Reanalysis Profile Downscaling with WRF Model and Sensitivity to PBL Parameterization Schemes Over a Subtropical Station

2021 ◽  
Author(s):  
Lucas Ribeiro Diaz ◽  
Daniel Caetano Santos ◽  
Pâmela Suélen Käfer ◽  
María Luján Iglesias ◽  
Nájila Souza da Rocha ◽  
...  
Keyword(s):  
Wrf Model ◽  
Parameterization Schemes ◽  
Pbl Parameterization

Reanalysis profile downscaling with WRF model and sensitivity to PBL parameterization schemes over a subtropical station

2021 ◽  
pp. 105724
Author(s):  
Lucas Ribeiro Diaz ◽  
Daniel Caetano Santos ◽  
Pâmela Suélen Käfer ◽  
María Luján Iglesias ◽  
Nájila Souza da Rocha ◽  
...  
Keyword(s):  
Wrf Model ◽  
Parameterization Schemes ◽  
Pbl 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 WRF-model sensitivity test and assimilation studies of Cempaka tropical cyclone

2021 ◽  
Vol 893 (1) ◽  
pp. 012029
Author(s):  
Fazrul Rafsanjani Sadarang ◽  
Fitria Puspita Sari
Keyword(s):  
Tropical Cyclone ◽  
Doppler Radar ◽  
Time Integration ◽  
Wrf Model ◽  
Radar Data ◽  
Control Model ◽  
Cyclone Track ◽  
Tropical Cyclone Track ◽  
Parameterization Schemes ◽  
Assimilation Scheme

Abstract The WRF model was used to forecast the most intensive stage of Cempaka Tropical Cyclone (TC) on 27 - 29 November 2017. This study evaluates the combination of cumulus and microphysics parameterization and the efficiency of assimilation method to predict pressure values at the center of the cyclone, maximum wind speed, and cyclone track. This study tested 18 combinations of cumulus and microphysics parameterization schemes to obtain the best combination of both parameterization schemes which later on called as control model (CTL). Afterward, assimilation schemes using 3DVAR cycles of 1, 3, 6 hours, and 4DVAR, namely RUC01, RUC03, RUC06, and 4DV, were evaluated for two domains with grid size of each 30 and 10 km. GFS data of 0.25-degree and the Yogyakarta Doppler Radar data were used as the initial data and assimilation data input, respectively. The result of the parameterization test shows that there is no combination of parameterization schemes that constantly outperform all variables. However, the combination of Kain-Fritsch and Thompson can produce the best prediction of tropical cyclone track compared to other combinations. While, the RUC03 assimilation scheme was noted as the most efficient method based on the accuracy of track prediction and duration of model time integration.

scholarly journals Assessment of a Regional-Scale Weather Model for Hydrological Applications in South Korea

2016 ◽  
Vol 6 (2) ◽  
pp. 28
Author(s):  
Yong Jung ◽  
Yuh-Lang Lin
Keyword(s):  
Weather Prediction ◽  
Regional Scale ◽  
Wrf Model ◽  
Domain Size ◽  
Cumulus Parameterization ◽  
Precipitation Forecast ◽  
Mountainous Region ◽  
Parameterization Schemes ◽  
Plain Region ◽  
Cumulus Parameterization Schemes

<p class="1Body">In this study, a regional numerical weather prediction (NWP) model known as the Weather Research Forescasting (WRF) model was adopted to improve the quantitative precipitation forecasts (QPF) by optimizing combined microphysics and cumulus parameterization schemes. Four locations in two regions (plain region for Sangkeug and Imsil; mountainous region for Dongchun and Bunchun) in Korean Peninsula were examined for QPF for two heavy rainfall events 2006 and 2008. The maximum Index of Agreement (IOA) was 0.96 at Bunchun in 2006 using the combined Thompson microphysics and the Grell cumulus parameterization schemes. Sensitivity of QPF on domain size at Sangkeug indicated that the localized smaller domain had 55% (from 0.35 to 0.90) improved precipitation accuracy based on IOA of 2008. For the July 2006 Sangkeug event, the sensitivity to cumulus parameterization schemes for precipitation prediction cannot be ignored with finer resolutions. In mountainous region, the combined Thompson microphysics and Grell cumulus parameterization schemes make a better quantitative precipitation forecast, while in plain region, the combined Thompson microphysics and Kain-Frisch cumulus parameterization schemes are the best.</p>

Comparison of WRF Model-Simulated and MODIS-Derived Cloud Data

2008 ◽  
Vol 136 (6) ◽  
pp. 1957-1970 ◽  
Author(s):  
Jason A. Otkin ◽  
Thomas J. Greenwald
Keyword(s):  
Wrf Model ◽  
Detailed Comparison ◽  
Cloud Microphysics ◽  
Cloud Data ◽  
Parameterization Schemes ◽  
Cloud Properties ◽  
Pbl Scheme ◽  
Resolution Model ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Upper Level

Abstract In this study, the ability of different combinations of bulk cloud microphysics and planetary boundary layer (PBL) parameterization schemes implemented in the Weather Research and Forecasting Model to realistically simulate the wide variety of cloud types associated with an extratropical cyclone is examined. An ensemble of high-resolution model simulations was constructed for this case using four microphysics and two PBL schemes characterized by different levels of complexity. Simulated cloud properties, including cloud optical thickness, cloud water path, cloud-top pressure, and radiative cloud phase, were subsequently compared to cloud data from three Moderate Resolution Imaging Spectroradiometer (MODIS) overpasses across different portions of the domain. A detailed comparison of the simulated datasets revealed that the PBL and cloud microphysics schemes both exerted a strong influence on the spatial distribution and physical properties of the simulated cloud fields. In particular, the low-level cloud properties were found to be very sensitive to the PBL scheme while the upper-level clouds were sensitive to both the microphysics and PBL schemes. Overall, the simulated cloud properties were broadly similar to the MODIS observations, with the most realistic cloud fields produced by the more sophisticated parameterization schemes.

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.

Sign in / Sign up

Export Citation Format

Share Document