天气预报的动力-随机差分模式
DYNAMIC-STOCHASTIC MODEL OF WEATHER FORECASTING
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摘要: 把天气预报提为气象场的演化问题,通过对偏微分方程中时间项的统计离散化,导得了使用多个起始场资料的预报模式。用正压模式和两层斜压模式的动力-随机差分格式分别进行了中期和月预报试验,效果与数值模式不相上下。Abstract: As weather forecasting is summed up as a problem of evolution of meteorological field, a forceasting model is derived by using a statistic discretization for the time differential term in a partial differnetial equation. Medium-range and month weather forecasting experiments are made with dynamic-stochastic difference schemes of barotropic model and two-layer baroclinic model respectively, forecast accuracy of models is comparable to a mumerical model.
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