Influence of land use land cover on cyclone track prediction – A study during Aila cyclone

K.V.S. Badrinath; D.V. Mahalakshmi; Satyaban Bishoyi Ratna

doi:10.2174/1874282301206010033

Influence of land use land cover on cyclone track prediction – A study during Aila cyclone

K.V.S. Badrinath, D.V. Mahalakshmi, Satyaban Bishoyi Ratna

Research output: Contribution to journal › Article › peer-review

11 Citations (Scopus)

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.

Original language	English
Pages (from-to)	33-41
Number of pages	9
Journal	Open Atmospheric Science Journal
Volume	6
DOIs	https://doi.org/10.2174/1874282301206010033
Publication status	Published - Jun 2012

Keywords

Mesoscale model
Cyclone track
Land use/land cover
Satellite data
Aila Cyclone

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.2174/1874282301206010033Licence: CC BY

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Cite this

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title = "Influence of land use land cover on cyclone track prediction – A study during Aila cyclone",

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 {\textquoteleft}Aila{\textquoteright} 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",

author = "K.V.S. Badrinath and D.V. Mahalakshmi and {Bishoyi Ratna}, Satyaban",

year = "2012",

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language = "English",

volume = "6",

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AU - Badrinath, K.V.S.

AU - Mahalakshmi, D.V.

AU - Bishoyi Ratna, Satyaban

PY - 2012/6

Y1 - 2012/6

N2 - 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.

AB - 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.

KW - Mesoscale model

KW - Cyclone track

KW - Land use/land cover

KW - Satellite data

KW - Aila Cyclone

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DO - 10.2174/1874282301206010033

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JO - Open Atmospheric Science Journal

JF - Open Atmospheric Science Journal

SN - 1874-2823

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