12/3/2015 3:16 AM 1 Influence of Land Use Land Cover (LULC) on Cyclone Track Prediction – A Study during AILA Cyclone COSPAR Training and Capacity Building.

Slides:

Advertisements

Similar presentations

What’s quasi-equilibrium all about?

Advertisements

Introduction to data assimilation in meteorology Pierre Brousseau, Ludovic Auger ATMO 08,Alghero, september 2008.

SNPP VIIRS green vegetation fraction products and application in numerical weather prediction Zhangyan Jiang 1,2, Weizhong Zheng 3,4, Junchang Ju 1,2,

The use of a high resolution model in a private environment

A numerical simulation of urban and regional meteorology and assessment of its impact on pollution transport A. Starchenko Tomsk State University.

An Intercomparison of Surface Observations and High-Resolution Forecasting Model Output for the Lake Okeechobee Region By Kathryn Shontz July 19, 2006.

NOAA/NWS Change to WRF 13 June What’s Happening? WRF replaces the eta as the NAM –NAM is the North American Mesoscale “timeslot” or “Model Run”

03/06/2015 Modelling of regional CO2 balance Tiina Markkanen with Tuula Aalto, Tea Thum, Jouni Susiluoto and Niina Puttonen.

Issues in Very High Resolution Numerical Weather Prediction Over Complex Terrain in Juneau, Alaska Don Morton 1,2, Delia Arnold 3,4, Irene Schicker 3,

Update of A Rapid Prototyping Capability Experiment to Evaluate CrIS / ATMS Observations for a Mesoscale Weather Event Valentine G. Anantharaj Xingang.

Weather Model Background ● The WRF (Weather Research and Forecasting) model had been developed by various research and governmental agencies became the.

Determining the Local Implications of Global Warming Professor Clifford Mass, Eric Salathe, Patrick Zahn, Richard Steed University of Washington.

Forecasting Tropical cyclones Regional Training Workshop on Severe Weather Forecasting and Warning Services (Macao, China, 9 April 2013)

Satellite Application on Weather Services in Japan Yasushi SUZUKI Japan Weather Association 12nd. GPM Applications Workshop, June/9-10/2015.

Satellite Imagery and Remote Sensing NC Climate Fellows June 2012 DeeDee Whitaker SW Guilford High Earth/Environmental Science & Chemistry.

1 Tropical cyclone (TC) trajectory and storm precipitation forecast improvement using SFOV AIRS soundings Jun Tim Schmit &, Hui Liu #, Jinlong Li.

The National Environmental Agency of Georgia L. Megrelidze, N. Kutaladze, Kh. Kokosadze NWP Local Area Models’ Failure in Simulation of Eastern Invasion.

RDFS Rapid Deployment Forecast System Visit at: Registration required.

Earth Science Division National Aeronautics and Space Administration 18 January 2007 Paper 5A.4: Slide 1 American Meteorological Society 21 st Conference.

Modelling of Acid deposition in South Asia Magnuz Engardt Swedish Meteorological and Hydrological Institute (SMHI) Introduction to Acid deposition.

Land Processes Group, NASA Marshall Space Flight Center, Huntsville, AL Response of Atmospheric Model Predictions at Different Grid Resolutions Maudood.

PHAiRS : Dust Modeling PHAiRS : Dust Modeling Dazhong Yin Slobodan Nickovic William A. Sprigg March 14, 2006.

In this study, HWRF model simulations for two events were evaluated by analyzing the mean sea level pressure, precipitation, wind fields and hydrometeors.

Remote Sensing Derived Land Use/Cover Data for Urban Modeling in MM5 and WRF Susanne Grossman-Clarke 1 Joseph A. Zehnder 1 William Stefanov 2 Matthias.

Non-hydrostatic Numerical Model Study on Tropical Mesoscale System During SCOUT DARWIN Campaign Wuhu Feng 1 and M.P. Chipperfield 1 IAS, School of Earth.

1/26 APPLICATION OF THE URBAN VERSION OF MM5 FOR HOUSTON University Corporation for Atmospheric Research Sylvain Dupont Collaborators: Steve Burian, Jason.

USING OF METEOSAT SECOND GENERATION HIGH RESOLUTION VISIBLE DATA FOR THE IMPOVEMENT OF THE RAPID DEVELOPPING THUNDERSTORM PRODUCT Oleksiy Kryvobok Ukrainian.

