Publications

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2008
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.

2009
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.

2011
Pan, LL, Chen SH, Cayan D, Lin MY, Hart Q, Zhang MH, Liu YB, Wang JZ.  2011.  Influences of climate change on California and Nevada regions revealed by a high-resolution dynamical downscaling study. Climate Dynamics. 37:2005-2020.   10.1007/s00382-010-0961-5   AbstractWebsite

In this study, the influence of climate change to California and Nevada regions was investigated through high-resolution (4-km grid spacing) dynamical downscaling using the WRF (Weather Research & Forecasting) model. The dynamical downscaling was performed to both the GFS (Global forecast model) reanalysis (called GFS-WRF runs) from 2000-2006 and PCM (Parallel Climate Model) simulations (called PCM-WRF runs) from 1997-2006 and 2047-2056. The downscaling results were first validated by comparing current model outputs with the observational analysis PRISM (Parameter-elevation Regressions on Independent Slopes Model) dataset. In general, the dominant features from GFS-WRF runs and PCM-WRF runs were consistent with each other, as well as with PRISM results. The influences of climate change on the California and Nevada regions can be inferred from the model future runs. The averaged temperature showed a positive trend in the future, as in other studies. The temperature increases by around 1-2A degrees C under the assumption of business as usual over 50 years. This leads to an upward shifting of the freezing level (the contour line of 0A degrees C temperature) and more rain instead of snow in winter (December, January, and February). More hot days (> 32.2A degrees C or 90A degrees F) and extreme hot days (> 37.8A degrees C or 100A degrees F) are predicted in the Sacramento Valley and the southern parts of California and Nevada during summer (June, July, and August). More precipitation is predicted in northern California but not in southern California. Rainfall frequency slightly increases in the coast regions, but not in the inland area. No obvious trend of the surface wind was indicated. The probability distribution functions (PDF) of daily temperature, wind and precipitation for California and Nevada showed no significant change in shape in either winter or summer. The spatial distributions of precipitation frequency from GFS-WRF and PCM-WRF were highly correlated (r = 0.83). However, overall positive shifts were seen in the temperature field; increases of 2A degrees C for California and 3A degrees C for Nevada in summer and 2.5A degrees C for California and 1.5A degrees C for Nevada in winter. The PDFs predicted higher precipitation in winter and lower precipitation in the summer for both California and Nevada.

2013
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.