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The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamflow changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; and 4) the methods used to statistically downscale GCM scenarios. In accounting for these differences, there is substantial evidence across studies that future Colorado River streamflow will be reduced under the current trajectories of anthropogenic greenhouse gas emissions because of a combination of strong temperature-induced runoff curtailment and reduced annual precipitation. Reconstructions of preinstrumental streamflows provide additional insights; the greatest risk to Colorado River streamflows is a multidecadal drought, like that observed in paleoreconstructions, exacerbated by a steady reduction in flows due to climate change. This could result in decades of sustained streamflows much lower than have been observed in the -100 years of instrumental record., The Colorado River is the primary water source for more than 30 million people in seven rapidly growing, mostly arid American states and Mexico. The Colorado River water supply system, [...]

Jerome Namias career at the Scripps Institution of Oceanography in La Jolla, CA, was characterized by his publication of 70 papers and 20 other articles. Considered as one of the world's leading meteorologists, Namias studied various concerns associated with short period climate variations and their predictability. He also conducted research on ocean influences and mechanisms affecting ocean temperature features in the eastern North Pacific.

Extreme daily precipitation contributes to flooding that can cause significant economic damages, and so is important to properly capture in gridded meteorological datasets. This work examines precipitation extremes, the mean precipitation on wet days, and fraction of wet days in two widely used gridded datasets over the conterminous United States. Compared to the underlying station observations, the gridded data show a 27% reduction in annual 1-day maximum precipitation, 25% increase in wet day fraction, 1.5–2.5 day increase in mean wet spell length, 30% low bias in 20-yr return values of daily precipitation, and 25% decrease in mean precipitation on wet days. It is shown these changes arise primarily from the time adjustment applied to put the precipitation gauge observations into a uniform time frame, with the gridding process playing a lesser role. A new daily precipitation dataset is developed that omits the time adjustment (as well as extending the gridded data by 7 years) and is shown to perform significantly better in reproducing extreme precipitation metrics. When the new dataset is used to force a land surface model, annually averaged 1-day maximum runoff increases 38% compared to the original data, annual mean runoff increases 17%, evapotranspiration drops 2.3%, and fewer wet days leads to a 3.3% increase in estimated solar insolation. These changes are large enough to affect portrayals of flood risk and water balance components important for ecological and climate change applications across the CONUS. [ABSTRACT FROM AUTHOR]

Fluctuations in spring climate in the western United States over the last 4-5 decades are described by examining changes in the blooming of plants and the timing of snowmelt-runoff pulses. The two measures of spring's onset that are employed are the timing of first bloom of lilac and honeysuckle bushes from a long-term cooperative phenological network, and the timing of the first major pulse of snowmelt recorded from high-elevation streams. Both measures contain year-to-year fluctuations, with typical year-to-year fluctuations at a given site of one to three weeks. These fluctuations are spatially coherent, forming regional patterns that cover most of the west. Fluctuations in lilac first bloom dates are highly correlated to those of honeysuckle, and both are significantly correlated with those of the spring snowmelt pulse. Each of these measures, then, probably respond to a common mechanism. Various analyses indicate that anomalous temperature exerts the greatest influence upon both interannual and secular changes in the onset of spring in these networks. Earlier spring onsets since the late 1970s are a remarkable feature of the records, and reflect the unusual spell of warmer-than-normal springs in western North America during this period. The warm episodes are clearly related to larger-scale atmospheric conditions across North America and the North Pacific, but whether this is predominantly an expression of natural variability or also a symptom of global warming is not certain.

Most of the great California–Nevada heat waves can be classified into primarily daytime or nighttime events depending on whether atmospheric conditions are dry or humid. A rash of nighttime-accentuated events in the last decade was punctuated by an unusually intense case in July 2006, which was the largest heat wave on record (1948–2006). Generally, there is a positive trend in heat wave activity over the entire region that is expressed most strongly and clearly in nighttime rather than daytime temperature extremes. This trend in nighttime heat wave activity has intensified markedly since the 1980s and especially since 2000. The two most recent nighttime heat waves were also strongly expressed in extreme daytime temperatures. Circulations associated with great regional heat waves advect hot air into the region. This air can be dry or moist, depending on whether a moisture source is available, causing heat waves to be expressed preferentially during day or night. A remote moisture source centered within a marine region west of Baja California has been increasing in prominence because of gradual sea surface warming and a related increase in atmospheric humidity. Adding to the very strong synoptic dynamics during the 2006 heat wave were a prolonged stream of moisture from this southwestern source and, despite the heightened humidity, an environment in which afternoon convection was suppressed, keeping cloudiness low and daytime temperatures high. The relative contributions of these factors and possible relations to global warming are discussed. [ABSTRACT FROM AUTHOR]

Short-term climate and weather systems can have a strong influence on mountain snowmelt, sometimes overwhelming the effects of elevation and aspect. Although most years exhibit a spring onset that starts first at lowest and moves to highest elevations, in spring 2002, flow in a variety of streams within the Tuolumne and Merced River basins of the southern Sierra Nevada all rose synchronously on 29 March. Flow in streams draining small high-altitude glacial subcatchments rose at the same time as that draining much larger basins gauged at lower altitudes, and streams from north- and south-facing cirques rose and fell together. Historical analysis demonstrates that 2002 was one among only 8 yr with such synchronous flow onsets during the past 87 yr, recognized by having simultaneous onsets of snowmelt at over 70% of snow pillow sites, having discharge in over 70% of monitored streams increase simultaneously, and having temperatures increase over 12°C within a 5-day period. Synchronous springs tend to begin with a low pressure trough over California during late winter, followed by the onset of a strong ridge and unusually warm temperatures. Synchronous springs are characterized by warmer than average winters and cooler than average March temperatures in California. In the most elevation-dependent, nonsynchronous years, periods of little or no storm activity, with warmer than average March temperatures, precede the onset of spring snowmelt, allowing elevation and aspect to influence snowmelt as spring arrives gradually. [ABSTRACT FROM AUTHOR]

Three long-range forecasting methods have been evaluated for prediction and downscaling of seasonal and intraseasonal precipitation statistics in California. Full-statistical, hybrid-dynamical-statistical and full-dynamical approaches have been used to forecast El Nino-Southern Oscillation (ENSO)-related total precipitation, daily precipitation frequency, and average intensity anomalies during the January-March season. For El Nino winters, the hybrid approach emerges as the best performer, while La Nina forecasting skill is poor. The full-statistical forecasting method features reasonable forecasting skill for both La Nina and El Nino winters. The performance of the full-dynamical approach could not be evaluated as rigorously as that of the other two forecasting schemes. Although the full-dynamical forecasting approach is expected to outperform simpler forecasting schemes in the long run, evidence is presented to conclude that, at present, the full-dynamical forecasting approach is the least viable of the three, at least in California. The authors suggest that operational forecasting of any intraseasonal temperature, precipitation, or streamflow statistic derivable from the available records is possible now for ENSO-extreme years. [ABSTRACT FROM AUTHOR]