Sensitivity of different convective parameterization schemes on tropical cyclone prediction using a mesoscale model

2014 ◽  
Vol 73 (2) ◽  
pp. 213-235 ◽  
Author(s):  
Saji Mohandas ◽  
Raghavendra Ashrit
2008 ◽  
Vol 136 (3) ◽  
pp. 865-879 ◽  
Author(s):  
Kun-Hsuan Chou ◽  
Chun-Chieh Wu

Abstract Issues concerning the initialization and simulation of tropical cyclones by integrating both dropwindsonde data and a bogused vortex into a mesoscale model have been studied. A method is proposed to combine dropwindsonde data with a bogused vortex for tropical cyclone initialization and to improve track and intensity prediction. A clear positive impact of this proposed method on both the tropical cyclone track and intensity forecasts in a mesoscale model is demonstrated in three cases of typhoons, including Meari (2004), Conson (2004), and Megi (2004). The effectiveness of the proposed method in improving the track and intensity forecasts is also demonstrated in the evaluation of all 10 cases of Dropwindsonde Observations for Typhoon Surveillance near the Taiwan Region (DOTSTAR) missions in 2004. This method provides a useful and practical means to improve operational tropical cyclone prediction with dropwindsonde observations.


2007 ◽  
Vol 64 (6) ◽  
pp. 1811-1834 ◽  
Author(s):  
Robert F. Rogers ◽  
Michael L. Black ◽  
Shuyi S. Chen ◽  
Robert A. Black

This study presents a framework for comparing hydrometeor and vertical velocity fields from mesoscale model simulations of tropical cyclones with observations of these fields from a variety of platforms. The framework is based on the Yuter and Houze constant frequency by altitude diagram (CFAD) technique, along with a new hurricane partitioning technique, to compare the statistics of vertical motion and reflectivity fields and hydrometeor concentrations from two datasets: one consisting of airborne radar retrievals and microphysical probe measurements collected from tropical cyclone aircraft flights over many years, and another consisting of cloud-scale (1.67-km grid length) tropical cyclone simulations using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Such comparisons of the microphysics fields can identify biases in the simulations that may lead to an identification of deficiencies in the modeling system, such as the formulation of various physical parameterization schemes used in the model. Improvements in these schemes may potentially lead to better forecasts of tropical cyclone intensity and rainfall. In Part I of this study, the evaluation framework is demonstrated by comparing the radar retrievals and probe measurements to MM5 simulations of Hurricanes Bonnie (1998) and Floyd (1999). Comparisons of the statistics from the two datasets show that the model reproduces many of the gross features seen in the observations, though notable differences are evident. The general distribution of vertical motion is similar between the observations and simulations, with the strongest up- and downdrafts making up a small percentage of the overall population in both datasets, but the magnitudes of vertical motion are weaker in the simulations. The model-derived reflectivities are much higher than observed, and correlations between vertical motion and hydrometeor concentration and reflectivity show a much stronger relationship in the model than what is observed. Possible errors in the data processing are discussed as potential sources of differences between the observed and simulated datasets in Part I. In Part II, attention will be focused on using the evaluation framework to investigate the role that different model configurations (i.e., different resolutions and physical parameterizations) play in producing different microphysics fields in the simulation of Hurricane Bonnie. The microphysical and planetary boundary layer parameterization schemes, as well as higher horizontal and vertical resolutions, will be tested in the simulation to identify the extent to which changes in these schemes are reflected in improvements of the statistical comparisons with the observations.


2006 ◽  
Vol 21 (4) ◽  
pp. 663-669 ◽  
Author(s):  
Dongliang Wang ◽  
Xudong Liang ◽  
Yihong Duan ◽  
Johnny C. L. Chan

Abstract The fifth-generation Pennsylvania State University–National Center for Atmospheric Research nonhydrostatic Mesoscale Model is employed to evaluate the impact of the Geostationary Meteorological Satellite-5 water vapor and infrared atmospheric motion vectors (AMVs), incorporated with the four-dimensional variational (4DVAR) data assimilation technique, on tropical cyclone (TC) track predictions. Twenty-two cases from eight different TCs over the western North Pacific in 2002 have been examined. The 4DVAR assimilation of these satellite-derived wind observations leads to appreciable improvements in the track forecasts, with average reductions in track error of ∼5% at 12 h, 12% at 24 h, 10% at 36 h, and 7% at 48 h. Preliminary results suggest that the improvement depends on the quantity of the AMV data available for assimilation.


2012 ◽  
Vol 2012 ◽  
pp. 1-18 ◽  
Author(s):  
Sujata Pattanayak ◽  
U. C. Mohanty ◽  
Krishna K. Osuri

The present study is carried out to investigate the performance of different cumulus convection, planetary boundary layer, land surface processes, and microphysics parameterization schemes in the simulation of a very severe cyclonic storm (VSCS) Nargis (2008), developed in the central Bay of Bengal on 27 April 2008. For this purpose, the nonhydrostatic mesoscale model (NMM) dynamic core of weather research and forecasting (WRF) system is used. Model-simulated track positions and intensity in terms of minimum central mean sea level pressure (MSLP), maximum surface wind (10 m), and precipitation are verified with observations as provided by the India Meteorological Department (IMD) and Tropical Rainfall Measurement Mission (TRMM). The estimated optimum combination is reinvestigated with six different initial conditions of the same case to have better conclusion on the performance of WRF-NMM. A few more diagnostic fields like vertical velocity, vorticity, and heat fluxes are also evaluated. The results indicate that cumulus convection play an important role in the movement of the cyclone, and PBL has a crucial role in the intensification of the storm. The combination of Simplified Arakawa Schubert (SAS) convection, Yonsei University (YSU) PBL, NMM land surface, and Ferrier microphysics parameterization schemes in WRF-NMM give better track and intensity forecast with minimum vector displacement error.


2012 ◽  
pp. 15-28 ◽  
Author(s):  
J. D. DOYLE ◽  
Y. JIN ◽  
R. M. HODUR ◽  
S. CHEN ◽  
H. JIN ◽  
...  

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