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We projected US agricultural production in 2030 and 2090 at 45 representative sites, using 2 scenarios of climate change, developed with the Hadley Centre Model and the Canadian Centre Climate Model, and the DSSAT (Decision Support Systems for Agro-technology Transfer) dynamic crop-growth models. These simulation results have previously been aggregated nationally with the aid of economic models to show an increase in overall US agricultural output under climate change. In this work, we analyzed the regional distribution of the simulated yields, showing that positive results largely depend on the precipitation increases projected by the climate scenarios. In contrast, in some important rainfed production areas where precipitation was projected to decrease, such as the Kansas and Oklahoma Bread Basket regions under the Canadian Centre Climate Model scenario, climate change resulted in significant reductions of grain yield (−30 to −40%), accompanied by increased year-to-year variability. We also discussed the response to additional factors affecting the simulated US crop production under climate change, such as higher temperature and elevated CO 2 .

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The ability to predict rainfall variability a season in advance could have a major impact on the fragile Kenyan economy. The ability to benefit from climate prediction arises from the intersection of human vulnerability, climate predictability, and decision capacity. Africa may be a prime potential benefactor of seasonal climate forecasting. With this in mind, the link between El Niño-related variability in rainfall at annual and seasonal scales and national-level maize yield in Kenya was explored. The spatial and seasonal variations in El Niño influence on rainfall are highly inconclusive in Kenya except for some highland high rainfall sites and seasons. Significant event-to-event variability was observed, however, during the October-January (OJ) crop growing season during El Niño events. Increases in the OJ seasonal rainfall during El Niño events were reflected in the annual rainfall. While the mean change in rainfall between El Niño and neutral was positive during OJ season and annually, however, the change was negative during the March-June (MJ) season. El Niño effects were greater on rainfall in the second growing season (OJ) for the 1982-83 and 1997-98 El Niño compared with the 1986-87, 1987-88, 1991 events. Sites on the highland ecoregion recorded a significant increase in rainfall during El Niño events compared with neutral years. However, the 1987-88 El Niño had a significant effect on the MJ growing season rainfall with consequent positive influence on national maize yield. Furthermore, 'super El Niños' may give rise to larger rainfall responses than normal El Niños at some sites; the magnitude varies from site to site and the effect is not obvious at some sites. The results lead to the conclusion that all El Niños are not equal in terms of their regional manifestation. All this clearly indicates the need to address critical user needs of climate information in order to produce information that is useful.

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