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

Usage commercial OKÀ jourLicence: LicenseRef-ECCC-Data-Services-End-use-2.1.1

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Le jeu complet n’est pas encore publié — revenez après la prochaine actualisation.Télécharger l'exemple CSV Télécharger l'exemple JSONLignes d’exemple seulement (jusqu’à 20) — pas le jeu de données complet.

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.

Les titres et les descriptions proviennent des sources de données, en anglais.

Source: Canadian Climate Anomaly Intelligence
Lignes: 64 942
Colonnes: 34
Cadence de la source: Mensuelle
Dernière actualisation: 27 sept. 2026
Thème: environment

Colonne	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)

10 premières lignes d’exemple — un aperçu, pas le jeu de données complet.

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

Profilé le 27 sept. 2026 à partir de l’instantané 20260927T025305Z-46c8ce7cf4ad

Mesuré

Complétude: 99,8 %
Lignes: 64 942
Colonnes: 34
Colonnes incomplètes: 5

Lignes par annéeyear · 1888–2026 · 139 ans

18882026

Colonne	Manquant	Distinctes	Plage	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 → 55,69médiane 49,72	1 140 hors du 1er–99e centile
londouble	0 %	122	-133,06 → -53,9médiane -112,1	510 hors du 1er–99e centile
country_codevarchar	0 %	1	—	CAN64 942
local_datevarchar	0 %	1 500	—	1987-0791 1989-0191 1989-0291
yearbigint	0 %	159	1 888 → 2 026médiane 1 991	1 098 hors du 1er–99e centile
monthbigint	0 %	13	1 → 12médiane 6
mean_temp_cdouble	0 %	23 812	-31,41 → 25,87médiane 7,12	1 300 hors du 1er–99e centile
normal_mean_temp_cdouble	0,69 %	986	-18,86 → 22,54médiane 6,85	1 231 hors du 1er–99e centile
temp_anomaly_cdouble	0,69 %	10 225	-20,69 → 11,9médiane -0,047	1 290 hors du 1er–99e centile
min_temp_cdouble	0 %	654	-52 → 17médiane -3	1 139 hors du 1er–99e centile
max_temp_cdouble	0 %	485	-18,9 → 45,5médiane 19,4	1 248 hors du 1er–99e centile
total_precip_mmdouble	0,6 %	5 098	0 → 1 588médiane 71,2	1 288 hors du 1er–99e centile
normal_precip_mmdouble	0 %	1 125	8,55 → 677,75médiane 80,57	1 214 hors du 1er–99e centile
precip_anomaly_pctdouble	0,9 %	18 776	-100 → 752,03médiane -8,97	1 283 hors du 1er–99e centile
total_snowfall_cmdouble	4,7 %	1 953	0 → 383,8médiane 0	618 hors du 1er–99e centile
heating_degree_daysdouble	0 %	11 205	0 → 1 532médiane 327,3	1 299 hors du 1er–99e centile
cooling_degree_daysdouble	0 %	1 592	0 → 244médiane 0	647 hors du 1er–99e centile
days_with_valid_mean_tempbigint	0 %	7	25 → 31médiane 31	486 hors du 1er–99e centile
days_with_valid_precipbigint	0 %	30	0 → 31médiane 31	587 hors du 1er–99e centile
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 → 100médiane 26,31	1 298 hors du 1er–99e centile
extreme_rankbigint	0 %	92	1 → 91médiane 31	436 hors du 1er–99e centile
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

Dirigez n’importe quel LLM vers le point d’accès des métadonnées — la documentation ci-dessus est aussi lisible par machine (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)

Point d’accès API : https://datazimuts.com/v1/datasets/eccc_climate_intel/ca_climate_anomaly_monthly

Astuce : récupérez /llms.txt pour le catalogue complet lisible par machine.

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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/fr/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/fr/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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