Impact of global warming on tropical cyclone structure change with a 20-km-mesh high-resolution global model Hiroyuki Murakami (AESTO/MRI, Japan) Akio.

Modern Era Retrospective-analysis for Research and Applications: Introduction to NASA’s Modern Era Retrospective-analysis for Research and Applications:

Understanding hydrologic changes: application of the VIC model Vimal Mishra Assistant Professor Indian Institute of Technology (IIT), Gandhinagar

Prediction of Tropical Cyclones Chapter 9. Tropical weather data from traditional sources (surface and radiosonde) is scarce, so remote sensing via other.

Weather forecasting by computer Michael Revell NIWA

Development Mechanism of Heavy Rainfall over Gangneung Associated with Typhoon RUSA Tae-Young Lee, Nam-San Cho, Ji-Sun Kang Kun-Young Byun, Sang Hun Park.

A Numerical Study of Early Summer Regional Climate and Weather. Zhang, D.-L., W.-Z. Zheng, and Y.-K. Xue, 2003: A Numerical Study of Early Summer Regional.

Simulation of heavy precipitation events in Madeira Island using resolution of 1 km Simulation de précipitations orographiques intenses sur Madère (résolution.

Lennart Bengtsson ESSC, Uni. Reading THORPEX Conference December 2004 Predictability and predictive skill of weather systems and atmospheric flow patterns.

Shuyi S. Chen Joseph Tenerelli Rosenstiel School of Marine and Atmospheric Science University of Miami Effects of Environmental Flow and Initial Vortex.

Impact of the backscatter kinetic energy on the perturbation of ensemble members for strong convective event Jakub Guzikowski

An Atmosphere-Ocean coupled model Morris, A., Bender and Isaac Ginis, 2000 : Real-case simulations of hurricane-ocean interaction using a high-resolution.

Model evolution of a START08 observed tropospheric intrusion Dalon Stone, Kenneth Bowman, Cameron Homeyer - Texas A&M Laura Pan, Simone Tilmes, Doug Kinnison.

Ensemble variability in rainfall forecasts of Hurricane Irene (2011) Molly Smith, Ryan Torn, Kristen Corbosiero, and Philip Pegion NWS Focal Points: Steve.

Bogdan Rosa 1, Marcin Kurowski 1 and Michał Ziemiański 1 1. Institute of Meteorology and Water Management (IMGW), Warsaw Podleśna, 61

Welcome to the PRECIS training workshop

Cycling Variational Assimilation of Remotely Sensed Observations for Simulations of Hurricane Katrina S.-H. Chen 1 E. Lim 2, W.-C. Lee 3, C. Davis 2, M.

RIME A possible experiment for Advancing Antarctic Weather Prediction David H. Bromwich 1, John J. Cassano 1, Thomas R. Parish 2, Keith M. Hines 1 1 -

Vincent N. Sakwa RSMC, Nairobi

The Assessment of Typhoon Hazards at Regional-Scales in the Pacific Regions with Downscaling Numerical Experiments Tetsuya Takemi Fourth Capacity Building.

2. WRF model configuration and initial conditions  Three sets of initial and lateral boundary conditions for Katrina are used, including the output from.

ESSL Holland, CCSM Workshop 0606 Predicting the Earth System Across Scales: Both Ways Summary:Rationale Approach and Current Focus Improved Simulation.

High-resolution operational NWP for forecasting meteotsunamis

Satellite based Sensors for Agricultural Applications

Numerical Weather Forecast Model (governing equations)

Overview of Downscaling

Grid Point Models Surface Data.

Coupled atmosphere-ocean simulation on hurricane forecast

IMPROVING HURRICANE INTENSITY FORECASTS IN A MESOSCALE MODEL VIA MICROPHYSICAL PARAMETERIZATION METHODS By Cerese Albers & Dr. TN Krishnamurti- FSU Dept.

NOAA - LAPS Albers, S., 1995: The LAPS wind analysis. Wea. and Forecasting, 10, Albers, S., J. McGinley, D. Birkenheuer, and J. Smart, 1996:

Shuyi S. Chen, Ben Barr, Milan Curcic and Brandon Kerns

Application of satellite-based rainfall and medium range meteorological forecast in real-time flood forecasting in the Upper Mahanadi River basin Trushnamayee.

