Elsevier

Journal of Arid Environments

Volume 70, Issue 4, September 2007, Pages 604-614
Journal of Arid Environments

Namaqualand's climate: Recent historical changes and future scenarios

https://doi.org/10.1016/j.jaridenv.2006.03.024Get rights and content

Abstract

A brief outline of some issues concerning global climate change research is presented before discussing local-scale changes in Namaqaland's rainfall. Using a gridded data set derived through interpolation of station records, trends in observed rainfall for the period 1950–1999 are discussed. To assess what changes may occur during the 21st century, the downscaled results of six different General Circulation Model projections are presented. The historical trends show some clear spatial patterns, which depict regions of wetting in the central coastal belt and the north-eastern part of the domain, and extensive drying along the escarpment. Reasonably good agreement is shown by the different downscaled projections. These suggest increased late summer convective precipitation in the north-east, but extensive drying along the coast in early and mid winter consistent with the poleward retreat of rain-bearing mid-latitude cyclones.

Introduction

Climate change is a highly topical issue in today's society. Its impacts extend across the physical, natural and social domains and are thus of importance to researchers in a wide range of disciplines. There is therefore a clear demand for reliable information regarding both past and future climate, but there are many uncertainties and caveats that restrict our knowledge of the climate system and climate change.

Station records provide the most direct measurements with which one can study historical trends in climate, but these can be unreliable, with large gaps often appearing in station time-series. Poor spatial coverage of stations is another problem, which is particularly evident in sparsely populated arid regions. Since a station represents only a single point, it may not be adequately representative of the surrounding region, especially in the presence of complex environmental gradients and highly cellular convective rainfall. To help overcome this, much work has been done to produce gridded data sets from existing station records in order to approximate the true spatio-temporal variability of climate variables (e.g. New et al., 2000; Hewitson and Crane, 2005). These gridded products are useful for many different applications, including historical analysis, vegetation and hydrological modelling, validation of climate model output, and climate downscaling. As is discussed below, this study makes use of one such product.

When one attempts to make projections of what the future climate may be, many more uncertainties are introduced (e.g. Allen et al., 2000; Weaver and Zwiers, 2000; Stott and Kettleborough, 2002). The primary tool for climate projections is the General Circulation Model (GCM), which is a numerical representation of the earth's atmosphere, oceans and land surface. Many different GCMs are in operation, each with different assumptions and parameterizations regarding the various physical processes. Sub-grid scale processes, such as cloud formation and precipitation, are particularly difficult to simulate and a variety of schemes exists to represent these. The land surface plays a very important role in the surface energy and water balance, but is also problematic to represent (Crossley et al., 2000). It is therefore clear that—complex and sophisticated as GCMs are—these models are by no means perfect representations of the climate system. Non-linear feedback and the inherently chaotic nature of the climate system (Lorenz, 1993; Palmer, 1999) make the task of climate modelling that much more difficult.

To derive a projection of future climate, a GCM is forced with a change in atmospheric chemistry as prescribed by an emission scenario. A group of scenarios for the 21st century is presented in the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES; Nakićenović et al., 2000). These scenarios are based on various assumptions about how the global economy will evolve over the upcoming century, and what the associated greenhouse gas emissions will be. These range from major reductions in global emissions to an acceleration in fossil fuel use and rapid increase in emissions. So, in addition to the caveats inherent in climate modelling, there is uncertainty about the true magnitude of anthropogenic forcing.

Spatial scale is yet another problem encountered by climatologists. GCMs, with typical grid sizes of 300–500 km, are skillful at the global, hemispheric and synoptic scales, but to use raw GCM output to evaluate a region, the size of Namaqualand would not be appropriate. To overcome this problem, various methods of downscaling have been developed (Murphy, 1998; Giorgi et al., 2001). The dynamical approach uses a Regional Climate Model (RCM), which is a numerical model with a much smaller grid size than a GCM and is nested within a GCM simulation (Takle et al., 1999; Pan et al., 2001). Statistical or empirical methods provide a computationally cheaper alternative to dynamical downscaling (Wilby et al., 1998; Hewitson and Crane, in press) and form the basis for the climate projections for Namaqualand discussed in this paper.

It is beyond the scope of this paper to delve too deeply into the numerous topics surrounding climate change, but for further reading, the IPCC Third Assessment Report currently represents the most comprehensive review of climate research (Houghton et al., 2001). The IPCC Fourth Assessment Report is due for publication in 2007.

Namaqualand is situated in the western part of South Africa. It extends from the Orange River in the north to Vanrhynsdorp and Calvinia in the south, and about 200–300 km inland of the West Coast. It is classed as a semi-arid winter rainfall region, but the geography of the area ensures that the climate is by no means uniform. Mean annual precipitation (MAP) ranges from 50 mm in the north-west to over 400 mm in the Kamiesberg (Cowling et al., 1999) and has been described as predictable and reliable (Hoffman and Cowling, 1987). The coastal belt extends 50–75 km inland and borders the cold Benguela upwelling system. This ocean system has a pronounced influence on climate, moderating temperatures and causing coastal fog to occur frequently. Further inland, the Kamiesberg rises to over 1600 m and to the east of the escarpment the interior plateau averages about 1000 m in altitude. The escarpment is important in modifying the rainfall brought by frontal systems, and controls shallow atmospheric features, most notably coastal trapped waves (coastal lows). In the north-east, as the Nama-Karoo biome is reached, summer convective precipitation events become an important contributor to annual rainfall.

The aim of this paper is to discuss changes in Namaqualand's rainfall using recently derived information concerning the past and future climate of South Africa as a whole. Firstly, trends in Namaqualand's rainfall for the period 1950–1999 are determined using a gridded rainfall data set, and secondly, scenarios of future rainfall change for the period 2070–2099 using a downscaled climate change product are presented.

Section snippets

Observed changes: 1950–1999

Trends in rainfall for the period 1950–1999 are discussed using the 10 km interpolated precipitation of Hewitson and Crane (2005). This data set uses all available station data from 1950 to 1999 (∼3000 stations across South Africa). Not all stations have presence through this period, but the available stations are used to define the spatial distance decay functions to interpolate the inter-station precipitation field from those stations reporting on any given day. The interpolation parameters

Observed changes: 1950–1999

The 50-year observed trends in seasonal rainfall shown in Fig. 1 reveal some clear patterns. The largest changes in seasonal totals have occurred in March–May (MAM) and June–August (JJA). This is to be expected, as the region receives the majority of its rainfall in the southern hemisphere's winter months (April–September). For all four periods there is a persistent spatial pattern in the anomalies. The central coastal region, with the exception of a small but distinct area of reduced rainfall

Discussion and conclusions

It is clear from the results that there is much local-scale variability in rainfall trends within the Namaqualand region. Historical changes are characterized by distinct areas of both increases and decreases in rainfall. Topography appears to be an important driver of these heterogeneities. This is most evident in the high-lying areas of the Kamiesberg, which experienced a localized decrease in rainfall, while the surrounding areas, including Kamieskroon, saw an increase during the 1950–1999

Acknowledgements

The authors wish to acknowledge funding provided by BIOTA Southern Africa, and the AIACC AF07 project.

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