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Sensitivity of tropical cyclone Jal simulations to physics parameterizations
R. Chandrasekar,
Published in Indian Academy of Sciences
2012
Volume: 121
   
Issue: 4
Pages: 923 - 946
Abstract
In this study, the sensitivity of numerical simulations of tropical cyclones to physics parameterizations is carried out with a view to determine the best set of physics options for prediction of cyclones originating in the north Indian Ocean. For this purpose, the tropical cyclone Jal has been simulated by the advanced (or state of science) mesoscale Weather Research and Forecasting (WRF) model on a desktop mini super computer CRAY CX1 with the available physics parameterizations. The model domain consists of one coarse and two nested domains. The resolution of the coarse domain is 90 km while the two nested domains have resolutions of 30 and 10 km, respectively. The results from the inner most domain have been considered for analyzing and comparing the results. Model simulation fields are compared with corresponding analysis or observation data. The track and intensity of simulated cyclone are compared with best track estimates provided by the Joint Typhoon Warning Centre (JTWC) data. Two sets of experiments are conducted to determine the best combination of physics schemes for track and intensity and it is seen that the best set of physics combination for track is not suitable for intensity prediction and the best combination for track prediction overpredicts the intensity of the cyclone. The sensitivity of the results to orography and level of nesting has also been studied. Simulations were also done for the cyclone Aila with (i) best set of physics and (ii) randomly selected physics schemes. The results of the Aila case show that the best set of physics schemes has more prediction skill than the randomly selected schemes in the case of track prediction. The cumulus (CPS), planetary boundary layer (PBL) and microphysics (MP) parameterization schemes have more impact on the track and intensity prediction skill than the other parameterizations employed in the mesoscale model. © Indian Academy of Sciences.
About the journal
JournalJournal of Earth System Science
PublisherIndian Academy of Sciences
ISSN02534126
Open AccessYes
Concepts (8)
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    Climate prediction
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    Numerical model
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    Parameterization
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    Sensitivity analysis
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    Tropical cyclone
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    Weather forecasting
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    Indian ocean
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    INDIAN OCEAN (NORTH)