Satellite Sensors – Historical Perspectives

Naval Research Laboratory

Coupled Atmosphere-Wave-Ocean Modeling Experiments in Hurricanes

Runoff Simulations in Region12 (or almost the State of Texas)

Satellite Foundational Course for JPSS (SatFC-J)

NWP Strategy of DWD after 2006 GF XY DWD Feb-19.

Generation of Simulated GIFTS Datasets

A Multiscale Numerical Study of Hurricane Andrew (1992)

XIAOLEI ZOU and QINGNONG XIAO J. Atmos. Sci., 57, 報告：黃小玲

Orographic Influences on Rainfall Associated with Tropical Cyclone

The Flux Model of Orographic Rain

Presentation transcript:

12/3/2015 3:16 AM 1 Influence of Land Use Land Cover (LULC) on Cyclone Track Prediction – A Study during AILA Cyclone COSPAR Training and Capacity Building Course, 1 – 12 Nov 2010, Fortaleza, Brazil D. V. Mahalakshmi and K. V. S. Badarinath Atmospheric Science Section, National Remote Sensing Centre, Dept. of Space, Govt. of India Hyderabad, India –

12/3/2015 3:16 AM 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.

12/3/2015 3:16 AM 3 AILA CYCLONE METEOSAT IMAGES 22May2009_00UTC

12/3/2015 3:16 AM 4 22May2009_06UTC

12/3/2015 3:16 AM 5 22May2009_12UTC

12/3/2015 3:16 AM 6 22May2009_18UTC

12/3/2015 3:16 AM 7 23May2009_00UTC

12/3/2015 3:16 AM 8 23May2009_06UTC

12/3/2015 3:16 AM 9 23May2009_12UTC

12/3/2015 3:16 AM 10 23May2009_18UTC

12/3/2015 3:16 AM 11 24May2009_06UTC

12/3/2015 3:16 AM 12 24May2009_12UTC

12/3/2015 3:16 AM 13 24May2009_18UTC

12/3/2015 3:16 AM 14 25May2009_00UTC

12/3/2015 3:16 AM 15 25May2009_06UTC

12/3/2015 3:16 AM 16 25May2009_12UTC

12/3/2015 3:16 AM 17 25May2009_18UTC

12/3/2015 3:16 AM 18 26May2009_00UTC

12/3/2015 3:16 AM 19 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.) INTRODUCTION

12/3/2015 3:16 AM 20 Comparison of USGS & AWiFS derived classified data

12/3/2015 3:16 AM 21 AWiFS derived Land use/ Land cover data input for NWP models 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/LCFig 2 -30s AWiFS derived LU/LC USGS-LULCAWiFS -LULC Fig-3 Comparison of 2min Global USGS LU/LC and AWiFS derived Indian region replaced USGS data Deciduous Forest / ScrubEvergreen ForestWater 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) Prediction between 22 nd June UTC (a)(b)

12/3/2015 3:16 AM 22 IRS – P6 ( RESOURCESAT-1) PayloadsLISS-IVLISS-IIIAWiFS Spatial resolution (m) Swath (Km)23.9 (MX mode) 70.3 (PAN mode) Spectral Bands (micron) 0.52 – – – – – – – – – – – 1.70 Quantization (bits)7710

12/3/2015 3:16 AM 23 MM5 Flow Chart

12/3/2015 3:16 AM 24 MM5 Model Configuration  Model integration: 0000 UTC 22 May 2009 to 12UTC of 26May2009.  NCEP FNL data at 1 0  1 0 resolution  Domain size of 74  98 grid points.

12/3/2015 3:16 AM 25 22May2009_12UTC_PSLV_850hPa USGS AWiFS

12/3/2015 3:16 AM 26 23May2009_12UTC_PSLV_850hPa USGS AWiFS

12/3/2015 3:16 AM 27 24May2009_12UTC_PSLV_850hPa USGS AWiFS

12/3/2015 3:16 AM 28 25May2009_09UTC_PSLV_850hPa USGS AWiFS

12/3/2015 3:16 AM 29 26May2009_09UTC_PSLV_850hPa USGSAWiFS

12/3/2015 3:16 AM 30 Comparison between Model and Actual Track

12/3/2015 3:16 AM 31 Comparison between Model and Actual Observation of Central Pressure & Wind Speed

12/3/2015 3:16 AM 32  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. Conclusions

12/3/2015 3:16 AM 33