Historic and future projected changes in Snow Water Equivalent (SWE) for Oregon and Washington


Overview


Water resource managers and aquatic wildlife specialists need high resolution hydrologic data to forecast operational or habitat shifts resulting from climate changes. In the Pacific Northwest, numerous resources and infrastructure are strongly dependent on the influence and seasonality of snowpack, in particular due to its influence on both summer and winter hydrology. Water resource managers and aquatic wildlife specialists need high resolution hydrologic data to forecast operational or habitat shifts resulting from climate changes. Unfortunately, observations of snowpack are unfortunately too sparse and often too short to reliably deduce climate impacts. This study applies a new 30 arc-second (~800 m) dataset produced by the Climate Impacts Group (CIG) to obtain estimates of historical and future projected changes in snowpack for the region.

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Domain

Figure 1 Map showing the domain used for the current dataset. The region covers most of the states of Oregon and Washington.


Methods and Products


The domain for this study covers nearly all of the states of Oregon and Washington (see Figure 1). Monthly historical (1915-2006) and future climate data (daily maximum temperature, minimum temperature, and precipitation) were obtained from the new 30 arc-second climate dataset mentioned above. These were then used to bias correct the daily 1/16th degree climate records generated previously by CIG, to obtain daily climate forcings at the new 30 arc-second resolution.

Due to the computational and storage limitations imposed by such a large number of grid cells, the future projections were limited to a set of 3 different projections for the decade of the 2040s, following the A1b emissions scenario (Nakicenovic et al., 2000). These projections were obtained from Littell et al. (2011), which used the spatially-explicit delta method of downscaling, applied to 3 different estimates of future climate: an average of the ten best climate models and two bracketing runs, one from the pcm1 model (which tends to be cooler than other models) and another from the miroc_3.2 model (which tends to be warmer).

To obtain estimates of Snow Water Equivalent (SWE), we implemented a modified version of the Variable Infiltration Capacity (VIC, Liang et al., 1994) macroscale model. Specifically, VIC was modified to include terrain slope and aspect in radiative calculations. To run VIC, the above climate dataset (daily maximum temperature, minimum temperature, and precipitation) was complemented with daily estimates of wind forcing obtained by linearly interpolating daily NCEP (National Centers for Environmental Prediction; Kalnay et al., 1996) reanalysis winds. With the exception of a few climate variables included in the soil files, which were taken directly from the 30 arc-second dataset, the vegetation and soil parameter files were obtained by linearly interpolating the values from the 1/16th degree files used in the Columbia Basin Climate Change Scenarios Project (CBCCSP, Hamlet et al., 2010). Finally, the snowband parameter file was generated to include a maximum of 5 subgrid elevation bands in each grid cell, defined based on a 2 arc-second (~60 m) resolution Digital Elevation Model (DEM). This latter file is particularly important for the present work, since it specifies the sub-grid elevation bands on which snow calculations are performed for each grid cell.

Monthly summaries and annual statistics of SWE are archived for the historical and future simulations and made available for download below. Specifically, the value of SWE is stored for each month for each grid cell in the simulation. In addition, a number of annual statistics are calculated (e.g., maximum swe, date of 10% accumulation, etc.). Summaries of the simulations are archived for the historical and future simulations. Daily results are also available upon request. Due to the size of the dataset, these are not posted for download.


Accessing the Data

Note:
Please use the contact information below to let us know how you plan to use the data -- we'd really like to know!

(Note that each data directory contains two subdirectories: one containing monthly summaries of the SWE simulations, and the other containing annual SWE statistics).


Funding


Funding for this project was provided by a grant from the USDA US Forest Service Region 6 Pacific Northwest Research Station.


References


Hamlet A.F. et al., 2010: Statistical downscaling techniques for global climate model simulations of temperature and precipitation with application to water resources planning studies. Chapter 4 in Final Project Report for the Columbia Basin Climate Change Scenarios Project.

Kalnay E. et al., 1996: The NCEP/NCAR 40-year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437-471.

Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges, 1994: A Simple hydrologically Based Model of Land Surface Water and Energy Fluxes for GSMs, J. Geophys. Res., 99(D7), 14,415-14,428.

Littell, J.S., M.M. Elsner, G. Mauger, E. Lutz, A.F. Hamlet,, and E. Salathé. 2011. Regional Climate and Hydrologic Change in the Northern US Rockies and Pacific Northwest: Internally Consistent Projections of Future Climate for Resource Management. DRAFT report available online here.

Nakicenovic, N et al. (2000). Special Report on Emissions Scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate Change.


Questions


Questions regarding this dataset can be directed to: