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Daily Gridded Meteorological Datasets

Gridded meteorological forcing datasets include observed daily station data interpolated to a resolution useful as target datasets for statistical downscaling and hydrologic modelling. Common variables include minimum and maximum temperature, and precipitation. The datasets hosted on this portal are all based on station data, but differ with respect to the selection of stations, their domains, resolution, record length and gridding methodology. The following describes them in reverse chronological order, with the most recently developed listed first.


PNWNAmet (1945-2012)

The PNWNAmet dataset was created circa 2014 at 1/16° (~6km) over a domain covering northwest North America (NWNA; 40°N to 72°N and -169°W to -101°W). PNWNAmet was created using the trivariate thin plate spline interpolation method with the algorithm implemented by Nychka et al. (2017). Minimum temperature, maximum temperature and precipitation were interpolated separately using latitude, longitude and a 1971-2000 climatology from ClimateWNA (v5.10) as predictors. ClimateWNA uses bilinear interpolation and an elevation adjustment  to create a scale-free, smooth at the boundaries, mosaic of available climatologies (Wang et al., 2006). Climatologies included were the latest available for the provinces, territories and states within NWNA, such as the 800 m, 1971-2000, PRISM products for BC and the contiguous US (Anslow, 2015; Daly et al., 2008). Elevation used in ClimateWNA was derived from the GEMTED2010 digital elevation model (Danielson and Gesch, 2011). Precipitation occurrence and square-root transformed precipitation amounts were interpolated separately on each day, combined, and transformed back to original units. After interpolation, the raw daily minimum and maximum temperature and precipitation surfaces were rescaled so that their climatological monthly means matched those of ClimateWNA following Hunter and Meetemeyer (2005). Wind data is also included, which is derived by re-gridding 10-m wind speed from the 20th Century Reanalysis V2 (20CR2) (Compo et al., 2011), as these are required by the VIC-GL hydrologic model. The wind data have not been adjusted to take wind field deformation by small-scale topographic features into account.

Station records were obtained from the second generation of Environment and Climate Change Canada's Adjusted and Homogenized Canadian Climate Data (AHCCD) (Mekis and Vincent, 2011; Vincent et al., 2012, 2002), the homogenized United States Historical Climatology Network (USHCN) in the contiguous US (Williams et al., 2006) and the Global Historical Climatology Network-Daily (GHCN-Daily) in Alaska (Menne et al., 2012). To maintain temporal consistency, selected stations had to have at least 40 years of complete records (< 10% missing days within a year) over the 1945-2012 period. To supplement sparse observations around the western and northern coasts of Alaska, daily data from  20CR2 (Compo et al., 2011) were used as virtual stations as they were the only daily reanalysis data available that cover the full 1945-2012 period. 

Please cite as Werner, A.T., Schnorbus, M.A., Shrestha, R.R., Cannon, A.J., Zwiers, F.W., Dayon G. and Anslow, F., 2019. A long-term, temporally consistent, gridded daily meteorological dataset for northwestern North America, Scientific Data, 6, 180299, doi:10.1038/sdata.2018.299.

NRCANmet (1950-2012)

The NRCANmet observational dataset was produced by Natural Resources Canada (NRCan) and is available at 300 arc second spatial resolution (1/12° grids, ~10 km) over Canada. The bulk of the daily minimum and maximum temperature, and precipitation amounts for the period 1950-2012 were produced circa 2011 by Hopkinson et al. (2011) and McKenney et al. (2011) on behalf of the Canadian Forest Service (CFS), NRCan. The dataset was updated in 2013 to correct for issues in the Churchill River area. Gridding was accomplished with the Australian National University Spline (ANUSPLIN) implementation of the trivariate thin plate splines interpolation method (Hutchinson et al., 2009) with latitude, longitude and elevation as predictors. Precipitation occurrence and square-root transformed precipitation amounts were interpolated separately on each day, combined, and transformed back to original units. 

