MEAN AND VARIANCE CHANGE IN CLIMATE SCENARIOS: METHODS, AGRICULTURAL APPLICATIONS, AND MEASURES OF UNCERTAINTY

Our central goal is to determine the importance of including both mean and variability changes in climate change scenarios in an agricultural context. By adapting and applying a stochastic weather generator, we first tested the sensitivity of the CERES-Wheat model to combinations of mean and variability changes of temperature and precipitation for two locations in Kansas. With a 2°C increase in temperature with daily (and interannual) variance doubled, yields were further reduced compared to the mean only change. In contrast, the negative effects of the mean temperature increase were greatly ameliorated by variance decreased by one-half. Changes for precipitation are more complex, since change in variability naturally attends change in mean, and constraining the stochastic generator to mean change only is highly artificial. The crop model is sensitive to precipitation variance increases with increased mean and variance decreases with decreased mean. With increased mean precipitation and a further increase in variability Topeka (where wheat cropping is not very moisture limited) experiences decrease in yield after an initial increase from the 'mean change only case. At Goodland Kansas, a moisture-limited site where summer fallowing is practiced, yields are decreased with decreased precipitation, but are further decreased when variability is further reduced. The range of mean and variability changes to which the crop model is sensitive are within the range of changes found in regional climate modeling (RegCM) experiments for a CO₂ doubling (compared to a control run experiment). We then formed two types of climate change scenarios based on the changes in climate found in the control and doubled CO₂ experiments over the conterminous U. S. of RegCM: (1) one using only mean monthly changes in temperature, precipitation, and solar radiation; and (2) another that included these mean changes plus changes in daily (and interannual) variability. The scenarios were then applied to the CERES-Wheat model at four locations (Goodland, Topeka, Des Moines, Spokane) in the United States. Contrasting model responses to the two scenarios were found at three of the four sites. At Goodland, and Des Moines mean climate change increased mean yields and decreased yield variability, but the mean plus variance climate change reduced yields to levels closer to their base (unchanged) condition. At Spokane mean climate change increased yields, which were somewhat further increased with climate variability change. Three key aspects that contribute to crop response are identified: the marginality of the current climate for crop growth, the relative size of the mean and variance changes, and timing of these changes. Indices for quantifying uncertainty in the impact assessment were developed based on the nature of the climate scenario formed, and the magnitude of difference between model and observed values of relevant climate variables.     

Chemical composition of the background aerosol at two sites in southwestern and northwestern China: potential influences of regional transport

Concentrations of organic carbon (OC), elemental carbon (EC), selected trace elements and water-soluble (WS) ions were determined for samples collected from August 2004 to February 2005 to assess the aerosol background at two remote sites in China. The OC and EC concentrations in PM₁₀ from near the Tibetan Plateau at Zhuzhang (ZUZ) were comparable with other background sites, averaging 3.1 and 0.34 μg m⁻³, respectively, with no pronounced seasonality. At Akdala (AKD) on northern margin of the Zhungaer Basin, the average concentrations were similar (mean OC = 2.9 μg m⁻³ and EC = 0.35 μg m⁻³), but the concentrations were higher in winter. The aerosol mass at both sites was dominated by OC and SO₄²⁻, but a stronger contribution from soil dust was observed at AKD. At ZUZ, NO₃⁻ showed a unique weather-related fluctuation in PM₁₀ with a periodicity of ∼1 week. Anthropogenic sources in the Sichuan Basin and southeastern Yunnan Province evidently influence ZUZ in summer and autumn while pollutants from Russia and the China–Mongolia border affect AKD nearly all year. The identification of these upwind sources demonstrates that transboundary transport needs to be taken into account when assessing air quality in remote parts of China.