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
气象与环境学报

气象与环境学报 ›› 2019, Vol. 35 ›› Issue (4): 8-15.doi: 10.3969/j.issn.1673-503X.2019.04.002

• 论文 • 上一篇    

大小兴安岭林区风场动力降尺度对比研究

孟莹莹1, 曹殿斌1, 吴岩1, 王子洋2   

  1. 1. 黑龙江省气象台, 黑龙江 哈尔滨 150030;
    2. 黑龙江省信息中心, 黑龙江 哈尔滨 150030
  • 收稿日期:2018-04-03 修回日期:2018-07-24 发布日期:2019-09-03
  • 通讯作者: 曹殿斌,男,高级工程师,E-mail:caodianbin_mail@126.com。 E-mail:caodianbin_mail@126.com
  • 作者简介:孟莹莹,女,1989年生,工程师,主要从事数值产品释用研究工作,E-mail:specialcherry@126.com。
  • 基金资助:
    中国气象局沈阳大气环境研究所开放基金项目（2016SYIAE06）资助。

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).

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摘要： 对2017年春季黑龙江省大、小兴安岭林区的6个代表站点10 m风场进行降尺度分析，并结合观测数据对比分析了WRF模式和CALMET降尺度模式的10 m风速、风向预报结果。结果表明：两模式逐小时风速预报与观测的相关系数为0.5-0.7，且随着风速的增加，模式的预报准确率逐渐提高，夜间的风速预报偏差较大，进入白天后，偏差明显减小。WRF模式对风速变化趋势的预报效果优于CALMET模式，与观测的风速相关性更高，而CALMET模式对较大风速的预报效果优于WRF模式。在风向预报方面，WRF和CALMET的风向模拟与观测风向均有较好的一致性，模式预报准确率较高的两个风向也刚好对应各站的盛行风向。同时，本文用回归方法对日平均风速进行订正发现，订正后各站的日平均风速预报准确率平均提高了50%，具有较好的业务应用价值。

关键词: 林区, 风场, WRF, CALMET, 预报订正

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

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