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Application of MK-PRISM for interpolation of wind speed and comparison with co-kriging in South Korea

机译：MK-PRISM在风速插值中的应用及与韩国克里格的比较

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摘要

The spatial distribution of wind speed is important information required to understand climate-related regional phenomena. This paper presents the Modified Korean Parameter-elevation Regression on Independent Slopes Model (MK-PRISM) as a method for spatial interpolation of monthly wind speeds. A database of gridded monthly mean wind speeds with a spatial resolution of 1km for the period of March 2011-February 2014 is constructed by MK-PRISM. Wind speed observation data collected from the 529 to 641 meteorological stations in South Korea were utilized as the input data for interpolation. The wind speed distribution estimated by co-kriging is used for comparison with the MK-PRISM results. Research demonstrates that the efficiency difference between the two models, MK-PRISM and co-kriging, is insignificant. The Kling and Gupta efficiencies of both models were 0.68-0.78 and the root mean square errors (RMSEs) were 0.44-0.68m/s. The spatial distribution of wind speeds, however, differs between MK-PRISM and co-kriging, which can be considered a reflection of the influence of topographic features such as terrain convexity, aspect, and coastal proximity. MK-PRISM can perform more appropriately to represent the phenomena where similar wind speeds appear continuously along ridges and coastlines. This suggests that a knowledge-based approach that considers topographic features can be successfully applied to the interpolation of monthly or seasonal wind speeds, similar to temperature and precipitation. The wind speed distribution generated by MK-PRISM can be utilized as important data for different geographical studies.
机译：风速的空间分布是了解与气候有关的区域现象所需的重要信息。本文提出了修正韩国参数高程独立斜坡模型（MK-PRISM），作为每月风速的空间插值方法。 MK-PRISM构建了2011年3月至2014年2月期间网格化的月平均风速数据库，其空间分辨率为1 km。从韩国的529到641个气象站收集的风速观测数据被用作插值的输入数据。通过共同克里金法估计的风速分布用于与MK-PRISM结果进行比较。研究表明，MK-PRISM和协同克里格这两种模型之间的效率差异不明显。两种模型的Kling和Gupta效率均为0.68-0.78，均方根误差（RMSE）为0.44-0.68m / s。但是，MK-PRISM和联合克里金法在风速的空间分布上有所不同，这可以认为是地形特征（如地形凸度，坡度和沿海邻近性）影响的反映。 MK-PRISM可以更适当地执行以表示类似的风速沿着山脊和海岸线连续出现的现象。这表明考虑地形特征的基于知识的方法可以成功地应用于月度或季节风速的内插，类似于温度和降水。 MK-PRISM生成的风速分布可以用作重要的数据，用于不同的地理研究。

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