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Higher global temperatures and increased levels of disturbance are contributing to greater tree mortality in many forest ecosystems. These same drivers can also limit forest regeneration, leading to vegetation type conversion. For the Sierra Nevada of California, little is known about how type conversion may affect streamflow, a critical source of water supply for urban, agriculture and environmental purposes. In this paper, we examined the effects of tree-to-shrub type conversion, in combination with climate change, on streamflow in two lower montane forest watersheds in the Sierra Nevada. A spatially distributed ecohydrologic model was used to simulate changes in streamflow, evaporation, and transpiration following type conversion, with an explicit focus on the role of vegetation size and aspect. Model results indicated that streamflow may show negligible change or small decreases following type conversion when the difference between tree and shrub leaf areas is small, partly due to the higher stomatal conductivity and the deep rooting depth of shrubs. In contrast, streamflow may increase when post-conversion shrubs have a small leaf area relative to trees. Model estimates also suggested that vegetation change could have a greater impact on streamflow magnitude than the direct hydrologic impacts of increased temperatures. Temperature increases, however, may have a greater impact on streamflow timing. Tree-to-shrub type conversion increased streamflow only marginally during dry years (annual precipitation < 800 mm), with most streamflow change observed during wetter years. These modeling results underscore the importance of accounting for changes in vegetation communities to accurately characterize future hydrologic regimes for the Sierra Nevada. [ABSTRACT FROM AUTHOR]

The Sierra Nevada and Southern Cascades—California's snowy mountains—are primary freshwater sources and natural reservoirs for the states of California and Nevada. These mountains receive precipitation overwhelmingly from wintertime storms including atmospheric rivers (ARs), much of it falling as snow at the higher elevations. Using a seven-decade record of daily observed temperature and precipitation as well as a snow reanalysis and downscaled climate projections, we documented historical and future changes in snow accumulation and snowlines. In four key subregions of California's snowy mountains, we quantified the progressing contribution of ARs and non-AR storms to the evolving and projected snow accumulation and snowlines (elevation of the snow-to-rain transition), exploring their climatology, variability and trends. Historically, snow makes up roughly a third of the precipitation affecting California's mountains. While ARs make up only a quarter of all precipitating days and, due to their relative warmth, produce snowlines higher than do other storms, they contribute over 40% of the total seasonal snow. Under projected unabated warming, snow accumulation would decline to less than half of historical by the late twenty-first century, with the greatest snow loss at mid elevations (from 1500 to 3300 m by the mountain sub-regions) during fall and spring. Central and Southern Sierra Nevada peaks above 3400 m might see occasionally extreme snow accumulations in January–February resulting entirely from wetter ARs. AR-related snowlines are projected to increase by more than 700 m, compared to about 500 m for other storms. We discuss likely impacts of the changing climate for water resources as well as for winter recreation. [ABSTRACT FROM AUTHOR]

This paper investigates the formation mechanisms for a local wind phenomenon known as Washoe Zephyr that occurs frequently in the lee of the Sierra Nevada. Unlike the typical thermally driven slope flows with upslope wind during daytime and downslope at night, the Washoe Zephyr winds blow down the lee slopes of the Sierra Nevada in the afternoon against the local pressure gradient. Long-term hourly surface wind data from several stations on the eastern slope of the Sierra Nevada and rawinsonde sounding data in the region are analyzed and numerical simulations are performed to test the suggested hypotheses on the formation mechanisms for this interesting phenomenon. The results from surface and upper-air climate data analyses and numerical modeling indicate that the Washoe Zephyr is primarily a result of a regional-scale pressure gradient that develops because of asymmetric heating of the atmosphere between the western side of the Sierra Nevada and the elevated, semiarid central Nevada and Great Basin on the eastern side of the Sierra Nevada. The frequent influence of the Pacific high on California in the summer season helps to enhance this pressure gradient and therefore strengthen the flow. Westerly synoptic-scale winds over the Sierra Nevada and the associated downward momentum transfer are not necessary for its development, but strong westerly winds aloft work in concert with the regional-scale pressure gradient to produce the strongest Washoe Zephyr events. [ABSTRACT FROM AUTHOR]

