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首页> 外文期刊>International Journal of Climatology: A Journal of the Royal Meteorological Society >High‐resolution monthly precipitation climatologies over Norway (1981–2010): Joining numerical model data sets and in situ observations
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High‐resolution monthly precipitation climatologies over Norway (1981–2010): Joining numerical model data sets and in situ observations

机译:在挪威的高分辨率月降水气候(1981-2010):加入数值模型数据集及原位观察

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>The 1981–2010 monthly precipitation climatologies for Norway at 1?km resolution are presented. They are computed by an interpolation procedure (HCLIM+RK) combining the output from a numerical model with the in situ observations. Specifically, the regional climate model data set HCLIM‐AROME, based on the dynamical downscaling of the global ERA‐Interim reanalysis onto 2.5 km resolution, is considered together with 2009 rain‐gauges located within the model domain. The precipitation climatologies are defined by superimposing the grid of 1981–2010 monthly normals from the numerical model and the kriging interpolation of station residuals. The combined approach aims at improving the quality of gridded climatologies and at providing reliable precipitation gradients also over those remote Norwegian regions not covered by observations, especially over the northernmost mountainous areas. The integration of rain‐gauge data greatly reduces the original HCLIM‐AROME biases. The HCLIM+RK errors obtained from the leave‐one‐out station validation turn out to be lower than those provided by two considered interpolation schemes based on observations only: a multi‐linear local regression kriging (MLRK) and a local weighted linear regression (LWLR). As average over all months, the mean absolute (percentage) error is 10.0 mm (11%) for HCLIM+RK, and 11.4 (12%) and 11.6 mm (12%) for MLRK and LWLR, respectively. In addition, by comparing the results at both station and grid cell level, the accuracy of MLRK and LWLR is more sensitive to the spatial variability of station distribution over the domain and their interpolated fields are more affected by discontinuities and outliers, especially over those areas not covered by the rain‐gauge network. The obtained HCLIM+RK climatologies clearly depict the main west‐to‐east gradient occurring from the orographic precipitation regime of the coast to the more continental climate of the inlan
机译:

1981-2010挪威的月度降水气候,展出了1个KM分辨率。它们由与原位观测的数字模型组合的插值过程(HCLIM + RK)计算。具体而言,区域气候模型数据集HCLIM-AROME基于全球时代临时再分析到2.5公里分辨率的动态缩小,与位于模型领域内的2009年雨水仪一起考虑。通过从数值模型和车站残留的Kriging插值叠加1981-2010每月法线的网格来定义降水气候。该组合方法旨在提高包装的气候质量,也可以在没有观察的远程挪威地区提供可靠的降水梯度,特别是在最北端的山区。雨量数据的整合大大降低了原始的HCLIM-偏偏见。从休假时验证获得的HCLIM + RK误差结果低于基于观察的两种考虑的插值方案提供的那些:多线性本地回归克里格(MLRK)和局部加权线性回归( lwlr)。对于所有月的平均值,平均绝对(百分比)误差为HCLIM + RK的10.0毫米(11%),分别用于MLRK和LWLR的11.4(12%)和11.6毫米(12%)。另外,通过将结果与网格电池单元的结果进行比较,MLRK和LWLR的准确性对域的站分布的空间可变性更敏感,并且其内插字段受到不连续性和异常值的影响,特别是在这些区域上没有雨量网络覆盖。所获得的HCLIM + RK气候清楚地描绘了从海岸的地形降水制度发生的主要西北梯度,以更大的INLAN的大陆气候

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