Fine-Scale Monthly Climate Change data
for the greater Pacific Northwest
This project was motivated by the need for fine-scale climate information for use in assessing climate change impacts to ecosystems and habitats. In impacts studies, a tension exists between the fine-scale resolution needs of decision makers and the constraints imposed by the sometimes-sparse network of climate observing stations. Past work by CIG and others has settled on a compromise resolution of 1/16th degree (~6 km) -- a resolution that has proven sufficient to resolve impacts at the watershed scale. Since then, datasets have become available which provide information on the mean climate at 30 arc-seconds (~800 m). In this project we apply the later datasets to their lower-resolution counterparts to obtain a set of new fine-scale climate datasets at 30 arc-second resolution.
Due to differences in the type and quality of the data available, two separate datasets were produced covering the following two regions:
- the Pacific Northwest up to 49N (hereafter referred to as "PNW")
- the PNW, British Columbia, and Alaska panhandle up to 60N ("WNA")
We developped gridded monthly historical and downscaled future climate datasets at 30 arc-second resolution using medium resolution regional datasets (listed in Table 1) as a basis. These were then interpolated to 30 arc-seconds and bias-corrected using 30 arc-second climatologies (1971-2000) from climateWNA (Wang et al., 2012) for the WNA region and PRISM (Parameter Regression on Independent Slopes Model, Daly et al., 2002). The result is a set of monthly historical datasets at 30 arc-second resolution. It is important to note that the PRISM data are likely to be of better quality than the climateWNA data, since the latter simply consists of a bilinear interpolation for both temperature and precipitation and an elevation correction for temperature (no correction is applied to the precipitation data).
Table 1 List of medium resolution datasets used as a basis for the 30 arc-second dataset
|Region||Source of Data||Resolution||Years|
|Pacific Northwest (PNW)||Columbia Basin Climate Change Scenarios Project (CBCCSP, Hamlet et al., 2010)||1/16th degree||1915-2006|
|British Columbia (BC)||Pacific Climate Impacts Consortium (PCIC, Werner et al., 2011)||1/16th degree||1950-2006|
|Alaska Panhandle||Scenarios Network for Alaska Planning (SNAP, 2011)||2 km||1950-2006|
Table 2 List of 30 arc-second resolution climatologies used to bias-correct the medium resolution datasets
|Coverage||Source of Data||Yrs in Avg|
|Conterminous U.S.||PRISM (Parameter Regression on Independent Slopes Model, Daly et al., 2002)||1971-2000|
|Western North America||climateWNA (Wang et al., 2012)||1971-2000|
This new 30 arc-second historical dataset was then used as the basis for the downscaling of global climate model (GCM) projections for each region. The statistical downscalings used for the WNA region are the "Transient", or BCSD nd Statistical Downscaling, Hamlet et al., 2010) method of downscaling, applied to all 19 available GCM projections archived as part of the IPCC fourth assessment. Only the A1b emissions scenario (Nakicenovic, 2000) was used for the WNA projections. The PNW downscalings reflect those used for the CBCCSP project mentioned above, and included both the Hybrid Delt and BCSD statistical downscalings (Hamlet et al., 2010). These are performed for both the A1b and B1 emissions scenarios. In addition, dynamically downscaled data are available for the PNW region, obtained from simulations of the Weather Research and Forecasting (WRF) model. The WRF model is an advanced mesoscale numerical weather prediction system (www.wrf-model.org). The WRF model configuration used here follows that used by Salathe et al. (2010) and Zhang et al. (2009).
For each of the above downscalings, the monthly gridded data are archived in ArcInfo GridAscii format. In addition, annual and decadal summaries are included for each variable (maximum temperature, minimum temperature, and precipitation). To simplify downloading, the files are grouped by variable and averaging period (monthly, annual, decadal) and stored in zipped files.
Accessing the Data
(Note that each data directory contains a subdirectory with zipped data files and another containing diagnostic plots. Downscaled data is organized by model name and emissions scenario.)
- Transient, or Bias Correction and Statistical Downscaling (BCSD)
- Hybrid Delta statistical downscaling
- WRF dynamic downscaling
This project was funded by ... need to get Meade to fill this part in.
Daly, C. et al., 2002: A knowledge-based approach to the statistical mapping of climate. Climate Research, 22 (2), 99-113.
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.
Nakicenovic, N et al. (2000). Special Report on Emissions Scenarios: A Special Report of Working Group III of the Intergovernmental Panel on Climate Change.
Salathe E.P., Leung L.R., Qian Y., and Zhang YX., 2010: Regional climate model projections for the State of Washington. Climatic Change, 102: 51-75.
SNAP (2011). Scenarios Network for Alaska and Arctic Planning. Retrieved March, 2011. http://www.snap.uaf.edu/
Wang, T., Hamann, A., Spittlehouse, D., and Murdock, T. N. 2012. ClimateWNA - High-Resolution Spatial Climate Data for Western North America. Journal of Applied Meteorology and Climatology, in press.
Werner, A.T., 2011: BCSD Downscaled Transient Climate Projections for Eight Select GCMs over British Columbia, Canada. Pacific Climate Impacts Consortium, University of Victoria, Victoria, BC, 63 pp.
Zhang Y.X, Duliere V., Mote P.W., and Salathe E.P., 2009: Evaluation of WRF and HadRM Mesoscale Climate Simulations over the US Pacific Northwest. J. Climate, 22: 5511-5526.
Questions regarding this dataset can be directed to Guillaume Mauger (gmauger at uw dot edu), (206) 685-0317[an error occurred while processing this directive]