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Abstract: Rainfall in southern California is highly variable, with some fluctuations explainable by climate patterns. Resulting runoff and heightened streamflow from rain events introduces freshwater plumes into the coastal ocean. Here we use a 105-year daily sea surface salinity record collected at Scripps Pier in La Jolla, California to show that El Niño Southern Oscillation and Pacific Decadal Oscillation both have signatures in coastal sea surface salinity. Averaging the freshest quantile of sea surface salinity over each year’s winter season provides a useful metric for connecting the coastal ocean to interannual winter rainfall variability, through the influence of freshwater plumes originating, at closest, 7.5 km north of Scripps Pier. This salinity metric has a clear relationship with dominant climate phases: negative Pacific Decadal Oscillation and La Niña conditions correspond consistently with lack of salinity anomaly/ dry winters. Fresh salinity anomalies (i.e., wet winters) occur during positive phase Pacific Decadal Oscillation and El Niño winters, although not consistently. This analysis emphasizes the strong influence that precipitation and consequent streamflow has on the coastal ocean, even in a region of overall low freshwater input, and provides an ocean-based metric for assessing decadal rainfall variability.

Atmospheric rivers (ARs) generate most of the economic losses associated with flooding in the western United States and are projected to increase in intensity with climate change. This is of concern as flood damages have been shown to increase exponentially with AR intensity. To assess how AR-related flood damages are likely to respond to climate change, we constructed county-level damage models for the western 11 conterminous states using 40 years of flood insurance data linked to characteristics of ARs at landfall. Damage functions were applied to 14 CMIP5 global climate models under the RCP4.5 "intermediate emissions" and RCP8.5 "high emissions" scenarios, under the assumption that spatial patterns of exposure, vulnerability, and flood protection remain constant at present day levels. The models predict that annual expected AR-related flood damages in the western United States could increase from $1 billion in the historical period to $2.3 billion in the 2090s under the RCP4.5 scenario or to $3.2 billion under the RCP8.5 scenario. County-level projections were developed to identify counties at greatest risk, allowing policymakers to target efforts to increase resilience to climate change.

In a single-site study (San Diego, CA, USA), we previously showed that Kawasaki Disease (KD) cases cluster temporally in bursts of approximately 7 days. These clusters occurred more often than would be expected at random even after accounting for long-term trends and seasonality. This finding raised the question of whether other locations around the world experience similar temporal clusters of KD that might offer clues to disease etiology. Here we combine data from San Diego and nine additional sites around the world with hospitals that care for large numbers of KD patients, as well as two multi-hospital catchment regions. We found that across these sites, KD cases clustered at short time scales and there were anomalously long quiet periods with no cases. Both of these phenomena occurred more often than would be expected given local trends and seasonality. Additionally, we found unusually frequent temporal overlaps of KD clusters and quiet periods between pairs of sites. These findings suggest that regional and planetary range environmental influences create periods of higher or lower exposure to KD triggers that may offer clues to the etiology of KD.

Abstract: Extreme daily precipitation contributes to flooding that can cause significant economic damages, and so is important to properly capture in gridded meteorological data sets. This work examines precipitation extremes, the mean precipitation on wet days, and fraction of wet days in two widely used gridded data sets over the conterminous U.S. (CONUS). 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 to 2.5 day increase in mean wet spell length, 30% low bias in 20-year 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 data set 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 data set 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.

ObjectiveTo test the hypothesis that cases of Kawasaki disease within a temporal cluster have a similar pattern of host response that is distinct from cases of Kawasaki disease in different observed clusters and randomly constructed clusters.Study designWe designed a case-control study to analyze 47 clusters derived from 1332 patients with Kawasaki disease over a 17-year period (2002-2019) from a single clinical site and compared the cluster characteristics with those of 2 control groups of synthetic Kawasaki disease clusters. We defined a "true" Kawasaki disease cluster as at least 5 patients within a 7-day moving window. The observed and synthetic Kawasaki disease clusters were compared with respect to demographic and clinical characteristics and median values for standard laboratory data using univariate analysis and a multivariate, rotated empirical orthogonal function analysis.ResultsIn a univariate analysis, the median values for age, coronary artery z-score, white blood cell count, erythrocyte sedimentation rate, C-reactive protein, and age-adjusted hemoglobin for several of the true Kawasaki disease clusters exceeded the 95th percentile for the 2 synthetic clusters. REOF analyses revealed distinct patterns of demographic and clinical measures within clusters.ConclusionsCases of Kawasaki disease within a cluster were more similar with respect to demographic and clinical features and levels of inflammation than would be expected by chance. These observations suggest that different triggers and/or different intensities of exposures result in clusters of cases of Kawasaki disease that share a similar response pattern. Analyzing cases within clusters or cases who share demographic and clinical features may lead to new insights into the etiology of Kawasaki disease.

