Constraints and opportunities in applying seasonal climate forecasts in agriculture

Abstract

Climate variability has an enormous impact on agricultural productivity, rural livelihoods, and economics at farm, regional, and national scales. An every-day challenge facing farmers is to make management decisions in the face of this climate variability. Being able to minimise losses in droughts and take advantage of favourable seasons is the promise of seasonal climate forecasts. The criteria for their adoption depends on what variables are forecast, their accuracy, the likely economic and/or natural resource benefits and how well they are communicated. In reviewing how current seasonal climate forecasts meet these criteria, it is clear that they offer considerable potential to buffer the effects of climate variability in agriculture, particularly in regions that have high levels of inter-annual rainfall variability and are strongly influenced by El Niño and La Niña events. However, the current skill, lead time, relevance to agricultural decisions, and communication techniques are not well enough advanced and/or integrated to lead to widespread confidence and adoption by farmers. The current challenges are to continue to improve forecast reliability and to better communicate the probabilistic outputs of seasonal climate forecasts to decision makers.

Access to Risk Mitigating Weather Forecasts and Changes in Farming Operations in East and West Africa: Evidence from a Baseline Survey

“…Some research findings have indicated the usefulness of weather forecasts for reducing vulnerability of rain-fed agriculture to drought, flooding and extremely low or high temperature [22][23][24][25][26]. Initiatives to promote access of African farmers to weather forecasts include formation of several regional Climate Outlook Forums (COFs) in the late 1990s [27][28][29][30].…”

Preface: Climate Predictions for Better Agricultural Risk Management

“…Similar to Ash et al (2007), they note that for successful adoption of SCF: (1) regions need to posses skilful and actionable forecasts, (2) regions need to be agriculturally active and support crops that are sensitive to climate variability (for the US, only the Florida peninsular and eastern and southern Texas appear to fulfil this criterion), and (3) processes need to be in place that encourage agricultural service agencies to include forecast-based decision support in their services. The authors stress the importance of participatory approaches that include all interested parties to ensure success in the development, implementation, and communication of farm-specific prediction products.…”

“…The discussion surrounding Ash et al (2007), Garbrecht and Schneider (2007), and Hayman et al (2007) highlighted the difficulties farmers have in integrating SCF into their decision making, which were echoed by Nelson et al (2007) in the policy domain. While science is geared towards providing detailed, quantitative solutions to precise questions, decision makers such as farmers and policy makers require holistic evaluations of multiple sources of risk.…”

“…The authors conclude that rapidly increasing computing power will allow us to increase the resolution and accuracy of GCMs and their derivatives, thereby increasing not only their relevance to the intended problem domain but also their scientific credibility. Ash et al (2007) highlight the constraints and opportunities in applying SCF from the perspective of farmers in Australia. They stress that farmers need to make management decisions on a daily basis in the face of climate variability.…”

Food price volatility and hunger alleviation – can Cannes work?

“…There is also an established link between global climate patterns and food price volatility [60]. Droughts in Australia and poor growing conditions in Russia, the United States and the Ukraine over several years significantly contributed to the 2008 spike in global wheat prices [28].…”