随机天气模型参数化方案的研究及其模拟能力评估

文中介绍了随机天气模型 WGEN的基本结构及其模拟原理 ,并针对其中随机过程的统计结构特征和 GCMs输出要素的不同时空尺度特点 ,利用动态数据的参数化分析方法等统计学技术 ,确定了该模型参数的估计方法。同时基于蒙特卡罗数值计算原理 ,给出了 WGEN的随机试验方法 ,并通过模拟基准气候 ,从时间分布和空间场两方面对模型在中国东北地区的模拟效果及其能力进行了评估。结果表明 ,模型对于最高气温、最低气温、降水和辐射等要素均具有较好的模拟效果 ,模拟序列与观测序列的取值分布有较一致的概率特性。由此可以结合 GCMs大尺度网格上输出的月和年要素值 ,通过调控随机过程的参数 ,生成具有不同气候变率的 2× CO2 逐日气候变化情景 ,实现气候预测模式与气候影响模式的嵌套 ,进一步研究气候变率变化的可能影响。

STUDY ON THE PARAMETERS PROGRAMME OF A STOCHASTIC WEATHER GENERATOR AND EVALUATION OfiTS SIMULATION

The fundamentals of a stochastic weather generator (WGEN) run for synthetic daily climate scenarios are discussed in detail, and in accordance with the statistic attributes of each stochastic process embodied and commonly available information from general circulation models (GCMs), its parameters programme is presented and specified through statistic techniques (such as parametric analysis of dynamic data etc.). A stochastic experiment of WGEN is presented and carried out on the basis of the principles of Monte Carlo numerical calculation. Proceed from the overall analysis of temporal and spatial statistic characteristics, evaluation of the present climate simulation in Northeast China from this experiment has been made. It is concluded that WGEN has fairly good skills in generating maximum temperature, minimum temperature, precipitation and radiation. The probability property of data sequence observed and simulated is rather identical as well. Therefore, daily climatic change scenarios with different climatic variabilities can be generated with the combination of yearly and monthly output of GCMs at large spatial resolution, and adjustment of WGEN parameters. Thus, a promising approach is given to link climate models with various impacts models, and study the impacts of the change in climate variability.