Metro daily thermal-demand intelligence (NASA POWER)

Name: Metro daily thermal-demand intelligence (NASA POWER)
Creator: NASA POWER
License: https://power.larc.nasa.gov/
Keywords: weather, temperature, degree-days, daily, metros, demand-forecasting, ml-features, us

Commercial use OKAgingLicense: CC0-1.0

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Daily heating/cooling degree-day panel for the 20 North-American prediction metros (15 US + 5 CA), from keyless NASA POWER daily 2-meter air temperature (2020-01-01 -> latest POWER day, ~2-day lag). Daily HDD/CDD (base 65F), trailing 7/30-day thermal loads, same-day-of-year anomalies vs a trailing-5-year baseline, heat-wave/cold-snap flags (metro 95th percentiles), season flags, and a documented 0-100 thermal_demand_score. The current daily companion to the weekly NOAA-GSOD metro_degree_days panel (which ends Aug 2025). Joinable by (date, metro) to Shopify/Stripe/HubSpot data. Caveats: POWER is a reanalysis/model blend, not station observations; first 6 days per metro lack a 7-day window (NaN, never padded); anomaly baselines need 3+ prior same-doy years. NASA US-government data, no copyright restriction (CC0-1.0), commercial use allowed.

Source: NASA POWER
Rows: 49,220
Columns: 26
Source cadence: Daily
Last refreshed: Sep 29, 2026
Theme: economics

Column	Type	Description
date	string	Reference day, ISO date. Panel runs 2020-01-01 to the latest POWER daily day (~2-day lag). (unit: ISO date)
metro	string	Metro label (primary international airport city), e.g. 'New York'. Primary join key with date.
state_province	string	US state or Canadian province of the metro.
country	string	Canonical country name via hub.normalize.
country_code	string	ISO alpha-3 country code (USA / CAN). (unit: ISO 3166-1 alpha-3)
icao	string	ICAO code of the metro's primary international airport (the POWER point location).
latitude	float	POWER point latitude (airport coordinates). (unit: decimal degrees)
longitude	float	POWER point longitude (airport coordinates). (unit: decimal degrees)
tavg_f	float	Daily mean 2-meter air temperature from POWER T2M, converted to Fahrenheit. (unit: degrees Fahrenheit)
hdd	float	Daily heating degree-days = max(0, 65 - tavg_f). (unit: degree-days (F))
cdd	float	Daily cooling degree-days = max(0, tavg_f - 65). (unit: degree-days (F))
total_dd	float	Daily total degree-days = hdd + cdd. (unit: degree-days (F))
hdd_7d	float	Trailing 7-day heating degree-day load (min 7 valid days; NaN on the metro's first 6 days). (unit: degree-days (F))
cdd_7d	float	Trailing 7-day cooling degree-day load (min 7 valid days; NaN on the metro's first 6 days). (unit: degree-days (F))
hdd_30d	float	Trailing 30-day heating degree-day load (min 30 valid days). (unit: degree-days (F))
cdd_30d	float	Trailing 30-day cooling degree-day load (min 30 valid days). (unit: degree-days (F))
temp_anomaly_f	float	tavg_f minus the trailing-5-calendar-year mean of the same day-of-year (min 3 prior years; NaN otherwise, never imputed). (unit: degrees Fahrenheit)
hdd_anomaly_5y	float	Daily hdd minus the trailing-5-year same-day-of-year mean (min 3 prior years). (unit: degree-days (F))
cdd_anomaly_5y	float	Daily cdd minus the trailing-5-year same-day-of-year mean (min 3 prior years). (unit: degree-days (F))
heat_wave_day	integer	1 when daily cdd is at or above the metro's own 95th percentile of daily cdd over the full panel. (unit: binary)
cold_snap_day	integer	1 when daily hdd is at or above the metro's own 95th percentile of daily hdd over the full panel. (unit: binary)
heating_season_flag	integer	1 in months Oct-Mar. (unit: binary)
cooling_season_flag	integer	1 in months Jun-Aug. (unit: binary)
thermal_demand_score	float	Documented 0-100 composite: 100 * percentile rank (average method) of the metro's trailing-7-day total degree-days (hdd_7d + cdd_7d) within its own full panel history. Higher = more thermal demand than the metro usually sees. NaN on the first 6 days per metro. (unit: 0-100 score)
source	string	Upstream source behind the row ('NASA POWER daily point T2M').
row_hash	string	Deterministic 16-hex row hash of metro + date (idempotency).

