This project is the most detailed study ever undertaken on the potential effect of climate change on California. This work examines a broad array of potentially affected sectors as well as the interactions between climate change and increased population, economic growth, and technological change. It considers a wide range of climate change scenarios, ranging from warmer and much wetter to warmer and much drier. Most climate models estimate that precipitation will increase. Climate change is likely to have substantial impacts on California. The location of natural vegetation will change dramatically. Productivity could increase under wetter conditions and biodiversity could be reduced under drier conditions. The combined effects of climate change and urbanization on vegetation could adversely affect some critical systems. Timber production may initially increase and then decrease, but producers and consumers may be more affected by changes in global timber prices. Higher temperatures will cause the snowpack to melt earlier in the year, increasing flood risks. Changes in the water supply are very sensitive to changes in precipitation. Agriculture will most likely demand more water, although population and economic growth will decrease the sector's allocation of water. Climate change could affect agriculture more favorably in northern California than in the south, but changes in technology may have a far greater impact statewide. Energy expenditures are projected to rise significantly. The costs involved in protecting coastal resources may rise as well, but by much smaller amounts. Finally, impacts on human health will be very sensitive to changes in climate variability.
Recent publications suggest that anthropogenic aerosols suppress orographic precipitation in California and elsewhere. A field campaign (SUPRECIP: Suppression of Precipitation) was conducted to investigate this hypothesized aerosol effect. The campaign consisted of aircraft measurements of the polluting aerosols, the composition of the clouds ingesting them, and the way the precipitation-forming processes are affected. SUPRECIP was conducted during February and March of 2005 and February and March of 2006. The flights documented aerosols and orographic clouds flowing into the central Sierra Nevada from upwind densely populated industrialized/urbanized areas and contrasted them with the aerosols and clouds downwind of the sparsely populated areas in the northern Sierra Nevada.
SUPRECIP found that the aerosols transported from the coastal regions are augmented by local sources in the Central Valley, resulting in high concentrations of aerosols in the eastern parts of the Central Valley and the Sierra foothills. This pattern is consistent with the detected patterns of suppressed orographic precipitation that occur primarily in the southern and central Sierra Nevada but not in the north. The precipitation suppression occurs mainly in the orographic clouds that are triggered from the boundary layer over the foothills and propagate over the mountains, although the elevated orographic clouds that form at the crest are minimally affected. The clouds are affected mainly during the second half of the day and the subsequent evening, when solar heating mixes the boundary layer up to cloud bases. Local, yet unidentified non-urban sources are suspected to play a major role.
The association between ambient temperature and mortality has been established worldwide, including our prior study in California. Here, we examined cause-specific mortality, age, race/ethnicity, gender, and education level to identify vulnerable subgroups of high ambient temperature. We obtained data from nine California counties from May to September 1999 to 2003, provided by the National Climatic Data Center (countywide weather) and the California Department of Health Services (individual mortality). Using a time-stratified case-crossover approach, we obtained county-specific estimates of mortality, which were combined in meta-analyses. A total of 231,676 non-accidental deaths were included. Each 10 degree Fahrenheit increase in mean daily apparent temperature corresponded to a 2.6 percent (95 percent confidence interval (CI): 1.3, 3.9) increase for cardiovascular mortality, with the most significant risk found for ischemic heart disease. Elevated risks were also found for persons at least 65 years of age (2.2 percent, 95 percent CI: 0.04, 4.0), infants one year of age and under (4.9 percent, 95 percent CI: -1.8, 11.6), and Black racial/ethnic group (4.9 percent, 95 percent CI: 2.0, 7.9). No differences were found by gender or education level. To prevent mortality associated with ambient temperature, persons with cardiovascular disease, the elderly, infants, Blacks among others should be targeted._x000B_
This report, an analysis of climate effects on agicultural systems, is a supplemental report to the main PIER-funded report that is an attachment to the Climate Action Team Report to the Governor and Legislature.
Four dynamic regional climate models (University of California, Santa Cruz'' RegCM3; the University of California, San Diego's RSM; the National Center for Atmospheric Research's WRF-RUC; and the Lawrence Berkeley National Laboratory/University of California, Berkeley's WRF-CLM3) and one statistical downscaling approach (the University of California, San Diego's CANA) were used to downscale 10 years of historical climate in California. To isolate possible limitations of the downscaling methods, initial and lateral boundary conditions from the National Centers for Environmental Prediction global reanalysis were used. Results of this downscaling were compared to observations and to an independent, fine-resolution reanalysis (the North American Regional Reanalysis). This evaluation is preparation for simulations of future-climate scenarios, the second phase of this California Energy Commission climate projections project, which will lead to probabilistic scenarios. Each model has its own strengths and weaknesses, which are summarized here. In general, the dynamic models perform as well as other state-of-the-art dynamical regional climate models, and the statistical model has comparable or superior skill, although for a very limited set of meteorological variables. As is typical of dynamical climate models, there remain uncertainties in simulating clouds, precipitation, and snow accumulation and depletion rates. Hence, the weakest aspects of the dynamical models are parameterized processes, while the weakest aspect of the statistical downscaling procedure is the limitation in predictive variables. However, the resulting simulations yield a better understanding of model spread and bias and will be used as part of the California probabilistic scenarios and impacts._x000B_
This report, an assessment of future CO2 and climate impacts on agriculture, is a supplemental report to the main PIER-funded report that is an attachment to the Climate Action Team Report to the Governor and Legislature.