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ENSEMBLE CLIMATE PREDICTION METHOD USING EMPIRICAL SINGULAR VECTOR

机译:经验奇异矢量的气候预估方法

摘要

PURPOSE: An ensemble climate predicting method using empirical singular vector is provided to linearlize an atmosphere-ocean model by singular-vector-decomposing empirical function to obtain the singular vector and using the singular vector as initial ensemble perturbation. CONSTITUTION: Empirical function is generated based on past climate data. The empirical function is singular-vector-decomposed to obtain empirical singular vector. The empirical singular vector is used as initial ensemble perturbation. The empirical function is obtained based on general formula 1 and general formula 2. In the chemical formulas, the X and the Xn are initial condition state vector of a dynamic climate model. Y and Y(n+) are the predicated value state vector of the dynamic climate model. The is predication progress time. The L is empirical function. The is error from linear supposition.
机译:目的:提供一种使用经验奇异向量的整体气候预测方法,通过对奇异向量分解经验函数以获取奇异向量并将奇异向量作为初始整体扰动来线性化大气-海洋模型。构成:经验函数是根据过去的气候数据生成的。对经验函数进行奇异矢量分解,以获得经验奇异矢量。经验奇异向量被用作初始整体扰动。基于通式1和通式2获得经验函数。在化学式中,X和Xn是动态气候模型的初始状态向量。 Y和Y(n +)是动态气候模型的预测值状态向量。谓词执行时间。 L是经验函数。来自线性假设的误差。

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