Quality-controlled, but unadjusted, station data from the National Climate Data Archive (NCDA) of Environment and Climate Change Canada data (Hutchinson et al., 2009) were interpolated onto the high-resolution grid using thin plate splines.  Station density varies over time with changes in station availability, peaking in the 1970s with a general decrease towards the present day (Hutchinson et al., 2009). Thus, the number of stations active across Canada between 1950 and 2011 ranged from 2000 to 3000 for precipitation and 1500 to 3000 for air temperature (Hopkinson et al., 2011). 

PBCmet (1950-2004)

The PCIC meteorology for BC (PBCmet) dataset was created circa 2007 at 1/16° (~6 km) over British Columbia and northern parts of Washington, Oregon, Idaho and Montana. 
This dataset was generated following Maurer et al. (2002) and Hamlet and Lettenmaier (2005). Interpolation was carried out with the SYMAP algorithm (Shepard, 1984). The interpolated data was then adjusted to the ~4km, 1961-1990, PRISM climatology (Daly et al., 1994) and interpolated to higher resolution (15-arc seconds) using ClimateWNA (Hamann and Wang, 2005; Wang et al., 2006).  ClimateWNA was, in this case, run using the Shuttle Radar Topography Mission (SRTM) (v3) digital elevation model (Jarvis et al., 2006). The dataset also includes daily wind speed surfaces generated by re-gridding estimates of 10-m wind speed from the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalysis (Kalnay et al., 1996) to 1/16° (~6 km) as they are require by the VIC hydrologic model. As with the PNWNAmet dataset, the wind data were not adjusted to take wind field deformation by small scale topographic features into account.

Station data was obtained from a mix of station networks, including those of Environment and Climate Change Canada’s NCDA, the US Cooperative Observer Network, the British Columbia Ministry of Forests and Range’s Fire and Weather Branch, the British Columbia Ministry of Environment’s Automated Snow Pillow network and BC Hydro’s climate and snow stations. To maximize station density, stations were included if they had at least 5 years of record, but were otherwise allowed to drop in and out during the 1950-2004 period. Maximum station density in VIC occurred in the 1990s (Stahl et al., 2006). when networks such as BC Hydro, Ministry of Forests and Ministry of Environment, came on line or expanded.. Data from the homogenized Historical Canadian Climate Database (Mekis and Hogg, 1999; Vincent and Gullett, 1999) and the US Historical Climate Network (Easterling et al., 2000; Hughes, 1993) (Hughes et al. 1992; Easterling et al. 1999) were used to adjusted the dataset and create temporal consistency.

See Schnorbus et al. (2011) or Schnorbus et al. (2014) for more information. 


The data is subject to PCIC's terms of use.


This data product is provided by the Pacific Climate Impacts Consortium with an open license on an “AS IS” basis without any warranty or representation, express or implied, as to its accuracy or completeness. Any reliance you place upon the information contained here is your sole responsibility and strictly at your own risk. In no event will the Pacific Climate Impacts Consortium be liable for any loss or damage whatsoever, including without limitation, indirect or consequential loss or damage, arising from reliance upon the data or derived information.


Anslow, F.S., 2015. Climate Analysis and Monitoring - Research Plan: 2015-2019. Pacific Climate Impacts Consortium

Compo, G.P., Whitaker, J.S., Sardeshmukh, P.D., Matsui, N., Allan, R.J., Yin, X., Gleason, B.E., Vose, R.S., Rutledge, G., Bessemoulin, P., Brönnimann, S., Brunet, M., Crouthamel, R.I., Grant, A.N., Groisman, P.Y., Jones, P.D., Kruk, M.C., Kruger, A.C., Marshall, G.J., Maugeri, M., Mok, H.Y., Nordli, Ø., Ross, T.F., Trigo, R.M., Wang, X.L., Woodruff, S.D., Worley, S.J., 2011. The Twentieth Century Reanalysis Project. Q. J. R. Meteorol. Soc. 137, 1–28. https://doi.org/10.1002/qj.776.

Daly, C., Halbleib, M., Smith, J.I., Gibson, W.P., Doggett, M.K., Taylor, G.H., Curtis, J., Pasteris, P.P., Usda, N., 2008. Physiographically sensitive mapping of climatological temperature and precipitation across the conterminous United States.