California’s winter storms produce intense rainfall capable of triggering shallow landslides, threatening lives and infrastructure. This study explores where hourly rainfall in the state meets or exceeds published values thought to trigger landslides after crossing a seasonal antecedent precipitation threshold. We answer the following questions: 1) Where in California are overthreshold events most common? 2) How are events distributed within the cool season (October–May) and interannually? 3) Are these events related to atmospheric rivers? To do this, we compile and quality control hourly precipitation data over a 22-yr period for 147 Remote Automated Weather Stations (RAWS). Stations in the Transverse and Coast Ranges and portions of the northwestern Sierra Nevada have the greatest number of rainfall events exceeding thresholds. Atmospheric rivers coincide with 60%–90% of these events. Overthreshold events tend to occur in the climatological wettest month of the year, and they commonly occur multiple times within a storm. These statewide maps depict where to expect intense rainfalls that have historically triggered shallow landslides. They predict that some areas of California are less susceptible to storm-driven landslides solely because high-intensity rainfall is unlikely. [ABSTRACT FROM AUTHOR]

Western US snowpack--snow that accumulates on the ground in the mountains--plays a critical role in regional hydroclimate and water supply, with 80% of snowmelt runoff being used for agriculture. While climate projections provide estimates of snowpack loss by the end of the century and weather forecasts provide predictions of weather conditions out to 2 weeks, less progress has been made for snow predictions at seasonal timescales (months to 2 years), crucial for regional agricultural decisions (e.g., plant choice and quantity). Seasonal predictions with climate models first took the form of El Niño predictions 3 decades ago, with hydroclimate predictions emerging more recently. While the field has been focused on single-season predictions (3 months or less), we are now poised to advance our predictions beyond this timeframe. Utilizing observations, climate indices, and a suite of global climate models, we demonstrate the feasibility of seasonal snowpack predictions and quantify the limits of predictive skill 8 months in advance. This physically based dynamic system outperforms observation-based statistical predictions made on July 1 for March snowpack everywhere except the southern Sierra Nevada, a region where prediction skill is nonexistent for every predictor presently tested. Additionally, in the absence of externally forced negative trends in snowpack, narrow maritime mountain ranges with high hydroclimate variability pose a challenge for seasonal prediction in our present system; natural snowpack variability may inherently be unpredictable at this timescale. This work highlights present prediction system successes and gives cause for optimism for developing seasonal predictions for societal needs. [ABSTRACT FROM AUTHOR]

While orographically driven snowfall is known to be important in mountainous regions, a complete understanding of orographic enhancement from the basin to the mountain range scale is often inhibited by limited distributed data and spatial and/or temporal resolutions. A novel, 90-m spatially distributed snow water equivalent (SWE) reanalysis was used to overcome these limitations. Leveraging this SWE information, the interannual variability of orographic gradients in cumulative snowfall (CS) was investigated over 14 windward (western) basins in the Sierra Nevada in California from water years 1985 to 2015. Previous studies have not provided a detailed multidecadal climatology of orographic CS gradients or compared wet-year and dry-year orographic CS patterns, distributions, and gradients across an entire mountain range. The magnitude of seasonal CS gradients range from over 15 cmSWEper 100-m elevation to under 1 cmper 100mwith a 31-yr average of 6.1 cm per 100m below ~2500m in the western basins. The 31-yr average CS gradients generally decrease in higher elevation zones across the western basins and become negative at the highest elevations. On average, integrated vapor transport and zonal winds at 700 hPa are larger during wet years, leading to higher orographically driven CS gradients across the Sierra Nevada than in dry years. Below ~2500 m, wet years yield greater enhancement (relative to dry years) by factors of approximately 2 and 3 in the northwestern and southwestern basins, respectively. Overall, the western Sierra Nevada experiences about twice as much orographic enhancement during wet years as in dry years below the elevation corresponding to the 31-yr average maximum CS. [ABSTRACT FROM AUTHOR]