Cold air pooling (CAP) occurs in low-lying areas where cold, dense air collects during nighttime hours, producing colder temperatures than surrounding higher elevations. Devils Postpile National Monument (DEPO) is confined by steep mountain ridges, which promote cold air drainage into lower-elevation meadows and river valleys. These low lying areas where CAP occurs could help facilitate a potential refugium from some of the greatest impacts of regional climate warming. A strong focus on CAP occurrence is part of a seven-step climate change refugia conservation cycle, outlined in Morelli et al. (2016), that DEPO has instituted, wherein resource management seeks to identify and focus on parts of the landscape that may be sheltered from the intensity and pace of rapid climate change. Locales that harbor persistent CAP may provide vulnerable species and ecosystems a sort of refuge, allowing more time to adapt to new conditions. Central to DEPO’s strategy is better monitoring and understanding of CAP occurrence. Based on observations from 10 years of temperature loggers in and around DEPO, CAP operates reliably throughout the year, and especially during summer. Importantly, CAP has occurred strongly during recent unusually warm years. These findings reinforce the value of monitoring and ongoing analysis as a way to guide conservation and adaptation using potential climate change refugia. As with this co-developed park–university investigation, other land managers could consider climate refugia-oriented management as a viable conservation and adaptation strategy.

California’s Central Valley (CV) is one of the most productive agricultural regions in the world, enabled by the conjunctive use of surface water and groundwater. We investigated variations in the CV’s managed surface water diversions relative to climate variability. Using a historical record (1979−2010) of diversions from 531 sites, we found diversions are largest in the wetter Sacramento basin to the north, but most variable in the drier Tulare basin to the south. A rotated empirical orthogonal function (REOF) analysis finds 72% of the variance of diversions is captured by the first three REOFs. The leading REOF (35% of variance) exhibited strong positive loadings in the Tulare basin, and the corresponding principal component time-series (RPC1) was strongly correlated (ρ > 0.9) with contemporaneous hydrologic variability. This pattern indicates larger than average diversions in the south, with neutral or slightly less than average diversions to the north during wet years, with the opposite true for dry years. The second and third REOFs (20% and 17% of variance, respectively), were strongest in the Sacramento basin and San Francisco Bay−Delta. RPC2 and RPC3 were associated with variations in agricultural- and municipal-bound diversions, respectively. RPC2 and RPC3 were also moderately correlated with 7-year cumulative precipitation based on lagged correlation analysis, indicating that diversions in the north and central portions of the CV respond to longer-term hydrologic variations. The results illustrate a dichotomy of regimes wherein diversions in the more arid Tulare are governed by year-to-year hydrologic variability, while those in wetter northern basins reflect land-use patterns and low-frequency hydrologic variations.

Daily precipitation in California has been projected to become less frequent even as precipitation extremes intensify, leading to uncertainty in the overall response to climate warming. Precipitation extremes are historically associated with Atmospheric Rivers (ARs). Sixteen global climate models are evaluated for realism in modeled historical AR behavior and contribution of the resulting daily precipitation to annual total precipitation over Western North America. The five most realistic models display consistent changes in future AR behavior, constraining the spread of the full ensemble. They, moreover, project increasing year-to-year variability of total annual precipitation, particularly over California, where change in total annual precipitation is not projected with confidence. Focusing on three representative river basins along the West Coast, we show that, while the decrease in precipitation frequency is mostly due to non-AR events, the increase in heavy and extreme precipitation is almost entirely due to ARs. This research demonstrates that examining meteorological causes of precipitation regime change can lead to better and more nuanced understanding of climate projections. It highlights the critical role of future changes in ARs to Western water resources, especially over California.

