted by the ensemble system. Forecasts are sharper for lower thresholds of rainfall and exhibit more reliability and better discrimination of events over shorter lead times. Similar to reliability, the rank distribution depends on forecast lead time as well as ensemble spread. The positive Brier skill score and Continuous Ranked Probability Skill Score values above 0.4 for probabilistic wind as well as precipitation forecasts of light to moderate category, consistently show high predictive skill till day-7, with reference to the long-term climatology. NEPS-G could predict an extreme rainfall event with high probabilities of precipitation exceeding thresholds classified by India Meteorological department, which are in good correspondence with that of rainfall observed by GPM IMERG. A monsoon index based on large-scale features of monsoon circulation could be predicted by the EPS with high probabilistic skill during the peak monsoon. © 2020 Elsevier B.V.
英文关键词	Climatology; Ensemble; Monsoon; Probabilistic forecasting; Reliability
语种	英语
scopus关键词	Atmospheric thermodynamics; Climatology; Rain; Rain gages; Ensemble forecasting; Ensemble prediction systems; Global precipitation measurements; Indian summer monsoon; Monsoon circulations; Precipitation forecast; Ranked probability skill scores; Tropical rainfall measuring missions; Weather forecasting; climatology; data assimilation; ensemble forecasting; monsoon; precipitation assessment; probability; reliability analysis; TRMM; weather forecasting; Gangetic Plain
来源期刊	Atmospheric Research
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/141672
作者单位	National Centre for Medium Range Weather Forecasting (NCMRWF), (Ministry of Earth Sciences, Government of India), A-50, Sector-62, Noida, 201309, India; Department of Geophysics, Banaras Hindu University, Varanasi, Uttar Pradesh, India
推荐引用方式 GB/T 7714	Chakraborty P.,Sarkar A.,Bhatla R.,et al. Assessing the skill of NCMRWF global ensemble prediction system in predicting Indian summer monsoon during 2018[J],2021,248.
APA	Chakraborty P.,Sarkar A.,Bhatla R.,&Singh R..(2021).Assessing the skill of NCMRWF global ensemble prediction system in predicting Indian summer monsoon during 2018.Atmospheric Research,248.
MLA	Chakraborty P.,et al."Assessing the skill of NCMRWF global ensemble prediction system in predicting Indian summer monsoon during 2018".Atmospheric Research 248(2021).