广西山区气候资源小网格推算模型

Small Grids Reckoning Models of Climate Resources in Guangxi Mountains

利用广西全区90个气象台站1971-2000年的气候观测资料和站点地理信息资料，采用全区和分区建模相结合的方法，建立了广西热量、光照和降水等气候资源的数学推算模型。并在GIS支持下，对模型进行了小网格推算和残差订正，保证每个网格点上的气候资源值是比较准确的。同时绘制了气候资源分布图，将其与广西气候资源实际分布情况进行了初步分析和比较，发现二者的空间分布趋势具有一致性，而且更加细腻、真实，说明推算模型能够反映广西气候资源的分布规律，具有良好的统计意义和实际意义，为气候区划、深化工作奠定了良好的基础。

Guangxi lies in the sub-tropic zone and to the southeast of Yungui plateau, and it has complicated geographical conditions and larger mountains, which lead to distinctly tridimensional character of climate resources. However, there are only 90 weather stations in Guangxi, and majority of them locate in the plain and valley of low height above sea level and few in alpine region. So the observation data of weather stations cannot fully reflect the actual distribution of climate resource and cannot also satisfied the need of precise agoclimatic divisions in mountains. In order to detail the actual distribution rule of climate resource in Guangxi, we need build some mathematic models that can represent the relationship between climate factors and geographical information of weather station. Then based on these models, we can calculate climate resource in the small grids where there aren＇ t weather stations by the GIS. Making use of the climate data from 1971 to 2000 and geographical information data of 90 weather stations in Guangxi, this paper built reckoning models of climate resource of ≥ 10℃ accumulative temperature, annual sunlight hours and annual precipitation by the statistical method of step regression in the whole or divisional region range, flccording to the reckoning models and based on ARCGIS, climate resources can be computed to small grids, and remain error was corrected for the models by mathematics method, which can ensure that values in small girds are right. During the building models, we compare several usual methods and found that the method of divisional region is suitable to ≥10℃ accumulative temperature, and this method divided Guangxi region into three small regions, in every small region we built regressive equation, therein to longitude, latitude and height above sea level as independent variables and ≥10℃ accumulative temperature as dependent variable, and model＇ s correlative coefficient is 〉 0. 86 and relative error is 〈 2%. And the method of whole region is fit to build the reckoning model of the annual sunlight hours, therein to latitude, height above sea level and gradient as independent variables and the annual sunlight hours as dependent variable, and model＇ s correlative coefficient is 0. 779 and relative error is 5.42%. For the reckoning model of annual precipitation, we consider the most height of mountains as effect factor of precipitation. The annual precipitation reckoning model＇ s correlative coefficient is 0. 629 and relative error is 10. 65%. Then we drew the subject maps of climate resources by GIS, distribution trend of climate resources in those maps was consistent with real status of Guangxi. What＇ s more, the maps that were drew by GIS looked more exquisite and veritable than those not drawing by GIS. Above proved that reckoning models could reflect the spatial distribution of climate resources in Guangxi and had nicer statistical and actual meaning. Therefore, building of reekoning models established nicer base for agoclimatic divisions in the future work.