We present hourly climate data to force land surface process models and assessments over the Merced and Tuolumne watersheds in the Sierra Nevada, California, for the water year 2010-2014 period. Climate data (38 stations) include temperature and humidity (23), precipitation (13), solar radiation (8), and wind speed and direction (8), spanning an elevation range of 333 to 2987 m. Each data set contains raw data as obtained from the source (Level 0), data that are serially continuous with noise and nonphysical points removed (Level 1), and, where possible, data that are gap filled using linear interpolation or regression with a nearby station record (Level 2). All stations chosen for this data set were known or documented to be regularly maintained and components checked and calibrated during the period. Additional time-series data included are available snow water equivalent records from automated stations (8) and manual snow courses (22), as well as distributed snow depth and co-located soil moisture measurements (2-6) from four locations spanning the rain-snow transition zone in the center of the domain. Spatial data layers pertinent to snowpack modeling in this data set are basin polygons and 100 m resolution rasters of elevation, vegetation type, forest canopy cover, tree height, transmissivity, and extinction coefficient. All data are available from online data repositories (https://doi.org/10.6071/M3FH3D).

Abstract. We present hourly climate data to force land surface process models and assessments over the Merced and Tuolumne watersheds in the Sierra Nevada, California, for the water year 2010–2014 period. Climate data (38 stations) includes temperature and humidity (23), precipitation (13), solar radiation (8), and wind speed and direction (8) spanning an elevation range of 333 to 2987 m. Each data set contains raw data as obtained from the source (level 0), data that are serially continuous with noise and non-physical points removed (level 1), and, where possible, data that are gap-filled using linear interpolation or regression with a nearby station record (level 2). All stations chosen for this data set were known or documented to be regularly maintained and components checked and calibrated during the period. Additional time-series data included are available snow water equivalent records from automated stations (8) and manual snow courses (22), as well as distributed snow-depth and co-located soil-moisture measurements (2–6) from four locations spanning the rain-to-snow transition zone in the centre of the domain. Spatial data layers pertinent to snowpack modelling in this data set are basin polygons and 100-m resolution rasters of elevation, vegetation type, forest basal area, tree height, and forest canopy cover, transmissivity, and extinction coefficient. All data are available from online data repositories (https://doi.org/10.6071/M3FH3D).

In most Mediterranean climate (MedClim) regions around the world, global climate models (GCMs) consistently project drier futures. In California, however, projections of changes in annual precipitation are inconsistent. Analysis of daily precipitation in 30 GCMs reveals patterns in projected hydrometeorology over each of the five MedClm regions globally and helps disentangle their causes. MedClim regions, except California, are expected to dry via decreased frequency of winter precipitation. Frequencies of extreme precipitation, however, are projected to increase over the two MedClim regions of the Northern Hemisphere where projected warming is strongest. The increase in heavy and extreme precipitation is particularly robust over California, where it is only partially offset by projected decreases in low-medium intensity precipitation. Over the Mediterranean Basin, however, losses from decreasing frequency of low-medium-intensity precipitation are projected to dominate gains from intensifying projected extreme precipitation. MedClim regions are projected to become more sub-tropical, i.e. made dryer via pole-ward expanding subtropical subsidence. California's more nuanced hydrological future reflects a precarious balance between the expanding subtropical high from the south and the south-eastward extending Aleutian low from the north-west. These dynamical mechanisms and thermodynamic moistening of the warming atmosphere result in increased horizontal water vapor transport, bolstering extreme precipitation events.

We use three 150 year preindustrial simulations of the Community Earth System Model to quantify the impacts of El Niño-Southern Oscillation (ENSO) events on shortwave and longwave cloud radiative effects (CRESW and CRELW). Compared to recent observations from the Clouds and the Earth’s Radiant Energy System data set, the model simulation successfully reproduces larger variations of CRESW and CRELW over the tropics. The ENSO cycle is found to dominate interannual variations of cloud radiative effects. Simulated cooling (warming) effects from CRESW (CRELW) are strongest over the tropical western and central Pacific Ocean during warm ENSO events, with the largest difference between 20 and 60Wm-2, with weaker effects of 10-40Wm-2 over Indonesian regions and the subtropical Pacific Ocean. Sensitivity tests show that variations of cloud radiative effects are mainly driven by ENSO-related changes in cloud fraction. The variations in midlevel and high cloud fractions each account for approximately 20-50% of the interannual variations of CRESW over the tropics and almost all of the variations of CRELW between 60°S and 60°N. The variation of low cloud fraction contributes to most of the variations of CRESW over the midlatitude oceans. Variations in natural aerosol concentrations explained 10-30% of the variations of both CRESW and CRELW over the tropical Pacific, Indonesian regions, and the tropical Indian Ocean. Changes in natural aerosol emissions and concentrations enhance 3-5% and 1-3% of the variations of cloud radiative effects averaged over the tropics.

