当前位置：
X-MOL 学术
›
Meteorol. Appl.
›
论文详情
Our official English website, www.x-mol.net, welcomes your
feedback! (Note: you will need to create a separate account there.)
Prediction of the August 2018 heavy rainfall events over Kerala with high‐resolution NWP models
Meteorological Applications ( IF 2.3 ) Pub Date : 2020-04-28 , DOI: 10.1002/met.1906 Raghavendra Ashrit 1 , Kuldeep Sharma 1 , Sushant Kumar 1 , Anumeha Dube 1 , S. Karunasagar 1 , T. Arulalan 1 , Ashu Mamgain 1 , Paromita Chakraborty 1 , Sumit Kumar 1 , Abhishek Lodh 1 , Devajyoti Dutta 1 , Imranali Momin 1 , M. T. Bushair 1 , Buddhi J. Prakash 1 , A. Jayakumar 1 , E. N. Rajagopal 1
Meteorological Applications ( IF 2.3 ) Pub Date : 2020-04-28 , DOI: 10.1002/met.1906 Raghavendra Ashrit 1 , Kuldeep Sharma 1 , Sushant Kumar 1 , Anumeha Dube 1 , S. Karunasagar 1 , T. Arulalan 1 , Ashu Mamgain 1 , Paromita Chakraborty 1 , Sumit Kumar 1 , Abhishek Lodh 1 , Devajyoti Dutta 1 , Imranali Momin 1 , M. T. Bushair 1 , Buddhi J. Prakash 1 , A. Jayakumar 1 , E. N. Rajagopal 1
Affiliation
|
The southern Indian state of Kerala experienced exceptionally high rainfall during August 2018, which led to devastating floods in many parts of the state. Prediction and early warning of severe weather events in vulnerable areas is crucial for disaster management agencies in order to protect life and property. In recent years, state‐of‐the‐art numerical weather prediction (NWP) models have been used operationally to predict rainfall over different spatial and temporal scales. In the present paper, predictions based on the National Centre for Medium Range Weather Forecasting (NCMRWF) models (NCUM, NCUM‐R and NEPS) are assessed over Kerala to demonstrate the capabilities of high‐resolution models. It is found that the deterministic NWP model (NCUM and NCUM‐R) forecasts are accurate at shorter lead times (up to Day 3) mainly in terms of timing and, to some extent, intensity. At higher lead times (beyond Day 3), the ensemble‐based probabilistic forecasts are useful and actionable.
中文翻译：
使用高分辨率NWP模型预测喀拉拉邦2018年8月的强降雨事件
印度南部喀拉拉邦在2018年8月经历了异常高的降雨，导致该州许多地方遭受了毁灭性的洪灾。为了保护生命和财产，脆弱地区的严重天气事件的预报和预警对于灾害管理机构至关重要。近年来，最先进的数值天气预报（NWP）模型已在操作上用于预测不同时空尺度上的降雨。在本文中，在喀拉拉邦评估了基于国家中型天气预报中心（NCMRWF）模型（NCUM，NCUM-R和NEPS）的预测，以证明高分辨率模型的功能。发现确定性NWP模型（NCUM和NCUM-R）预测在较短的交货时间（直到第3天）上是准确的，主要是在时间方面，在某种程度上，强度。在更高的交货时间（超过第3天）时，基于集合的概率预测是有用且可行的。
更新日期：2020-04-28
中文翻译：
使用高分辨率NWP模型预测喀拉拉邦2018年8月的强降雨事件
印度南部喀拉拉邦在2018年8月经历了异常高的降雨，导致该州许多地方遭受了毁灭性的洪灾。为了保护生命和财产，脆弱地区的严重天气事件的预报和预警对于灾害管理机构至关重要。近年来，最先进的数值天气预报（NWP）模型已在操作上用于预测不同时空尺度上的降雨。在本文中，在喀拉拉邦评估了基于国家中型天气预报中心（NCMRWF）模型（NCUM，NCUM-R和NEPS）的预测，以证明高分辨率模型的功能。发现确定性NWP模型（NCUM和NCUM-R）预测在较短的交货时间（直到第3天）上是准确的，主要是在时间方面，在某种程度上，强度。在更高的交货时间（超过第3天）时，基于集合的概率预测是有用且可行的。
京公网安备 11010802027423号