Abstract
Probabilistic forecasting of tropical cyclone (TC) from ensemble prediction systems provides flow-dependent uncertainty associated with the model forecast and helps in better decision making. NCMRWF global and regional ensemble prediction systems (NEPS-G and NEPS-R) have been used in forecasting the intensity and track of the Super Cyclone ‘Amphan’, which hit eastern India and Bangladesh in May 2020. Observation shows very heavy rainfall (>11.5 cm/day) over West Bengal and Bangladesh on 20th May 2020. NEPS-R predicted very heavy rainfall in day-2 forecasts with a probability in the range of 50–70%. NEPS-G also could predict very heavy rainfall in day-2 forecast with probability lying in the same range but over a small area. In its day-5 forecast also, NEPS-G was able to predict very heavy rainfall with a probability lying in the range of 30–50%. The prediction of time and magnitude of the maximum intensity by NEPS-R was predicted better from the initial condition of 00 UTC 16th May 2020. Prediction of intensification is better in NEPS-R forecast. Both NEPS-G and NEPS-R are under-dispersive in 10 m maximum wind forecasting. The RMSE-spread relationship of maximum wind speed is better in the NEPS-R forecast till 72 hrs forecast lead time. The reliability of both NEPS-G and NEPS-R strike probability forecasts is good and NEPS-G shows better reliability at lower probability values. The mean direct position error (DPE) from NEPS-G does not exceed 350 km in day-5 and 270 km in day-3 forecast lead time. The mean DPE of NEPS-R forecast is about 175 km in day-3 forecast lead time. Both NEPS-G and NEPS-R predicted early landfall, but the error in the landfall time does not exceed 3 hrs within the last 72 hrs before landfall. NEPS-R at short range and NEPS-G at longer range show reasonable skill in prediction of tropical cyclone ‘Amphan’.
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Acknowledgements
The authors gratefully acknowledge the Ministry of Earth Sciences, Government of India for providing encouragement and required resources to carry out this research. The authors acknowledge India Meteorological Department (IMD) for the surface wind and best track observations used for verification of the model forecasts.
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Abhijit Sarkar: Conception of the idea, design and drafting of the manuscript, analysis and interpretation of the results. S Kiran Prasad: Conception of the idea, contribution of the results from regional ensemble prediction system, analysis and interpretation of results, preparation of the original and revised draft of the manuscript, critical review and important intellectual input. Ashu Mamgain: Implementation of the global ensemble prediction system. Anumeha Dube: Contribution to the verification of the model output, drafting and important intellectual input. Paromita Chakraborty: Conception of the idea, graphical presentation of the results from global ensemble prediction system, preparation of the original and revised draft of the manuscript, critical review, important intellectual input and correspondence. Sushant Kumar: Verification of model output, critical review, and important intellectual input. Sagili Karunasagar: Verification of the model output, critical review, and analysis of the results. Mohan S Thota: Graphical presentations, analysis of the results, and critical review. Gauri Shanker: Graphical presentations of results, preparation of the draft of the manuscript, and critical review. Raghavendra Ashrit: Conception of the idea, verification of the model output, critical review, and important intellectual input. A K Mitra: Conception of the idea, interpretation of data, critical review, and important intellectual input.
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Communicated by Parthasarathi Mukhopadhyay
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Sarkar, A., Prasad, S.K., Mamgain, A. et al. Probabilistic forecasting of Super Cyclone ‘Amphan’ using NCMRWF global and regional ensemble prediction systems. J Earth Syst Sci 131, 260 (2022). https://doi.org/10.1007/s12040-022-01985-z
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DOI: https://doi.org/10.1007/s12040-022-01985-z