Adjusted and Homogenized Canadian Climate Data - AHCCD & CanHom

Summary Description

The Adjusted and Homogenized Canadian Climate Data (AHCCD) are climate station datasets of quality-controlled and homogenized historical climate data from Environment and Climate Change Canada (ECCC). They provide long-term station-based observations for temperature, precipitation, wind and atmospheric pressure across Canada. The datasets incorporate adjustments to the historical station data for non-climatic factors (e.g., station relocations, site exposure, instrumentation changes, observer, observing procedures) to ensure consistency and reliability. AHCCD data was developed for climate research, climate change studies and trend analysis. The next generation of homogenized Canadian climate data has been published under the name Canadian Homogenized Surface Air Temperature (CanHomT V4) (Wan et al. (2025)). Publication of updated Canadian Homogenized Precipitation (CanHomP V2, Wang & Feng (2026)) and Canadian Homogenized Wind Speed data (CanHomW, Wang et al. (2025)) shall follow. The detailed descriptions of the AHCCD/CanHom datasets are listed under the Dataset Characteristics below.

AHCCD_temperature_stations

AHCCD Temperature Stations with starting dates prior to 1990 (blue), starting dates from 1990 (green), and stations closed but with more than 30 years of data (red) (figure from Vincent et al. (2020)).

Dataset Characteristics

When to use AHCCD & CanHom

  • When you need information about past climate.
  • When you don’t mind temporal or spatial discontinuities.
  • When you need near-surface temperature or precipitation data.
  • When you need information about extremes.
  • When you need to detect historical trends.
  • When you need to validate reanalysis data.
  • When you need to establish local thresholds or reference climatologies.

Strengths and Limitations

Key Strengths of AHCCD & CanHom

Strength Description
Homogenized time series Adjustments remove artificial shifts due to non-climatic influences, thus allowing more accurate trend analysis.
Long-term coverage. Long term data containing many stations with over 100 years of record.
National consistency Standardized methodologies applied across the Canadian network.
Data source for ECCC’s climate indicators Used in the development of Canadian climate change indicators and official climate assessments.

Limitations of AHCCD & CanHom

Limitation Description
Station coverage gaps Sparse in some northern or remote regions, limiting spatial completeness.
Point locations Station-based data may not represent broader regional conditions, particularly in more northern station sparse areas where the next station may be far away and in complex terrain where local conditions change over short distances.
Varying temporal coverage The length of the data records vary by station and variable. There may be gaps in the station’s data or a station may have been retired. The dataset is updated at irregular intervals but the latest observations may not have been processed.
Historical instrumentation issues Despite adjustments, early observations may be affected by poorer instrumentation or manual practices, which may increase uncertainty.

Expert Guidance

Environment and Climate Change Canada (ECCC) produces the Adjusted and Homogenized Canadian Climate Data (AHCCD) for use in climate research and climate change studies and the data have been used in the production of climate trends (Vincent et al. (2015), Vincent et al. (2018)). The data are collected from Reference Climate Stations and some Canadian Aviation Weather Service stations. The AHCCD stations keep the same IDs as the Meteorological Service of Canada (MSC) stations to facilitate comparison. Note that the governments AHCCD web site and the AHCCD Technical Documentation mention that AHCCD data should not be used for legal purposes since they are different from official MSC in situ records.

The data are point data and may not be representative of a large region, especially in complex terrain. Althought the time series are quality controlled there may be missing values in the data, varying by variable station and time (see figure above). The length of the records for individual stations may vary significantly, and some records are from stations that have been closed. In some instances AHCCD data from nearby stations may be merged to create a longer record.

The non-climatic shifts in tempertature data are identified by statistically comparing adjacent stations. Station metadata are investigated to understand non-climatic causes and determine a corrective measure if a shift has been identified. A recurring adjustment is related to the change in observing time at principal stations in 1961. The correction of the temperature record results in a slightly stronger warming in the homogenized dataset than the unadjusted data: For southern Canada this trend changed from 1.32° to 1.62°C for 1900–2018, with a smaller change for all of Canada (Vincent et al. (2020)).

Precipitation data correction accounts for a number of known errors in precipitation measurements, such as underestimation of actually gauged precipitation and limits to the minimum measurable amount. Snow measurements adjust for varying snow density depending on geographical location. Updates of historical adjusted precipitation has been interrupted since Autumn 2017. This hiatus is related to the integration of manual observations to an increasingly automated station network. Updates are planned to be resumed, but no time has been specified. Check for update on this prior to publication!

Monthly datasets for Precipitation (Wang & Feng (2026)) and for Wind (Wang et al. (2025)) have been published. Qian et al. (2025) use CanHomT and CanHomP to derive observed changes in Canada’s snowfall. Wang & Feng (2026) analyze trends in extremme precipitation indices using the next generation of Canadian Homogenized Daily Precipitation, CanHomP V2, however the data are not published at the time of this writing.Check for update on data availablility of precip prior to publication!

