Canadian provincial climate anomalies (monthly)
Province x month rollup of the Canadian climate-anomaly station panel (ECCC keyless MSC GeoMet OGC API): number of reporting stations, median temperature anomaly in C, median precipitation anomaly in %, share of stations running warm (>= +2 C), cold (<= -2 C), wet (>= +50 % precip) and dry (<= -50 % precip), and the mean extreme_score with a per-month provincial rank. One row per (province, month); provinces with no reporting stations in a month are absent, never zero-filled. ECCC Data Services End-use Licence v2.1.1 — commercial_use = yes, attribution required. Primary key: (as_of, province_code, local_date). Cadence: monthly.
- Rows
- 10,966
- Columns
- 16
- Source cadence
- Monthly
- Last refreshed
- Sep 27, 2026
- Theme
- environment
| Column | Type | Description |
|---|---|---|
| as_of | string | Reference month: the last complete calendar month (YYYY-MM). Fixed per run so identical input produces an identical content hash. (unit: month) |
| province_code | string | Canadian province/territory code (e.g. ON, QC, BC). |
| local_date | string | The month the rollup covers (YYYY-MM, station local time). (unit: month) |
| year | integer | Calendar year. (unit: year) |
| month | integer | Calendar month (1-12). (unit: month) |
| n_stations | integer | Panel stations reporting in the province-month. (unit: count) |
| median_temp_anomaly_c | float | Median station temperature anomaly vs 1981-2010 normals across the province's panel stations. (unit: degrees C) |
| share_warm_months | float | Share of the province's stations with temp anomaly >= +2 C. (unit: share) |
| share_cold_months | float | Share of the province's stations with temp anomaly <= -2 C. (unit: share) |
| median_precip_anomaly_pct | float | Median station precipitation anomaly vs normals (null when no station has a computable precipitation anomaly). (unit: percent) |
| share_wet_months | float | Share of the province's stations with precip anomaly >= +50 %. (unit: share) |
| share_dry_months | float | Share of the province's stations with precip anomaly <= -50 %. (unit: share) |
| mean_extreme_score | float | Mean station extreme_score in the province-month. (unit: score) |
| province_extreme_rank | integer | Provincial rank within the month by mean_extreme_score (1 = most extreme). (unit: rank) |
| source_url | string | The exact GeoMet OGC API items URL queried for this run. (unit: URL) |
| row_hash | string | SHA-256 (16 hex chars) over the row's content fields; identical input yields an identical hash. (unit: hash) |
First 10 sample rows — a preview, not the complete dataset.
| as_of | province_code | local_date | year | month | n_stations | median_temp_anomaly_c | share_warm_months | share_cold_months | median_precip_anomaly_pct | share_wet_months | share_dry_months | mean_extreme_score | province_extreme_rank | source_url | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026-08 | AB | 1946-03 | 1,946 | 3 | 1 | 2.668 | 1 | 0 | -83.13 | 0 | 1 | 58.29 | 4 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | 96677eab7abc5879 |
| 2026-08 | AB | 1946-04 | 1,946 | 4 | 1 | 2.897 | 1 | 0 | -64.67 | 0 | 1 | 55.61 | 2 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | 18f21980b924a56f |
| 2026-08 | AB | 1946-05 | 1,946 | 5 | 1 | -1.048 | 0 | 0 | -30.13 | 0 | 0 | 22.14 | 4 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | ed5374f04fa01e91 |
| 2026-08 | AB | 1946-06 | 1,946 | 6 | 1 | -1.807 | 0 | 0 | 73.16 | 1 | 0 | 44.54 | 1 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | 3a1c8bf6779fc401 |
| 2026-08 | AB | 1946-07 | 1,946 | 7 | 1 | 0.433 | 0 | 0 | -32.67 | 0 | 0 | 15.21 | 7 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | 16639c43e5c01edb |
| 2026-08 | AB | 1946-08 | 1,946 | 8 | 1 | -0.655 | 0 | 0 | 15.53 | 0 | 0 | 12.85 | 8 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | f58fddc0fb2d7986 |
