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Downscaling Of Gcm Forecasts To Streamflow Over Scandinavia

机译:Gcm预报的缩减规模对斯堪的纳维亚半岛的流量

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A seasonal forecasting technique to produce probabilistic and deterministic streamflow forecasts for 23 basins in Norway and northern Sweden is developed in this work. Large scale circulation and moisture fields, forecasted by the ECHAM4.5 model 4 months in advance, are used to forecast spring flows. The technique includes model output statistics (MOS) based on a non-linear Neural Network (NN) approach. Results show that streamflow forecasts from Global Circulation Model (GCM) predictions, for the Scandinavia region are viable and highest skill values were found for basins located in south-western Norway. The physical interpretation of the forecasting skill is that stations close to the Norwegian coast are directly exposed to prevailing winds from the Atlantic Ocean, which constitute the principal source of predictive information from the atmosphere on the seasonal timescale.
机译:在这项工作中,开发了一种季节性预测技术,可以对挪威和瑞典北部的23个盆地进行概率和确定性的流量预测。 ECHAM4.5模型提前4个月预测了大范围的循环和湿度场,用于预测春季流量。该技术包括基于非线性神经网络(NN)方法的模型输出统计(MOS)。结果表明,从全球循环模型(GCM)预测得出的斯堪的纳维亚地区的流量预测是可行的,并且发现挪威西南部盆地的最高技能值。预报技巧的物理解释是,靠近挪威海岸的气象站直接暴露于大西洋的盛行风中,这是从大气中获取季节性信息的主要来源。

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