Publications

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2018
Sumargo, E, Cayan DR.  2018.  The influence of cloudiness on hydrologic fluctuations in the mountains of the western United States. Water Resources Research. 54:8478-8499.   10.1029/2018wr022687   AbstractWebsite

This study investigates snowmelt and streamflow responses to cloudiness variability across the mountainous parts of the western United States. Twenty years (1996-2015) of Geostationary Operational Environmental Satellite-derived cloud cover indices (CC) with 4-km spatial and daily temporal resolutions are used as a proxy for cloudiness. The primary driver of nonseasonal fluctuations in daily mean solar insolation is the fluctuating cloudiness. We find that CC fluctuations are related to snowmelt and snow-fed streamflow fluctuations, to some extent (correlations of <0.5). Multivariate linear regression models of daily snowmelt (MELT) and streamflow (AQ) variations are constructed for each month from February to July, when snowmelt is most active. Predictors include CC from five antecedent days up to the current day. The CC-MELT and CC-AQ associations vary with time and location. The results show the dominance of negative correlations between CC and MELT, exemplifying the cloud-shading (or clear-sky) effect on snowmelt. The magnitude of the CC-MELT association (R-2) amounts to 5-61%, typically peaking in May. These associations fade earlier in summer during dry years than wet years, indicating the differing responses of thicker versus thinner snowpack. The CC-AQ association displays a less consistent pattern, with R-2 amounting to 2-47%. Nevertheless, MELT and AQ fluctuations exhibit spatially extensive patterns of correlations with daily cloudiness anomalies, indicating that the effects of cloudiness often operate over regional spatial scales. Plain Language Summary Much of the water supply in the western United States originates as mountain streams, which derive much of their water from snowmelt. The primary driver of mountain snowmelt is solar energy, and cloud cover regulates how much solar energy can reach the snow surface. Despite this fact, how snowmelt and streamflow respond to cloud cover (or its absence) has not been thoroughly studied. In our study, we describe snowmelt and streamflow responses to cloud cover using satellite images of cloud cover and surface records of snowmelt and streamflow. We find significant snowmelt and daily streamflow rate responses to cloud cover. Importantly, during the peak snowmelt season, snowmelt and streamflow decrease when cloud cover increases, and vice versa, confirming the cloud-shading effect on the snow surface. However, this cause-and-effect process is not so simple. We also find that cloud cover (or its absence) in the previous few days can affect how much snow melts and the streamflow rate is in a day. Snowmelt and streamflow responses to cloud cover are stronger, albeit shorter-lived, in dry years than in wet years, highlighting the relative importance of cloud cover in drier years.

2016
Ralph, FM, Prather KA, Cayan D, Spackman JR, DeMott P, Dettinger M, Fairall C, Leung R, Rosenfeld D, Rutledge S, Waliser D, White AB, Cordeira J, Martin A, Helly J, Intrieri J.  2016.  CalWater field studies designed to quantify the roles of atmospheric rivers and aerosols in modulating US West Coast precipitation in a changing climate. Bulletin of the American Meteorological Society. 97:1209-1228.   10.1175/bams-d-14-00043.1   AbstractWebsite

The variability of precipitation and water supply along the U.S. West Coast creates major challenges to the region’s economy and environment, as evidenced by the recent California drought. This variability is strongly influenced by atmospheric rivers (ARs), which deliver much of the precipitation along the U.S. West Coast and can cause flooding, and by aerosols (from local sources and transported from remote continents and oceans) that modulate clouds and precipitation. A better understanding of these processes is needed to reduce uncertainties in weather predictions and climate projections of droughts and floods, both now and under changing climate conditions.To address these gaps, a group of meteorologists, hydrologists, climate scientists, atmospheric chemists, and oceanographers have created an interdisciplinary research effort, with support from multiple agencies. From 2009 to 2011 a series of field campaigns [California Water Service (CalWater) 1] collected atmospheric chemistry, cloud microphysics, and meteorological measurements in California and associated modeling and diagnostic studies were carried out. Based on the remaining gaps, a vision was developed to extend these studies offshore over the eastern North Pacific and to enhance land-based measurements from 2014 to 2018 (CalWater-2). The dataset and selected results from CalWater-1 are summarized here. The goals of CalWater-2, and measurements to date, are then described.CalWater is producing new findings and exploring new technologies to evaluate and improve global climate models and their regional performance and to develop tools supporting water and hydropower management. These advances also have potential to enhance hazard mitigation by improving near-term weather prediction and subseasonal and seasonal outlooks.