For wind speed adjustments, the key measure is the standardization of the measuring height at 10m above ground based on meta data and the measurement instrument setup. Furthermore, non-climatic causes of shifts in wind speed are identified by comparing monthly means at stations to modeled monthly means.

The non-climatic shifts that are corrected in AHCCD sea level pressure and station pressure data are related to station elevation, station relocation and errors during digitization of paper records. The correction process also scans for unusually high or low values, sudden extremes or physically implausible pressure changes.

More details on the methodology can be found in the AHCCD Technical Documentation and the references therein.

Variables available in AHCCD & CanHom

For details click on variable group to uncollapse

Daily temperature values
  • Minimum temperature [˚C]
  • Maximum temperature [˚C]
  • Mean temperature [˚C]
  • >330 locations in Canada

For more details see the website on daily AHCCD data

Monthly, seasonal, and annual mean
  • Minimum temperature [˚C]
  • Maximum temperature [˚C]
  • Mean temperature [˚C]
  • 780 locations in Canada

For more details see the AHCCD Technical Documentation and the Adjusted and homogenized Canadian climate data web page for temperature data and references therein.

Daily precipitation values
  • Daily liquid precipitation (rain) [mm/period]
  • Daily solid precipitation (snow) [mm/period]
  • Daily total precipitation (rain and snow) [mm/period]
  • >460 locations in Canada

For more details see the website on daily AHCCD data

Monthly, seasonal, and annual mean
  • Liquid precipitation (rain) [mm/period]
  • Solid precipitation (snow) [mm/period]
  • Total precipitation (rain and snow) [mm/period]
  • 467 locations in Canada

For more details see the AHCCD Technical Documentation and the Adjusted and homogenized Canadian climate data web page for precipitation data and references therein.

Monthly, seasonal and annual means of hourly wind speed
  • Wind speed [m/s]
  • Evaluated at standard 10 metre level
  • 156 locations in Canada

For more details see the AHCCD Technical Documentation and the Adjusted and homogenized Canadian climate data web page for wind speed data and references therein.

Monthly, seasonal and annual means of hourly measurements
  • Station level pressure [Pa]
  • Sea Level pressure [Pa]
  • 626 locations in Canada

For more details see the AHCCD Technical Documentation and the Adjusted and homogenized Canadian climate data web page for wind speed data and references therein.

Data Access

Daily AHCCD station data can be found on ClimateData.ca or downloaded via the Climate Data Extraction Tool (Monthly, seasonal and annual AHCCD station data). A collection of all daily AHCCD station data in a single netCDF file is available on PAVICS.

References

(click to expand)
Mekis, É., & Vincent, L. A. (2011). An overview of the second generation adjusted daily precipitation dataset for trend analysis in canada. Atmosphere-Ocean, 49(2), 163–177.
Qian, B., Wang, X. L., Zwiers, F. W., & Feng, Y. (2025). Observed changes in canada’s snowfall as inferred from precipitation and daily mean temperatures. Atmosphere-Ocean, 0(0), 1–15.
Vincent, L. A., Hartwell, M. M., & and, X. L. W. (2020). A third generation of homogenized temperature for trend analysis and monitoring changes in canada’s climate. Atmosphere-Ocean, 58(3), 173–191.
Vincent, L. A., Zhang, X., Brown, R. D., … Wang, X. L. (2015). Observed trends in canada’s climate and influence of low-frequency variability modes. Journal of Climate, 28(11), 4545–4560.
Vincent, L. A., Zhang, X., Mekis, É., Wan, H., & and, E. J. B. (2018). Changes in canada’s climate: Trends in indices based on daily temperature and precipitation data. Atmosphere-Ocean, 56(5), 332–349.
Wan, H., Spassiani, A. C., & Vincent, L. A. (2025). Canada’s fourth generation of homogenized surface air temperature and its trends for 1948–2023. Atmosphere-Ocean, 63(4), 223–240.
Wan, H., Wang, X. L., & Swail, V. R. (2007). A quality assurance system for canadian hourly pressure data. Journal of Applied Meteorology and Climatology, 46(11), 1804–1817.
Wan, H., Wang, X. L., & Swail, V. R. (2010). Homogenization and trend analysis of canadian near-surface wind speeds. Journal of Climate, 23(5), 1209–1225.
Wang, X. L., & Feng, Y. (2026). Observed trends in precipitation extreme indices as inferred from a homogenized daily precipitation dataset for canada. Weather and Climate Extremes, 51, 100860.
Wang, X. L., Feng, Y., Isaac, V., Zwiers, F. W., Vincent, L. A., & Hartwell, M. M. (2025). Observed surface wind speed trends inferred from homogenized in situ data and reanalysis datasets. Atmosphere-Ocean, 0(0), 1–17.