PreprintArticleVersion 1Preserved in Portico This version is not peer-reviewed
Performance of High-Resolution WRF Modeling System in Simulation of Severe Tropical Cyclones over the Bay of Bengal Using IMDAA Regional Reanalysis Dataset
Version 1
: Received: 6 February 2024 / Approved: 7 February 2024 / Online: 7 February 2024 (13:14:08 CET)
How to cite:
Koteshwaramma, T.; Singh, K.S.; Nayak, S. Performance of High-Resolution WRF Modeling System in Simulation of Severe Tropical Cyclones over the Bay of Bengal Using IMDAA Regional Reanalysis Dataset. Preprints2024, 2024020432. https://doi.org/10.20944/preprints202402.0432.v1
Koteshwaramma, T.; Singh, K.S.; Nayak, S. Performance of High-Resolution WRF Modeling System in Simulation of Severe Tropical Cyclones over the Bay of Bengal Using IMDAA Regional Reanalysis Dataset. Preprints 2024, 2024020432. https://doi.org/10.20944/preprints202402.0432.v1
Koteshwaramma, T.; Singh, K.S.; Nayak, S. Performance of High-Resolution WRF Modeling System in Simulation of Severe Tropical Cyclones over the Bay of Bengal Using IMDAA Regional Reanalysis Dataset. Preprints2024, 2024020432. https://doi.org/10.20944/preprints202402.0432.v1
APA Style
Koteshwaramma, T., Singh, K.S., & Nayak, S. (2024). Performance of High-Resolution WRF Modeling System in Simulation of Severe Tropical Cyclones over the Bay of Bengal Using IMDAA Regional Reanalysis Dataset. Preprints. https://doi.org/10.20944/preprints202402.0432.v1
Chicago/Turabian Style
Koteshwaramma, T., Kuvar Satya Singh and Sridhara Nayak. 2024 "Performance of High-Resolution WRF Modeling System in Simulation of Severe Tropical Cyclones over the Bay of Bengal Using IMDAA Regional Reanalysis Dataset" Preprints. https://doi.org/10.20944/preprints202402.0432.v1
Abstract
This study examines the performance of the Indian Monsoon Data Assimilation and Analy-sis (IMDAA) in predicting five extremely severe cyclonic storms (ESCS) over the Bay of Bengal. The Advanced Research version of the WRF (ARW) model is utilized for this analysis over the last two decades. The initial and lateral boundary conditions are derived from the IMDAA datasets with a horizontal resolution of 0.12° × 0.12°. Five ESCSs from the past two decades are considered: Sidr 2007, Phailin 2013, Hudhud 2014, Fani 2019, and Amphan 2020. The model is integrated up to 96 hours using double nested domains of 12 km and 4 km. Model performance is evaluated using the 4 km results, compared with available observational datasets, including the best-fit data from the India Meteorological Department (IMD), The Tropical Rainfall Measuring Mission (TRMM) satellite, and Doppler Weather Radar (DWR). The results indicate that IMDAA provides accurate forecasts for ESCSs Fani, Hudhud, and Sidr in terms of track, intensity, and mean sea level pressure, aligning well with IMD observational datasets. However, Sidr's track deviates more from the observations. The calculated mean absolute maximum sustained wind speed errors range from 8.4 m/s to 10.6 m/s from day-1 to day-4, while mean track errors range from 114 km to 496 km during the same period. Statistical analysis, including bias, mean error, and standard deviation, underscores the significance of ESCS prediction. The discussion also covers rainfall prediction, maximum reflectivity, and the associated structure of the storms.
Keywords
IMDAA; ESCS; WRF; bay of bengal; reanalysis
Subject
Environmental and Earth Sciences, Atmospheric Science and Meteorology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
