Forecasting extreme precipitation event over Munsiyari (Uttarakhand) using 3DVAR data assimilation in mesoscale model

A localized extreme precipitation event occurred over Munsiyari (Uttarakhand, India) on 2nd July 2018 causing flash floods, landslides and damage to the hydropower project. A preliminary study has been carried out by using Weather Research and Forecasting (WRF) model with three-dimensional variation...

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Bibliographic Details
Published in:Journal of Earth System Science 2020-12, Vol.129 (1), p.40, Article 40
Main Authors: Narasimha Rao, N, Shekhar, M S, Singh, G P
Format: Article
Language:English
Subjects:
Climate change
Cloud water
Data assimilation
Data collection
Earth and Environmental Science
Earth Sciences
Extreme weather
Flash flooding
Flash floods
Flood damage
Floods
Hydroelectric power
Landslides
Landslides & mudslides
Mathematical models
Microphysics
Precipitation
Precipitation forecasting
Radiation
Rain
Relative humidity
Remote sensing
Space Exploration and Astronautics
Space Sciences (including Extraterrestrial Physics
Storm damage
Temperature
Three dimensional models
Vertical velocities
Weather
Weather forecasting
Wind
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Summary:A localized extreme precipitation event occurred over Munsiyari (Uttarakhand, India) on 2nd July 2018 causing flash floods, landslides and damage to the hydropower project. A preliminary study has been carried out by using Weather Research and Forecasting (WRF) model with three-dimensional variation data assimilation technique (3DVAR) to examine the feasibility of the model to predict the localized phenomena. Sensitivity experiments were carried out with two different microphysics in the model. Results show that P3 1-category plus double moment cloud water microphysics scheme with 3DVAR in WRF simulates the quantity of precipitation closer to the observed precipitation over Munsiyari. The vertical velocity and relative humidity were also simulated well during 3DVAR data assimilation as compared to without data assimilation over study region.
ISSN:2347-4327
0253-4126
0973-774X
DOI:10.1007/s12040-019-1315-2