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

date	metro	state_province	country	country_code	icao	latitude	longitude	tavg_f	hdd	total_dd	hdd_7d	cdd_7d	hdd_30d	cdd_30d	temp_anomaly_f	hdd_anomaly_5y	cdd_anomaly_5y	heating_season_flag	thermal_demand_score	source	row_hash
2020-01-01	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	41.846	23.154	23.154	—	—	—	—	—	—	—	1	—	NASA POWER daily point T2M	8fa6b67e8acf5b99
2020-01-02	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	45.806	19.194	19.194	—	—	—	—	—	—	—	1	—	NASA POWER daily point T2M	805002fb54bf3462
2020-01-03	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	62.276	2.724	2.724	—	—	—	—	—	—	—	1	—	NASA POWER daily point T2M	ac4adc664878c22f
2020-01-04	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	49.154	15.846	15.846	—	—	—	—	—	—	—	1	—	NASA POWER daily point T2M	666f8b76bbfa3dd3
2020-01-05	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	38.444	26.556	26.556	—	—	—	—	—	—	—	1	—	NASA POWER daily point T2M	a42ffaab1f7255ba
2020-01-06	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	45.662	19.338	19.338	—	—	—	—	—	—	—	1	—	NASA POWER daily point T2M	01ef6b4f05d75e67
2020-01-07	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	46.706	18.294	18.294	125.106	0	—	—	—	—	—	1	79.1	NASA POWER daily point T2M	1f6e7d4de9bbda57
2020-01-08	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	44.438	20.562	20.562	122.514	0	—	—	—	—	—	1	77.5	NASA POWER daily point T2M	ddb4b467af1fb59f
2020-01-09	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	47.048	17.952	17.952	121.272	0	—	—	—	—	—	1	76.5	NASA POWER daily point T2M	b6a0bb7f2081aa7c
2020-01-10	Atlanta	Georgia	—	USA	KATL	33.63	-84.442	55.94	9.06	9.06	127.608	0	—	—	—	—	—	1	80.8	NASA POWER daily point T2M	60f9a7d3feb25935

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_thermal_demand_intel/metro_daily_thermal_demand" | jq '{title, rows, columns_count, license}'

Python

import requests

ds = requests.get("https://datazimuts.com/v1/datasets/metro_thermal_demand_intel/metro_daily_thermal_demand").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_thermal_demand_intel/metro_daily_thermal_demand

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

Cite this snapshot

Pinned to snapshot 20260929T105935Z-1415892c6633 and its content hash, so readers get exactly the data you used.

APA

NASA POWER. (2026). Metro daily thermal-demand intelligence (NASA POWER) [Data set, snapshot 20260929T105935Z-1415892c6633, sha256 1415892c6633]. Datazimuts. Retrieved 2026-09-30, from https://datazimuts.com/en/datasets/metro_thermal_demand_intel/metro_daily_thermal_demand?snapshot=20260929T105935Z-1415892c6633

BibTeX

@misc{dz_metro_thermal_demand_intel_metro_daily_t_1415892c,
  title        = {{Metro daily thermal-demand intelligence (NASA POWER)}},
  author       = {{NASA POWER}},
  year         = {2026},
  publisher    = {Datazimuts},
  howpublished = {\url{https://datazimuts.com/en/datasets/metro_thermal_demand_intel/metro_daily_thermal_demand?snapshot=20260929T105935Z-1415892c6633}},
  note         = {Snapshot 20260929T105935Z-1415892c6633, sha256 1415892c66332eb0b410a7c7b3760ccc84f49d0c5bfd942a0ded2ab18a6b29da; accessed 2026-09-30}
}

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<iframe src="https://datazimuts.com/embed/chart?dataset=metro_thermal_demand_intel%2Fmetro_daily_thermal_demand&lang=en&theme=auto&snapshot=20260929T105935Z-1415892c6633&x=date&y=latitude&agg=avg" title="Metro daily thermal-demand intelligence (NASA POWER)" width="100%" height="380" style="border:0" loading="lazy"></iframe>

Metro daily thermal-demand intelligence (NASA POWER)

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