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Statistical downscaling and scenario construction of precipitation in Scania, southern Sweden

机译:瑞典南部斯堪尼亚的统计降尺度和降水情景构建

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Statistical downscaling models for precipitation In Scania, southern Sweden, have been developed and applied to calculate the changes in the future Scanian precipitation climate due to projected changes in the atmospheric composition. The models are based on multiple linear regression, linking large-scale predictors at monthly time resolution to regional statistics of daily precipitation on a monthly basis. To account for spatial precipitation variability within the area, the precipitation statistics were derived for different regions in Scania. The final downscaling models, developed for different regions and seasons, use atmospheric circulation, large-scale humidity and precipitation as predictors. Among the precipitation statistics examined, only the models for estimating the mean precipitation and the frequency of wet days were skilful. Based on the Canadian Global Circulation Model 1 (CGCM1), a future scenario of these two statistics was created. The downscaled scenario shows a significant increase of the annual mean precipitation by about 10% and a slight decrease in the frequency of wet days, indicating an increase in the precipitation amounts as well as in the precipitation intensity. The main increase of precipitation amounts and intensity occur during winter, while the summer precipitation amounts decrease slightly. The seasonal changes found in precipitation are likely attributed to changes in the westerly flow of the atmospheric circulation.
机译:在瑞典南部的斯堪尼亚,已开发出统计的降尺度模型,并将其用于计算由于预计的大气成分变化而导致的斯堪尼亚未来降水气候的变化。这些模型基于多重线性回归,将每月时间分辨率下的大型预测因子与每月日降水量的区域统计联系起来。为了说明该区域内的空间降水变化,得出了斯堪尼亚不同地区的降水统计数据。针对不同地区和季节开发的最终降尺度模型使用大气环流,大规模湿度和降水作为预测指标。在检验的降水统计数据中,只有用于估算平均降水和湿天频率的模型才是熟练的。基于加拿大全球流通模型1(CGCM1),创建了这两种统计数据的未来方案。缩小规模的情景表明,年平均降水量显着增加了约10%,而湿天的频率略有下降,表明降水量和降水强度都有所增加。降水量和强度的主要增加发生在冬季,而夏季降水量略有减少。降水中发现的季节性变化可能归因于大气环流的西风流变化。

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