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首页> 外文期刊>SOLA: Scientific Online Letters on the Atmosphere >Future Changes of Snow Depth in a Non-Hydrostatic Regional Climate Model with Bias Correction
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Future Changes of Snow Depth in a Non-Hydrostatic Regional Climate Model with Bias Correction

机译：带有偏差校正的非静水区域气候模型中雪深的未来变化

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References(11) Cited-By(2) Supplementary materials(2) To accurately simulate the present and project the late 21st century climates of Japan, we carried out 20-year integrations with a 5-km-mesh, non-hydrostatic regional climate model (NHRCM) nested within a 20-km-mesh Atmospheric Global Circulation Model (AGCM20). The NHRCM simulated monthly mean snow depths more accurately than AGCM20 which used to drive NHRCM. However, NHRCM underestimated snow depths on the Japan Sea side of northern Japan. Because a sample size was insufficient for correcting bias with a cumulative distribution function mapping (CDFM) method at one site, we applied a regional frequency analysis method to group AMeDAS sites in Hokkaido. We tested two kinds of bias corrections: CDFM and a bias correction (designated PBC) based on equating the histograms of model results and observational data. Both methods greatly reduced the biases of simulated snow depths, but PBC produced a greater reduction in the root mean square error in almost every region. The results of PBC indicated that snow depth will decrease more than 80 cm in western parts of Hokkaido in the future.
机译：参考文献（11）引用依据（2）补充材料（2）为了准确模拟当前并预测日本21世纪末的气候，我们对5公里网眼的非静水区域气候进行了20年的整合模型（NHRCM）嵌套在20公里网眼的全球大气环流模型（AGCM20）中。与用来驱动NHRCM的AGCM20相比，NHRCM模拟的月平均积雪深度更准确。但是，NHRCM低估了日本北部日本海一侧的积雪深度。由于样本量不足以使用一个站点的累积分布函数映射（CDFM）方法来校正偏差，因此我们将区域频率分析方法应用于北海道的AMeDAS站点分组。我们基于模型结果和观测数据的直方图相等，测试了两种偏差校正：CDFM和偏差校正（指定为PBC）。两种方法都大大降低了模拟雪深的偏差，但是PBC几乎在每个区域都产生了均方根误差的更大减小。 PBC的结果表明，未来北海道西部的积雪深度将减少80厘米以上。

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