Challenges and Opportunities Provided by Seasonal Climate Forecasts: A Literature Review

Abstract

Use of seasonal climate forecasts is a rapidly evolving area. Effective research and application of climate forecasts require close cooperation between scientists in diverse disciplines and decision makers. Successful collaboration requires all players to at least partially understand each other's perspectives. Issues associated with seasonal forecasts, through a selected review of both physical and social sciences literature, is presented. Our hope is that the review will improve research in this area by stimulating further collaborations.

Economics and climate applications: exploring the frontier

“…They go on to hypothesize, 'Educated people make good innovators, so that education speeds the process of technological diffusion' (Nelson & Phelps 1996, p. 70). Studies specific to the adoption of climate forecasts in the decision-making process have also emphasized decision maker education as a key to the use of climate forecasts (Hill & Mjelde 2002). One study developed materials to teach decision making and the use of probabilistic information in general, and weather and climate forecasts in particular, to junior high school students (Hoyle et al 2006).…”

“…In the present study, rather than overlapping with previous reviews of the literature on the use of economic methodology to address climate forecast issues (see e.g. Hill & Mjelde 2002), we focus first on 4 methodologies used by economists to model decision-making (and thus to determine the value of information). Though other methodologies have provided invaluable contributions to the economics of information and the valuation of climate forecasts, they are not discussed due to space limitations.…”

Valuing drought information for irrigation farmers: potential development of a hydrological risk insurance in Spain

“…Accurate climate information, such as that provided in climate predictions, can support and facilitate these decisions by helping farmers to increase the efficiency of agricultural management while boosting food and livelihood security (Hansen et al, 2006). The value of climate information will depend on whether the information enables individuals to increase their utility relative to what it would be if that information was unavailable (Hill and Mjelde, 2002). In other words, the value of information is the expected gain in a decision outcome from using additional information.…”

“…The insights that emerge from these analyses can greatly enhance agricultural management by shedding light on farmers' decision making processes (Hill and Mjelde, 2002). Recent studies claim that in order to be useful for farmers climate information needs to be salient, credible, and legitimate -where salience refers to the relevance of climate information, credibility refers to its technical quality, and legitimacy refers to the perception that the information has been developed for the Abbreviations used: AEMET (Spanish Meteorological Agency); C (cost of the insurance); CARA (constant absolute risk aversion); CE (certain equivalent); DR (demand-reliability); GCM (global circulation model); GDP (gross domestic product); OLS (ordinary least squares); RCP (representative concentration pathways); SPI (standardized precipitation index); SRES (special report on emissions scenarios); VIF (variance inflation factor); WAPA (water and policy analysis).…”

Optimal Crop Insurance Under Climate Variability: Contrasting Insurer and Farmer Interests

“…Several studies have shown that agricultural management has been improved during the last years based on the prediction of seasonal climate (Baigorria et al, 2008;Podestá et al, 2002;Nnaji, 2001). Predictability of seasonal climate variations can help in reducing farm risk by tailoring agricultural management strategies to mitigate the impacts of adverse conditions or to take advantage of favorable conditions (Letson et al, 2005;Hill and Mjelde, 2002). In this respect, crop insurance offers farmers economic stability under the uncertainty of future random events, including climate (Mahul, 2001).…”