Daly, C., Neilson, R.P., Phillips, D.L., 1994. A statistical-topographic model for mapping climatological precipitation over mountainous terrain. J. Appl. Meteorol. 33, 140–158.

Danielson, J.J., Gesch, D.B., 2011. Global multi-resolution terrain elevation data 2010 (GMTED2010) U.S. Geological Survey Open-File Report 2011–1073, 26 p.

Easterling, D.R., Meehl, G.A., Parmesan, C., Changnon, S., Karl, T.R., Mearns, L.O., 2000. Climate extremes: Observations, modeling and impacts. Science 289, 2068–2073.

Eum, H.-I., Dibike, Y., Prowse, T., Bonsal, B., 2014a. Inter-comparison of high-resolution gridded climate data sets and their implication on hydrological model simulation over the Athabasca Watershed, Canada. Hydrol. Process. 28, 4250–4271. https://doi.org/10.1002/hyp.10236.

Eum, H.-I., Yonas, D., Prowse, T., 2014b. Uncertainty in modelling the hydrologic responses of a large watershed: a case study of the Athabasca River basin, Canada. Hydrol. Process. 28, 4272–4293. https://doi.org/10.1002/hyp.10230.

Hamann, A., Wang, T.L., 2005. Models of climatic normals for genecology and climate change studies in British Columbia. Agric. For. Meteorol. 128, 211–221. https://doi.org/doi: 10.1016/j.agrformet.2004.10.004.

Hamlet, A.F., Lettenmaier, D.P., 2005. Production of Temporally Consistent Gridded Precipitation and Temperature Fields for the Continental United States. J. Hydrometeorol. 6, 330–336.

Hopkinson, R.F., McKenney, D.W., Milewska, E.J., Hutchinson, M.F., Papadopol, P., Vincent, L.A., 2011. Impact of Aligning Climatological Day on Gridding Daily Maximum–Minimum Temperature and Precipitation over Canada. J. Appl. Meteorol. Climatol. 50, 1654–1665. https://doi.org/10.1175/2011JAMC2684.1.

Hughes, J.P., 1993. A class of stochastic models for relating synoptic atmospheric patterns to local hydrologic phenomena. Thesis PH D–UNIVERSITY Wash. 1993 Source Diss. Abstr. Int. 54, 4233–4233.

Hunter, R.D., Meentemeyer, R.K., 2005. Climatologically Aided Mapping of Daily Precipitation and Temperature. J. Appl. Meteorol. 44, 1501–1510. https://doi.org/10.1175/JAM2295.1.

Hutchinson, M.F., McKenney, D.W., Lawrence, K., Pedlar, J.H., Hopkinson, R.F., Milewska, E., Papadopol, P., 2009. Development and Testing of Canada-Wide Interpolated Spatial Models of Daily Minimum–Maximum Temperature and Precipitation for 1961–2003. J. Appl. Meteorol. Climatol. 48, 725–741. https://doi.org/10.1175/2008JAMC1979.1.

Jarvis, A., Reuter, H.I., Nelson, A., Guevara, E., 2006. Hole-filled seamless SRTM data V3.1 available from the CGIAR-CSI SRTM 90m Database.

Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Leetmaa, A., Reynolds, R., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K.C., Ropelewski, C., Wang, J., Jenne, R., Joseph, D., 1996. The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc. 77, 437–471. https://doi.org/doi: 10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2.

Maurer, E.P., Wood, A.W., Adam, J.C., Lettenmaier, D.P., Nijssen, B., 2002. A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States. J. Clim. 15, 3237–3251. https://doi.org/doi: 10.1175/1520-0442(2002)015<3237:ALTHBD>2.0.CO;2.

McKenney, D.W., Hutchinson, M.F., Papadopol, P., Lawrence, K., Pedlar, J., Campbell, K., Milewska, E., Hopkinson, R.F., Price, D., Owen, T., 2011. Customized Spatial Climate Models for North America. Bull. Am. Meteorol. Soc. 92, 1611–1622. https://doi.org/10.1175/2011BAMS3132.1.

