Canadian climate anomaly intelligence (monthly)

Name: Canadian climate anomaly intelligence (monthly)
Creator: Canadian Climate Anomaly Intelligence
License: https://eccc-msc.github.io/open-data/licence/readme_en/
Keywords: canada, climate, monthly, signals, rankings, temperature-anomaly, precipitation, anomaly-detection, degree-days

Commercial use OKFreshLicense: LicenseRef-ECCC-Data-Services-End-use-2.1.1

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The full snapshot isn't published yet — check back after the next refresh.Download sample CSV Download sample JSONSample rows only (up to 20) — not the complete dataset.

Monthly temperature and precipitation anomalies versus 1981-2010 climate normals for a curated panel of long-record Canadian climate stations, from ECCC's keyless MSC GeoMet OGC API (climate-monthly collection). Each row is one (station, month): mean/min/max temperature, the official normal, the temperature anomaly in C, total precipitation, its normal, the precipitation anomaly in %, snowfall, heating/cooling degree days, warm/cold/wet/dry extreme-month flags, station-record warmest/coldest flags, and a documented 0-100 extreme_score (0.50 |temp anomaly| + 0.30 |precip anomaly| + 0.20 station-record flag) ranked per month with a top-10 most-extreme flag. Station-months below the 25-valid-day coverage gate are dropped, never interpolated. Units: degrees C; mm; %. Caveats: station-identifier based (retired identifiers end, never spliced); ECCC revises history so re-ingests can legitimately differ; normals reference 1981-2010. ECCC Data Services End-use Licence v2.1.1 — commercial_use = yes, attribution required. Primary key: (as_of, station_id, local_date). Cadence: monthly.