This study uses a century length preindustrial climate simulation by the Community Earth System Model (CESM 1.0) to explore statistical relationships between dust, clouds, and atmospheric circulation and to suggest a semidirect dynamical mechanism linking subtropical North Atlantic lower tropospheric cloud cover with North African dust transport. The length of the run allows us to account for interannual variability of North African dust emissions and transport in the model. CESM’s monthly climatology of both aerosol optical depth and surface dust concentration at Cape Verde and Barbados, respectively, agree well with available observations, as does the aerosol size distribution at Cape Verde. In addition, CESM shows strong seasonal cycles of dust burden and lower tropospheric cloud fraction, with maximum values occurring during boreal summer, when a strong correlation between these two variables exists over the subtropical North Atlantic. Calculations of Estimated Inversion Strength (EIS) and composites of EIS on high and low downstream North African dust months during boreal summer reveal that dust is likely increasing inversion strength over this region due to both solar absorption and reflection. We find no evidence for a microphysical link between dust and lower tropospheric clouds in this region. These results yield new insight over an extensive period of time into the complex relationship between North African dust and North Atlantic lower tropospheric clouds, which has previously been hindered by spatiotemporal constraints of observations. Our findings lay a framework for future analyses using different climate models and submonthly data over regions with different underlying dynamics.

Evidence indicates that the densely cultivated region of northeastern China acts as a source for the wind-borne agent of Kawasaki disease (KD). KD is an acute, coronary artery vasculitis of young children, and still a medical mystery after more than 40 y. We used residence times from simulations with the flexible particle dispersion model to pinpoint the source region for KD. Simulations were generated from locations spanning Japan from days with either high or low KD incidence. The postepidemic interval (1987-2010) and the extreme epidemics (1979, 1982, and 1986) pointed to the same source region. Results suggest a very short incubation period (

The change in flooding potential along the California coast over the twenty‐first century was estimated from both ocean wave and sea level rise projections produced from global climate model data. Changes in flooding potential were inferred from changes in wave runup (the vertical height reached by wave‐driven water levels), which depends on the instantaneous sea level (or still water level), beach slope, and wave height and wave period. The still water level is the superposition of regional (or relative) mean sea level, the tide, and non‐tide sea level fluctuations. Non‐tide sea level fluctuations include both the steric response associated with El Niño–related variability that can persist up to a year or more, and local storm–forced variability (storm surge). The potential for greatest coastal flooding occurs when extremes in waves and still water level occur nearly simultaneously. Wave activity provides the primary driving force for coastal flooding. Wave model significant wave height (Hs) and non‐tide sea level projections were generated for a seven global climate model simulations. Comparison of the Hs and non‐ tide projections with wave model hindcast Hs and observed non‐tide fluctuations suggest that the characteristics and incidence of extreme Hs and non‐tide fluctuations will not increase appreciably over the twenty‐first century. Thus, because astronomical tide‐forcing will not increase, increases in relative mean sea level will largely determine the potential for increased ocean‐driven flooding along the California coast. If relative mean sea level along the California coast reaches global mean sea level rise projections associated with climate change, extreme flooding events expected to occur once in about 100 years under stationary relative mean sea levels will occur annually.

Blue oak tree-ring chronologies correlate highly with winter–spring precipitation totals over California, with Sacramento and San Joaquin river stream flow, and with seasonal variations in the salinity gradient in San Francisco Bay. The convergence of fresh and saline currents can influence turbidity, sediment accumulation, and biological productivity in the estuary. Three selected blue oak chronologies were used to develop a 625-year-long reconstruction of the seasonal salinity gradient, or low salinity zone (LSZ), which provides a unique perspective on the interannual-to-decadal variability of this important estuarine habitat indicator. The reconstruction was calibrated with instrumental LSZ data for the winter–spring season, and explains 73% of the variance in the February–June position of the LSZ from 1956 to 2003. Because this calibration period post-dates the sweeping changes that have occurred to land cover, channel morphology, and natural streamflow regimes in California, the reconstruction provides an idealized estimate for how the LSZ might have fluctuated under the seasonal precipitation variations of the past 625 years, given the modern geometry and bathymetry of the estuary and land cover across the drainage basin. The February–June season integrates precipitation and runoff variability during the cool season, and does not extend into the late-summer dry season when LSZ extremes can negatively affect Sacramento–San Joaquin Delta (Delta) agriculture and some aquatic organisms. However, there is such strong inter-seasonal persistence in the instrumental LSZ data that precipitation totals during the cool season can strongly pre-condition LSZ position in late summer. The 625-year-long reconstruction indicates strong interannual and decadal variability, the frequent recurrence of consecutive 2-year LSZ maxima and minima, large-scale ocean atmospheric forcing, and an interesting asymmetrical influence of warm El Niño–Southern Oscillation (ENSO) events.

