主办单位:中国气象局沈阳大气环境研究所
国际刊号:ISSN 1673-503X
国内刊号:CN 21-1531/P

Journal of Meteorology and Environment ›› 2019, Vol. 35 ›› Issue (4): 8-15.doi: 10.3969/j.issn.1673-503X.2019.04.002

• ARTICLES • Previous Articles    

Comparisons of dynamic downscaling of the wind field in forest areas of Da-Xiao-Xing'anling Mountains

MENG Ying-ying1, CAO Dian-bin1, WU Yan1, WANG Zi-yang2   

  1. 1. Heilongjiang Meteorological Observatory, Harbin 150030, China;
    2. Heilongjiang Information Center, Harbin 150030, China
  • Received:2018-04-03 Revised:2018-07-24 Published:2019-09-03
  • Supported by:
    This work is supported by the National Science and Technology Support Program (No.2015BAA05B01) and the National Key R&D Program of China (No.2017YFC0210203).

Abstract: In this study,we conducted the downscaling analysis of 10-m wind fields at 6 stations in Da-Xiao-Xing'anling Mountains during spring in 2017.We also used the observations to evaluate the 10-m wind speed and direction simulated with the Weather Research and Forecasting (WRF) model and with the CALMET downscaling model.The correlation coefficients between observed hourly wind speeds and that simulated with the two models reach 0.5-0.7.The prediction accuracy gradually increases with the increase of wind speed.The forecasting deviation of wind speed is relatively large at night and decreases during the daytime.The WRF model predicts the variability of wind speeds better than the CALMET model,and that has a higher correlation with the observations;but for the case of strong winds,the CALMET model performs better than the WRF model.The wind direction simulations of WRF and CALMET models are both in a good agreement with the observations.Wind directions with high prediction accuracy correspond to the prevailing wind directions of each station.Meanwhile,a simple-regression method is used to correct daily mean wind speed.Results indicate that the forecasting accuracy of daily mean wind speed increases by 50% on average,with good prospects in the operational application.

Key words: Forest area, Wind field, WRF (Weather Research and Forecasting), CALMET, Forecasting correction

CLC Number: