Application of hind cast in identifying extreme events over India

Autor:	C. J. Johny, V. S. Prasad
Rok vydání:	2020
Předmět:	010504 meteorology & atmospheric sciences Climatology Extreme events General Earth and Planetary Sciences Environmental science Bias correction 010502 geochemistry & geophysics 01 natural sciences Extreme temperature Lead time 0105 earth and related environmental sciences
Zdroj:	Journal of Earth System Science. 129
ISSN:	0973-774X 2347-4327
Popis:	India Meteorological Department (IMD) is operationally producing forecasts at T1534 resolution using NCMRWF GFS (NGFS) model and biases are reported in some regions. In order to identify the model biases and applying necessary correction measures to improve forecast, retrospective forecast is carried out for the 20 yrs period from 1999–2018 using operational version of NGFS model. In this study, model’s ability to predict extreme temperature and rainfall events in Indian region irrespective of model biases is investigated. It is found that model is able to predict extreme temperature events accurately with sufficiently long lead time (7 days). In case of extreme rainfall at shorter lead time (3 days), model is able to predict accurately and accuracy decreases with increase in lead time. Employing bias correction methods reduced large biases in some regions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::30119354305acd111967c6965208c1a4 https://doi.org/10.1007/s12040-020-01435-8 Zobrazit plný text záznamu Full text from SpringerLink