A Novel Framework for Spatio-Temporal Analysis of Temperature Profiles Applied to Europe

IF 2.6 3区 地球科学 Q3 METEOROLOGY & ATMOSPHERIC SCIENCES
S. Jamaer, D. Allaerts, J. Meyers, N. P. M. van Lipzig
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引用次数: 0

Abstract

Abstract Vertical temperature profiles influence the wind power generation of large offshore wind farms through stability-dependent effects such as blockage and gravity waves. However, numerical tools that are used to model these effects are often computationally too expensive to cover the large variety of atmospheric states occurring over time. Generally, an informed decision about which representative non-idealized situations to simulate is missing because of the lack of easily available information on representative vertical profiles, taking into account their spatio-temporal variability. Therefore, we present a novel framework that allows a smart selection of vertical temperature profiles. The framework consists of an improved analytical temperature model for the atmospheric boundary layer and lower troposphere, a subsequent clustering of these profiles to identify representatives, and lastly, a determination of areas with similar spatio-temporal characteristics of vertical profiles. When applying this framework on European ERA5 data, physically realistic representatives were identified for Europe, excluding the Mediterranean. Two or three profiles were found to be dominant for the open ocean, whereas more profiles prevail for land. Over the open ocean, weak temperature gradients in the boundary layer and a clear capping inversions are widespread, and stable profiles are absent except in the region of the East Icelandic current. Interestingly, according to the ERA5 data, at its resolution, coastal areas and seas surrounded by land behave more similar to the land areas than to the open ocean, implying that a larger set of model integrations are needed for these areas to obtain representative results for offshore wind power assessments compared to the open ocean.
应用于欧洲的温度分布时空分析新框架
垂直温度分布通过堵塞和重力波等稳定性依赖效应影响大型海上风电场的风力发电。然而,用于模拟这些效应的数值工具通常在计算上过于昂贵,无法涵盖随时间发生的各种大气状态。一般来说,考虑到它们的时空变异性,由于缺乏关于代表性垂直剖面的容易获得的信息,因此缺乏关于模拟哪些具有代表性的非理想情况的明智决策。因此,我们提出了一个新的框架,允许智能选择垂直温度分布。该框架包括改进的大气边界层和对流层下层的解析温度模式,随后对这些剖面进行聚类以识别代表,最后确定垂直剖面具有相似时空特征的区域。在将此框架应用于欧洲ERA5数据时,确定了欧洲(地中海除外)的实际代表。发现两个或三个剖面在公海中占主导地位,而更多的剖面在陆地上占主导地位。在公海上,边界层的弱温度梯度和明显的盖层反转普遍存在,除了东冰岛流区域外,没有稳定的剖面。有趣的是,根据ERA5的数据,在其分辨率下,沿海地区和被陆地包围的海洋的表现与陆地区域比与公海更相似,这意味着与公海相比,这些地区需要更大的模型集成集来获得具有代表性的海上风电评估结果。
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来源期刊
Journal of Applied Meteorology and Climatology
Journal of Applied Meteorology and Climatology 地学-气象与大气科学
CiteScore
5.10
自引率
6.70%
发文量
97
审稿时长
3 months
期刊介绍: The Journal of Applied Meteorology and Climatology (JAMC) (ISSN: 1558-8424; eISSN: 1558-8432) publishes applied research on meteorology and climatology. Examples of meteorological research include topics such as weather modification, satellite meteorology, radar meteorology, boundary layer processes, physical meteorology, air pollution meteorology (including dispersion and chemical processes), agricultural and forest meteorology, mountain meteorology, and applied meteorological numerical models. Examples of climatological research include the use of climate information in impact assessments, dynamical and statistical downscaling, seasonal climate forecast applications and verification, climate risk and vulnerability, development of climate monitoring tools, and urban and local climates.
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