Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1016/j.atmosres.2019.104832 |
Verification of high resolution (12 km) Global Ensemble Prediction System | |
Mamgain, Ashu; Sarkar, Abhijit; Rajagopal, E. N. | |
2020-05-15 | |
发表期刊 | ATMOSPHERIC RESEARCH
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ISSN | 0169-8095 |
EISSN | 1873-2895 |
出版年 | 2020 |
卷号 | 236 |
文章类型 | Article |
语种 | 英语 |
国家 | India |
英文摘要 | Ensemble Prediction Systems (EPSs) are used to estimate the uncertainty in a weather forecast as well as the most likely outcome. To improve weather forecasts and services, the global EPS at the NCMRWF has been upgraded to 12 km horizontal resolution (with 22 perturbed +1 control members). Although the upgraded version of EPS had become operational from 1st June 2018 in the newly acquired high-performance computing system (HPCS), the previous EPS at 33 km horizontal resolution (with 44 perturbed +1 control members) was also running in the old HPCS till 16th July 2018. As compared to the old EPS in NCMRWF, the new EPS includes perturbations in initial state of sea surface temperature, soil moisture content and deep soil temperature. The analysis of the new EPS also includes some more sources of observations. The perturbed 22 members long forecast of the new EPS provided at 00 UTC is the combination of 11 members from 00 UTC cycle and lagged 11 members from 12 UTC cycle of previous day. In the present study, the performances of the new and old EPS are compared for the period from 1st June to 16th July 2018. Performances of both the systems are assessed considering different attributes of probabilistic forecasting. The verification of precipitation, geopotential height at 500 hPa and zonal wind at 850 hPa has been carried out over the northern hemisphere, southern hemisphere and a smaller tropical region which includes India. The metrics used for verification are ensemble-spread, ensemble root-mean-square error, brier score, brier skill score, relative operating characteristics, reliability, sharpness diagrams, rank histogram, ranked probability score, continuous ranked probability score and continuous ranked probability skill score. Two heavy rainfall events have also been considered for subjective comparison of probabilistic prediction capabilities of both the systems. The results show that the new EPS is more skilful in probabilistic forecasts especially over the Indian region and it significantly outperforms the old EPS in probabilistic forecasts of the selected extreme weather events. |
英文关键词 | Ensemble Prediction System Ensemble member Probabilistic forecasts Ensemble-spread Brier score Reliability diagram |
领域 | 地球科学 |
收录类别 | SCI-E |
WOS记录号 | WOS:000525322900026 |
WOS关键词 | RAINFALL ; PERTURBATIONS ; PERFORMANCE ; TRANSFORM ; ECMWF ; INDIA ; TRMM |
WOS类目 | Meteorology & Atmospheric Sciences |
WOS研究方向 | Meteorology & Atmospheric Sciences |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/278866 |
专题 | 地球科学 |
作者单位 | Minist Earth Sci, Earth Syst Sci Org, NCMRWF, A-50,Sect 62, Noida 201309, Uttar Pradesh, India |
推荐引用方式 GB/T 7714 | Mamgain, Ashu,Sarkar, Abhijit,Rajagopal, E. N.. Verification of high resolution (12 km) Global Ensemble Prediction System[J]. ATMOSPHERIC RESEARCH,2020,236. |
APA | Mamgain, Ashu,Sarkar, Abhijit,&Rajagopal, E. N..(2020).Verification of high resolution (12 km) Global Ensemble Prediction System.ATMOSPHERIC RESEARCH,236. |
MLA | Mamgain, Ashu,et al."Verification of high resolution (12 km) Global Ensemble Prediction System".ATMOSPHERIC RESEARCH 236(2020). |
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