Source: Canadian Climate Anomaly Intelligence
Rows: 64,942
Columns: 34
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)
station_id	string	ECCC climate identifier (e.g. 6158875). Station-identifier based: retired identifiers end, never spliced. (unit: id)
station_name	string	Station name.
province_code	string	Canadian province/territory code (e.g. ON, QC, BC).
lat	float	Station latitude (WGS84). (unit: degrees)
lon	float	Station longitude (WGS84). (unit: degrees)
country_code	string	ISO alpha-3 country code; constant 'CAN'.
local_date	string	The month the row covers (YYYY-MM, station local time). (unit: month)
year	integer	Calendar year. (unit: year)
month	integer	Calendar month (1-12). (unit: month)
mean_temp_c	float	Monthly mean temperature (ECCC monthly summary). (unit: degrees C)
normal_mean_temp_c	float	1981-2010 climate normal mean temperature for the month. (unit: degrees C)
temp_anomaly_c	float	Temperature anomaly vs the 1981-2010 normal (mean minus normal). (unit: degrees C)
min_temp_c	float	Monthly minimum temperature. (unit: degrees C)
max_temp_c	float	Monthly maximum temperature. (unit: degrees C)
total_precip_mm	float	Monthly total precipitation (null when the precipitation coverage gate fails). (unit: mm)
normal_precip_mm	float	1981-2010 climate normal total precipitation for the month. (unit: mm)
precip_anomaly_pct	float	Precipitation anomaly vs the normal, in % (null when the normal is missing/zero or the precipitation coverage gate fails). (unit: percent)
total_snowfall_cm	float	Monthly total snowfall. (unit: cm)
heating_degree_days	float	Monthly heating degree days (base 18 C, ECCC convention). (unit: degree days)
cooling_degree_days	float	Monthly cooling degree days (base 18 C, ECCC convention). (unit: degree days)
days_with_valid_mean_temp	integer	Days with valid mean temperature in the month (>= 25 required by the coverage gate). (unit: days)
days_with_valid_precip	integer	Days with valid precipitation in the month (>= 25 required for precipitation-derived fields). (unit: days)
warm_month	boolean	True when temp_anomaly_c >= +2 C.
cold_month	boolean	True when temp_anomaly_c <= -2 C.
wet_month	boolean	True when precip_anomaly_pct >= +50 %.
dry_month	boolean	True when precip_anomaly_pct <= -50 %.
is_record_warm	boolean	True when this is the station's warmest temperature anomaly in its own history window.
is_record_cold	boolean	True when this is the station's coldest temperature anomaly in its own history window.
extreme_score	float	Documented 0-100 climate-extreme score: 100 * (0.50 * clip(\|temp_anomaly_c\| / 4, 0, 1) + 0.30 * clip(\|precip_anomaly_pct\| / 100, 0, 1) + 0.20 * record_flag) — absolute across months and snapshots. (unit: score)
extreme_rank	integer	Extreme rank within the month (1 = most extreme; ties broken by \|temp_anomaly_c\| desc, station_id asc). (unit: rank)
is_top10	boolean	True for the 10 most extreme station-months per month.
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	station_id	station_name	province_code	lat	lon	country_code	local_date	year	month	mean_temp_c	normal_mean_temp_c	temp_anomaly_c	min_temp_c	max_temp_c	total_precip_mm	normal_precip_mm	precip_anomaly_pct	total_snowfall_cm	heating_degree_days	cooling_degree_days	days_with_valid_mean_temp	days_with_valid_precip	warm_month	cold_month	wet_month	dry_month	is_record_warm	is_record_cold	extreme_score	extreme_rank	is_top10	source_url	row_hash
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1911-11	1,911	11	4.533	—	—	-4.4	13.3	182	213.04	-14.57	0	404	0	30	30	false	false	false	false	false	false	4.37	3	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	8acf48ac1a2984be
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1915-08	1,915	8	17.71	—	—	7.8	31.1	0.3	24.83	-98.79	0	26.7	17.7	31	31	false	false	false	true	false	false	29.64	4	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	03eb26015ccce197
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1915-09	1,915	9	12.883	—	—	3.3	21.7	10.7	32.59	-67.17	0	153.5	0	30	30	false	false	false	true	false	false	20.15	4	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	72f6d905ae8f5690
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1915-10	1,915	10	10.423	—	—	3.3	17.2	140.9	112.76	24.96	0	234.9	0	31	31	false	false	false	false	false	false	7.49	7	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	d6c9421b2afd5352
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1915-11	1,915	11	5.527	—	—	-1.1	12.2	172	213.04	-19.26	0	374.2	0	30	30	false	false	false	false	false	false	5.78	7	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	545502cb112b8a1a
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1915-12	1,915	12	4.848	—	—	-4.4	12.2	188.2	146.78	28.22	1.3	407.7	0	31	31	false	false	false	false	false	false	8.47	4	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	eac865de2a1d35a3
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1916-01	1,916	1	-2.241	—	—	-10.6	8.9	130.4	168.1	-22.43	92.3	587	0	29	31	false	false	false	false	false	false	6.73	7	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	c5eaded4e716ee3d
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1916-02	1,916	2	3.379	—	—	-6.7	15	163.7	107.48	52.31	111.7	424	0	29	29	false	false	true	false	false	false	15.69	7	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	6cf617b82a520392
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1916-03	1,916	3	5.352	—	—	-1.7	11.7	181	89.17	102.98	0	392.1	0	31	31	false	false	true	false	false	false	30	5	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	319a8308fdb2405f
2026-08	1015105	METCHOSIN	BC	48.374	-123.561	CAN	1916-04	1,916	4	8.313	—	—	1.1	15.6	32.4	59.8	-45.82	0	290.6	0	30	30	false	false	false	false	false	false	13.75	7	true	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=8501900	5413428b05a5fd51

