Sensitivity of tropical cyclone Jal simulations to physics parameterizations

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.

The efficiency of the Weather Research and Forecasting (WRF) model for simulating typhoons

“…In this part, two sets of simulations were defined according to the previous studies by Chandrasekar and Balaji (2012), and Angevine (2010), which were considered as the best physics options for wind prediction. The simulations are indicated by abbreviations of Sim 7, and Sim 8, respectively.…”

“…Angevine (2010) presented that Mellor Yamada Janjic (PBL and surface layer) with a combination of 5-layer thermal diffusion (land surface), Eta (microphysics), RRTM (long-wave radiation), Dudhia (shortwave radiation), KF (cumulus parameterization) showed small differences in assessing important parameters like SST and LHF, when PBL and surface layer changed to TEMF. Chandrasekar and Balaji (2012) also investigated the sensitivity of numerical simulations of tropical cyclones to physics parameterizations, with a view to determining the best set of physics options for prediction of cyclones originating in the north Indian Ocean. In another study by Mandal et al (2004), the sensitivity of the MM5 model was investigated, with respect to the tracking and intensity of tropical cyclones over the north Indian Ocean.…”

Effects of the Representation of Convection on the Modelling of Hurricane Tomas (2010)

“…Several studies [3][4][5][6] have explored the Weather Research and Forecasting (WRF) model predictive ability sensitivity to its different physical parameterizations, that is, to the effects of varying the computational horizontal and vertical resolutions and the number of domains.…”

“…In a study of the sensitivity in simulations of TC Jal (2010) to WRF physics parameterizations, Chandrasekar and Balaji [4] used a setup of 3 domains of 90, 30, and 10 km of horizontal resolution, respectively, with the scope of determining the best combination of physics schemes for track and intensity forecasts. They showed that their best set of physics combination worked properly for track prediction but variably for predicted cyclone intensity, with the cumulus parameterization having more impact on intensity prediction than any of the other physics subgrid schemes, whereas for 2 Advances in Meteorology both track and intensity prediction skill, it was the cumulus together with the PBL and microphysics parameterizations that played a larger role than the other physics schemes (land surface and radiation) of the model.…”

A comparative evaluation of impact of domain size and parameterization scheme on simulation of tropical cyclones in the Bay of Bengal

“…Similarly, the tropical cyclones are primarily driven by convective heating, and thus, representation of convection plays a very important role in simulation of tropical cyclones. The importance of convection and thus convective parameterization scheme in mesoscale simulation is well known, and a large number of studies [Seth and Giorgi, 1998;Liang et al, 2001;Landman et al, 2005;Stensrud, 2007;Hogan and Pauley, 2007;Bao et al, 2012;Chandrasekar and Balaji, 2012;Deshpande et al, 2010Deshpande et al, , 2012 have examined this issue in the context of various mesoscale systems over different regions [Gomez et al, 2011]. While the importance of domain size for simulation of extreme rainfall events has been demonstrated [Goswami et al, 2012], it is not clear however if such sensitivity to size of the domain also holds for atmospheric systems of larger scales, such as tropical cyclones.…”