Climate change scenarios for the California region

To investigate possible future climate changes in California, a set of climate change model simulations was selected and evaluated. From the IPCC Fourth Assessment, simulations of twenty-first century climates under a B1 (low emissions) and an A2 (a medium-high emissions) emissions scenarios were evaluated, along with occasional comparisons to the A1fi (high emissions) scenario. The climate models whose simulations were the focus of the present study were from the Parallel Climate Model (PCM1) from NCAR and DOE, and the NOAA Geophysical Fluid Dynamics Laboratory CM2.1 model (GFDL). These emission scenarios and attendant climate simulations are not “predictions,” but rather are a purposely diverse set of examples from among the many plausible climate sequences that might affect California in the next century. Temperatures over California warm significantly during the twenty-first century in each simulation, with end-of-century temperature increases from approximately +1.5°C under the lower emissions B1 scenario in the less responsive PCM1 to +4.5°C in the higher emissions A2 scenario within the more responsive GFDL model. Three of the simulations (all except the B1 scenario in PCM1) exhibit more warming in summer than in winter. In all of the simulations, most precipitation continues to occur in winter. Relatively small (less than ~10%) changes in overall precipitation are projected. The California landscape is complex and requires that model information be parsed out onto finer scales than GCMs presently offer. When downscaled to its mountainous terrain, warming has a profound influence on California snow accumulations, with snow losses that increase with warming. Consequently, snow losses are most severe in projections by the more responsive model in response to the highest emissions

The Key Role of Heavy Precipitation Events in Climate Model Disagreements of Future Annual Precipitation Changes in California

Climate model simulations disagree on whether future precipitation will increase or decrease over California, which has impeded efforts to anticipate and adapt to human-induced climate change. This disagreement is explored in terms of daily precipitation frequency and intensity. It is found that divergent model projections of changes in the incidence of rare heavy (\u3e60 mm day−1) daily precipitation events explain much of the model disagreement on annual time scales, yet represent only 0.3% of precipitating days and 9% of annual precipitation volume. Of the 25 downscaled model projections examined here, 21 agree that precipitation frequency will decrease by the 2060s, with a mean reduction of 6–14 days yr−1. This reduces California\u27s mean annual precipitation by about 5.7%. Partly offsetting this, 16 of the 25 projections agree that daily precipitation intensity will increase, which accounts for a model average 5.3% increase in annual precipitation. Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from 16 global general circulation models downscaled with different combinations of dynamical methods [Weather Research and Forecasting (WRF), Regional Spectral Model (RSM), and version 3 of the Regional Climate Model (RegCM3)] and statistical methods [bias correction with spatial disaggregation (BCSD) and bias correction with constructed analogs (BCCA)], although not all downscaling methods were applied to each global model. Model disagreements in the projected change in occurrence of the heaviest precipitation days (\u3e60 mm day−1) account for the majority of disagreement in the projected change in annual precipitation, and occur preferentially over the Sierra Nevada and Northern California. When such events are excluded, nearly twice as many projections show drier future conditions

Probabilistic estimates of future changes in California temperature and precipitation usingstatistical and dynamical downscaling

Sixteen global general circulation models were used to develop probabilistic projections of temperature (T) and precipitation (P) changes over California by the 2060s. The global models were downscaled with two statistical techniques and three nested dynamical regional climate models, although not all global models were downscaled with all techniques. Both monthly and daily timescale changes in T and P are addressed, the latter being important for a range of applications in energy use, water management, and agriculture. The T changes tend to agree more across downscaling techniques than the P changes. Year-to-year natural internal climate variability is roughly of similar magnitude to the projected T changes. In the monthly average, July temperatures shift enough that that the hottest July found in any simulation over the historical period becomes a modestly cool July in the future period. Januarys as cold as any found in the historical period are still found in the 2060s, but the median and maximum monthly average temperatures increase notably. Annual and seasonal P changes are small compared to interannual or intermodel variability. However, the annual change is composed of seasonally varying changes that are themselves much larger, but tend to cancel in the annual mean. Winters show modestly wetter conditions in the North of the state, while spring and autumn show less precipitation. The dynamical downscaling techniques project increasing precipitation in the Southeastern part of the state, which is influenced by the North American monsoon, a feature that is not captured by the statistical downscaling

