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Conditioning Ensemble Streamflow Prediction Forecasts Using Climate Signals in the Midwestern U.S.

机译:调节集合的流出预测在美国中西部气候信号中使用气候信号的预测预测

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Assimilation of seasonal climate forecasts is widely recognized as a potential means of improving the accuracy and reliability of National Weather Service long lead-time (1- month to 1-year) Ensemble Streamflow Prediction (ESP) forecasts. Such forecasts are not widely used, however, for a number of reasons. In the Midwestern U.S., few strong and consistent teleconnections have been identified for forecasting, perhaps due to nonlinear interactions of both Atlantic and Pacific Ocean patterns. Further, there is no consensus that the resulting forecast skill is sufficient to support water resources decision making. In this paper, we evaluate a set of climate patterns that may serve as useful indicators for seasonal (1- to 3-month) streamflow forecasts in the Midwestern U.S. Streamflow persistence and predictability based on simulated soil moisture are used as benchmarks for comparison with climate-based forecasts. Various procedures are discussed for assimilating climate forecasts into ESP forecasts, and forecast skill is assessed using re-sampling procedures. Finally, the value of seasonal forecasts for water resources management applications is discussed.
机译:季节性气候预测的同化被广泛认为是提高国家天气服务长期交付时间(1个月至1年)集合流程预测(ESP)预测的潜在手段。然而,由于多种原因,这些预测并未被广泛使用。在美国中西部,已经确定了很少有强大且一致的电信连接用于预测,也许是由于大西洋和太平洋模式的非线性相互作用。此外,没有共识,即由此产生的预测技能足以支持水资源决策。在本文中,我们评估了一系列可作为季节性指标(1至3个月)流出预测的一套气候模式,其在美国中西部的流流持久性和基于模拟土壤水分的可预测性用作与气候相比的基准基于预测。讨论各种程序来吸收气候预测转化为ESP预测,并使用重新采样程序评估预测技能。最后,讨论了水资源管理应用季节性预测的价值。

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