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    Developing a Climate Prediction System over Southwest China Using the 8-km Weather Research and Forecasting (WRF) Model: System Design, Model Calibration, and Performance Evaluation

    Source: Weather and Forecasting:;2022:;volume( 037 ):;issue: 009::page 1703
    Author:
    Entao Yu
    ,
    Jiehua Ma
    ,
    Jianqi Sun
    DOI: 10.1175/WAF-D-21-0188.1
    Publisher: American Meteorological Society
    Abstract: A high-resolution, short-term climate prediction system for summer (June–July–August) climate over Southwest China has been developed using the Weather Research and Forecasting (WRF) Model nested with a global climate prediction system (PCCSM4). The system includes 12 ensemble members generated by PCCSM4 with different initial conditions, and the finest horizontal resolution of WRF is 8 km. This study evaluates the ability of the WRF Model to predict summer climate over Southwest China, focusing on the system design, model tuning, and evaluation of baseline model performance. Sensitivity simulations are first conducted to provide the optimal model configuration, and the model performance is evaluated against available observational data using reforecast simulations for 1981–2020. When compared to PCCSM4, the WRF Model shows major improvements in predicting the spatial distribution of major variables such as 2-m temperature, 10-m wind speed, and precipitation. WRF also shows better skill in predicting interannual temperature variability and extreme temperature events, with higher anomaly correlation coefficients. However, large model biases remain in seasonal precipitation anomaly predictions. Overall, this study highlights the potential advantages of using the high-resolution WRF Model to predict summer climate conditions over Southwest China.
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      Developing a Climate Prediction System over Southwest China Using the 8-km Weather Research and Forecasting (WRF) Model: System Design, Model Calibration, and Performance Evaluation

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4289673
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    • Weather and Forecasting

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    contributor authorEntao Yu
    contributor authorJiehua Ma
    contributor authorJianqi Sun
    date accessioned2023-04-12T18:26:29Z
    date available2023-04-12T18:26:29Z
    date copyright2022/09/01
    date issued2022
    identifier otherWAF-D-21-0188.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4289673
    description abstractA high-resolution, short-term climate prediction system for summer (June–July–August) climate over Southwest China has been developed using the Weather Research and Forecasting (WRF) Model nested with a global climate prediction system (PCCSM4). The system includes 12 ensemble members generated by PCCSM4 with different initial conditions, and the finest horizontal resolution of WRF is 8 km. This study evaluates the ability of the WRF Model to predict summer climate over Southwest China, focusing on the system design, model tuning, and evaluation of baseline model performance. Sensitivity simulations are first conducted to provide the optimal model configuration, and the model performance is evaluated against available observational data using reforecast simulations for 1981–2020. When compared to PCCSM4, the WRF Model shows major improvements in predicting the spatial distribution of major variables such as 2-m temperature, 10-m wind speed, and precipitation. WRF also shows better skill in predicting interannual temperature variability and extreme temperature events, with higher anomaly correlation coefficients. However, large model biases remain in seasonal precipitation anomaly predictions. Overall, this study highlights the potential advantages of using the high-resolution WRF Model to predict summer climate conditions over Southwest China.
    publisherAmerican Meteorological Society
    titleDeveloping a Climate Prediction System over Southwest China Using the 8-km Weather Research and Forecasting (WRF) Model: System Design, Model Calibration, and Performance Evaluation
    typeJournal Paper
    journal volume37
    journal issue9
    journal titleWeather and Forecasting
    identifier doi10.1175/WAF-D-21-0188.1
    journal fristpage1703
    journal lastpage1719
    page1703–1719
    treeWeather and Forecasting:;2022:;volume( 037 ):;issue: 009
    contenttypeFulltext
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