Trends in recent temperature observations and model projections of the future are characterized by greater warming of daily minimum (tmin) relative to maximum (tmax) temperatures. To aid understanding of how tmin and tmax differentially affect crop yields, we analyzed variations of regional spring wheat yields and temperatures for three irrigated sites in western North America that were characterized by low correlations between tmin and tmax. The crop model CERES-Wheat v3.5 was evaluated in each site and used to project future response to temperature changes. Tmin and tmax exhibited distinct historical correlations with yields, with CERES successfully capturing the observed relationships in each region. In the Yaqui Valley of Mexico, historical yields were strongly correlated with tmin but not tmax. However, CERES projections of response to increased tmin or tmax (holding other variables constant) were similar (6% °C^-1), indicating that the apparent historical importance of tmin mainly results from covariation between temperatures and solar radiation and not greater direct effects of tmin on yields. In the San Luis-Mexicali Valley of Mexico and in the Imperial Valley of California, the opposite was observed: historical yield correlations with tmin and tmax were similar, but projected responses to tmax were roughly three times larger than tmin. The latter is explained by opposing effects of tmin and tmax on grain filling rates in CERES, with higher tmin increasing harvest indices. This model mechanism was not clearly supported by historical data and remains an area of uncertainty for projecting yield responses to climate change.

Several impacts of climate change may depend more on changes in mean daily minimum (Tmin) or maximum (Tmax) temperatures than daily averages. To evaluate uncertainties in these variables, we compared projections of Tmin and Tmax changes by 2046-2065 for 12 climate models under an A2 emission scenario. Average modeled changes in Tmin were similar to those for Tmax, with slightly greater increases in Tmin consistent with historical trends exhibiting a reduction in diurnal temperature ranges. In contrast, the inter-model variability of Tmin and Tmax projections exhibited substantial differences. For example, inter-model standard deviations of June-August Tmax changes were more than 50% greater than for Tmin throughout much of North America, Europe, and Asia. Model differences in cloud changes, which exert relatively greater influence on Tmax during summer and Tmin during winter, were identified as the main source of uncertainty disparities. These results highlight the importance of considering separately projections for Tmax and Tmin when assessing climate change impacts, even in cases where average projected changes are similar. In addition, impacts that are most sensitive to summertime Tmin or wintertime Tmax may be more predictable than suggested by analyses using only projections of daily average temperatures.

Climate change, as an environmental hazard operating at the global scale, poses a unique and "involuntary exposure" to many societies, and therefore represents possibly the largest health inequity of our time. According to statistics from the World Health Organization (WHO), regions or populations already experiencing the most increase in diseases attributable to temperature rise in the past 30 years ironically contain those populations least responsible for causing greenhouse gas warming of the planet. Average global carbon emissions approximate one metric ton per year (tC/yr) per person. In 2004, United States per capita emissions neared 6 tC/yr (with Canada and Australia not far behind), and Japan and Western European countries range from 2 to 5 tC/yr per capita. Yet developing countries' per capita emissions approximate 0.6 tC/yr, and more than 50 countries are below 0.2 tC/yr (or 30-fold less than an average American). This imbalance between populations suffering from an increase in climate-sensitive diseases versus those nations producing greenhouse gases that cause global warming can be quantified using a "natural debt" index, which is the cumulative depleted CO2 emissions per capita. This is a better representation of the responsibility for current warming than a single year's emissions. By this measure, for example, the relative responsibilities of the U.S. in relation to those of India or China is nearly double that using an index of current emissions, although it does not greatly change the relationship between India and China. Rich countries like the U.S. have caused much more of today's warming than poor ones, which have not been emitting at significant levels for many years yet, no matter what current emissions indicate. Along with taking necessary measures to reduce the extent of global warming and the associated impacts, society also needs to pursue equitable solutions that first protect the most vulnerable population groups; be they defined by demographics, income, or location. For example, according to the WHO, 88% of the disease burden attributable to climate change afflicts children under age 5 (obviously an innocent and "nonconsenting" segment of the population), presenting another major axis of inequity. Not only is the health burden from climate change itself greatest among the world's poor, but some of the major mitigation approaches to reduce the degree of warming may produce negative side effects disproportionately among the poor, for example, competition for land from biofuels creating pressure on food prices. Of course, in today's globalized world, eventually all nations will share some risk, but underserved populations will suffer first and most strongly from climate change. Moreover, growing recognition that society faces a nonlinear and potentially irreversible threat has deep ethical implications about humanity's stewardship of the planet that affect both rich and poor.

The integration of the agricultural and energy sectors caused by rapid growth in the biofuels market signals a new era in food policy and sustainable development. For the first time in decades, agricultural commodity markets could experience a sustained increase in prices, breaking the long-term price decline that has benefited food consumers worldwide. Whether this transition occurs, and how it will affect global hunger and poverty, remain to be seen. Will food markets begin to track the volatile energy market in terms of price and availability? Will changes in agricultural commodity markets benefit net food producers and raise farm incomes in poor countries? How will biofuels-induced changes in agricultural commodity markets affect net consumers of food? At risk are over 800 million food-insecure people, mostly in rural areas and dependant to some extent on agriculture for incomes, who live on less than $1 per day and spend the majority of their incomes on food. An additional 2 to 2.5 billion people living on $1 to $2 per day are also at risk, as rising commodity prices could pull them swiftly into a food-insecure state.

We select a 30-day delay in monsoon onset as a threshold beyond which significant impact on the country's rice economy is likely to occur. To project the future probability of monsoon delay and changes in the annual cycle of rainfall, we use output from the Intergovernmental Panel on Climate Change AR4 suite of climate models, forced by increasing greenhouse gases, and scale it to the regional level by using empirical downscaling models.

Our results reveal a marked increase in the probability of a 30-day delay in monsoon onset in 2050, as a result of changes in the mean climate, from 9-18% today (depending on the region) to 30-40% at the upper tail of the distribution. Predictions of the annual cycle of precipitation suggest an increase in precipitation later in the crop year (April-June) of 10% but a substantial decrease (up to 75% at the tail) in precipitation later in the dry season (July-September). These results indicate a need for adaptation strategies in Indonesian rice agriculture, including increased investments in water storage, drought-tolerant crops, crop diversification, and early warning systems.

Changes in the global production of major crops are important drivers of food prices, food security and land use decisions. Average global yields for these commodities are determined by the performance of crops in millions of fields distributed across a range of management, soil and climate regimes. Despite the complexity of global food supply, here we show that simple measures of growing season temperatures and precipitation--spatial averages based on the locations of each crop--explain about 30% or more of year-to-year variations in global average yields for the world's six most widely grown crops. For wheat, maize, and barley, there is a clearly negative response of global yields to increased temperatures. Based on these sensitivities and observed climate trends, we estimate that warming since 1981 has resulted in annual combined losses of these three crops representing roughly 40 MT or $5 billion per year, as of 2002. While these impacts are small relative to the technological yield gains over the same period, the results demonstrate already occurring negative impacts of climate trends on crop yields at the global scale.