High-resolution climate variable generation for the Western Cape
Date
2007-03
Authors
Joubert, Sarah Joan
Journal Title
Journal ISSN
Volume Title
Publisher
Stellenbosch : University of Stellenbosch
Abstract
Due to the relative scarcity of weather stations, the climate conditions of large areas are not
adequately represented by a weather station. This is especially true for regions with complex
topographies or low population densities. Various interpolation techniques and software packages
are available with which the climate of such areas can be calculated from surrounding weather
stations’ data. This study investigates the possibility of using the software package ANUSPLIN to
create accurate climate maps for the Western Cape, South Africa.
ANUSPLIN makes use of thin plate smoothing splines and a digital elevation model to convert
point data into grid format to represent an area’s climatic conditions. This software has been used
successfully 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 (distance
from 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 the
elevation 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 study
investigates 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 of
90m x 90m. This is done for monthly mean daily maximum and minimum temperature and the
mean monthly rainfall for the study area for each month of the year.
Not many projects where additional variables have been incorporated in the interpolation process
using ANUSPLIN are to be found in the literature, thus further investigation into the correct
transformation and the units of these variables had to be done before they could be successfully
incorporated. It was found that distance to oceans influences a region’s maximum and minimum
temperatures, and to a lesser extent rainfall, while aspect and slope has an influence on a region’s
rainfall.
In order to assess the accuracy of the interpolation process, two methods were employed, namely
statistical values produced during the spline function calculations by ANUSPLIN, and the removal
of 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 additional
variables were incorporated into the interpolation process.
Once the best transformations and units were identified for the additional variables, climate maps
were produced in order to compare them with existing climate grids available for the study area. In
general the temperatures were higher than those of the existing grids. For the rainfall grids
ANUSPLIN’s produced higher rainfall values throughout the study region compared to the existing
grids, except for the Southwestern Cape where the rainfall values were lower on north-facing slopes
and high-lying area
Description
Thesis (MSc (Geography and Environmental Studies))--University of Stellenbosch, 2007.
Keywords
Digital elevation models (DEM), Spatial interpolation, ANUSPLIN, Topographic dependence, Thin plate smoothing splines, Dissertations -- Geography and environmental studies, Theses -- Geography and environmental studies