| 2026-08 | AB | 1946-09 | 1,946 | 9 | 1 | 0.133 | 0 | 0 | -44.58 | 0 | 0 | 15.04 | 6 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | 85362ba815ba9549 |
| 2026-08 | AB | 1946-10 | 1,946 | 10 | 1 | -0.961 | 0 | 0 | -63.03 | 0 | 1 | 30.92 | 3 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | 6c2e8d05f26f92ce |
| 2026-08 | AB | 1946-11 | 1,946 | 11 | 1 | -3.377 | 0 | 1 | 35.06 | 0 | 0 | 52.73 | 2 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | 004217751373f6a4 |
| 2026-08 | AB | 1946-12 | 1,946 | 12 | 1 | -4.612 | 0 | 1 | -16.34 | 0 | 0 | 54.9 | 1 | https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900 | a841c3cd8bbd5163 |
Profiled Sep 27, 2026 from snapshot 20260927T025309Z-38aad7205ae0
Measured- Completeness
- 99.9%
- Rows
- 10,966
- Columns
- 16
- Columns with gaps
- 2
| Column | Missing | Distinct | Range | Distribution |
|---|---|---|---|---|
| as_ofvarchar | 0% | 1 | — |
|
| province_codevarchar | 0% | 9 | — |
|
| local_datevarchar | 0% | 1,500 | — |
|
| yearbigint | 0% | 159 | 1,888 → 2,026median 1,974 | 173 outside 1st–99th percentile |
| monthbigint | 0% | 13 | 1 → 12median 6 | |
| n_stationsbigint | 0% | 39 | 1 → 39median 3 | 109 outside 1st–99th percentile |
| median_temp_anomaly_cdouble | 0.04% | 4,714 | -17.42 → 9.35median -0.175 | 220 outside 1st–99th percentile |
| share_warm_monthsdouble | 0% | 181 | 0 → 1median 0 | |
| share_cold_monthsdouble | 0% | 197 | 0 → 1median 0 | |
| median_precip_anomaly_pctdouble | 1.5% | 6,627 | -100 → 560.24median -8.91 | 216 outside 1st–99th percentile |
| share_wet_monthsdouble | 0% | 201 | 0 → 1median 0 | |
| share_dry_monthsdouble | 0% | 204 | 0 → 1median 0 | |
| mean_extreme_scoredouble | 0% | 5,026 | 0.14 → 97.69median 28.19 | 220 outside 1st–99th percentile |
| province_extreme_rankbigint | 0% | 10 | 1 → 9median 4 | |
| source_urlvarchar | 0% | 1 | — |
|
| row_hashvarchar | 0% | 12,606 | — |
|
- Current
20260927T025309Z-38aad7205ae0 · sha256 38aad7205ae0…
10,966 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/eccc_climate_intel/ca_climate_province_monthly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/eccc_climate_intel/ca_climate_province_monthly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/eccc_climate_intel/ca_climate_province_monthly
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260927T025309Z-38aad7205ae0 and its content hash, so readers get exactly the data you used.
Canadian Climate Anomaly Intelligence. (2026). Canadian provincial climate anomalies (monthly) [Data set, snapshot 20260927T025309Z-38aad7205ae0, sha256 38aad7205ae0]. Datazimuts. Retrieved 2026-09-27, from https://datazimuts.com/en/datasets/eccc_climate_intel/ca_climate_province_monthly?snapshot=20260927T025309Z-38aad7205ae0
@misc{dz_eccc_climate_intel_ca_climate_province_m_38aad720,
title = {{Canadian provincial climate anomalies (monthly)}},
author = {{Canadian Climate Anomaly Intelligence}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/eccc_climate_intel/ca_climate_province_monthly?snapshot=20260927T025309Z-38aad7205ae0}},
note = {Snapshot 20260927T025309Z-38aad7205ae0, sha256 38aad7205ae0dbb97cf7da537b85338205740c17fce101ad4e7a437ee1c88f9f; accessed 2026-09-27}
}Embed a table or a chart
Paste this into any page. The embed is pinned to the same snapshot, follows the reader's light or dark setting, and always shows the source, license and a link back.
<iframe src="https://datazimuts.com/embed/chart?dataset=eccc_climate_intel%2Fca_climate_province_monthly&lang=en&theme=auto&snapshot=20260927T025309Z-38aad7205ae0&x=local_date&y=year&agg=avg" title="Canadian provincial climate anomalies (monthly)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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