Canadian Gridded Climate Dataset - NRCanMET

Summary Description

The ANUSPLIN Canadian Gridded Climate Dataset (NRCanMET) is a high-resolution, station-based gridded climate dataset produced by Natural Resources Canada (NRCan) and Agriculture and Agri-Food Canada. It provides daily and monthly interpolated climate variables across Canada, utilizing the Australian National University Spline (ANUSPLIN) interpolation package. The dataset provides information coninuous in time and space for climate research and environmental studies. A variation of the dataset is PCIC-Blend which combines NRCanMET with regional station interpolation datasets.

ERA5-Land Example

Percent difference in mean annual precipitation for NRCANmet minus PNWNAmet (from Werner et al. (2019))

Dataset Characteristics

  • Current version: No official versioning, see Expert Guidance. The latest version was generated in 2022.
  • Temporal coverage: 1950–2020
  • Temporal resolution: Daily and monthly
  • Spatial coverage: Canadian landmass (Apparently the latest version covers Can & US!!!)
  • Spatial resolution: ~10 km grid spacing (0.1°)
  • Data type: Quality-controlled station observations interpolated using ANUSPLIN
  • Web references:
    NRCanMET data descriptions are provided on the Northern Climate Data Report and Inventory (NCDRI) Web Site for temperature and precipitation.
  • Reference publications: See references below

Strengths and Limitations

Key Strengths of NRCanMET

Strength Description
Observation-based The dataset is entirely based on quality controlled observed data.
High Spatial Resolution Provides detailed climate information at ~10 km resolution across Canada.
Long-Term Coverage Spans over six decades, enabling comprehensive climate trend analyses.
Quality-Controlled Data Utilizes quality-controlled station observations for interpolation.

Key Limitations of NRCanMET

Limitation Description
Temporal Inconsistency Station availability and density varies over time, affecting data consistency over time.
Interpolation Limitations Accuracy depends on the density and distribution of input stations.
Artefacts in the Data The interpolation procedure occasionnaly produces local artefacts of unrealistic values.
Lack of Real-Time Updates Dataset extends up to 2020, updates are irregular.
Limited Variables Focuses primarily on temperature and precipitation; other climate variables are not included.

Expert Guidance

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The ANUSPLIN Canadian Gridded Climate Dataset (NRCanMET) is a widely used gridded dataset derived from observed station data, providing continuous climate and weather information in space and time. The long time period makes it useful for climate studies and it has been employed in the bias adjustment of climate model simulation data, namely the data backing the ClimateData.ca web site.

The ANUSPLIN algorithm is designed to interpolate irregularly distributed station data and accounts for elevation variations, balancing fidelity to data with smoothness while avoiding overfitting. It produces smooth, realistic surfaces well suited for environmental modeling, agriculture, forestry, or hydrology studies. The station data used for the NRCanMET dataset are quality controlled but not homogenized. Although elevation data are used in the interpolation scheme, reanalysis data appear to better represent orographic influence on climate variables.

Like any such interpolated data it is highly dependent on the quality of the input data and its reliability diminishes with the availability of station data or the distance to the latter. Particularly in areas of sparse station networks like the Canadian North, the interpolation is less capable of capturing local variation between stations far apart. This is particularly the case for precipitation since, other than temperature, it is not continuous in time and space. Further, the interpolation algorithm may introduce artefacts of unrealistic values in the data fields, some of which have been corrected in updates.

Different versions of the dataset have been published but as of this writing no offical versioning of the dataset has been established. The versions differ in the version of the ANUSPLIN algorithm, in the stations used and the temporal coverage as more recent years were produced in each iteration. The latest version ToDo: To be confirmed (available through PAVICS) also extends it’s spatial coverage to include the US.

General bias for tmin, tmax, precip? Ask Gabriel!

Generally, three versions of the dataset exist:

  • NRCanMET v1 (1950-2013)
  • NRCanMET v2 (1950-2017)
  • NRCanMET v2 (1949-2020)

The versions are generally very similar in their temperature values with v2 having less temperature reversals, where Tmin > Tmax. Regarding precipitation, v2 is somewhat dryer than v1. For Northern and Eastern stations, biases compared to stations are lower for v2. The dataset is particulary dryer over the western mountains which motivated the generation of PCIC-Blend, a combination of NRCanMET with a distinct gridded dataset over western Canada and the north-western US (Werner et al. (2019)).

When comparing temperature data processed by PCIC and Ouranos, a mean difference of 0.15 ˚C was found. This could be traced back to the adjustment of the raw data provided in Kelvin using 273 ˚C and 273.15 ˚C by PCIC and Ouranos respectively.

Example Applications

links to Electricity Sector Applications

Variables available in NRCanMET

For details click on variable group to uncollapse

  • Daily maximum temperature (°C)
  • Daily minimum temperature (°C)
  • Monthly maximum temperature (°C)
  • Monthly minimum temperature (°C)
  • Pentad (°C)
  • Climatological means (°C)
  • Daily total precipitation (mm)
  • Monthly total precipitation (mm)
  • Pentad (°C)
  • Climatological means (°C)

Data Access

NRCanMET gridded data is freely available upon contact with Dr. Dan McKenney, Canadian Forest Service, Natural Resources Canada, Dan.Mckenney@canada.ca.

ToDo: Check: Can we put this link to the daily data on NRCan’S FTP - Check with NRCan!?

The dataset is also available on PAVICS. To avoid downloading very large datasets in their entirety PAVICS allows partial/regional extraction and provides a tutorial to do so, using the CaSR reanalysis as an example . With a free PAVICS user account, the Jupyter notebook with the Python code in the tutorial can be directly used on PAVICS.

Another option to obtain NRCanMET is from the website of the Pacific Climate Impacts Consortium. Note that this version covers only the time period 1950-2012.

References

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. Journal of Applied Meteorology and Climatology 50, 1654–1665. https://doi.org/10.1175/2011JAMC2684.1
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. Journal of Applied Meteorology and Climatology 48, 725–741. https://doi.org/10.1175/2008JAMC1979.1
MacDonald, H., McKenney, D.W., Papadopol, P., Lawrence, K., Pedlar, J., Hutchinson, M.F., 2020. North american historical monthly spatial climate dataset, 1901–2016. Scientific Data 7, 411. https://doi.org/10.1038/s41597-020-00737-2
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. Bulletin of the American Meteorological Society 92, 1611–1622. https://doi.org/10.1175/2011BAMS3132.1
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. https://doi.org/10.1038/sdata.2018.299