Persistent drought presents one of the greatest risks of climate change faced by the western United States. Highlighting this risk is from paleo hydrological evidence that during the medieval period (~900-1400 AD) this region experienced two extensive droughts of greater duration than any experienced in recorded history. However, much remains to be learned about these “mega droughts,” including the severity of deficit in precipitation and snowpack in California’s Sierra Nevada Mountain range, which currently serve as a crucial source of fresh water to California agriculture, industry and domestic users. To possibly extract a record of the hydrological conditions in the Sierra Nevada during this era, cores of annually laminated sediment from Swamp Lake, in the northwest portion of Yosemite Park were collected. Stable hydrogen isotope (δD) ratios of plant leaf-wax lipid compounds preserved in the lake sediments and the thickness of the annual sedimentary laminations (varves) show promise as potential proxies for recording past hydroclimate variability in the Sierra Nevada Mountains. δD measurements at annual to interannual resolution were made for two time periods: the 20th century and the 13th-15th centuries while varve thickness was measured over the entire period 1150-2006 AD. We find significant negative correlations between 20th century δD fluctuations and instrumentally recorded variability in total precipitation, snow water equivalence (SWE) and Palmer Drought Severity Index (PDSI). Medieval δD values correspond to independent regional hydrologic reconstructions at the decadal to multi-decadal scale, which appear to delineate relatively dry medieval episodes. An issue that is still unclear is that the mean δD during this period is little different from that during the relatively moist contemporaneous period. This finding is at odds with evidence from submerged tree stumps for two prolonged droughts separated by about 200 years. Varve thickness measurements are on going, but results thus far reveal difficulties in using this proxy for reconstructing past Sierra Nevada hydroclimate variability, the most significant being the complexity of the seasonal deposition cycle and sub-millimeter thicknesses. Overall, geochemical and geomorphological information gleaned from Swamp Lake sediment cores provide an independent means of reconstructing hydroclimate in the Sierra Nevada and provide a unique perspective on the mega-drought intervals in the Sierra Nevada Mountains.

During the past year, an investigation has been initiated regarding how future climate changes may impact the hydrology of the Tijuana River Watershed – a binational watershed. The study has used gridded observed daily precipitation and temperatures and downscaled daily precipitation and temperature projections from three global climate models (GCM) to drive the VIC macroscale hydrologic model. Sensitivity analysis using VIC suggests about 2% reduction of runoff for each 1% reduction in precipitation. A 1oC increase in average temperature produces about 3% reduction of runoff. All three GCM simulations yield annual warming, with end-of-century temperature increases from approximately +1oC under a lower emission scenario in the less responsive PCM1 to +3oC in a higher emission scenario with the more responsive GFDL model. Climate projections suggest greater warming in the spring and summer months ranging between 2oC to 3oC under the higher emission scenario. Two of the three GCM simulations yield more frequent summer drying as gauged by VIC simulated soil moisture in the twenty-first century under the higher emission scenario. Summer soil moisture declines most, and most rapidly, in the later part of the twenty-first century. This initial evaluation provides perhaps the first direct estimates of the climate change impacts on the Tijuana River Watershed. However, transforming these results into a more useable projections and impacts will be a task for the future and will require collaboration and interaction between local stakeholders and the researchers.