Climate scenarios for California

Possible future climate changes in California are investigated from a varied set of climate change model simulations. These simulations, conducted by three state-of-the-art global climate models, provide trajectories from three greenhouse gas (GHG) emission scenarios. These scenarios and the resulting climate simulations are not “predictions,” but rather are a limited sample from among the many plausible pathways that may affect California’s climate. Future GHG concentrations are uncertain because they depend on future social, political, and technological pathways, and thus the IPCC has produced four “families” of emission scenarios. To explore some of these uncertainties, emissions scenarios A2 (a medium-high emissions) and B1 (low emissions) were selected from the current IPCC Fourth climate assessment, which provides several recent model simulations driven by A2 and B1 emissions. The global climate model simulations addressed here were from PCM1, the Parallel Climate Model from the National Center for Atmospheric Research (NCAR) and U.S. Department of Energy (DOE) group, and CM2.1 from the National Oceanic and Atmospheric Administration (NOAA) Geophysical Fluids Dynamics Laboratory (GFDL). As part of the scenarios assessment, a statistical technique using properties of historical weather data was employed to correct model biases and “downscale” the global-model simulation of future climates to a finer level of detail, onto a grid of approximately 7 miles (12 kilometers), which is more suitable for impact studies at the scales needed by California decision makers. In current climate-change simulations, temperatures over California warm significantly during the twenty-first century, with temperature increases from approximately +3ºF (1.5ºC) in the lower emissions scenario (B1) within the less responsive model (PCM1) to +8ºF (4.5ºC) in the higher emissions scenario (A2) within the more responsive model (CM2.1). Three of the simulations (all except the low-emission scenario run of the low-response model) exhibit more warming in summer than in winter. In all of the simulations, most precipitation continues to occur in winter, with virtually all derived from North Pacific winter storms. Relatively little change in overall precipitation is projected. Climate warming has a profound influence in diminishing snow accumulations, because there is more rain and less snow, and earlier snowmelt. These snow losses increase as the warming increases, so that they are most severe under climate changes projected by the more sensitive model with the higher GHG emissions

Climate change scenarios for the California region.

Abstract To investigate possible future climate changes in California, a set of climate change scenario in PCM1) exhibit more warming in summer than in winter. In all of the simulations, most precipitation continues to occur in winter, and relatively small (less than ~10%) change in overall precipitation is projected. The California landscape is complex and requires that model information be parsed out onto finer scales than GCMs presently offer. When downscaled to its mountainous terrain, warming has a profound influence on California snow accumulations, with snow losses that increase with warming. Consequently, snow losses are most severe in projections by the more responsive model in response to the highest emissions. i

Seasonality of Kawasaki disease: a global perspective

Background: Understanding global seasonal patterns of Kawasaki disease (KD) may provide insight into the etiology of this vasculitis that is now the most common cause of acquired heart disease in children in developed countries worldwide. Methods: Data from 1970-2012 from 25 countries distributed over the globe were analyzed for seasonality. The number of KD cases from each location was normalized to minimize the influence of greater numbers from certain locations. The presence of seasonal variation of KD at the individual locations was evaluated using three different tests: time series modeling, spectral analysis, and a Monte Carlo technique. Results: A defined seasonal structure emerged demonstrating broad coherence in fluctuations in KD cases across the Northern Hemisphere extra-tropical latitudes. In the extra-tropical latitudes of the Northern Hemisphere, KD case numbers were highest in January through March and approximately 40% higher than in the months of lowest case numbers from August through October. Datasets were much sparser in the tropics and the Southern Hemisphere extra-tropics and statistical significance of the seasonality tests was weak, but suggested a maximum in May through June, with approximately 30% higher number of cases than in the least active months of February, March and October. The seasonal pattern in the Northern Hemisphere extra-tropics was consistent across the first and second halves of the sample period. Conclusion: Using the first global KD time series, analysis of sites located in the Northern Hemisphere extra-tropics revealed statistically significant and consistent seasonal fluctuations in KD case numbers with high numbers in winter and low numbers in late summer and fall. Neither the tropics nor the Southern Hemisphere extra-tropics registered a statistically significant aggregate seasonal cycle. These data suggest a seasonal exposure to a KD agent that operates over large geographic regions and is concentrated during winter months in the Northern Hemisphere extra-tropics

Patterns of care in older patients with squamous cell carcinoma of the head and neck: A Surveillance, Epidemiology, and End Results-Medicare analysis