2015
Shukla, S, Steinemann A, Iacobellis SF, Cayan DR.  2015.  Annual drought in California: Association with monthly precipitation and climate phases. Journal of Applied Meteorology and Climatology. 54:2273-2281.   10.1175/jamc-d-15-0167.1   AbstractWebsite

Annual precipitation in California is more variable than in any other state and is highly influenced by precipitation in winter months. A primary question among stakeholders is whether low precipitation in certain months is a harbinger of annual drought in California. Historical precipitation data from 1895 to 2013 are investigated to identify leading monthly indicators of annual drought in each of the seven climate divisions (CDs) as well as statewide. For this study, drought conditions are defined as monthly/annual (October-September) precipitation below the 20th/30th percentile, and a leading indicator is defined as a monthly drought preceding or during an annual drought that has the strongest association (i.e., joint probability of occurrence) with a statewide annual drought. Monthly precipitation variability and contributions to annual precipitation, along with joint probabilities of drought among the winter months, are first analyzed. Then the probabilities of annual drought and the variability in leading indicators are analyzed according to different climate phases and CDs. This study identified December within a water year as being the leading indicator that is most frequently associated with annual drought statewide (56%) and in most of the CDs (the highest was CD2 at 65%). Associated with its leading-indicator status, December drought was most frequently associated with drought in other winter months (joint probability > 30%). Results from this study can help stakeholders to understand and assess the likelihood of annual drought events given monthly precipitation preceding or early in the water year.

2014
Pierce, DW, Cayan DR, Thrasher BL.  2014.  Statistical downscaling using Localized Constructed Analogs (LOCA). Journal of Hydrometeorology. 15:2558-2585.   10.1175/jhm-d-14-0082.1   AbstractWebsite

A new technique for statistically downscaling climate model simulations of daily temperature and precipitation is introduced and demonstrated over the western United States. The localized constructed analogs (LOCA) method produces downscaled estimates suitable for hydrological simulations using a multiscale spatial matching scheme to pick appropriate analog days from observations. First, a pool of candidate observed analog days is chosen by matching the model field to be downscaled to observed days over the region that is positively correlated with the point being downscaled, which leads to a natural independence of the downscaling results to the extent of the domain being downscaled. Then, the one candidate analog day that best matches in the local area around the grid cell being downscaled is the single analog day used there. Most grid cells are downscaled using only the single locally selected analog day, but locations whose neighboring cells identify a different analog day use a weighted combination of the center and adjacent analog days to reduce edge discontinuities. By contrast, existing constructed analog methods typically use a weighted average of the same 30 analog days for the entire domain. By greatly reducing this averaging, LOCA produces better estimates of extreme days, constructs a more realistic depiction of the spatial coherence of the downscaled field, and reduces the problem of producing too many light-precipitation days. The LOCA method is more computationally expensive than existing constructed analog techniques, but it is still practical for downscaling numerous climate model simulations with limited computational resources.

Maurer, EP, Brekke L, Pruitt T, Thrasher B, Long J, Duffy P, Dettinger M, Cayan D, Arnold J.  2014.  An enhanced archive facilitating climate impacts and adaptation analysis. Bulletin of the American Meteorological Society. 95:1011-+.   10.1175/bams-d-13-00126.1   AbstractWebsite

We describe the expansion of a publicly available archive of downscaled climate and hydrology projections for the United States. Those studying or planning to adapt to future climate impacts demand downscaled climate model output for local or regional use. The archive we describe attempts to fulfill this need by providing data in several formats, selectable to meet user needs. Our archive has served as a resource for climate impacts modelers, water managers, educators, and others. Over 1,400 individuals have transferred more than 50 TB of data from the archive. In response to user demands, the archive has expanded from monthly downscaled data to include daily data to facilitate investigations of phenomena sensitive to daily to monthly temperature and precipitation, including extremes in these quantities. New developments include downscaled output from the new Coupled Model Intercomparison Project phase 5 (CMIP5) climate model simulations at both the monthly and daily time scales, as well as simulations of surface hydrological variables. The web interface allows the extraction of individual projections or ensemble statistics for user-defined regions, promoting the rapid assessment of model consensus and uncertainty for future projections of precipitation, temperature, and hydrology. The archive is accessible online (http://gdo-dcp.ucllnl.org/downscaled_cmip_projections).