A 5-yr climatology of westerly wind events in Owens Valley, California, is derived from data measured by a mesoscale network of 16 automatic weather stations. Thermally driven up- and down-valley flows are found to account for a large part of the diurnal wind variability in this approximately north-south-oriented deepU-shaped valley. High-wind speed events at the western side of the valley deviate from this basic pattern by showing a higher percentage of westerly winds. In general, strong westerly winds in Owens Valley tend to be more persistent and to display higher sustained speeds than strong winds from other quadrants. The highest frequency of strong winds at the valley floor is found in the afternoon hours from April to September, pointing to thermal forcing as a plausible controlling mechanism. However, the most intense westerly wind events (westerly windstorms) can happen at any time of the day throughout the year. The temperature and humidity variations caused by westerly windstorms depend on the properties of the approaching air masses. In some cases, the windstorms lead to overall warming and drying of the valley atmosphere, similar to foehn or chinook intrusions. The key dynamical driver of westerly windstorms in Owens Valley is conjectured to be the downward penetration of momentum associated with mountain waves produced by the Sierra Nevada ridgeline to the west of the valley. [ABSTRACT FROM AUTHOR]

California's Sierra Nevada is a high-elevation mountain range with significant seasonal snow cover. Under anthropogenic climate change, amplification of the warming is expected to occur at elevations near snow margins due to snow albedo feedback. However, climate change projections for the Sierra Nevada made by global climate models (GCMs) and statistical downscaling methods miss this key process. Dynamical downscaling simulates the additional warming due to snow albedo feedback. Ideally, dynamical downscaling would be applied to a large ensemble of 30 or more GCMs to project ensemble-mean outcomes and intermodel spread, but this is far too computationally expensive. To approximate the results that would occur if the entire GCM ensemble were dynamically downscaled, a hybrid dynamical-statistical downscaling approach is used. First, dynamical downscaling is used to reconstruct the historical climate of the 1981-2000 period and then to project the future climate of the 2081-2100 period based on climate changes from five GCMs. Next, a statistical model is built to emulate the dynamically downscaled warming and snow cover changes for any GCM. This statistical model is used to produce warming and snow cover loss projections for all available CMIP5 GCMs. These projections incorporate snow albedo feedback, so they capture the local warming enhancement (up to 3°C) from snow cover loss that other statistical methods miss. Capturing these details may be important for accurately projecting impacts on surface hydrology, water resources, and ecosystems. [ABSTRACT FROM AUTHOR]

This study presents the climatology of the vertical structure of water vapor flux above the Sierra Nevada during significant cool season (November-April) precipitation events. Atmospheric river (AR) and non-AR events are analyzed to better understand the effect of this structure on precipitation patterns. Daily measurements of cool season precipitation at seven weather stations around the Tahoe basin from 1974 to 2012 and NCEP/CPC gridded daily precipitation analysis along the Sierra crest for the period 1948-2012 are examined. NCEP-NCAR reanalysis and soundings from Oakland are used to look at upper atmospheric conditions, including the presence of vapor transport by low- and midlevel jets on storm days as well as upstream static stability in relation to significant precipitation events. Key findings are as follows: 1) ARs play a disproportionately large role in generating Tahoe basin precipitation during the cool season; 2) strong midlevel vapor transport needs to occur in tandem with low-level transport to achieve the most extreme 2-day precipitation in the Tahoe basin; 3) when low- to midlevel vapor transport is present on days with a defined AR, the local maximum in 2-day precipitation intensity decreases with distance from the Sierra crest, and on non-AR days, the relative increase in 2-day precipitation intensity due to low- and midlevel vapor transport does not vary based on distance from the Sierra crest; 4) AR and non-AR moisture fluxes are significantly modified by upstream static stability; and 5) understanding the impacts of ARs and their lower- and midlevel moisture flux structure are crucial components of the hydrometeorology in this region. [ABSTRACT FROM AUTHOR]

