Mark Tadross

The Interannual Variability of the Onset of the Maize Growing Season over South Africa and Zimbabwe

Abstract Subsistence farmers within southern Africa have identified the onset of the maize growing season as an important seasonal characteristic, advance knowledge of which would aid preparations for the planting of rain-fed maize. Onset over South Africa and Zimbabwe is calculated using rainfall data from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) and the Computing Center for Water Research (CCWR). The two datasets present similar estimates of the mean, standard deviation, and trend of onset for the common period (1979–97) over South Africa. During this period, onset has been tending to occur later in the season, in particular over the coastal regions and the Limpopo valley. However, the CCWR data (1950–97) indicate that this is part of long-term (decadal) variability. Characteristic rainfall patterns associated with late and early onset are estimated using a self-organizing map (SOM). Late onset is associated with heavier rainfall over the subcontinent. When onset is ea...

Climate Change Adaptation for Conservation in Madagascar

Madagascars imperilled biota are now experiencing the effects of a new threat—climate change ([Raxworthy et al . 2008][1]). With more than 90% endemism among plants, mammals, reptiles and amphibians, the stakes are high. The pristine landscapes that allowed this exceptional biodiversity to

Estimating least-developed countries' vulnerability to climate-related extreme events over the next 50 years.

When will least developed countries be most vulnerable to climate change, given the influence of projected socio-economic development? The question is important, not least because current levels of international assistance to support adaptation lag more than an order of magnitude below what analysts estimate to be needed, and scaling up support could take many years. In this paper, we examine this question using an empirically derived model of human losses to climate-related extreme events, as an indicator of vulnerability and the need for adaptation assistance. We develop a set of 50-year scenarios for these losses in one country, Mozambique, using high-resolution climate projections, and then extend the results to a sample of 23 least-developed countries. Our approach takes into account both potential changes in countries’ exposure to climatic extreme events, and socio-economic development trends that influence countries’ own adaptive capacities. Our results suggest that the effects of socio-economic development trends may begin to offset rising climate exposure in the second quarter of the century, and that it is in the period between now and then that vulnerability will rise most quickly. This implies an urgency to the need for international assistance to finance adaptation.

Attribution of extreme weather to anthropogenic greenhouse gas emissions: Sensitivity to spatial and temporal scales

Recent studies have examined the anthropogenic contribution to specific extreme weather events, such as the European (2003) and Russian (2010) heat waves. While these targeted studies examine the attributable risk of an event occurring over a specified temporal and spatial domain, it is unclear how effectively their attribution statements can serve as a proxy for similar events occurring at different temporal and spatial scales. Here we test the sensitivity of attribution results to the temporal and spatial scales of extreme precipitation and temperature events by applying a probabilistic event attribution framework to the output of two global climate models, each run with and without anthropogenic greenhouse gas emissions. Attributable risk tends to be more sensitive to the temporal than spatial scale of the event, increasing as event duration increases. Globally, correlations between attribution statements at different spatial scales are very strong for temperature extremes and moderate for heavy precipitation extremes.

Evaluation and projections of extreme precipitation over southern Africa from two CORDEX models

The study focuses on the analysis of extreme precipitation events of the present and future climate over southern Africa. Parametric and non-parametric approaches are used to identify and analyse these extreme events in data from the Coordinated Regional Climate Downscaling Experiment (CORDEX) models. The performance of the global climate model (GCM) forced regional climate model (RCM) simulations shows that the models are able to capture the observed climatological spatial patterns of the extreme precipitation. It is also shown that the downscaling of the present climate are able to add value to the performance of GCMs over some areas depending on the metric used. The added value over GCMs justifies the additional computational effort of RCM simulation for the generation of relevant climate information for regional application. In the climate projections for the end of twenty-first Century (2069–2098) relative to the reference period (1976–2005), annual total precipitation is projected to decrease while the maximum number of consecutive dry days increases. Maximum 5-day precipitation amounts and 95th percentile of precipitation are also projected to increase significantly in the tropical and sub-tropical regions of southern Africa and decrease in the extra-tropical region. There are indications that rainfall intensity is likely to increase. This does not equate to an increase in total rainfall, but suggests that when it does rain, the intensity is likely to be greater. These changes are magnified under the RCP8.5 when compared with the RCP4.5 and are consistent with previous studies based on GCMs over the region.

