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Improving the understanding of the predictability of extreme weather events through data assimilation and ensemble approaches
Year |
Title of Project |
Funding Agency |
Project cost |
2023 – 2025
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Implementation of Ensemble Forecast Sensitivity Approach to Estimate the Impact of Observations in IMD GFS forecast
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Monsoon Mission (Ministry of Earth Science) |
58.0 Lakhs |
2022 – 2024 | Improving the Prediction of Thunderstorms using Dual – Resolution Hybrid Ensemble – Variational Data Assimilation System in WRF model
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Ministry of Earth Science (MoES) |
75.0 Lakhs |
2018 – 2019
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Implementing 4DVAR Data Assimilation in SASE forecasts |
SASE, DRDO |
10.0 Lakhs |
2014 – 2017
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Use of Hybrid Ensemble Data Assimilation system in NARL operational forecasts
|
ASRG |
8.0 Lakhs |
Student Name | Title of Thesis & Year of completion | Current Position |
Dr. Rekha Bharali Gogoi
| Impact of Ensemble Derived Flow-dependent Background Error Covariance in a Data Assimilation System for Regional-scale NWP model
Year: 2021 |
Scientist – F NESAC, DoS, Umiam |
Dr. Arpita Munsi
(Co-guided with Dr. Amit P Kesarkar, NARL)
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Understanding the helical evolution of tropical cyclones and their interaction with the upper ocean
Year: 2022 |
Research Associate, NARL |
Dr. Babitha George
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Predictability and Dynamics of Extreme Weather Events over the Indian Subcontinent using Ensemble Sensitivity Analysis in EnKF Data Assimilation System
Year: 2023 | Earth Sciences department, Vrije Universiteit Amsterdam, Netherlands |
A probabilistic method has been developed to identify regions of Initial Condition uncertainty in the NWP model
Forecast errors can be reduced if observations are assimilated in regions with the largest percentage of analysis error growth. In our recent study, the regions where additional observations will impact the forecasts over the Indian subcontinent during the summer monsoon season have been identified using the ensemble approach.
You may read the details here: https://assets.researchsquare.com/files/rs-2893417/v1/74e2a094-565d-41f1-b004-08d742468068.pdf?c=1683814947