2013
Stahle, DW, Griffin RD, Meko DM, Therrell MD, Edmondson JR, Cleaveland MK, Stahle LN, Burnette DJ, Abatzoglou JT, Redmond KT, Dettinger MD, Cayan DR.  2013.  The ancient blue oak woodlands of California: Longevity and hydroclimatic history. Earth Interactions. 17   10.1175/2013ei000518.1   AbstractWebsite

Ancient blue oak trees are still widespread across the foothills of the Coast Ranges, Cascades, and Sierra Nevada in California. The most extensive tracts of intact old-growth blue oak woodland appear to survive on rugged and remote terrain in the southern Coast Ranges and on the foothills west and southwest of Mt. Lassen. In the authors' sampling of old-growth stands, most blue oak appear to have recruited to the canopy in the middle to late nineteenth century. The oldest living blue oak tree sampled was over 459 years old, and several dead blue oak logs had over 500 annual rings. Precipitation sensitive tree-ring chronologies up to 700 years long have been developed from old blue oak trees and logs. Annual ring-width chronologies of blue oak are strongly correlated with cool season precipitation totals, streamflow in the major rivers of California, and the estuarine water quality of San Francisco Bay. A new network of 36 blue oak chronologies records spatial anomalies in growth that arise from latitudinal changes in the mean storm track and location of land-falling atmospheric rivers. These long, climate-sensitive blue oak chronologies have been used to reconstruct hydroclimatic history in California and will help to better understand and manage water resources. The environmental history embedded in blue oak growth chronologies may help justify efforts to conserve these authentic old-growth native woodlands.

Pierce, DW, Cayan DR.  2013.  The uneven response of different snow measures to human-induced climate warming. Journal of Climate. 26:4148-4167.   10.1175/jcli-d-12-00534.1   AbstractWebsite

The effect of human-induced climate warming on different snow measures in the western United States is compared by calculating the time required to achieve a statistically significant linear trend in the different measures, using time series derived from regionally downscaled global climate models. The measures examined include the water content of the spring snowpack, total cold-season snowfall, fraction of winter precipitation that falls as snow, length of the snow season, and fraction of cold-season precipitation retained in the spring snowpack, as well as temperature and precipitation. Various stakeholders may be interested in different sets of these variables. It is found that temperature and the fraction of winter precipitation that falls as snow exhibit significant trends first, followed in 5-10 years by the fraction of cold-season precipitation retained in the spring snowpack, and later still by the water content of the spring snowpack. Change in total cold-season snowfall is least detectable of all the measures, since it is strongly linked to precipitation, which has large natural variability and only a weak anthropogenic trend in the western United States. Averaging over increasingly wider areas monotonically increases the signal-to-noise ratio of the 1950-2025 linear trend from 0.15 to 0.37, depending on the snow measure.

DeFlorio, MJ, Pierce DW, Cayan DR, Miller AJ.  2013.  Western US extreme precipitation events and their relation to ENSO and PDO in CCSM4. Journal of Climate. 26:4231-4243.   10.1175/jcli-d-12-00257.1   AbstractWebsite

Water resources and management over the western United States are heavily impacted by both local climate variability and the teleconnected responses of precipitation to the El Nino-Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO). In this work, regional precipitation patterns over the western United States and linkages to ENSO and the PDO are analyzed using output from a Community Climate System Model version 4 (CCSM4) preindustrial control run and observations, with emphasis on extreme precipitation events. CCSM4 produces realistic zonal gradients in precipitation intensity and duration over the western United States, with higher values on the windward side of the Cascade Mountains and Sierra Nevada and lower values on the leeward. Compared to its predecessor CCSM3, CCSM4 shows an improved teleconnected signal of both ENSO and the PDO to large-scale circulation patterns over the Pacific-North America region and also to the spatial pattern and other aspects of western U.S. precipitation. The so-called drizzle problem persists in CCSM4 but is significantly improved compared to CCSM3. In particular, it is found that CCSM4 has substantially less precipitation duration bias than is present in CCSM3. Both the overall and extreme intensity of wintertime precipitation over the western United States show statistically significant linkages with ENSO and PDO in CCSM4. This analysis provides a basis for future studies using greenhouse gas (GHG)-forced CCSM4 runs.

2012
Dettinger, MD, Ralph FM, Hughes M, Das T, Neiman P, Cox D, Estes G, Reynolds D, Hartman R, Cayan D, Jones L.  2012.  Design and quantification of an extreme winter storm scenario for emergency preparedness and planning exercises in California. Natural Hazards. 60:1085-1111.   10.1007/s11069-011-9894-5   AbstractWebsite

