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Mark A. Snyder and Lisa C. Sloan

Abstract

Regional climate models (RCMs) have improved our understanding of the effects of global climate change on specific regions. The need for realistic forcing has led to the use of fully coupled global climate models (GCMs) to produce boundary conditions for RCMs. The advantages of using fully coupled GCM output is that the global-scale interactions of all components of the climate system (ocean, sea ice, land surface, and atmosphere) are considered. This study uses an RCM, driven by a fully coupled GCM, to examine the climate of a region centered over California for the time periods 1980–99 and 2080–99. Statistically significant increases in mean monthly temperatures by up to 7°C are found for the entire state. Large changes in precipitation occur in northern California in February (increase of up to 4 mm day−1 or 30%) and March (decrease of up to 3 mm day−1 or 25%). However, in most months, precipitation changes between the cases were not statistically significant. Statistically significant decreases in snow accumulation of over 100 mm (50%) occur in some months. Temperature increases lead to decreases in snow accumulation that impact the hydrologic budget by shifting spring and summer runoff into the winter months, reinforcing results of other studies that used different models and driving conditions.

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Jason L. Bell, Lisa C. Sloan, and Mark A. Snyder

Abstract

In this study a regional climate model is employed to expand on modeling experiments of future climate change to address issues of 1) the timing and length of the growing season and 2) the frequency and intensity of extreme temperatures and precipitation. The study focuses on California as a climatically complex region that is vulnerable to changes in water supply and delivery. Statistically significant increases in daily minimum and maximum temperatures occur with a doubling of atmospheric carbon dioxide concentration. Increases in daily temperatures lead to increases in prolonged heat waves and length of the growing season. Changes in total and extreme precipitation vary depending upon geographic location.

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David W. Pierce, Daniel R. Cayan, Tapash Das, Edwin P. Maurer, Norman L. Miller, Yan Bao, M. Kanamitsu, Kei Yoshimura, Mark A. Snyder, Lisa C. Sloan, Guido Franco, and Mary Tyree

Abstract

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 (>60 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's 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 (>60 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.

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William J. Gutowski Jr., Raymond W. Arritt, Sho Kawazoe, David M. Flory, Eugene S. Takle, Sébastien Biner, Daniel Caya, Richard G. Jones, René Laprise, L. Ruby Leung, Linda O. Mearns, Wilfran Moufouma-Okia, Ana M. B. Nunes, Yun Qian, John O. Roads, Lisa C. Sloan, and Mark A. Snyder

Abstract

This paper analyzes the ability of the North American Regional Climate Change Assessment Program (NARCCAP) ensemble of regional climate models to simulate extreme monthly precipitation and its supporting circulation for regions of North America, comparing 18 years of simulations driven by the National Centers for Environmental Prediction (NCEP)–Department of Energy (DOE) reanalysis with observations. The analysis focuses on the wettest 10% of months during the cold half of the year (October–March), when it is assumed that resolved synoptic circulation governs precipitation. For a coastal California region where the precipitation is largely topographic, the models individually and collectively replicate well the monthly frequency of extremes, the amount of extreme precipitation, and the 500-hPa circulation anomaly associated with the extremes. The models also replicate very well the statistics of the interannual variability of occurrences of extremes. For an interior region containing the upper Mississippi River basin, where precipitation is more dependent on internally generated storms, the models agree with observations in both monthly frequency and magnitude, although not as closely as for coastal California. In addition, simulated circulation anomalies for extreme months are similar to those in observations. Each region has important seasonally varying precipitation processes that govern the occurrence of extremes in the observations, and the models appear to replicate well those variations.

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