No abstract

Global climate change is a detectable and attributable global phenomenon, yet its manifestation at the regional scale, especially within the rainfall record, can be difficult to identify. This problem is particularly acute over southern Africa, a region characterised by a low density of observations and highly dependent on rural agriculture, where the impact of rainfall changes on maize cultivation critically depends on the timing with respect to the crop phenological cycle. To evaluate changes in rainfall affecting maize cropping, daily rainfall observations from 104 stations across Malawi, Mozambique, Zambia and Zimbabwe were used to detect trends in planting dates, rainfall cessation and duration of the rainfall season, as well as number of dry days, length of dry spells and measures of rainfall intensity during critical periods for growing maize. Correlations with the Southern Oscillation Index (SOI) and Antarctic Oscillation (AAO) were used to infer how large-scale climate variability affects these attributes of rainfall and highlight where (and when) trends may contribute to more frequent crossings of critical thresholds. The El Niño Southern Oscillation (ENSO) was associated with changes in planting and cessation dates as well as the frequency of raindays during the rainfall season (particularly early in the season). AAO mainly affected raindays towards the end of the season when maize was planted late. Trends are discussed relative to changes projected in empirically downscaled scenarios of rainfall from 7 general circulation models for the 2046-2065 period, assuming an SRES A2 emissions scenario.

Improvements in the ability to model El Niñ o and other large-scale interannual climate variations have allowed for the development of seasonal climate forecasts, predicting rainfall and temperature anomalies for many places around the world. These forecasts have allowed developing countries to predict shortfalls in grain yields, with benefits for food security. Several countries communicate the forecasts to subsistence farmers, which could allow them to mitigate the effects of drought on their harvests by adapting their cropping decisions accordingly. However, it has not been demonstrated that subsistence farmers benefit from having access to the forecasts. Here we present evidence of subsistence farmers using the forecasts over multiple years to make different decisions and significantly improving their harvests when they do so. In a controlled study, farmers in Zimbabwe who reported adapting their farming methods to seasonal climate forecasts significantly improved their harvests over baseline amounts. Moreover, farmers who had attended a brief workshop and learned more about the forecasts were significantly more likely to use the forecasts than were farmers who learned of the forecasts through nonparticipatory channels.climate change ͉ climate forecasting ͉ sustainable development

Abstract. Disaster risk reduction efforts traditionally focus on long-term preventative measures or post-disaster response. Outside of these, there are many short-term actions, such as evacuation, that can be implemented in the period of time between a warning and a potential disaster to reduce the risk of impacts. However, this precious window of opportunity is regularly overlooked in the case of climate and weather forecasts, which can indicate heightened risk of disaster but are rarely used to initiate preventative action. Barriers range from the protracted debate over the best strategy for intervention to the inherent uncomfortableness on the part of donors to invest in a situation that will likely arise but is not certain. In general, it is unclear what levels of forecast probability and magnitude are "worth" reacting to. Here, we propose a novel forecast-based financing system to automatically trigger action based on climate forecasts or observations. The system matches threshold forecast probabilities with appropriate actions, disburses required funding when threshold forecasts are issued, and develops standard operating procedures that contain the mandate to act when these threshold forecasts are issued. We detail the methods that can be used to establish such a system, and provide illustrations from several pilot cases. Ultimately, such a system can be scaled up in disaster-prone areas worldwide to improve effectiveness at reducing the risk of disaster.

In 2008, the International Federation of Red Cross and Red Crescent Societies (IFRC) used a seasonal forecast for West Africa for the first time to implement an Early Warning, Early Action strategy for enhanced flood preparedness and response. Interviews with disaster managers suggest that this approach improved their capacity and response. Relief supplies reached flood victims within days, as opposed to weeks in previous years, thereby preventing further loss of life, illness, and setbacks to livelihoods, as well as augmenting the efficiency of resource use. This case demonstrates the potential benefits to be realised from the use of medium-to-long-range forecasts in disaster management, especially in the context of potential increases in extreme weather and climate-related events due to climate variability and change. However, harnessing the full potential of these forecasts will require continued effort and collaboration among disaster managers, climate service providers, and major humanitarian donors.