The USGS Multihazards Project is working with numerous agencies to evaluate and plan for hazards and damages that could be caused by extreme winter storms impacting California. Atmospheric and hydrological aspects of a hypothetical storm scenario have been quantified as a basis for estimation of human, infrastructure, economic, and environmental impacts for emergency-preparedness and flood-planning exercises. In order to ensure scientific defensibility and necessary levels of detail in the scenario description, selected historical storm episodes were concatentated to describe a rapid arrival of several major storms over the state, yielding precipitation totals and runoff rates beyond those occurring during the individual historical storms. This concatenation allowed the scenario designers to avoid arbitrary scalings and is based on historical occasions from the 19th and 20th Centuries when storms have stalled over the state and when extreme storms have arrived in rapid succession. Dynamically consistent, hourly precipitation, temperatures, barometric pressures (for consideration of storm surges and coastal erosion), and winds over California were developed for the so-called ARkStorm scenario by downscaling the concatenated global records of the historical storm sequences onto 6- and 2-km grids using a regional weather model of January 1969 and February 1986 storm conditions. The weather model outputs were then used to force a hydrologic model to simulate ARkStorm runoff, to better understand resulting flooding risks. Methods used to build this scenario can be applied to other emergency, nonemergency and non-California applications.

Hanson, RT, Flint LE, Flint AL, Dettinger MD, Faunt CC, Cayan D, Schmid W.  2012.  A method for physically based model analysis of conjunctive use in response to potential climate changes. Water Resources Research. 48   10.1029/2011wr010774   AbstractWebsite

Potential climate change effects on aspects of conjunctive management of water resources can be evaluated by linking climate models with fully integrated groundwater-surface water models. The objective of this study is to develop a modeling system that links global climate models with regional hydrologic models, using the California Central Valley as a case study. The new method is a supply and demand modeling framework that can be used to simulate and analyze potential climate change and conjunctive use. Supply-constrained and demand-driven linkages in the water system in the Central Valley are represented with the linked climate models, precipitation-runoff models, agricultural and native vegetation water use, and hydrologic flow models to demonstrate the feasibility of this method. Simulated precipitation and temperature were used from the GFDL-A2 climate change scenario through the 21st century to drive a regional water balance mountain hydrologic watershed model (MHWM) for the surrounding watersheds in combination with a regional integrated hydrologic model of the Central Valley (CVHM). Application of this method demonstrates the potential transition from predominantly surface water to groundwater supply for agriculture with secondary effects that may limit this transition of conjunctive use. The particular scenario considered includes intermittent climatic droughts in the first half of the 21st century followed by severe persistent droughts in the second half of the 21st century. These climatic droughts do not yield a valley-wide operational drought but do cause reduced surface water deliveries and increased groundwater abstractions that may cause additional land subsidence, reduced water for riparian habitat, or changes in flows at the Sacramento-San Joaquin River Delta. The method developed here can be used to explore conjunctive use adaptation options and hydrologic risk assessments in regional hydrologic systems throughout the world.

2011
Zhao, Z, Chen SH, Kleeman MJ, Tyree M, Cayan D.  2011.  The impact of climate change on air quality-related meteorological conditions in california. Part I: Present time simulation analysis. Journal of Climate. 24:3344-3361.   10.1175/2011jcli3849.1   AbstractWebsite

This study investigates the impacts of climate change on meteorology and air quality conditions in California by dynamically downscaling Parallel Climate Model (PCM) data to high resolution (4 km) using the Weather Research and Forecast (WRF) model. This paper evaluates the present years' (2000-06) downscaling results driven by either PCM or National Centers for Environmental Prediction (NCEP) Global Forecasting System (GFS) reanalysis data. The analyses focused on the air quality-related meteorological variables, such as planetary boundary layer height (PBLH), surface temperature, and wind. The differences of the climatology from the two sets of downscaling simulations and the driving global datasets were compared, which illustrated that most of the biases of the downscaling results were inherited from the driving global climate model (GCM). The downscaling process added mesoscale features but also introduced extra biases into the driving global data. The main source of bias in the PCM data is an imprecise prediction of the location and strength of the Pacific subtropical high (PSH). The analysis implied that using simulation results driven by PCM data as the input for air quality models will likely underestimate air pollution problems in California. Regional-averaged statistics of the downscaling results were estimated for two highly polluted areas, the South Coast Air Basin (SoCAB) and the San Joaquin Valley (SJV), by comparing to observations. The simulations driven by GFS data overestimated surface temperature and wind speed for most of the year, indicating that WRF has systematic errors in these two regions. The simulation matched the observations better during summer than winter in terms of bias. WRF has difficulty reproducing weak surface wind, which normally happens during stagnation events in these two regions. The shallow summer PBLH in the Central Valley is caused by the dominance of high pressure systems over the valley and the strong valley wind during summer. The change of meteorology and air quality in California due to climate change will be explored in Part II of this study, which compares the future (2047-53) and present (2000-06) simulation results driven by PCM data and is presented in a separate paper.

