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首页> 外文期刊>Hydrology and Earth System Sciences >Predictability of soil moisture and river flows over France for the spring season
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Predictability of soil moisture and river flows over France for the spring season

机译:法国春季土壤湿度和河流流量的可预测性

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摘要

Sources of spring predictability of the hydrological system over France were studied on a seasonal time scale over the 1960-2005 period. Two random sampling experiments were set up in order to test the relative importance of the land surface initial state and the atmospheric forcing. The experiments were based on the SAFRAN-ISBA-MODCOU hydrometeorological suite which computed soil moisture and river flow forecasts over a 8-km grid and more than 880 river-gauging stations. Results showed that the predictability of hydrological variables primarily depended on the seasonal atmospheric forcing (mostly temperature and total precipitation) over most plains, whereas it mainly depended on snow cover over high mountains. However, the Seine catchment area was an exception as the skill mainly came from the initial state of its large and complex aquifers. Seasonal meteorological hindcasts with the Météo-France ARPEGE climate model were then used to force the ISBA-MODCOU hydrological model and obtain seasonal hydrological forecasts from 1960 to 2005 for the entire March-April-May period. Scores from this seasonal hydrological forecasting suite could thus be compared with the random atmospheric experiment. Soil moisture and river flow skill scores clearly showed the added value in seasonal meteorological forecasts in the north of France, contrary to the Mediterranean area where values worsened.
机译:在1960-2005年期间的季节时间尺度上研究了法国水文系统春季可预测性的来源。为了测试地表初始状态和大气强迫的相对重要性,建立了两个随机抽样实验。实验是基于SAFRAN-ISBA-MODCOU水文气象套件进行的,该套件计算了一个8公里长的网格和880多个测水站的土壤湿度和河流流量预报。结果表明,水文变量的可预测性主要取决于大多数平原的季节性大气强迫(主要是温度和总降水),而主要取决于高山上的积雪。但是,塞纳河集水区是一个例外,因为该技术主要来自其大型而复杂的含水层的初始状态。然后使用法国气象局ARPEGE气候模式的季节性气象后兆来强迫ISBA-MODCOU水文模型,并获得整个3月至4月至5月期间1960年至2005年的季节性水文预报。因此,可以将该季节性水文预报套件中的得分与随机大气实验进行比较。土壤湿度和河流流量技能得分清楚地表明了法国北部季节性气象预报中的增加值,而地中海地区的值却在恶化。

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