Visibility in coastal regions has a significant impact on government, commercial, and private sector activities. The primary phenomenon significantly affecting visibility along the western United States coastal regions is fog. Fog is a natural hazard to boating, commercial shipping, and other waterway activities.The West Coast of the United States has been identified as one of the major fog producing regions of the world. Present accuracy in predicting marine coastal fog and low stratus clouds is limited. Although most weather forecasting has improved with recent advances in atmospheric circulation models and satellite observations, there is relatively little operational guidance for the prediction of marine and coastal fog.Currently the forecasting of visibility relies mainly on the availability of local observations and experience with local weather tendencies. National Weather Service and other forecasters typically focus on selected local conditions which usually presage fog formation and if a sufficient number are present, they will forecast possible fog for the region. However, this level of information and experience is not available in all coastal areas. Results in this study suggest that attention to the large-scale circulation in addition to local conditions may lead to increased skill and accuracy in extended range forecasts.The large-scale structure and interannual variability of fog have not been well described because data has been unavailable and a large volume of data is required. In the present analysis, several years of observations from a set of coastal weather stations and a set of comprehensive marine weather reports (primarily ships) is used to examine large-scale processes and local conditions which affect fog formation. A discussion of fog observation criteria is given. In addition, evidence is provided by a collection of observations of hours of fog-horn operations at several coastal sites over 15 years, starting in 1950.The relationship between local and large-scale conditions, and fog and stratus formation may yield improved predictability of fog. This study indicates that large-scale conditions, especially regional-hemispheric circulation, are a vital component of both high and low fog occurrences; moreover, atmospheric circulation in the Eastern North Pacific Ocean and on the West Coast may contribute to improved forecasts for the development and persistence of fog.

An important part of the water supply in California and the western United States is derived from runoff fed by mountain snow melt. Snow accumulation responds to both precipitation and temperature variations, and forms an interesting climatic index, since it integrates these influences over the entire late fall-spring period. The study area includes the Sierra Nevada, which accumulates most of the snow pack and comprises a major portion of the water-bearing region of California. The purpose of this study is to shed light upon the link between climate and year-to-year variability in the snow pack. Specifically, we wanted to determine (a) the dependence of snow pack and streamflow upon natural climate variability, and (b) if the relationships linking snow and streamflow to climate variations are stable over the history of instrumental records by using pre-1948 historical records to test the results from 1948-present. The basis of the study will be several long series of historical observations containing observed variability over daily-toseasonal time scales. Our focus is on measurements on/around April 1, when snow accumulation is typically greatest. The primary data is from a network of mountainous snow courses; many have records of six decades or more. For any given year, the spring snow water equivalent (SWE) anomaly at a particular snow course is likely to be 25-60% of its long-term average. Although effects vary with region and with elevation, in general, the anomalous winter precipitation has the strongest influence on spring SWE fluctuations. Anomalous temperature has a weaker effect overall, but it has great influence in lower elevations such as in the coastal Northwest, and during spring in higher elevations. Patterns of the precipitation, temperature, and snow anomalies extend over broad regional areas, much larger than individual watersheds. These surface anomalies are organized by the atmospheric circulation, with primary anomaly centers over the North Pacific Ocean as well as over western North America. For most of the regions, anomalously low SWE is associated with a winter circulation resembling the PNA pattern. With a strong low in the central North Pacific and high pressure over the Pacific Northwest, this pattern diverts North Pacific storms northward, away from the region. Both warm and cool phases of ENSO tend to produce regional patterns with out-of-phase SWE anomalies in the Northwest and the Southwest.

There is considerable seasonal-to-interannual variability in the flow of major watersheds in the Sierra Nevadas. This study examines that variability in terms of seasonal average surface weather variables, including atmospheric circulation, temperature, precipitation, and snow.Of particular importance is an apparent decline in spring-early summer runoff from the Sierra Nevadas first pointed out by M. Roos of the California Department of Water Resources. While measured October-September (water year) and April-July (AMJJ) runoff have increased, the AMJ J / annual fractional runoff has decreased by approximately 10% over the 80+ years of record.Further inspection shows that many streams in the West have a significant decline in spring-early summer fractional runoff as seen from a network of river gauging stations from Alaska south to Arizona and from California east to the Rockies. The cause of the trends at these stations is complex, involving both precipitation and temperature. For many basins the fractional spring-early summer runoff is affected by climatic behavior across all the seasons. In the Sierra, the decreased AMJJ fraction appears to have been produced by increased precipitation in the late summer, fall, and winter with decreased precipitation in spring. In addition, temperature along the West Coast has increased during the non-summer seasons, enhancing earlier runoff, and possibly evapotranspiration in spring.Other combinations of temperature and precipitation were involved in fractional runoff trends in other regions. Reversals in temperature and precipitation trends in remote regions over the eastern part of North America suggest that much of these changes were produced by shifts in the long wave patterns of atmospheric circulation, perhaps discounting a greenhouse effect scenario.Additional studies partially funded by this grant involve the influence of large scale atmospheric features usually emanating from the North Pacific Ocean during winter. These winter atmospheric patterns have strong connections to fluctuations in streamflow in watersheds in California and elsewhere in western North America.