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COSPAR Training and Capacity Building Course , 1 – 12 Nov 2010, Fortaleza, Brazil

Influence of Land Use Land Cover (LULC) on Cyclone Track Prediction – A Study during AILA Cyclone. D. V. Mahalakshmi and K. V. S. Badarinath. Atmospheric Science Section, National Remote Sensing Centre, Dept. of Space, Govt. of India Hyderabad, India Email – badrinath_kvs@nrsa.gov.in.

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COSPAR Training and Capacity Building Course , 1 – 12 Nov 2010, Fortaleza, Brazil

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  1. Influence of Land Use Land Cover (LULC) on Cyclone Track Prediction – A Study during AILA Cyclone D. V. Mahalakshmi and K. V. S. Badarinath Atmospheric Science Section, National Remote Sensing Centre, Dept. of Space, Govt. of India Hyderabad, India Email – badrinath_kvs@nrsa.gov.in COSPAR Training and Capacity Building Course , 1 – 12 Nov 2010, Fortaleza, Brazil

  2. OBJECTIVE • To study the influence of Land Use/ Land Cover (LULC) Change on the forecasting of cyclone intensity and track prediction. In the Mesoscale Model(MM5) terrain, Indian portion of LU/LC data from USGS was replaced IRS AWiFS derived LULC map.

  3. AILA CYCLONE METEOSAT IMAGES 22May2009_00UTC

  4. 22May2009_06UTC

  5. 22May2009_12UTC

  6. 22May2009_18UTC

  7. 23May2009_00UTC

  8. 23May2009_06UTC

  9. 23May2009_12UTC

  10. 23May2009_18UTC

  11. 24May2009_06UTC

  12. 24May2009_12UTC

  13. 24May2009_18UTC

  14. 25May2009_00UTC

  15. 25May2009_06UTC

  16. 25May2009_12UTC

  17. 25May2009_18UTC

  18. 26May2009_00UTC

  19. INTRODUCTION Land use/Land cover (LULC) are one of the dynamic features that under go rapid changes due to anthropogenic and associated developmental activities . Accurate prediction of tropical cyclone track and intensity are challenging task for any operational meteorological agency as it involves using of state of the art numerical models and realistic data sets . Land use/land cover changes influence energy fluxes through surface roughness changes. (The present study pertains to AILA cyclone that occurred in BoB during May 22 – 25, 2009.)

  20. Comparison of USGS & AWiFS derived classified data

  21. AWiFS derived Land use/ Land cover data input for NWP models (a) (b) USGS-LULC AWiFS -LULC Fig-3 Comparison of 2min Global USGS LU/LC and AWiFS derived Indian region replaced USGS data Evergreen Forest Deciduous Forest /Scrub Water • So far USGS derived global coverage with resolution of 1 degree,30,10,5,2 minutes and 30 seconds has been used to run Mesoscale Models. (1993 AVHRR based) • IRS-AWiFS derived LU/LC with 56 m resolution have been scaled to different resolutions & Indian region is replaced with AWiFS derived data and made compatible to mesoscale model run. • WRF/MM5 compatible inputs provided to CTCZ program, NCMRWF, SHAR Centre, IMD for evaluation and operational use. • As per user feedback, model output provides better results with the use of AWiFS derived LULC layer instead of using USGS derived LULC layers. Fig1-30sec USGS LU/LC Fig 2 -30s AWiFS derived LU/LC Prediction between 22nd June 2008 06-12 UTC Fig4 - SHAR MM5 Prediction of Acc. Rain (mm) on 21 June 2008 using (a) Land use USGS(2min) and (b) AWiFS derived Land use (2min)

  22. IRS – P6 ( RESOURCESAT-1)

  23. MM5 Flow Chart

  24. MM5 Model Configuration • Model integration: 0000 UTC 22 May 2009 to 12UTC of 26May2009. • NCEP FNL data at 1010 resolution • Domain size of 7498 grid points.

  25. USGS AWiFS 22May2009_12UTC_PSLV_850hPa

  26. AWiFS USGS 23May2009_12UTC_PSLV_850hPa

  27. USGS AWiFS 24May2009_12UTC_PSLV_850hPa

  28. USGS AWiFS 25May2009_09UTC_PSLV_850hPa

  29. USGS AWiFS 26May2009_09UTC_PSLV_850hPa

  30. Comparison between Model and Actual Track

  31. Comparison between Model and Actual Observation of Central Pressure & Wind Speed

  32. Conclusions • The movement of the system was better simulated in terms of direction and intensity with AWiFS LULC data compared to that in USGS. This has been attributed to better representation of surface roughness and energy fluxes with the current land use/land cover data set. • The intensity of tropical cyclones in terms of MSLP and maximum sustainable wind illustrates that USGS has a tendency to intensify the system earlier than actual observation. AWiFS gives reasonably good results for the time variation of MSLP and wind matching with the observations.

  33. Thanks for your kind attention

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