Das, T, Pierce DW, Cayan DR, Vano JA, Lettenmaier DP.  2011.  The importance of warm season warming to western US streamflow changes. Geophysical Research Letters. 38   10.1029/2011gl049660   AbstractWebsite

Warm season climate warming will be a key driver of annual streamflow changes in four major river basins of the western U.S., as shown by hydrological model simulations using fixed precipitation and idealized seasonal temperature changes based on climate projections with SRES A2 forcing. Warm season (April-September) warming reduces streamflow throughout the year; streamflow declines both immediately and in the subsequent cool season. Cool season (October-March) warming, by contrast, increases streamflow immediately, partially compensating for streamflow reductions during the subsequent warm season. A uniform warm season warming of 3 C drives a wide range of annual flow declines across the basins: 13.3%, 7.2%, 1.8%, and 3.6% in the Colorado, Columbia, Northern and Southern Sierra basins, respectively. The same warming applied during the cool season gives annual declines of only 3.5%, 1.7%, 2.1%, and 3.1%, respectively. Citation: Das, T., D. W. Pierce, D. R. Cayan, J. A. Vano, and D. P. Lettenmaier (2011), The importance of warm season warming to western U. S. streamflow changes, Geophys. Res. Lett., 38, L23403, doi: 10.1029/2011GL049660.

Das, T, Dettinger MD, Cayan DR, Hidalgo HG.  2011.  Potential increase in floods in California's Sierra Nevada under future climate projections. Climatic Change. 109:71-94.   10.1007/s10584-011-0298-z   AbstractWebsite

California's mountainous topography, exposure to occasional heavily moisture-laden storm systems, and varied communities and infrastructures in low lying areas make it highly vulnerable to floods. An important question facing the state-in terms of protecting the public and formulating water management responses to climate change-is "how might future climate changes affect flood characteristics in California?" To help address this, we simulate floods on the western slopes of the Sierra Nevada Mountains, the state's primary catchment, based on downscaled daily precipitation and temperature projections from three General Circulation Models (GCMs). These climate projections are fed into the Variable Infiltration Capacity (VIC) hydrologic model, and the VIC-simulated streamflows and hydrologic conditions, from historical and from projected climate change runs, allow us to evaluate possible changes in annual maximum 3-day flood magnitudes and frequencies of floods. By the end of the 21st Century, all projections yield larger-than-historical floods, for both the Northern Sierra Nevada (NSN) and for the Southern Sierra Nevada (SSN). The increases in flood magnitude are statistically significant (at p <= 0.01) for all the three GCMs in the period 2051-2099. The frequency of flood events above selected historical thresholds also increases under projections from CNRM CM3 and NCAR PCM1 climate models, while under the third scenario, GFDL CM2.1, frequencies remain constant or decline slightly, owing to an overall drying trend. These increases appear to derive jointly from increases in heavy precipitation amount, storm frequencies, and days with more precipitation falling as rain and less as snow. Increases in antecedent winter soil moisture also play a role in some areas. Thus, a complex, as-yet unpredictable interplay of several different climatic influences threatens to cause increased flood hazards in California's complex western Sierra landscapes.

2010
Maurer, EP, Hidalgo HG, Das T, Dettinger MD, Cayan DR.  2010.  The utility of daily large-scale climate data in the assessment of climate change impacts on daily streamflow in California. Hydrology and Earth System Sciences. 14:1125-1138.   10.5194/hess-14-1125-2010   AbstractWebsite

Three statistical downscaling methods were applied to NCEP/NCAR reanalysis (used as a surrogate for the best possible general circulation model), and the downscaled meteorology was used to drive a hydrologic model over California. The historic record was divided into an 'observed' period of 1950-1976 to provide the basis for downscaling, and a 'projected' period of 1977-1999 for assessing skill. The downscaling methods included a bias-correction/spatial downscaling method (BCSD), which relies solely on monthly large scale meteorology and resamples the historical record to obtain daily sequences, a constructed analogues approach (CA), which uses daily large-scale anomalies, and a hybrid method (BCCA) using a quantile-mapping bias correction on the large-scale data prior to the CA approach. At 11 sites we compared three simulated daily flow statistics: streamflow timing, 3-day peak flow, and 7-day low flow. While all downscaling methods produced reasonable streamflow statistics at most locations, the BCCA method consistently outperformed the other methods, capturing the daily large-scale skill and translating it to simulated streamflows that more skillfully reproduced observationally-driven streamflows.