Climate change, groundwater and intensive commercial farming in the semi-arid northern Sandveld, South Africa

Progress in the area of international climate negotiation has been the site of substantively increased activity of late, yet the task of utilizing appropriate spatial scale climate change projections to understand climate change impacts on sensitive sectors remains challenging. The study described here, undertaken in semi-arid south western South Africa, shows how downscaled climate change projections may be used to characterize climate change impacts in an area that is both valuable from a conservation point of view, yet at the same time serves as host to input intensive commercial agribusiness in the form of potato and rooibos tea production. Such potentially polarized land management objectives have given rise to initiatives to develop better practice guidelines for undertaking intensive commercial agriculture in a sensitive biodiverse environment. The study suggests that climate change may make the achievement of such better practice significantly more challenging. Climate change is here seen as one of a number of critically interacting multiple stressors affecting the area; including the trend to input-intensive farming and competing demands for water.

Climate change and desertification in South Africa – science and response

Despite significant attention paid to desertification and climate change in the last few decades, interactions between the phenomena, as well as implications thereof, have received less of a focus. Such a trend is particularly marked in the science– policy arena, at multiple scales. Reynolds et al. (2007) observe, for example, the lack of a focused international science programme in desertification—a gap that may compound the problem. This article seeks to unpack two-way interactions between climate change and desertification, using selected case studies from the South and southern African, and global, contexts. It considers emerging approaches to responding to climate change in the context of desertification, emphasising the need for improved integrated biophysical and social science approaches, a focus on multiple synergies and cross-sectoral strategies, and the need for improved communication across the science–policy divide.

Seasonal variation in the nitrogen nutrition and carbon assimilation in wild and cultivated Aspalathus linearis (rooibos tea)

The Fynbos Biome of southern Africa is a Mediterranean-climate ecosystem with highly infertile soil. It is home to the endemic leguminous shrub Aspalathus linearis (rooibos tea), which is both an invaluable wild resource and commercially cultivated plant. Wild rooibos has a narrow geographic range and is confined to mountain ranges of the Cederberg Region. Under projected climate change, warmer and more arid conditions may place additional pressure on these range-restricted plants to survive in an already resource-limited environment. To understand the adaptive strategies that may allow rooibos to persist in its habitat under future climate change, the present study evaluated changes in the photosynthetic activity and nutrient cycling of wild and cultivated A. linearis, at the temperature and rainfall extremes of summer and winter. Wild and cultivated rooibos tea had different methods of adapting to nitrogen (N) nutrition and carbon (C) assimilation during wet and dry seasons. In particular, the wild plants were better able to tolerate summer drought by increased water use efficiency and maintaining higher levels of biological N2 fixation than was the cultivated tea.

Crop model usefulness in drylands of southern Africa: an application of DSSAT

Crop models are useful tools for simulating impacts of climate and agricultural practices on crops. Models have to demonstrate the ability to simulate actual crop growth response in particular environments before application. Data limitations in southern Africa frequently hinder adequate assessment of crop models before application. The DSSAT model was used to test the usefulness of crop models under data-limited dryland conditions of southern Africa by validation using data from experimental trial reports and district-wide crop yield estimates. Two crops each were selected in three locations to represent varying cropping and physical conditions in southern Africa, i.e. maize and sorghum (Mohales Hoek, Lesotho and Big Bend, Swaziland) and maize and groundnut (Lilongwe, Malawi). DSSAT performs well in simulating crop yields obtained from experimental trials. District-wide simulated mean crop yields were acceptable (relative difference ranged from −12.2% to +2.36%). However, the models capture of seasonal yield variation for some locations and crops was uncertain due to climate extremes. It was concluded that satisfactory crop model testing before application is possible and that DSSAT crop models are useful even under data-limited conditions.

Wave spectra of SAR imagery of the Odden ice tongue

SAR imagery from the ERS-1 satellite provides an excellent tool for continuous observation of sea-ice in polar regions. On the basis of a theoretical model, wave spectra derived from SAR images can be used to detect ice thickness in the Marginal Ice Zone if the ice is composed of frazil or pancake. A field experiment involving several scientific institutions was performed in the Odden ice tongue in the Greenland Sea during April 1993. A set of 24 high-resolution SAR images for the same period and covering the same area was acquired and processed. The image analysis consisted of the following steps: (1) geo-location and geo-reference of each image onto a UTM map projection; (2) mosaicking, after compression, of all images onto a general map of the Odden; (3) extraction of full resolution windows, 512/spl times/512 pixel size, outside (open sea) and inside the ice cover in the image; (4) wave spectra computation by means of the Optical Fourier Transform; (5) contour plot and peak detection of wave spectra. The analysis gives the change of wavelength and angle of refraction of the dominant wave entering the ice field. Ice thickness values derived from the theory were larger than those measured during the field experiment. This finding suggests a need to refine the dispersion relation in the theoretical model.