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Sensitivity of WRF-simulated 10 m wind over the Persian Gulf to different boundary conditions and PBL parameterization schemes

机译:WRF模拟10米风对不同边界条件和PBL参数化方案的波斯湾的敏感性

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摘要

A sensitivity analysis of the Weather Research and Forecasting (WRF) mesoscale model with the Advanced Research WRF (ARW) dynamical solver for wind simulation at 10 m above ground level was conducted through different initial and boundary conditions datasets, and various planetary boundary layer (PBL) schemes throughout the year 2017 over the Persian Gulf region. Owing to the wide variety of approaches and development periods of analysis and reanalysis data (e.g. assimilation system) as well as different methods for PBL parameterization (closure formulations), this paper aims to obtain an efficient set up of the WRF model configuration in terms of the lowest error in simulating surface wind. Three datasets including ERA-Interim reanalysis, NCEP-R2 reanalysis, and NCEP-FNL analysis as initial and boundary conditions to the model and six PBL schemes including ACM2, BouLac, MYJ, MYNN, QNSE, and YSU accompanied by their relevant surface-layer schemes were used to accomplish this goal. Available observational wind data including 23 synoptic weather stations located in the region were used to compare the model wind simulation. Comparing WRF wind simulations with observations at synoptic weather stations indicates that; irrespective of the type of PBL scheme, ERA-Interim, and NCEP-FNL datasets exhibit better performance than the NCEP-R2. In addition, in the case of considering PBL schemes, results show that the configuration including the YSU scheme and ERA-Interim reanalysis data leads to the best estimation of wind speed and configuration including YSU and NCEP-FNL data produces the least error for wind direction. The performance of the model in summer shows higher errors compared to the winter season. It is due to the obvious differences between initial and boundary conditions data with observation data. The success of the YSU scheme in comparison with other schemes is rooted in the nonlocal closure of this scheme, which includes local gradients correction and entrainment sentences.
机译:通过不同的初始和边界条件数据集,以及各种行星边界层(PBL)的天气研究与地面上高于地面的风模的天气研究和预测WRF(ARW)动态求解器的敏感性分析。 )2017年全年波斯湾地区的计划。由于各种各样的分析和分析数据(例如同化系统)以及PBL参数化的不同方法(封闭配方),本文旨在以拟处获得WRF模型配置的有效设置模拟表面风中的最低误差。三个数据集包括ERA-Interim Reanalysis,NCEP-R2再分析和NCEP-FNL分析作为模型的初始和边界条件和六种PBL方案,包括ACM2,Boulac,MyJ,MyNN,QNSE和YSU伴随着其相关的表面层计划用于实现这一目标。可用的观测风数据包括位于该地区的23个天气气象站,用于比较模型风模拟。将WRF风模拟与揭示天气站的观测相比表明;无论PBL方案,ERA临时和NCEP-FNL数据集的类型如何表现出比NCEP-R2更好的性能。此外,在考虑PBL方案的情况下,结果表明包括YSU方案和ERA-Instim重新分析数据的配置导致风速和配置的最佳估计,包括YSU和NCEP-FNL数据产生风向的最小误差。与冬季相比,夏季模型的性能显示出更高的误差。它是由于初始和边界条件数据之间具有观察数据的明显差异。与其他方案相比,YSU方案的成功源于该方案的非函数闭合,包括本地梯度校正和夹带句。

著录项

  • 来源
    《Oceanographic Literature Review》 |2020年第9期|1892-1892|共1页
  • 作者单位

    Iranian National Institute for Oceanography and Atmospheric Science (INIOAS) Iran;

    Iranian National Institute for Oceanography and Atmospheric Science (INIOAS) Iran;

    Iranian National Institute for Oceanography and Atmospheric Science (INIOAS) Iran;

    Iranian National Institute for Oceanography and Atmospheric Science (INIOAS) Iran;

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