2009
Hidalgo, HG, Das T, Dettinger MD, Cayan DR, Pierce DW, Barnett TP, Bala G, Mirin A, Wood AW, Bonfils C, Santer BD, Nozawa T.  2009.  Detection and attribution of streamflow timing changes to climate change in the western United States. Journal of Climate. 22:3838-3855.   10.1175/2009jcli2470.1   AbstractWebsite

This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow "center'' timing (the day in the "water-year'' on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States-the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier "center'' timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States.

Das, T, Hidalgo HG, Dettinger MD, Cayan DR, Pierce DW, Bonfils C, Barnett TP, Bala G, Mirin A.  2009.  Structure and detectability of trends in hydrological measures over the western United States. Journal of Hydrometeorology. 10:871-892.   10.1175/2009jhm1095.1   AbstractWebsite

This study examines the geographic structure of observed trends in key hydrologically relevant variables across the western United States at (1)/(8)degrees spatial resolution during the period 1950-99. Geographical regions, latitude bands, and elevation classes where these trends are statistically significantly different from trends associated with natural climate variations are identified. Variables analyzed include late-winter and spring temperature, winter-total snowy days as a fraction of winter-total wet days, 1 April snow water equivalent (SWE) as a fraction of October-March (ONDJFM) precipitation total [precip(ONDJFM)], and seasonal [JFM] accumulated runoff as a fraction of water-year accumulated runoff. Observed changes were compared to natural internal climate variability simulated by an 850-yr control run of the finite volume version of the Community Climate System Model, version 3 (CCSM3-FV), statistically downscaled to a (1)/(8)degrees grid using the method of constructed analogs. Both observed and downscaled model temperature and precipitation data were then used to drive the Variable Infiltration Capacity (VIC) hydrological model to obtain the hydrological variables analyzed in this study. Large trends (magnitudes found less than 5% of the time in the long control run) are common in the observations and occupy a substantial part (37%-42%) of the mountainous western United States. These trends are strongly related to the large-scale warming that appears over 89% of the domain. The strongest changes in the hydrologic variables, unlikely to be associated with natural variability alone, have occurred at medium elevations [750-2500 m for JFM runoff fractions and 500-3000 m for SWE/Precip(ONDJFM)] where warming has pushed temperatures from slightly below to slightly above freezing. Further analysis using the data on selected catchments indicates that hydroclimatic variables must have changed significantly (at 95% confidence level) over at least 45% of the total catchment area to achieve a detectable trend in measures accumulated to the catchment scale.

2008
Kueppers, LM, Snyder MA, Sloan LC, Cayan D, Jin J, Kanamaru H, Kanamitsu M, Miller NL, Tyree M, Due H, Weare B.  2008.  Seasonal temperature responses to land-use change in the western United States. Global and Planetary Change. 60:250-264.   10.1016/j.gloplacha.2007.03.005   AbstractWebsite

In the western United States, more than 79 000 km 2 has been converted to irrigated agriculture and urban areas. These changes have the potential to alter surface temperature by modifying the energy budget at the land-atmosphere interface. This study reports the seasonally varying temperature responses of four regional climate models (RCMs) - RSM, RegCM3, MM5-CLM3, and DRCM - to conversion of potential natural vegetation to modern land-cover and land-use over a 1-year period. Three of the RCMs supplemented soil moisture, producing large decreases in the August mean (- 1.4 to -3.1 degrees C) and maximum (-2.9 to -6.1 degrees C) 2-m air temperatures where natural vegetation was converted to irrigated agriculture. Conversion to irrigated agriculture also resulted in large increases in relative humidity (9% to 36% absolute change). Modeled changes in the August minimum 2-m air temperature were not as pronounced or consistent across the models. Converting natural vegetation to urban land-cover produced less pronounced temperature effects in all models, with the magnitude of the effect dependent upon the preexisting vegetation type and urban parameterizations. Overall, the RCM results indicate that the temperature impacts of land-use change are most pronounced during the summer months, when surface heating is strongest and differences in surface soil moisture between irrigated land and natural vegetation are largest. (c) 2007 Elsevier B.V. All rights reserved.