Mekis, E., Hogg, W.D., 1999. Rehabilitation and Analysis of Canadian Daily Precipitation Time Series. Atmosphere-Ocean 37, 53–85.

Mekis, É., Vincent, L.A., 2011. An Overview of the Second Generation Adjusted Daily Precipitation Dataset for Trend Analysis in Canada. Atmosphere-Ocean 49, 163–177. https://doi.org/doi: 10.1080/07055900.2011.583910.

Menne, M.J., Durre, I., Vose, R.S., Gleason, B.E., Houston, T.G., 2012. An Overview of the Global Historical Climatology Network-Daily Database. J. Atmospheric Ocean. Technol. 29, 897–910. https://doi.org/10.1175/JTECH-D-11-00103.1.

Nychka, D., Furrer, R., Paige, J., Sain, S., 2017. fields: Tools for Spatial Data.

Schnorbus, M.A., Bennett, K.E., Werner, A.T., Berland, A.J., 2011. Hydrologic Impacts of Climate Change in the Peace, Campbell and Columbia Watersheds, British Columbia, Canada. Pacific Climate Impacts Consortium, University of Victoria, Victoria, BC.

Schnorbus, M., Werner, A., Bennett, K., 2014. Impacts of climate change in three hydrologic regimes in British Columbia, Canada. Hydrol. Process. 28, 1170–1189. https://doi.org/10.1002/hyp.9661.

Shepard, D.S., 1984. Computer mapping: The SYMAP interpolation algorithm, in: Gaille, G.L., Willmott, C.J. (Eds.), Spatial Statistics and Models. Reidel, pp. 133–145.

Stahl, K., Moore, R.D., Floyer, J.A., Asplin, M.G., McKendry, I.G., 2006. Comparison of approaches for spatial interpolation of daily air temperature in a large region with complex topography and highly variable station density. Agric. For. Meteorol. 139, 224–236 https://doi.org/10.1016/j.agrformet.2006.07.004.

Vincent, L.A., Gullett, D.W., 1999. Canadian historical and homogeneous temperature datasets for climate change analyses. Int. J. Climatol. 19, 1375–1388. https://doi.org/10.1002/(SICI)1097-0088(199910)19:12<1375::AID-JOC427>3.0.CO;2-0.

Vincent, L.A., Wang, X.L., Milewska, E.J., Wan, H., Yang, F., Swail, V., 2012. A second generation of homogenized Canadian monthly surface air temperature for climate trend analysis. J. Geophys. Res. Atmospheres 117, D18110. https://doi.org/10.1029/2012JD017859.

Vincent, L.A., Zhang, X., Bonsal, B.R., Hogg, W.D., 2002. Homogenzation of daily temperatures over Canada. J. Clim. 15, 1322–1334.

Wang, T., Hamann, A., Spittlehouse, D.L., Aitken, S.N., 2006. Development of scale-free climate data for Western Canada for use in resource management. Int. J. Climatol. 26, 383–397. https://doi.org/10.1002/joc.1247.
Williams, C.N., Vose, R.S., Easterling, D.R., Menne, M.J., 2006. United States Historical Climatology Network Daily Temperature, Precipitation, and Snow Data. (No. ORNL/CDIAC-118, NDP-070.). Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee.

Werner, A.T., Schnorbus, M.A., Shrestha, R.R., Cannon, A.J., Zwiers, F.W., Dayon G., Anslow, F., 2019. A long-term, temporally consistent, gridded daily meteorological dataset for northwestern North America, Scientific Data, 6, 180299, doi:10.1038/sdata.2018.299.

Wong, J.S., Razavi, S., Bonsal, B.R., Wheater, H.S., Asong, Z.E., 2017. Inter-comparison of daily precipitation products for large-scale hydro-climatic applications over Canada. Hydrol Earth Syst Sci 21, 2163–2185. https://doi.org/10.5194/hess-21-2163-2017.