Future projection of maximum cyclone density region and landfall locations over the North Indian Ocean using COAWST model
Abstract
Cyclone is one of the severe weather phenomenon that is extremely hazardous to the coastal regions. The accuracy and advancement in the prediction of cyclone induced hazards such as storm surge, coastal erosion, torrential rainfall can considerably improve the mitigation plan and policies in order to save and rescue the people and property. In the present study, the cyclone density estimation studied on the basis of IB-TrACS data of number of cyclones for the 26 years (1979 to 2014) time duration over North Indian Ocean (NIO). This analysis suggested that over NIO, the maximum number of cyclones occurrence was in the post-monsoon season. The historical temperature and salinity fields from the EN4 data of Met Office Hadely Center for the post monsoon season of the same time period (1979 to 2014) were utilised to calculate the trend per decade over NIO. The student t-test analysis for the trend of temperature and salinity has proved 95% significance over most of the region of NIO. The combination of freshening and warming trend per decade had explained the maximum cyclone density over the head Bay of Bengal (BoB) region for the considered time duration. Under the global warming conditions, it is required to investigate the relationship between changing temperature and salinity fields and variation in maximum cyclone density region along with most probable landfall locations. In order to understand this, several idealistic experiments were designed where different intensity cyclones were generated on the maximum density location over NIO. The COAWST (Coupled Ocean-Atmosphere Wave-Sediment Transport Modeling System) model simulations were performed by providing open boundaries and surface forcing from 13 multi-model ensemble mean of CMIP5 for the future time period of 30 years (2070-2100). The results depicted a strong response towards the changing salinity in contrast to changing temperature for the future global warming scenario.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2018
- Bibcode:
- 2018AGUFM.A43Q3398P
- Keywords:
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- 3315 Data assimilation;
- ATMOSPHERIC PROCESSESDE: 3360 Remote sensing;
- ATMOSPHERIC PROCESSESDE: 3372 Tropical cyclones;
- ATMOSPHERIC PROCESSESDE: 4313 Extreme events;
- NATURAL HAZARDS