纬向平均环流预报的系统性误差及其改进

大量的月预报实例分析表明,纬向平均环流(本指高度场纬向平均分量)存在明显的系统性预报误差,且在总误差中占有可观的份额。国内外其它模式也存在类似的现象。为克服这一困难,本尝试了“结合”(hybrid)的途径。应用重构相空间理论和非线性时空序列预测方法,在大量历史资料的基础上,构造了月尺度逐侯纬向平均高度场(零波分量)距平场的非线性预报模型。然后,将非线性预报和谱模式动力预报结合起来,即将非线性预报结果转化为模式需要的颅报量,再在模式积分过程中的每一步取代其相应部分,实施过程订正。初步试验结果表明,这种途样合效地减少了模式纬向环流的预报误差;特别是通过非线性波流相互作用,还改善了部分波动分量的预报。

Amplitude-Phase Characteristics of the Annual Cycle of Surface Air Temperature in the Northern Hemisphere

An analysis of a large number of cases of 500 hPa height monthly prediction shows that systematicerrors exist in the zonal mean components which account for a large portion of the total forecast errors, andsuch errors are commonly seen in other prediction models. To overcome the difficulties of the numericalmodel, the authors attempt a "hybrid" approach to improving the dynamical extended-range (monthly)prediction. The monthly pentad-mean nonlinear dynamical regional prediction model of the zonal-meangeopotential height (wave number 0) based on a large amount of data is constituted by employing thereconstruction of phase-space theory and the spatio-temporal series predictive method. The dynamicalprediction of the numerical model is then combined with that of the nonlinear model, i.e., the pentad-mean zonal-mean height produced by the nonlinear model is transformed to its counterpart in the numericalmodel by nudging during the time integration. The forecast experiment results show that the above hybridapproach not only reduces the systematic error in zonal mean height by the numerical model, but alsomakes an improvement in the non-axisymmetric components due to the wave-flow interaction.