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首页> 外文期刊>Journal of hydrometeorology >Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts
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Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

机译：交互式植被物候，土壤湿度和每月温度预报

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摘要

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observationsas well as quantifying the inherent predictability of temperature within each ensembleshows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.
机译：表征植物物候变化的时间尺度通常比表征大气过程的时间尺度长得多。因此，在大气预报系统中对物候过程进行显式建模可能会为季后或季节预报提供技巧。我们在这里使用装有动态植被物候模型的预测系统来检验这种可能性。我们进行了三个实验，每个实验都包含128个独立的暖季月度预测：1）实际初始化土壤水分状态和碳状态（例如确定叶面积指数的状态）的实验，2）碳的实验在整个预报过程中，将气候状态指定为气候状态; 3）在整个预报过程中，将碳和土壤水分状态都指定为气候状态的实验。根据观测值评估每个集合体中的每月气温预测，并对每个集合体中的温度固有的可预测性进行量化，这表明动态物候确实可以对季节变化做出积极的贡献，尽管影响很小，但其影响却远远小于土壤湿度。

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