A new monthly volcanic forcing dataset is included in a coupled GCM for a more physically consistent treatment of the stratospheric sulfate aerosol history from explosive volcanism. The volcanic forcing is different from previous versions in that there is an individual evolution of the aerosol for each event. Thus the seasonal and latitudinal dependence of the volcanic aerosol can affect global climate in a more realistic way prior to the satellite period, compared to earlier volcanic forcing datasets. Negative radiative forcing from volcanic activity is greatest in the early 20th century prior to 1915 and in the late 20th century after 1960. The combination of volcanic and solar forcing contributes to an early-20th century warming, followed by relative cooling in late 20th century. Consequently, the addition of natural forcing factors to the anthropogenic GHG forcing in late 20th century is required to simulate the observed late 20th century warming.

Foodborne diseases have large economic and societal impacts worldwide. To evaluate how the risks of foodborne diseases might change in response to climate change, credible and usable climate information tailored to the specific application question is needed. Global Climate Model (GCM) data generally need to, both, be downscaled to the scales of the application to be usable, and represent, well, the key characteristics that inflict health impacts. This study presents an evaluation of temperature-based heat indices for the Washington D.C. area derived from statistically downscaled GCM simulations for 1971-2000--a necessary step in establishing the credibility of these data. The indices approximate high weekly mean temperatures linked previously to occurrences of Salmonella infections. Due to bias-correction, included in the Asynchronous Regional Regression Model (ARRM) and the Bias Correction Constructed Analogs (BCCA) downscaling methods, the observed 30-year means of the heat indices were reproduced reasonably well. In April and May, however, some of the statistically downscaled data misrepresent the increase in the number of hot days towards the summer months. This study demonstrates the dependence of the outcomes to the selection of downscaled climate data and the potential for misinterpretation of future estimates of Salmonella infections.