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_
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_
Long-term variations in climate (temperature and precipitation) in portions of California are not sufficiently well-sampled in some remote areas lacking meteorological or hydrological stations. A combined strategy of small clusters of climate stations arranged from the coast to the mountains was adopted to guide the deployment of a network of new long-term monitoring sites. This strategy for the stations installed as part of this project was suggested through consultation with research and operational entities throughout the state, but priority was given to stations located in the coastal environment and high elevations above the average winter snow line. A set of 15 sites had instruments installed to become a part of this study; they provide ongoing measurements with 10-minute resolution, at elevations ranging from sea level to over 14,000 feet. Almost the entire range of elevation in California is now sampled for climate monitoring as a result of this project. Most stations are located where future site disruption is judged to be unlikely. A few sites were established to monitor particular climate elements such as wind, temperature, or humidity. Coastal sites have shown very large differences in short vertical and horizontal distances, confirming the rationale for close spacing in certain settings. Measure data are posted immediately to the Web. Methods to graph, summarize, and download the data have been working very well. Experimental techniques are showing that higher elevations appear to have begun warming significantly over the last one to two decades in comparison with lower elevation areas. The project motivated the development of the California Climate Tracker, a method for showing the climate history of the state and 11 subregions for the past 115 years. This tool is intended for a wide audience and can be accessed through the California Climate Data Archive and the Western Regional Climate Center._x000B_
Research has suggested that carbon can be captured through changes in farming practices, thereby helping California reach its greenhouse gas emission reduction goals as put forward under the California Global Warming Solutions Act of 2006, Assembly Bill 32, (Núñez, Chapter 488, Statutes of 2006). This study assessed the potential and economic feasibility of soil carbon sequestration and reduction of trace gas emissions in California agricultural soils. To accomplish this, the researchers integrated databases that include geographic data on environmental factors and land use data with ecosystem simulation models and economic analyses. The resulting assessment tool analyzes land use and management impacts on carbon stocks and associated greenhouse gas fluxes between California agricultural soils and the atmosphere. The study found that adjusting farming practices could reduce greenhouse gas emissions by about 0.5 to 3 megagrams of carbon dioxide equivalent per hectare per year. The variation in this number is mainly on the type of farming practice used. This potential increased in the following order: low nitrogen fertilizer input, reduced tillage, manure application, and winter cover cropping. Even higher potentials could be reached when these single management options are combined. However, the uncertainty around the carbon reduction potentials of a single field remains large. More research is needed to reduce this uncertainty.
The frequency of Santa Ana wind events is investigated within a high-resolution downscaling of the European Centre for Medium-Range Weather Forecasts ERA-40 reanalysis data to 6 kilometer resolution over Southern California. In this climate reconstruction, the number of Santa Ana days per winter season declines significantly over the 44-year reanalysis period, resulting in over 30 percent fewer events per year over the final decade of the reconstruction (1991-2001) compared to the first decade (1959-1969). This study investigates this signal further in late-twentieth and mid-twenty-first century realizations of the National Center for Atmospheric Research Community Climate System Model, version 3.0, global climate change scenario run downscaled to a 12-kilometer resolution over California. The reduction in events per year in the mid-twenty-first century compared with the late-twentieth century is similar to that seen in the ERA-40 downscaling, suggesting the cause of the decrease is a change in the climate due to anthropogenic forcing. A regression model is used to reproduce the Santa Ana time series based on two previously documented forcing mechanisms: synoptically-forced strong offshore winds at the mountain tops (which transport offshore momentum to the surface), and a local desert-ocean temperature gradient causing katabatic-like winds as the cold desert air pours down the coastal topography. Both past and future climate simulations show a large reduction in the contribution of the local thermodynamic forcing. This reduction is due to the differential warming that occurs during transient climate change conditions, with more warming in the desert interior than over the ocean. Thus the mechanism responsible for the decrease in Santa Ana frequency originates from a well-known aspect of the climate response to increasing greenhouse gases, but cannot be understood or simulated without mesoscale atmospheric dynamics._x000B_
