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ADVANCES IN MOUNTAIN MICROCLIMATE SIMULATION

山地小气候模拟研究进展


山地气候是最为复杂的气候类型之一,加上观测点少,气象资料比较缺乏,研究的难度很大,采用模型模拟的方法对山地气候进行研究是气象和生态学的交叉领域,得到气象和生态学者的广泛重视。目前,山地小气候模型模拟已得到很大的发展,作者从温度、降水、湿度、太阳辐射和风场5 个方面综述了国内外在这方面的研究进展:1)温度场的模拟主要是以分离&综合法改进后的多元回归法为主;2)降水模拟的方法主要有地形因子相关法(又可分为单要素、双要素、三要素和多要素)和趋势面法;3)关于湿度,一般气象站只观测水汽压和相对湿度,但一般的生态系统模型却是以水气压饱和差来表征湿度的,用湿度-辐射循环法模拟;4)太阳辐射的模拟很复杂,主要以直接辐射、散射辐射、反射辐射和总辐射分别来模拟;5)风场主要模拟方法有诊断方法和预报方法。以上对山地小气候的模型模拟总的特点为:区域性强、经验性大、普适性(理论性)差。同时,我们根据实际研究工作,展望了未来山地气候中小尺度模拟研究的两个侧重点:1)今后要综合、动态地模拟山地小气候系统,用现代理论尤其是非线性理论来研究山地气候,以加强理论方面的研究;2)加强对先进技术(例如GIS、RS 等)的吸收利用。

 

Abstract The mountain microclimate system is one of the most complicated climate systems. Meteorological stations in mountain regions are limed, which make it difficult for us to study, explore, and make use of the mountain microclimate. Fortunately, the computer has become a powerful tool in researching the variation of the mountain microclimate. The study of the mountain microclimate, based on the simulation model, is the cross subject of meteorology and ecology. In this paper, the advances of mountain microclimate simulations of the temperature, the precipitation, the humidity, the solar radiation and the wind are reviewed, respectively. There are various simulations including l) the model of‘ temperature, a multitudinous regression (both linear regression and non-linear regression) basing on the separated-integrated method; 2) trend surface analysis and topographic factor correlation analysis (including monofactorial, bifactorial, trifactorial and multifactorial) applied in the simulations of the precipitation; 3) models for the relative humidity and the vapor pressure which are the main parameters describing the humidity for the weather stations, but in most of the ecological models, the humidity is represented as the vapor pressure deficit and is simulated by the iterative algorithm between humidity and radiation; 4) the simulation of the solar radiation which is relatively complex, and is commonly simulated in the direct radiation, the diffuse radiation, the reflective radiation, and the total radiation, respectively; and 5) the methods of wind simulation which include diagnosis and forecast.

     Based on our studies, we propose methods to improve the algorithm for estimating the mountain microclimate. It is well known that, in the past, when people simulated the mountainous climate, they always took it as a linear, balance and simple system. But we know now the mountainous climate is more complex and, we should regard it as a dynamic and complicated system in the future. When simulating it, we must combine it with the modem theories, especially the modem non-linear theory, to reinforce the theoretical study. At the same time, GIS and RS had proved to be useful in the simulation of the radiation. We should try to incorporate the advanced technologies (eg. GIS and RS) with other mountain microclimate models to improve their precision and help us better understand the microclimate in the mountainous region.