Unified model rainfall forecasts over India during 2007–2018: Evaluating extreme rains over hilly regions
| العنوان: | Unified model rainfall forecasts over India during 2007–2018: Evaluating extreme rains over hilly regions |
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| المؤلفون: | Ashis K. Mitra, E. N. Rajagopal, Sean Milton, Raghavendra Ashrit, Sushant Kumar, Kuldeep Sharma |
| المصدر: | Journal of Earth System Science. 130 |
| بيانات النشر: | Springer Science and Business Media LLC, 2021. |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Horizontal resolution, Index (economics), 010504 meteorology & atmospheric sciences, Forecast skill, Extremal dependence, Unified Model, 010502 geochemistry & geophysics, Numerical weather prediction, 01 natural sciences, Statistical power, Climatology, Rare events, General Earth and Planetary Sciences, Environmental science, 0105 earth and related environmental sciences |
| الوصف: | Prediction of heavy/extreme rains is still a challenge, even for the most advanced state-of-the-art high-resolution Numerical Weather Prediction (NWP) modelling systems. Hydrological models use the rainfall forecasts from the NWP models as input. This study evaluates the performance of the UK Met Office Unified Model (UM) in predicting the rainfall exceeding 80th and 90th percentiles. Such high rainfall amounts occur over the Western Ghats (WGs) and North East (NE) India mainly due to the forced ascent of air parcels. Apart from the significant upgrades in the UM's dynamical core, the model features an increased horizontal grid (40–10 km) and vertical resolution (50–70 levels). The prediction skill of heavy rainfall events improves with an increased horizontal resolution of the model. The probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) are the verification metrics used. As per these metrics, model rainfall forecasts have improved during 2007–2018 (increase in CSI from 0.29 to 0.38, POD from 0.45 to 0.55, and decrease in FAR from 0.55 to 0.45). Additionally, to verify extreme and rare events, the symmetric extremal dependence index (SEDI) is also used. SEDI also shows an increase from 0.47 to 0.62 and 0.16 to 0.41 over WGs and NE India during the study period, suggesting an improved skill of predicting heavy rains over the mountains. The improved forecast performance is consistent and relatively higher over WGs than over NE states. |
| تدمد: | 0973-774X 2347-4327 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::4db6bc7537b4d4a88ee415b44add6f80 https://doi.org/10.1007/s12040-021-01595-1 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi...........4db6bc7537b4d4a88ee415b44add6f80 |
| قاعدة البيانات: | OpenAIRE |
Find this article in full text from Springer Verlag. | تدمد: | 0973774X 23474327 |
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