首页> 外文期刊>Journal of Applied Meteorology and Climatology >Improving Lake-Breeze Simulation with WRF Nested LES and Lake Model over a Large Shallow Lake
【24h】

Improving Lake-Breeze Simulation with WRF Nested LES and Lake Model over a Large Shallow Lake

机译:用WRF嵌套LES和Lake Model改善Lake-Breeze仿真在一个大浅湖中

获取原文
获取原文并翻译 | 示例
           

摘要

The Weather Research and Forecasting (WRF) Model is used in large-eddy simulation (LES) mode to investigate a lake-breeze case occurring on 12 June 2012 over the Lake Taihu region of China. Observational data from 15 locations, wind profiler radar, and the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to evaluate the WRF nested-LES performance in simulating lake breezes. Results indicate that the simulated temporal and spatial variations of the lake breeze by WRF nested LES are consistent with observations. The simulations with high-resolution grid spacing and the LES scheme have a high correlation coefficient and low mean bias when evaluated against 2-m temperature, 10-m wind, and horizontal and vertical lake-breeze circulations. The atmospheric boundary layer (ABL) remains stable over the lake throughout the lake-breeze event, and the stability becomes even stronger as the lake breeze reaches its mature stage. The improved ABL simulation with LES at a grid spacing of 150 m indicates that the non-LES planetary boundary layer parameterization scheme does not adequately represent subgrid-scale turbulent motions. Running WRF fully coupled to a lake model improves lake-surface temperature and consequently the lake-breeze simulations. Allowing for additional model spinup results in a positive impact on lake-surface temperature prediction but is a heavy computational burden. Refinement of a water-property parameter used in the Community Land Model, version 4.5, within WRF and constraining the lake-surface temperature with observational data would further improve lake-breeze representation.
机译:天气研究和预测(WRF)模型用于大涡模拟(LES)模式,调查2012年6月12日在中国湖中发生的湖风案例。从15个位置,风分析仪雷达和适度分辨率成像光谱仪(MODIS)的观测数据用于评估模拟湖布雷兹的WRF嵌套性能。结果表明,WRF嵌套LES湖风的模拟时间和空间变化与观察结果一致。具有高分辨率网格间距的模拟和LES方案具有高相关系数和当评估为2米的温度,10米风和水平和垂直湖 - 微风循环时具有高的相关系数和低平均偏置。大气边界层(ABL)在整个湖流活动中仍然稳定,随着湖风达到其成熟阶段,稳定性变得更加强劲。在150米的网格间隔中具有LES的改进的ABL模拟表明非LES行星边界层参数化方案不充分代表底片级湍流运动。完全耦合到湖型模型的运行WRF改善了湖面温度,从而提高了湖流模拟。允许额外的模型旋转导致对湖面温度预测的积极影响,但是一种沉重的计算负担。在Community Land Model中使用的水性参数,3.5版,在WRF中和用观测数据约束湖面温度的水性参数将进一步提高湖风表示。

著录项

  • 来源
  • 作者单位

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

    Univ Oklahoma Ctr Anal &

    Predict Storms Norman OK 73019 USA;

    Nanjing Univ Informat Sci &

    Technol Yale Nanjing Univ Informat Sci &

    Technol Ctr Atmo Key Lab Meteorol Disaster Collaborat Innovat Ctr Minist Educ Int Joint Lab Climate &

    Environm Chan Nanjing Jiangsu Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 大气科学(气象学);
  • 关键词

    Land surface model; Large eddy simulations; Model evaluation; performance; Numerical weather prediction; forecasting; Coastal meteorology;

    机译:陆地面模型;大涡模拟;模型评估;性能;数值天气预报;预测;沿海气象学;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号