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首页> 外文期刊>SOLA: Scientific Online Letters on the Atmosphere >Bias Correction of Snow Depth by Using Regional Frequency Analysis in the Non-Hydrostatic Regional Climate Model around Japan
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Bias Correction of Snow Depth by Using Regional Frequency Analysis in the Non-Hydrostatic Regional Climate Model around Japan

机译：在日本附近的非静水区域气候模型中，使用区域频率分析对雪深进行偏差校正

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References(16) The 5-km-mesh, Non-Hydrostatic Regional Climate Model was used to simulate snow depths in Japan and to project their changes in the future. The simulated snow depths had large biases, and bias corrections were required to project future snow depths accurately. We developed a new method of bias correction that is accurate and easily implemented for automatic use on a computer. Three classification methods of regional frequency analysis were tested in nine regions of Japan. The classification method based on the second order of L-moments (L-cv) was the best bias correction method among those tested. We checked that this bias correction was useful method for future climate projections by using the test sample estimate. Snow depth in the future climate was projected to decrease by about 50 cm, such that the average snow depth over Japan was about 30 cm in the future climate. The projected decrease in the maximum snow depth was large in the Nagano and Gifu regions and small in the Hokkaido region compared with other regions.
机译：参考文献（16）使用5公里网眼的非静水区域气候模型来模拟日本的积雪深度并预测其未来的变化。模拟的雪深有较大的偏差，需要进行偏差校正才能准确预测未来的雪深。我们开发了一种精确且易于实现的偏差校正新方法，可在计算机上自动使用。在日本的九个地区测试了三种区域频率分析的分类方法。在测试的那些方法中，基于L阶二阶（L-cv）的分类方法是最好的偏差校正方法。我们通过使用测试样本估计值检查了这种偏差校正对未来气候预测的有用方法。预计未来气候中的积雪深度将减少约50厘米，因此日本未来气候中的平均积雪深度约为30厘米。与其他地区相比，长野和岐阜地区的最大降雪深度预计下降幅度较大，而北海道地区的降幅最大。

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