Profiled Sep 27, 2026 from snapshot 20260927T025305Z-46c8ce7cf4ad

Measured

Completeness: 99.8%
Rows: 64,942
Columns: 34
Columns with gaps: 5

Rows per yearyear · 1888–2026 · 139 years

18882026

Column	Missing	Distinct	Range	Distribution
as_ofvarchar	0%	1	—	2026-0864,942
station_idvarchar	0%	81	—	40134801,630 10906601,497 10365701,410
station_namevarchar	0%	80	—	INDIAN HEAD CDA1,630 BARKERVILLE1,497 QUATSINO1,410
province_codevarchar	0%	9	—	BC29,336 QC8,512 ON7,684
latdouble	0%	127	42.04 → 55.69median 49.72	1,140 outside 1st–99th percentile
londouble	0%	122	-133.06 → -53.9median -112.1	510 outside 1st–99th percentile
country_codevarchar	0%	1	—	CAN64,942
local_datevarchar	0%	1,500	—	1987-0791 1989-0191 1989-0291
yearbigint	0%	159	1,888 → 2,026median 1,991	1,098 outside 1st–99th percentile
monthbigint	0%	13	1 → 12median 6
mean_temp_cdouble	0%	23,812	-31.41 → 25.87median 7.12	1,300 outside 1st–99th percentile
normal_mean_temp_cdouble	0.69%	986	-18.86 → 22.54median 6.85	1,231 outside 1st–99th percentile
temp_anomaly_cdouble	0.69%	10,225	-20.69 → 11.9median -0.047	1,290 outside 1st–99th percentile
min_temp_cdouble	0%	654	-52 → 17median -3	1,139 outside 1st–99th percentile
max_temp_cdouble	0%	485	-18.9 → 45.5median 19.4	1,248 outside 1st–99th percentile
total_precip_mmdouble	0.6%	5,098	0 → 1,588median 71.2	1,288 outside 1st–99th percentile
normal_precip_mmdouble	0%	1,125	8.55 → 677.75median 80.57	1,214 outside 1st–99th percentile
precip_anomaly_pctdouble	0.9%	18,776	-100 → 752.03median -8.97	1,283 outside 1st–99th percentile
total_snowfall_cmdouble	4.7%	1,953	0 → 383.8median 0	618 outside 1st–99th percentile
heating_degree_daysdouble	0%	11,205	0 → 1,532median 327.3	1,299 outside 1st–99th percentile
cooling_degree_daysdouble	0%	1,592	0 → 244median 0	647 outside 1st–99th percentile
days_with_valid_mean_tempbigint	0%	7	25 → 31median 31	486 outside 1st–99th percentile
days_with_valid_precipbigint	0%	30	0 → 31median 31	587 outside 1st–99th percentile
warm_monthboolean	0%	2	—	false57,155 true7,787
cold_monthboolean	0%	2	—	false55,676 true9,266
wet_monthboolean	0%	2	—	false55,693 true9,249
dry_monthboolean	0%	2	—	false54,005 true10,937
is_record_warmboolean	0%	2	—	false64,850 true92
is_record_coldboolean	0%	2	—	false64,851 true91
extreme_scoredouble	0%	6,221	0 → 100median 26.31	1,298 outside 1st–99th percentile
extreme_rankbigint	0%	92	1 → 91median 31	436 outside 1st–99th percentile
is_top10boolean	0%	2	—	false51,063 true13,879
source_urlvarchar	0%	1	—	https://api.weather.gc.ca/collections/climate-monthly/items?f=json&limit=2000&CLIMATE_IDENTIFIER=850190064,942
row_hashvarchar	0%	61,643	—	0002933cf22ef9cf1 00034e41629c49c11 0007a53cc77f8bda1

Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).

cURL

curl "https://datazimuts.com/v1/datasets/eccc_climate_intel/ca_climate_anomaly_monthly" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/eccc_climate_intel/ca_climate_anomaly_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_anomaly_monthly

Tip: fetch /llms.txt for the full machine-readable catalog.

Cite this snapshot

Pinned to snapshot 20260927T025305Z-46c8ce7cf4ad and its content hash, so readers get exactly the data you used.

APA

Canadian Climate Anomaly Intelligence. (2026). Canadian climate anomaly intelligence (monthly) [Data set, snapshot 20260927T025305Z-46c8ce7cf4ad, sha256 46c8ce7cf4ad]. Datazimuts. Retrieved 2026-09-27, from https://datazimuts.com/en/datasets/eccc_climate_intel/ca_climate_anomaly_monthly?snapshot=20260927T025305Z-46c8ce7cf4ad

BibTeX

@misc{dz_eccc_climate_intel_ca_climate_anomaly_mo_46c8ce7c,
  title        = {{Canadian climate anomaly intelligence (monthly)}},
  author       = {{Canadian Climate Anomaly Intelligence}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/eccc_climate_intel/ca_climate_anomaly_monthly?snapshot=20260927T025305Z-46c8ce7cf4ad}},
  note         = {Snapshot 20260927T025305Z-46c8ce7cf4ad, sha256 46c8ce7cf4ad44ec9e0e9924168e9713cfcac2e40b8cf4a1f23a16754e55d9ad; accessed 2026-09-27}
}

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Canadian climate anomaly intelligence (monthly)

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