Pierce, DW, Barnett TP, Hidalgo HG, Das T, Bonfils C, Santer BD, Bala G, Dettinger MD, Cayan DR, Mirin A, Wood AW, Nozawa T.  2008.  Attribution of declining western US snowpack to human effects. Journal of Climate. 21:6425-6444.   10.1175/2008jcli2405.1   AbstractWebsite

Observations show snowpack has declined across much of the western United States over the period 1950-99. This reduction has important social and economic implications, as water retained in the snowpack from winter storms forms an important part of the hydrological cycle and water supply in the region. A formal model-based detection and attribution (D-A) study of these reductions is performed. The detection variable is the ratio of 1 April snow water equivalent (SWE) to water-year-to-date precipitation (P), chosen to reduce the effect of P variability on the results. Estimates of natural internal climate variability are obtained from 1600 years of two control simulations performed with fully coupled ocean-atmosphere climate models. Estimates of the SWE/P response to anthropogenic greenhouse gases, ozone, and some aerosols are taken from multiple-member ensembles of perturbation experiments run with two models. The D-A shows the observations and anthropogenically forced models have greater SWE/P reductions than can be explained by natural internal climate variability alone. Model-estimated effects of changes in solar and volcanic forcing likewise do not explain the SWE/P reductions. The mean model estimate is that about half of the SWE/P reductions observed in the west from 1950 to 1999 are the result of climate changes forced by anthropogenic greenhouse gases, ozone, and aerosols.

2007
Maurer, EP, Stewart IT, Bonfils C, Duffy PB, Cayan D.  2007.  Detection, attribution, and sensitivity of trends toward earlier streamflow in the Sierra Nevada. Journal of Geophysical Research-Atmospheres. 112   10.1029/2006jd008088   AbstractWebsite

[1] Observed changes in the timing of snowmelt dominated streamflow in the western United States are often linked to anthropogenic or other external causes. We assess whether observed streamflow timing changes can be statistically attributed to external forcing, or whether they still lie within the bounds of natural ( internal) variability for four large Sierra Nevada ( CA) basins, at inflow points to major reservoirs. Streamflow timing is measured by "center timing'' (CT), the day when half the annual flow has passed a given point. We use a physically based hydrology model driven by meteorological input from a global climate model to quantify the natural variability in CT trends. Estimated 50-year trends in CT due to natural climate variability often exceed estimated actual CT trends from 1950 to 1999. Thus, although observed trends in CT to date may be statistically significant, they cannot yet be statistically attributed to external influences on climate. We estimate that projected CT changes at the four major reservoir inflows will, with 90% confidence, exceed those from natural variability within 1 - 4 decades or 4 - 8 decades, depending on rates of future greenhouse gas emissions. To identify areas most likely to exhibit CT changes in response to rising temperatures, we calculate changes in CT under temperature increases from 1 to 5 degrees. We find that areas with average winter temperatures between -2 degrees C and -4 degrees C are most likely to respond with significant CT shifts. Correspondingly, elevations from 2000 to 2800 m are most sensitive to temperature increases, with CT changes exceeding 45 days ( earlier) relative to 1961 - 1990.

2006
Alfaro, EJ, Gershunov A, Cayan D.  2006.  Prediction of summer maximum and minimum temperature over the central and western United States: The roles of soil moisture and sea surface temperature. Journal of Climate. 19:1407-1421.   10.1175/jcli3665.1   AbstractWebsite

A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June-August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90 degrees W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950-2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly. skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona.

2005
Stewart, IT, Cayan DR, Dettinger MD.  2005.  Changes toward earlier streamflow timing across western North America. Journal of Climate. 18:1136-1155.   10.1175/jcli3321.1   AbstractWebsite

The highly variable timing of streamflow in snowmelt-dominated basins across western North America is an important consequence, and indicator, of climate fluctuations. Changes in the timing of snowmelt-derived streamflow from 1948 to 2002 were investigated in a network of 302 western North America gauges by examining the center of mass for flow, spring pulse onset dates, and seasonal fractional flows through trend and principal component analyses. Statistical analysis of the streamflow timing measures with Pacific climate indicators identified local and key large-scale processes that govern the regionally coherent parts of the changes and their relative importance. Widespread and regionally coherent trends toward earlier onsets of springtime snowmelt and streamflow have taken place across most of western North America, affecting an area that is much larger than previously recognized. These timing changes have resulted in increasing fractions of annual flow occurring earlier in the water year by 1-4 weeks. The immediate (or proximal) forcings for the spatially coherent parts of the year-to-year fluctuations and longer-term trends of streamflow timing have been higher winter and spring temperatures. Although these temperature changes are partly controlled by the decadal-scale Pacific climate mode [Pacific decadal oscillation (PDO)], a separate ani significant part of the variance is associated with a springtime warming trend that spans the PDO phases.

