scholarly journals Sensitivity of Indian summer monsoon simulation to physical parameterization schemes in the WRF model

2017 ◽  
Vol 74 (1) ◽  
pp. 43-66 ◽  
Author(s):  
JV Ratnam ◽  
SK Behera ◽  
R Krishnan ◽  
T Doi ◽  
SB Ratna
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Wrf Model ◽  
Parameterization Schemes ◽  
Physical Parameterization

scholarly journals Combinational Optimization of the WRF Physical Parameterization Schemes to Improve Numerical Sea Breeze Prediction Using Micro-Genetic Algorithm

2021 ◽  
Vol 11 (23) ◽  
pp. 11221
Author(s):  
Ji Won Yoon ◽  
Sujeong Lim ◽  
Seon Ki Park
Keyword(s):  
Genetic Algorithm ◽  
Wind Speed ◽  
Land Surface ◽  
Wrf Model ◽  
Longwave Radiation ◽  
Sea Breeze ◽  
Meteorological Variables ◽  
Parameterization Schemes ◽  
Micro Genetic Algorithm ◽  
Physical Parameterization

This study aims to improve the performance of the Weather Research and Forecasting (WRF) model in the sea breeze circulation using the micro-Genetic Algorithm (micro-GA). We found the optimal combination of four physical parameterization schemes related to the sea breeze system, including planetary boundary layer (PBL), land surface, shortwave radiation, and longwave radiation, in the WRF model coupled with the micro-GA (WRF-μGA system). The optimization was performed with respect to surface meteorological variables (2 m temperature, 2 m relative humidity, 10 m wind speed and direction) and a vertical wind profile (wind speed and direction), simultaneously for three sea breeze cases over the northeastern coast of South Korea. The optimized set of parameterization schemes out of the WRF-μGA system includes the Mellor–Yamada–Nakanishi–Niino level-2.5 (MYNN2) for PBL, the Noah land surface model with multiple parameterization options (Noah-MP) for land surface, and the Rapid Radiative Transfer Model for GCMs (RRTMG) for both shortwave and longwave radiation. The optimized set compared with the various other sets of parameterization schemes for the sea breeze circulations showed up to 29 % for the improvement ratio in terms of the normalized RMSE considering all meteorological variables.

scholarly journals Evaluation of upper tropospheric humidity from NCEP analysis and WRF Model Forecast with Kalpana observation during Indian summer monsoon 2010

2012 ◽  
Vol 19 (2) ◽  
pp. 152-160 ◽  
Author(s):  
Prashant Kumar ◽  
Munn V. Shukla ◽  
Pradeep K. Thapliyal ◽  
Jagat H. Bisht ◽  
P. K. Pal
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Wrf Model ◽  
Model Forecast ◽  
Upper Tropospheric Humidity

scholarly journals Evaluation of the Simulation of Typhoon Lekima (2019) Based on Different Physical Parameterization Schemes and FY-3D Satellite’s MWHS-2 Data Assimilation

2021 ◽  
Vol 13 (22) ◽  
pp. 4556
Author(s):  
Dongmei Xu ◽  
Xuewei Zhang ◽  
Hong Li ◽  
Haiying Wu ◽  
Feifei Shen ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Wrf Model ◽  
Background Field ◽  
Weather Research And Forecasting ◽  
Initial Field ◽  
Parameterization Schemes ◽  
Microwave Humidity Sounder ◽  
Radiance Data ◽  
Physical Parameterization

In this study, the case of super typhoon Lekima, which landed in Jiangsu and Zhejiang Province on 4 August 2019, is numerically simulated. Based on the Weather Research and Forecasting (WRF) model, the sensitivity experiments are carried out with different combinations of physical parameterization schemes. The results show that microphysical schemes have obvious impacts on the simulation of the typhoon’s track, while the intensity of the simulated typhoon is more sensitive to surface physical schemes. Based on the results of the typhoon’s track and intensity simulation, one parameterization scheme was further selected to provide the background field for the following data assimilation experiments. Using the three-dimensional variational (3DVar) data assimilation method, the Microwave Humidity Sounder-2 (MWHS-2) radiance data onboard the Fengyun-3D satellite (FY-3D) were assimilated for this case. It was found that the assimilation of the FY-3D MWHS-2 radiance data was able to optimize the initial field of the numerical model in terms of the model variables, especially for the humidity. Finally, by the inspection of the typhoon’s track and intensity forecast, it was found that the assimilation of FY-3D MWHS-2 radiance data improved the skill of the prediction for both the typhoon’s track and intensity.

Evaluation of Upper Tropospheric Humidity in WRF Model during Indian Summer Monsoon

2019 ◽  
Vol 55 (4) ◽  
pp. 575-588
Author(s):  
Attada Raju ◽  
Prashant Kumar ◽  
Anant Parekh ◽  
K. Ravi Kumar ◽  
C. Nagaraju ◽  
...  
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Wrf Model ◽  
Upper Tropospheric Humidity

Simulation of the Indian summer monsoon regional climate using advanced research WRF model

2012 ◽  
Vol 33 (5) ◽  
pp. 1195-1210 ◽  
Author(s):  
C. V. Srinivas ◽  
D. Hariprasad ◽  
D. V. Bhaskar Rao ◽  
Y. Anjaneyulu ◽  
R. Baskaran ◽  
...  
Keyword(s):  
Summer Monsoon ◽  
Indian Summer Monsoon ◽  
Regional Climate ◽  
Wrf Model

scholarly journals Sensitivity Study of WRF Simulations over Tanzania for Extreme Events during Wet and Dry Seasons

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 459
Author(s):  
Abubakar Lungo ◽  
Sangil Kim ◽  
Meiyan Jiang ◽  
Giphil Cho ◽  
Yongkuk Kim
Keyword(s):  
Wrf Model ◽  
Sensitivity Study ◽  
Cloud Microphysics ◽  
Dry Season ◽  
Grid Spacing ◽  
Wet Season ◽  
Parameterization Schemes ◽  
Dry Seasons ◽  
Physical Parameterization ◽  
Wet And Dry Seasons

Precipitation prediction is important to help mitigate the effects of drought and floods on various social and economic activities. This research is to improve the forecasting skill over Tanzania by providing suitable combinations of physical parameterization schemes and horizontal grid spacing of the Weather Research Forecasting (WRF) model for daily forecasting over Tanzania. The performance of different schemes on the precipitation systems during the wet and dry seasons over Tanzania is evaluated such that the sensitivity tests was performed for the WRF model at different horizontal resolutions, and for different physical parameterization schemes (convective and cloud microphysics). The results showed that the improved grid spacing was better at completing forecasts during the wet season, but had little significant impacts during the dry season. Model simulations with combinations of Lin et al. microphysics and the multiscale Kain–Fritsch scheme showed greater success during the both seasons; therefore, these combinations were recommended for Tanzania to resolve weather systems during the wet and dry season simulations, respectively.

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