Response of Soybean and Sorghum to Varying Spatial Scales of Climate Change Scenarios in the Southeastern United States

This study examines how uncertainty associated with the spatial scale of climate change scenarios influences estimates of soybean and sorghum yield response in the southeastern United States. We investigated response using coarse (300-km, CSIRO) and fine (50-km, RCM) scale climate change scenarios and considering climate changes alone, climate changes with CO₂ fertilization, and climate changes with CO₂ fertilization and adaptation. Relative to yields simulatedunder a current, control climate scenario, domain-wide soybean yield decreased by 49% with the coarse-scale climate change scenario alone, and by26% with consideration for CO₂ fertilization. By contrast, thefine-scale climate change scenario generally exhibited higher temperatures and lower precipitation in the summer months resulting in greater yield decreases (69% for climate change alone and 54% with CO₂fertilization). Changing planting date and shifting cultivars mitigated impacts, but yield still decreased by 8% and 18% respectively for the coarse andfine climate change scenarios. The results were similar for sorghum. Yield decreased by 51%, 42%, and 15% in response to fine-scaleclimate change alone, CO₂ fertilization, and adaptation cases, respectively– significantly worse than with the coarse-scale (CSIRO) scenarios. Adaptation strategies tempered the impacts of moisture and temperature stress during pod-fill and grain-fill periods and also differed with respect to the scale of the climate change scenario.     

Spatial Scale Effects of Climate Scenarios on Simulated Cotton Production in the Southeastern U.S.A.

We examine the effect of climate scenarios generated using results from climate models of different spatial resolution on yields simulated by the deterministic cotton model GOSSYM for the southeastern U.S.A. Two related climate change scenarios were used: a coarse-scale scenario produced from results of a general circulation model (GCM) which also provided the boundary conditions to a regional climate model (RCM), from which a fine-scale scenario was constructed. Cotton model simulations were performed for three cases: climate change alone; climate change and elevatedCO₂; climate change, elevated CO₂ and adaptations to climate change. In general, significant differences in state-average projected yield changes between the coarse and fine-scale scenarios are found for these three cases. In the first two cases, different directions of change are found in some sub-regions. With adaptation, yields substantially increase for both climate scenarios, but more so for the coarse-scale scenario (30%domain-average increase). Under irrigation, yield change differences between the two climate scenarios are small in all three cases, and yields are higher under irrigation ( 35% domain-average increase with adaptation case) compared to dryland conditions. For the climate change alone case, differences in summer water-stress levels explain the contrasts in dryland yield patterns between the coarse and fine-scale climate scenarios.     

Contents of Volume 60

Volume Contents

Contents of Volume 60     

Global Climate Change — the Latest Assessment: Does Global Warming Warrant a Health Warning?

Global climate change is a qualitatively distinct, and very significant, addition to the spectrum of environmental health hazards encountered by humankind. Historically, environmental health concerns have focused on toxicological or microbiological risks to health from local exposures. However, the scale of environmental health hazards is today increasing; indeed, the burgeoning human impact on the environment has begun to alter global biophysical systems (such as the climate system). As a consequence, a range of larger-scale environmental hazards to human population health has emerged. This includes the health risks posed by climate change, stratospheric ozone depletion, loss of biodiversity, stresses on terrestrial and ocean food-producing systems, changes in hydrological systems and the supplies of freshwater, and the global spread of persistent organic pollutants. Appreciation of this scale and type of influence on human health entails an ecological perspective — a perspective that recognises that the foundations of long-term good health in populations reside in the continued stability and functioning of the biosphere's "life-supporting" ecological and physical systems. This revised version was published online in September 2006 with corrections to the Cover Date.     

The Effects of Spatial Scale of Climate Scenarios on Economic Assessments: An Example from U.S. Agriculture

The appropriate level of spatial resolution for climate scenarios is a key uncertainty in climate impact studies and regional integrated assessments. To the extent that such uncertainty may affect the magnitude of economic estimates of climate change, it has implications for the public policy debates concerning the efficiency of CO₂ control options. In this article, we investigate the effects that different climate scenario resolutions have on economic estimates of the impacts of future climate changeon agriculture in the United States. These results are derived via a set of procedures and an analytical model that has been used previously in climate change assessments. The results demonstrate that the spatial scale of climate scenarios affects the estimates of both regional changes in crop yields and the economic impact on the agricultural sector as a whole. An assessment based on the finer scale climatological information consistently yielded a less favorable assessment of the implications of climate change. Regional indicators of economic activity were of opposite sign in some regions, based on the scenario scale. Such differences in economic magnitudes or signs are potentially important in examining whether past climate change assessments may misstate the economic consequences of such changes. The results reported here suggest that refinement of the spatial scale of scenarios should be carefully considered in future impacts research.     

Climate Change and Forest Fire Potential in Russian and Canadian Boreal Forests

In this study outputs from four current General Circulation Models (GCMs) were used to project forest fire danger levels in Canada and Russia under a warmer climate. Temperature and precipitation anomalies between 1 × CO₂ and 2 × CO₂ runs were combined with baseline observed weather data for both countries for the 1980–1989 period. Forecast seasonal fire weather severity was similar for the four GCMs, indicating large increases in the areal extent of extreme fire danger in both countries under a 2 × CO₂ climate scenario. A monthly analysis, using the Canadian GCM, showed an earlier start to the fire season, and significant increases in the area experiencing high to extreme fire danger in both Canada and Russia, particularly during June and July. Climate change as forecast has serious implications for forest fire management in both countries. More severe fire weather, coupled with continued economic constraints and downsizing, mean more fire activity in the future is a virtual certainty. The likely response will be a restructuring of protection priorities to support more intensive protection of smaller, high-value areas, and a return to natural fire regimes over larger areas of both Canada and Russia, with resultant significant impacts on the carbon budget.     

Analysis of variability and diurnal range of daily temperature in a nested regional climate model: comparison with observations and doubled CO2 results

Analysis of daily variability of temperature in climate model experiments is important as a model diagnostic and for determination of how such variability may change under perturbed climate conditions. The latter could be important from a climate impacts perspective. We analyze daily mean, diurnal range and variability of surface air temperature in two continuous 3 1/2 year long climate simulations over the continental USA, one for present day conditions and one for conditions under doubled carbon dioxide concentration, conducted with a regional climate model (RegCM), on a 60 km grid, nested in a general circulation model (GCM). Model output is compared with a 30-year daily observational data set for various regions of the USA. In comparison with observations the diurnal range in the model control run is somewhat too low although the daily temperature mean is often well reproduced. The daily variability of temperature is underestimated by the model in all areas, but particularly when and where the observed variability is relatively high. Causes for these underestimations are traced to deficiencies in the general circulation of the driving GCM. With doubled CO₂, both maximum and minimum temperatures increase, but the change in the diurnal temperature range (DTR) varies spatially and seasonally. On an annual average over the land domain, the DTR decreases by 0.25'C. Changes in DTR are most strongly correlated with changes in absorbed shortwave radiation at the surface, which explains 72% of the variance in DTR on an annual basis. Change in evaporation was a factor affecting DTR only in the summer when it explained 52% of the variance. The most significant findings with CO₂ doubling are substantial decreases in daily variability in winter over large portions of the domain, and localized increases in summer. Causes for these changes are traced to fluctuations in the intensity and position of the jet stream.