In this study, researchers performed a projection of the cold season regional climate change signals in the surface hydroclimate fields corresponding to the mid-twenty-first century in California. The projection used the dynamical downscaling method in which a global climate scenario generated by the National Center for Atmospheric Research Community Climate System Model-3 (CCSM-3) is downscaled using a regional climate model, the Weather Research and Forecast model. The global climate scenario is based on the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (SRES) A1B emission profile. The cold season covers the six-month period October through March, which includes fall (October�December) and winter (January�March). The regional climate change signals are calculated as the differences between the regional climate model climatology for two 20-year periods: the late twentieth century (1961�1980) and the mid-twenty-first century (2035�2054). The results show that the low-level temperature in California will increase by 1 degrees C to 2.5 degrees C (1.8 degrees F to 4.5 degrees F), with larger increases in high-elevation regions and in winter. Noticeable decreases in snowfall, snow-water equivalent, and surface albedo in high-elevation regions in the projected mid-twenty-first century climate suggest that the temperature increases in the high-elevation regions are partially amplified by local feedback through snow and surface albedo. Precipitation decreases over the entire cold season. The precipitation change signals show well-defined interseasonal variations; a pattern of positive (negative) signals in the northern (southern) California region during fall is reversed in winter. The seasonal variations in the precipitation change pattern are primarily associated with the climate change signals in rainfall. Snowfall decreases in the warmer climate, most noticeably in winter. The changes in seasonal precipitation result in the reduction in snowmelt, seasonal-mean snow-water equivalent, and runoff during the cold season, especially in high-elevation regions. The decrease in the high-elevation snowpack is of a special concern, as it is among the main sources of warm season water supply in California._x000B_
Assessing reservoir operations risk under climate change. Brekke, Levi D.; Maurer, Edwin P.; Anderson, Jamie D.; Dettinger, Michael D.; Townsley, Edwin S.; Harrison, Alan & Pruitt, Tom.
Water Resources Research:
http://dx.doi.org/10.1029/2008WR006941 DOI: 10.1029/2008WR006941
Risk-based planning offers a robust way to identify strategies that permit adaptive water resources management under climate change. This paper presents a flexible methodology for conducting climate change risk assessments involving reservoir operations. Decision makers can apply this methodology to their systems by selecting future periods and risk metrics relevant to their planning questions and by collectively evaluating system impacts relative to an ensemble of climate projection scenarios (weighted or not). This paper shows multiple applications of this methodology in a case study involving California's Central Valley Project and State Water Project systems. Multiple applications were conducted to show how choices made in conducting the risk assessment, choices known as analytical design decisions, can affect assessed risk. Specifically, risk was reanalyzed for every choice combination of two design decisions: (1) whether to assume climate change will influence flood-control constraints on water supply o rations (and how), and (2) whether to weight climate change scenarios (and how). Results show that assessed risk would motivate different planning pathways depending on decision-maker attitudes toward risk (e.g., risk neutral versus risk averse). Results also show that assessed risk at a given risk attitude is sensitive to the analytical design choices listed above, with the choice of whether to adjust flood-control rules under climate change having considerably more influence than the choice on whether to weight climate scenarios.
Research has suggested that carbon can be captured through changes in farming practices, thereby helping California reach its greenhouse gas emission reduction goals as put forward under the California Global Warming Solutions Act of 2006, Assembly Bill 32, (N��ez, Chapter 488, Statutes of 2006). This study assessed the potential and economic feasibility of soil carbon sequestration and reduction of trace gas emissions in California agricultural soils. To accomplish this, the researchers integrated databases that include geographic data on environmental factors and land use data with ecosystem simulation models and economic analyses. The resulting assessment tool analyzes land use and management impacts on carbon stocks and associated greenhouse gas fluxes between California agricultural soils and the atmosphere. The study found that adjusting farming practices could reduce greenhouse gas emissions by about 0.5 to 3 megagrams of carbon dioxide equivalent per hectare per year. The variation in this number is mainly on the type of farming practice used. This potential increased in the following order: low nitrogen fertilizer input, reduced tillage, manure application, and winter cover cropping. Even higher potentials could be reached when these single management options are combined. However, the uncertainty around the carbon reduction potentials of a single field remains large. More research is needed to reduce this uncertainty. _x000B__x000B_