High-resolution climate variable generation for the Western Cape

[摘要] Due to the relative scarcity of weather stations, the climate conditions of large areas are notadequately represented by a weather station. This is especially true for regions with complextopographies or low population densities. Various interpolation techniques and software packagesare available with which the climate of such areas can be calculated from surrounding weatherstations' data. This study investigates the possibility of using the software package ANUSPLIN tocreate accurate climate maps for the Western Cape, South Africa.ANUSPLIN makes use of thin plate smoothing splines and a digital elevation model to convertpoint data into grid format to represent an area's climatic conditions. This software has been usedsuccessfully throughout the world, therefore a large body of literature is available on the topic,highlighting the limitations and successes of this interpolation method.Various factors have an effect on a region's climate, the most influential being location (distancefrom the poles or equator), topography (height above sea level), distance from large water bodies,and other topographical factors such as slope and aspect. Until now latitude, longitude and theelevation of a weather station have most often been used as input variables to create climate grids,but the new version of ANUSPLIN (4.3) makes provision for additional variables. This studyinvestigates the possibility of incorporating the effect of the surrounding oceans and topography(slope and aspect) in the interpolation process in order to create climate grids with a resolution of90m x 90m. This is done for monthly mean daily maximum and minimum temperature and themean monthly rainfall for the study area for each month of the year.Not many projects where additional variables have been incorporated in the interpolation processusing ANUSPLIN are to be found in the literature, thus further investigation into the correcttransformation and the units of these variables had to be done before they could be successfullyincorporated. It was found that distance to oceans influences a region's maximum and minimumtemperatures, and to a lesser extent rainfall, while aspect and slope has an influence on a region'srainfall.In order to assess the accuracy of the interpolation process, two methods were employed, namelystatistical values produced during the spline function calculations by ANUSPLIN, and the removalof a selected number of stations in order to compare the interpolated values with the actual measured values. The analysis showed that more accurate maps were obtained when additionalvariables were incorporated into the interpolation process.Once the best transformations and units were identified for the additional variables, climate mapswere produced in order to compare them with existing climate grids available for the study area. Ingeneral the temperatures were higher than those of the existing grids. For the rainfall gridsANUSPLIN's produced higher rainfall values throughout the study region compared to the existinggrids, except for the Southwestern Cape where the rainfall values were lower on north-facing slopesand high-lying area

[发布机构] Stellenbosch University