We present a unique water-balance approach for modeling snowpack under historic, current and future climates throughout the Sierra Nevada Ecoregion. Our methodology uses a finer scale (270 m) than previous regional studies and incorporates cold-air pooling, an atmospheric process that sustains cooler temperatures in topographic depressions thereby mitigating snowmelt. Our results are intended to support management and conservation of snow-dependent species, which requires characterization of suitable habitat under current and future climates. We use the wolverine (Gulo gulo) as an example species and investigate potential habitat based on the depth and extent of spring snowpack within four National Park units with proposed wolverine reintroduction programs. Our estimates of change in spring snowpack conditions under current and future climates are consistent with recent studies that generally predict declining snowpack. However, model development at a finer scale and incorporation of cold-air pooling increased the persistence of April 1st snowpack. More specifically, incorporation of cold-air pooling into future climate projections increased April 1st snowpack by 6.5% when spatially averaged over the study region and the trajectory of declining April 1st snowpack reverses at mid-elevations where snow pack losses are mitigated by topographic shading and cold-air pooling. Under future climates with sustained or increased precipitation, our results indicate a high likelihood for the persistence of late spring snowpack at elevations above approximately 2,800 m and identify potential climate refugia sites for snow-dependent species at mid-elevations, where significant topographic shading and cold-air pooling potential exist. [ABSTRACT FROM AUTHOR]

A study of the California Sierra Nevada snowpack has been conducted using snow station observations and reanalysis surface temperature data. Monthly snow water equivalent (SWE) measurements were combined from two datasets to provide sufficient data from 1930 to 2008. The monthly snapshots are used to calculate peak snow mass timing for each snow season. Since 1930, there has been an overall trend toward earlier snow mass peak timing by 0.6 days per decade. The trend toward earlier timing also occurs at nearly all individual stations. Even stations showing an increase in 1 April SWE exhibit the trend toward earlier timing, indicating that enhanced melting is occurring at nearly all stations. Analysis of individual years and stations reveals that warm daily maximum temperatures averaged over March and April are associated with earlier snow mass peak timing for all spatial and temporal scales included in the dataset. The influence is particularly pronounced for low accumulation years indicating the potential importance of albedo feedback for the melting of shallow snow. The robustness of the early spring temperature influence on peak timing suggests the trend toward earlier peak timing is attributable to the simultaneous warming trend (0.1°C decade−1 since 1930, with an acceleration in warming in later time periods). Given future scenarios of warming in California, one can expect acceleration in the trend toward earlier peak timing; this will reduce the warm season storage capacity of the California snowpack. [ABSTRACT FROM AUTHOR]

Biogeographical patterns within the California Floristic Province have been greatly affected by geological and climatic events. Here, we investigate the phylogeography of foxtail pine ( Pinus balfouriana) in an effort to date its range disjunction using molecular data and to further our understanding of phylogeographical patterns for plants within the California Floristic Province. The distribution of foxtail pine is characterized by a 500-km disjunction separating populations located in the Klamath Mountains from those in the southern Sierra Nevada. Previous authors suggested that this disjunction occurred approximately 4000–8000 years ago during the Holocene Xerotherm when western North America became warmer and drier. Those dates, however, are inconsistent with the morphological differences that separate regional populations into formally recognized subspecies. Using the coalescent-based isolation with migration model and DNA sequence data from the chloroplast, mitochondrial, and nuclear genomes, we evaluate several hypotheses addressing the timing of this range disjunction and its effects on subsequent patterns of gene flow. Results from all three genomes are largely consistent with Middle to Early Pleistocene divergence dates. Those dates correspond to the Sherwin glaciation, which was the largest Pleistocene glacial episode in the Sierra Nevada. Gene flow, moreover, was only documented using data from the chloroplast genome, suggesting that low levels of long-distance pollen dispersal ( Nem<0.5) have occurred since this divergence event. These results are extended to a discussion of the biogeographical development of subalpine forests in California. [ABSTRACT FROM AUTHOR]