2003
Dettinger, MD, Cayan DR.  2003.  Interseasonal covariability of Sierra Nevada streamflow and San Francisco Bay salinity. Journal of Hydrology. 277:164-181.   10.1016/s0022-1694(03)00078-7   AbstractWebsite

The ecosystems of the San Francisco Bay estuary are influenced by the salinity of its waters, which in turn depends on flushing by freshwater inflows from the western slopes of the Sierra Nevada. Estimates of full-natural flows in eight major rivers that flush the Bay are analyzed here by extended empirical-orthogonal-function analyses to characterize distinct `modes' of seasonal flow and runoff variability. These modes provide a clear identification of the seasons in which the various rivers respond to hydroclimatic forcings and the seasons during which the rivers most strongly affect San Francisco Bay salinities. About 60 percent of the runoff variability is shared by the rivers over the course of a year but season-to-season differences among the rivers are more subtly distributed. Autumn and winter streamflows respond directly to concurrent (autumn and winter) precipitation and temperatures. Autumn and winter salinities are dominated by these flows, which in each season reflect mostly variations in flows from the central Sierra Nevada and the large Sacramento River. In contrast, spring runoff-rate and streamflow modes are functions of precipitation and temperature during the entire wet (winter and spring) season and are dominated by rivers of the central and southern Sierra Nevada. In turn, the critical spring salinities depend most on the streamflow fluctuations in those central and southern rivers. Published by Elsevier Science B.V.

2001
Biondi, F, Gershunov A, Cayan DR.  2001.  North Pacific decadal climate variability since 1661. Journal of Climate. 14:5-10.   10.1175/1520-0442(2001)014<0005:npdcvs>2.0.co;2   AbstractWebsite

Climate in the North Pacific and North American sectors has experienced interdecadal shifts during the twentieth century. A network of recently developed tree-ring chronologies for Southern and Baja California extends the instrumental record and reveals decadal-scale variability back to 1661. The Pacific decadal oscillation (PDO) is closely matched by the dominant mode of tree-ring variability that provides a preliminary view of multiannual climate fluctuations spanning the past four centuries. The reconstructed PDO index features a prominent bidecadal oscillation, whose amplitude weakened in the late 1700s to mid-1800s. A comparison with proxy records of ENSO suggests that the greatest decadal-scale oscillations in Pacific climate between 1706 and 1977 occurred around 1750, 1905, and 1947.

2000
Peterson, DH, Smith RE, Dettinger MD, Cayan DR, Riddle L.  2000.  An organized signal in snowmelt runoff over the western United States. Journal of the American Water Resources Association. 36:421-432.   10.1111/j.1752-1688.2000.tb04278.x   AbstractWebsite

Daily-to-weekly discharge during the snowmelt season is highly correlated among river basins in the upper elevations of the central and southern Sierra Nevada (Carson, Walker, Tuolumne, Merced, San Joaquin, Kings, and Kern Rivers). In many cases, the upper Sierra Nevada watershed operates in a single mode (with varying catchment amplitudes). In some years, with appropriate lags, this mode extends to distant mountains. A reason for this coherence is the broad scale nature of synoptic features in atmospheric circulation which provide anomalous insolation and temperature forcings that span a large region, sometimes the entire western U.S. These correlations may fall off dramatically, however, in dry years when the snowpack is spatially patchy.

1999
Cayan, DR, Redmond KT, Riddle LG.  1999.  ENSO and hydrologic extremes in the western United States. Journal of Climate. 12:2881-2893.   10.1175/1520-0442(1999)012<2881:eaheit>2.0.co;2   AbstractWebsite

Frequency distributions of daily precipitation in winter and daily stream flow from late winter to early summer, at several hundred sites in the western United States, exhibit strong and systematic responses to the two phases of ENSO. Most of the stream flows considered are driven by snowmelt. The Southern Oscillation index (SOI) is used as the ENSO phase indicator. Both modest (median) and larger (90th percentile) events were considered. In years with negative SOI values (El Nino), days with high daily precipitation and stream flow are more frequent than average over the Southwest and less frequent over the Northwest. During years with positive SOI values (La Nino), a nearly opposite pattern is seen. A more pronounced increase is seen in the number of days exceeding climatological 90th percentile values than in the number exceeding climatological 50th percentile values, for both precipitation and stream flow. Stream flow responses to ENSO extremes are accentuated over precipitation responses. Evidence suggests that the mechanism for this amplification involves ENSO-phase differences in the persistence and duration of wet episodes, affecting the efficiency of the process by which precipitation is converted to runoff. The SOI leads the precipitation events by several months,and hydrologic lags (mostly through snowmelt) delay the stream flow response by several more months. The combined 6-12-month predictive aspect of this relationship should be of significant benefit in responding to flood (or drought) risk and in improving overall water management in the western states.