Doppler-Lidar Evaluation of HRRR-Model Skill at Simulating Summertime Wind Regimes in the Columbia River Basin during WFIP2
Doppler-Lidar Evaluation of HRRR-Model Skill at Simulating Summertime Wind Regimes in the Columbia River Basin during WFIP2
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WFIP2 期间模拟哥伦比亚河流域夏季风况的 HRRR 模型技能的多普勒激光雷达评估
DOI：
10.1175/waf-d-21-0012.1
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发表时间：
2021
影响因子：
2.9
通讯作者：
Lantz, K.O.
中科院分区：
文献类型：
--
作者：
Banta, Robert M.;Pichugina, Yelena L.;Darby, Lisa S.;Brewer, W. Alan;Olson, Joseph B.;Kenyon, Jaymes S.;Baidar, S.;Benjamin, S.G.;Fernando, H.J.S.;Lantz, K.O.
复杂地形的位置经常有可重复的近地面风模式，如天气间隙流和局部热力强迫流。一个例子是俄勒冈州-华盛顿州中东部的哥伦比亚河谷，这是一个重要的风能发电区，也是第二个风力预报改进项目（WFIP 2）的所在地。WFIP 2期间部署的三台多普勒激光雷达的数据定义和表征了夏季风态及其大尺度背景，并通过检查模型[NOAA的高分辨率快速刷新（HRRR版本1）]预测不同流态风速剖面的能力差异来深入了解NWP模型误差。根据激光雷达测量的转子层风的每日时间序列确定了七种状态，然后提出了两大类。首先，在三个制度的主要动力强迫是大规模的压力梯度。第二，在另外两个制度的主导强迫是昼夜加热冷却循环（区域海风型动力学），包括海上入侵先前描述的，它产生了强大的夜间风在该地区。对于大尺度气压梯度区域，HRRR的风速偏差约为1 m s− 1，RMSE为2-3 m s−1。误差大得多的热力强迫制度，由于过早消亡的强夜间流动HRRR。因此，表面加热在产生流动中的作用越占主导地位，误差就越大。主要的误差可能来自大气的表面加热、边界层对加热的反应以及相关的地形相互作用。测量/建模研究计划的设计应确定哪些建模过程产生最大的误差，以便改进这些过程并减少误差。
Complex-terrain locations often have repeatable near-surface wind patterns, such as synoptic gap flows and local thermally forced flows. An example is the Columbia River Valley in east-central Oregon–Washington, a significant wind energy generation region and the site of the Second Wind Forecast Improvement Project (WFIP2). Data from three Doppler lidars deployed during WFIP2 define and characterize summertime wind regimes and their large-scale contexts, and provide insight into NWP model errors by examining differences in the ability of a model [NOAA’s High-Resolution Rapid Refresh (HRRR version 1)] to forecast wind speed profiles for different flow regimes. Seven regimes were identified based on daily time series of the lidar-measured rotor-layer winds, which then suggested two broad categories. First, in three of the regimes the primary dynamic forcing was the large-scale pressure gradient. Second, in two other regimes the dominant forcing was the diurnal heating-cooling cycle (regional sea-breeze-type dynamics), including themarine intrusionpreviously described, which generates strong nocturnal winds over the region. For the large-scale pressure gradient regimes, HRRR had wind speed biases of ~1 m s−1and RMSEs of 2–3 m s−1. Errors were much larger for the thermally forced regimes, owing to the premature demise of the strong nocturnal flow in HRRR. Thus, the more dominant the role of surface heating in generating the flow, the larger the errors. Major errors could result from surface heating of the atmosphere, boundary layer responses to that heating, and associated terrain interactions. Measurement/modeling research programs should be designed to determine which of these modeled processes produce the largest errors, so those processes can be improved and errors reduced.
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影响因子：
2.9
作者：
Temple R. Lee;Michael Buban;D. Turner;T. Meyers;C. Baker
通讯作者：
Temple R. Lee;Michael Buban;D. Turner;T. Meyers;C. Baker
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DOI：
--
发表时间：
2016
期刊：
影响因子：
--
作者：
I. Djalalova;J. Olson;J. Carley;L. Bianco;J. Wilczak;Y. Pichugina;R. Banta;M. Marquis;J. Cline
通讯作者：
J. Cline
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影响因子：
2.9
作者：
R. Fovell;A. Gallagher
通讯作者：
A. Gallagher
萨克拉门托山谷夏季风流状况
DOI：
--
发表时间：
1999
期刊：
影响因子：
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作者：
Laura L. Zaremba;J. Carroll
通讯作者：
J. Carroll
哥伦比亚河流域温度和风廓线仪对持续冷池事件的识别和表征
DOI：
--
发表时间：
--
期刊：
影响因子：
--
作者：
K. A. M. C. C. Affrey;J. A. M. W. Ilczak;L. A. B. Ianco;E. R. G. Rimit;J. U. S. Harp;R. O. B. Anta;K. A. F. Riedrich;H. J. S. F. Ernando;R. A. K. Rishnamurthy;EO LAURAS.L;P. A. M. Uradyan
通讯作者：
P. A. M. Uradyan