RESEARCH ARTICLE


Influence of Land Use Land Cover on Cyclone Track Prediction – A Study During Aila Cyclone



K. V.S. Badarinath1, D. V. Mahalakshmi*, 1, Satyaban Bishoyi Ratna2
1 Atmospheric Science Section, Oceanography Division, Atmospheric and Ocean Sciences Group, National Remote Sensing Center, Hyderabad-500625, India
2 Application Laboratory, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokohama, Japan


Article Metrics

CrossRef Citations:
0
Total Statistics:

Full-Text HTML Views: 165
Abstract HTML Views: 568
PDF Downloads: 227
Total Views/Downloads: 960
Unique Statistics:

Full-Text HTML Views: 114
Abstract HTML Views: 409
PDF Downloads: 180
Total Views/Downloads: 703



© 2012 Badarinathet al.;

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* ddress correspondence to this author at the Atmospheric Science Section, Oceanography Division, Atmospheric and Ocean Sciences Group, National Remote Sensing Center, Hyderabad-500625, India; Tel: +040-23884558; E-mail: mahameteorology@gmail.com


Abstract

Land-surface processes are one of the important drivers for weather and climate systems over the tropics. Realistic representation of land surface processes in mesoscale models over the region will help accurate simulation of numerical forecasts. The present study examines the influence of Land Use/ Land Cover Change (LULC) on the forecasting of cyclone intensity and track prediction using Mesoscale Model (MM5). Gridded land use/land cover data set over the Indian region compatible with the MM5 model were generated from Indian Remote Sensing Satellite (IRS-P6) Advanced Wide Field Sensor (AWiFS) for the year 2007-2008. A case study of simulation of ‘Aila’ cyclone has been considered to see the impact of these two sets of LULC data with the use of MM5 model. Results of the study indicated that incorporation of current land use/land cover data sets in mesoscale model provides better forecasting of cyclonic track.

Keywords: Mesoscale model, Cyclone Track, Land Use/Land Cover, Satellite Data, Aila Cyclone.