Metro heating and cooling degree days, weekly

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Weekly heating and cooling degree days (base 65F) for 20 North-American metros (15 US + 5 CA), 2016-2025, computed from NOAA NCEI Global Summary of the Day daily station observations at each metro's primary international airport. Ships ML-ready derived features: weekly HDD/CDD sums, heating/cooling season flags, year-on-year changes vs the same ISO week, anomalies vs the trailing 10-year same-week mean, and heat-wave / cold-snap flags at the metro's 90th percentile. Station (USAF, WBAN) identifiers from the NCEI ISD-history roster, verified 2026-09-29.

Source: Metro heating/cooling degree days, weekly (derived)
Rows: 10,046
Columns: 22
Source cadence: Yearly
Last refreshed: Sep 29, 2026
Theme: economics

Column	Type	Description
week_start	date	Monday starting the observation week. (unit: date)
metro	string	Metropolitan area name.
state_province	string	US state or Canadian province of the metro.
country	string	Country name (United States or Canada).
country_code	string	ISO 3166-1 alpha-3 country code (USA or CAN).
icao	string	ICAO code of the metro's primary international airport, where the GSOD station sits.
latitude	float	Station latitude, decimal degrees. (unit: decimal degrees)
longitude	float	Station longitude, decimal degrees. (unit: decimal degrees)
temp_avg_f	float	Weekly mean of daily mean temperatures in Fahrenheit. Daily mean = (MAX + MIN) / 2 when both present, else the GSOD TEMP mean; GSOD missing values are never imputed. (unit: degrees Fahrenheit)
days_valid	integer	Number of days in the week with a valid mean temperature (0-7). Weeks with fewer than 6 are dropped, never padded. (unit: days)
hdd_weekly	float	Derived: sum of daily heating degree days over the week, where daily HDD = max(0, 65 - daily mean temp F). Connector-defined transformation. (unit: Fahrenheit degree-days)
cdd_weekly	float	Derived: sum of daily cooling degree days over the week, where daily CDD = max(0, daily mean temp F - 65). Connector-defined transformation. (unit: Fahrenheit degree-days)
total_dd_weekly	float	Derived: hdd_weekly + cdd_weekly, the total weekly temperature-driven energy/demand load. (unit: Fahrenheit degree-days)
heating_season_flag	boolean	Derived: true when the ISO week is 40-52 or 1-13 (heating season).
cooling_season_flag	boolean	Derived: true when the ISO week is 22-38 (cooling season).
hdd_yoy_change	float	Derived: hdd_weekly minus the same metro's hdd_weekly for the same ISO week one year earlier. Null when the prior-year week is unavailable. (unit: Fahrenheit degree-days)
cdd_yoy_change	float	Derived: cdd_weekly minus the same metro's cdd_weekly for the same ISO week one year earlier. Null when the prior-year week is unavailable. (unit: Fahrenheit degree-days)
hdd_anomaly_vs_10y	float	Derived: hdd_weekly minus the trailing 10-year mean of the same ISO week for the same metro (min 5 prior years). Null when fewer than 5 prior years exist. (unit: Fahrenheit degree-days)
cdd_anomaly_vs_10y	float	Derived: cdd_weekly minus the trailing 10-year mean of the same ISO week for the same metro (min 5 prior years). Null when fewer than 5 prior years exist. (unit: Fahrenheit degree-days)
heat_wave_week	boolean	Derived: true when cdd_weekly is at or above the metro's own 90th percentile of weekly CDD over the full panel.
cold_snap_week	boolean	Derived: true when hdd_weekly is at or above the metro's own 90th percentile of weekly HDD over the full panel.
row_hash	string	Deterministic md5 of 'MDD\|<metro>\|<week_start>'; identical inputs hash identically.

First 10 sample rows — a preview, not the complete dataset.

week_start	metro	state_province	country	country_code	icao	latitude	longitude	temp_avg_f	days_valid	hdd_weekly	cdd_weekly	total_dd_weekly	heating_season_flag	cooling_season_flag	hdd_yoy_change	cdd_yoy_change	hdd_anomaly_vs_10y	cdd_anomaly_vs_10y	heat_wave_week	cold_snap_week	row_hash
2016-01-04T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	43.229	7	152.4	0	152.4	true	false	—	—	—	—	false	true	89f59f610bece0766f9c1a4a43eb753d
2016-01-11T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	43.386	7	151.3	0	151.3	true	false	—	—	—	—	false	true	27f872c2731a5f90f8425163117e1655
2016-01-18T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	36.707	7	198.05	0	198.05	true	false	—	—	—	—	false	true	bc02e14641dac674768ceb79d0b5701c
2016-01-25T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	47.336	7	123.65	0	123.65	true	false	—	—	—	—	false	true	8a18f6b8d5282d787a8027f78d8a7c5f
2016-02-01T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	52.121	7	90.15	0	90.15	true	false	—	—	—	—	false	false	34881d77343ad9c556e4a3d144cde656
2016-02-08T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	39.957	7	175.3	0	175.3	true	false	—	—	—	—	false	true	b6d8f6d6e5b6be6483e19231949b7d82
2016-02-15T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	49.264	7	110.15	0	110.15	true	false	—	—	—	—	false	false	1dee24b066649b7c4edbe877e380f6c5
2016-02-22T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	52.514	7	87.4	0	87.4	true	false	—	—	—	—	false	false	622731b10fd629394f80dfc521a96b3d
2016-02-29T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	51.521	7	94.35	0	94.35	true	false	—	—	—	—	false	false	fa3fb383b57f02f78d74376514a91334
2016-03-07T00:00:00	Atlanta	Georgia	United States	USA	KATL	33.63	-84.442	64.15	7	20	14.05	34.05	true	false	—	—	—	—	false	false	c40c62c1033d143c4acaa2f2980af774

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

cURL

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

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/metro_degree_days/metro_degree_days_weekly").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/metro_degree_days/metro_degree_days_weekly

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

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Pinned to snapshot 20260929T041824Z-4ad6e770f29a and its content hash, so readers get exactly the data you used.

APA

Metro heating/cooling degree days, weekly (derived). (2026). Metro heating and cooling degree days, weekly [Data set, snapshot 20260929T041824Z-4ad6e770f29a, sha256 4ad6e770f29a]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/en/datasets/metro_degree_days/metro_degree_days_weekly?snapshot=20260929T041824Z-4ad6e770f29a

BibTeX

@misc{dz_metro_degree_days_metro_degree_days_week_4ad6e770,
  title        = {{Metro heating and cooling degree days, weekly}},
  author       = {{Metro heating/cooling degree days, weekly (derived)}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/metro_degree_days/metro_degree_days_weekly?snapshot=20260929T041824Z-4ad6e770f29a}},
  note         = {Snapshot 20260929T041824Z-4ad6e770f29a, sha256 4ad6e770f29a5f6fe8d6fa856192afa19086737d47cac432ea7ba06bd65f3892; accessed 2026-09-30}
}

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Metro heating and cooling degree days, weekly

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