There is growing evidence in the literature that older patients may not benefit from more intensive therapy for Head and Neck Squamous Cell Carcinoma (HNSCC). A growing number of patients with Head and Neck Squamous Cell Carcinoma (HNSCC) are age 65 and older; however, much of the evidence base informing treatment decisions is based on substantially younger and healthier clinical trial populations. The purpose of this study was to assess the patterns of care of older HNSCC patients to better understand how age is associated with treatment decision

Climate Change Scenarios for the San Francisco Region

Climate model simulations were used to investigate possible changes in regional climate over California. To accomplish this, the model simulations were downscaled from the coarse global climate model resolution (usually 150 kilometers [km] or greater horizontal grid spacing) to about 12 km horizontal grid spacing over the California region, using statistical techniques. The global model output was used in a statistical modeling scheme to produce sea-level projections for selected California coastal sites. Six global climate models and two greenhouse emissions scenarios, the medium-high emissions Special Report on Emissions Scenarios (SRES) A2 and the lower emissions SRES B1 were considered. By the end of the twenty-first century, the envelope of warming in the models projections, as an annual average, ranges from about 2°C to 6°C (about 3.5 °F to 11°F). On average, mean annual temperature of the A2 scenarios is about 1.5°C (about 3°F) greater than that of the B1 scenario. There is greater warming in summer than in winter. All simulations indicate that hot daytime and nighttime temperatures (heat waves) increase in frequency, magnitude, and duration from the historical period and during the projected period through the first half of the twenty-first century. Projected precipitation is marked by considerable variability between years and decades. In the southern half of California, the models show a decline in annual precipitation. Sea level, at hourly intervals for the historical through the projected twenty-first century, is estimated for selected tide gage sites along the California coast, with rises in the sample of simulations considered here ranging from 27 to 48 centimeters (cm) (11 to 19 in) over historical levels by 2050, and ranging from 77 cm to 140 cm (30 to 55 in) over historical levels by 2100. The rise of mean sea level would provoke an increase in extreme events, as gaged by exceedances above a relatively high or rare historical threshold. Such events become much more frequent and have longer durations than has been seen historically

Climate Change Scenarios for the San Francisco Region

Climate model simulations were used to investigate possible changes in regional climate over California. To accomplish this, the model simulations were downscaled from the coarse global climate model resolution (usually 150 kilometers [km] or greater horizontal grid spacing) to about 12 km horizontal grid spacing over the California region, using statistical techniques. The global model output was used in a statistical modeling scheme to produce sea-level projections for selected California coastal sites. Six global climate models and two greenhouse emissions scenarios, the medium-high emissions Special Report on Emissions Scenarios (SRES) A2 and the lower emissions SRES B1 were considered. By the end of the twenty-first century, the envelope of warming in the models projections, as an annual average, ranges from about 2°C to 6°C (about 3.5 °F to 11°F). On average, mean annual temperature of the A2 scenarios is about 1.5°C (about 3°F) greater than that of the B1 scenario. There is greater warming in summer than in winter. All simulations indicate that hot daytime and nighttime temperatures (heat waves) increase in frequency, magnitude, and duration from the historical period and during the projected period through the first half of the twenty-first century. Projected precipitation is marked by considerable variability between years and decades. In the southern half of California, the models show a decline in annual precipitation. Sea level, at hourly intervals for the historical through the projected twenty-first century, is estimated for selected tide gage sites along the California coast, with rises in the sample of simulations considered here ranging from 27 to 48 centimeters (cm) (11 to 19 in) over historical levels by 2050, and ranging from 77 cm to 140 cm (30 to 55 in) over historical levels by 2100. The rise of mean sea level would provoke an increase in extreme events, as gaged by exceedances above a relatively high or rare historical threshold. Such events become much more frequent and have longer durations than has been seen historically

Climate Change and Sea Level Rise Scenarios for California Vulnerability and Adaptation Assessment

This white paper provides an evaluation of physical elements of climate change and sea level rise that are contained in the California Climate Change Vulnerability and Adaptation Assessment. The analyses use six global climate models, each run under the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios B1 and A2 scenarios. From the global climate models and associated downscaled output, these scenarios contain a range of warming, continued interannual and decadal variation of precipitation with incremental changes by the middle and end of twenty‐first century, substantial loss of mountain snow pack, and a range of sea level rise along the California coast