Assimilation of satellite and other data for the forecasting of tropical cyclones over NIO
Keywords:OSE, FSOI, Tropical cyclone
Tropical Cyclones that occur over the North Indian Ocean (NIO) are warm cored, highly devastating and short-lived compared to other oceanic basins. Numerical prediction of these cyclones is mainly an initial value problem. Accuracy of the initial position largely depends on forecasting model, density & quality of observations and data assimilation scheme. State of the art numerical modeling systems are able to predict the genesis of most cyclonic systems reasonably well, but often, they fail to maintain the correct position and intensity. Satellite observations play an important role in cyclone prediction as they also cover data sparse open ocean. Often intensity and structural characteristics of these systems need to be inferred from the remotely sensed data. Satellite observations are increasingly being used to better initialize the tropical cyclones' location and intensity in the NWP systems. This study highlights India's efforts in the reception and assimilation of satellite and various other observations from different sources. The impacts of these observations are studied by carrying out Observing System Experiment (OSE) and through Forecast Sensitivity Observation Impact (FSOI) studies. Some of the recent OSEs on Tropical Cyclones over the NIO and a list of more beneficial observations through FSOI are presented in this paper.
How to Cite
Copyright (c) 2021 MAUSAM
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
All articles published by MAUSAM are licensed under the Creative Commons Attribution 4.0 International License. This permits anyone.
Anyone is free:
- To Share - to copy, distribute and transmit the work
- To Remix - to adapt the work.
Under the following conditions:
- Share - copy and redistribute the material in any medium or format
- Adapt - remix, transform, and build upon the material for any purpose, even