Major-city daily weather signals (Open-Meteo, 24 cities)
Value-added daily weather signals panel from the keyless Open-Meteo Archive API (ERA5 reanalysis, CC BY 4.0): one row per (city, day) over the trailing year for 24 major cities on every continent — daily temperature max/min/mean and range, precipitation, wind and gust maxima, shortwave radiation, FAO evapotranspiration, heating/cooling degree days (18 C base), temperature and precipitation anomalies, heatwave / heavy-rain / extreme-wind flags, MoM/YoY temperature changes, 30-day volatility and 3-sigma anomaly flags. The exogenous weather layer for demand, energy, retail and logistics models.
- Rows
- 8,760
- Columns
- 27
- Source cadence
- Daily
- Last refreshed
- Oct 6, 2026
- Theme
- climate
| Column | Type | Description |
|---|---|---|
| date | date | Calendar date (UTC); the daily.time values are aggregated to. |
| city_code | string | — |
| city_name | string | — |
| country | string | — |
| latitude | float | — |
| longitude | float | — |
| temp_max_c | float | Maximum 2m air temperature of the day, in °C, as published by the Open-Meteo Archive API. (unit: °C) |
| temp_min_c | float | Minimum 2m air temperature of the day, in °C, as published by the Open-Meteo Archive API. (unit: °C) |
| temp_mean_c | float | Mean 2m air temperature of the day, in °C, as published by the Open-Meteo Archive API. (unit: °C) |
| temp_range_c | float | — |
| precip_mm | float | Daily precipitation sum, in mm, as published by the Open-Meteo Archive API. (unit: mm) |
| wind_max_kmh | float | Maximum 10m wind speed of the day, in km/h, as published by the Open-Meteo Archive API. (unit: km/h) |
| wind_gusts_max_kmh | float | Maximum 10m wind gusts of the day, in km/h, as published by the Open-Meteo Archive API. (unit: km/h) |
| radiation_mj_m2 | float | Daily shortwave radiation sum, in MJ/m², as published by the Open-Meteo Archive API. (unit: MJ/m²) |
| et0_mm | float | FAO reference evapotranspiration (ET₀) of the day, in mm, as published by the Open-Meteo Archive API. (unit: mm) |
| hdd_18c | float | — |
| cdd_18c | float | — |
| temp_anomaly_30d | float | — |
| temp_mom_change | float | — |
| temp_yoy_change | float | — |
| precip_anomaly_30d | float | — |
| heatwave_flag | integer | — |
| heavy_rain_flag | integer | — |
| wind_extreme_flag | integer | — |
| volatility_30d | float | — |
| anomaly_flag | integer | — |
| row_hash | string | — |
First 10 sample rows — a preview, not the complete dataset.
| date | city_code | city_name | country | latitude | longitude | temp_max_c | temp_min_c | temp_mean_c | temp_range_c | precip_mm | wind_max_kmh | wind_gusts_max_kmh | radiation_mj_m2 | et0_mm | hdd_18c | cdd_18c | temp_anomaly_30d | temp_mom_change | temp_yoy_change | precip_anomaly_30d | heatwave_flag | heavy_rain_flag | wind_extreme_flag | volatility_30d | anomaly_flag | row_hash |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2025-10-05 | ber | Berlin | Germany | 52.52 | 13.41 | 13.9 | 8.9 | 11.3 | 5 | 2.2 | 25.7 | 56.5 | 9.3 | 1.82 | 6.7 | 0 | -2.737 | -6.3 | 0.4 | 0.71 | 0 | 0 | 0 | 3.609 | 0 | 6d976e3a9d2bbfc4 |
| 2025-10-06 | ber | Berlin | Germany | 52.52 | 13.41 | 14.9 | 9.5 | 11.9 | 5.4 | 1 | 29.3 | 65.9 | 8.03 | 1.62 | 6.1 | 0 | -1.98 | -4.7 | 2.7 | -0.52 | 0 | 0 | 0 | 3.596 | 0 | c0154a2f1108bf59 |
| 2025-10-07 | ber | Berlin | Germany | 52.52 | 13.41 | 14.9 | 8.6 | 12 | 6.3 | 1.7 | 9.6 | 18.4 | 3.11 | 0.59 | 6 | 0 | -1.733 | -4.4 | 0.8 | 0.123 | 0 | 0 | 0 | 3.58 | 0 | 6a051b9b767ab4b9 |
| 2025-10-08 | ber | Berlin | Germany | 52.52 | 13.41 | 15.8 | 12.3 | 14 | 3.5 | 3 | 11.7 | 25.6 | 3.28 | 0.63 | 4 | 0 | 0.367 | -3 | -1.4 | 1.323 | 0 | 0 | 0 | 3.527 | 0 | 0291e59c992250e2 |
| 2025-10-09 | ber | Berlin | Germany | 52.52 | 13.41 | 14.7 | 11.6 | 12.9 | 3.1 | 0.7 | 16.3 | 38.5 | 7.61 | 1.37 | 5.1 | 0 | -0.543 | -5.7 | -3.3 | -1 | 0 | 0 | 0 | 3.401 | 0 | beb885fcd3edf3a5 |
| 2025-10-10 | ber | Berlin | Germany | 52.52 | 13.41 | 14.7 | 11.6 | 13.4 | 3.1 | 1.4 | 25.6 | 59.4 | 5.19 | 1.22 | 4.6 | 0 | 0.127 | -5.1 | -1.5 | 0.05 | 0 | 0 | 0 | 3.265 | 0 | 8151957e47f63f21 |
| 2025-10-11 | ber | Berlin | Germany | 52.52 | 13.41 | 16.3 | 11.6 | 14 | 4.7 | 0.4 | 22.5 | 54 | 5.37 | 1.39 | 4 | 0 | 0.827 | -3 | 5.3 | -0.86 | 0 | 0 | 0 | 3.192 | 0 | 599cfc7c7f57443e |
| 2025-10-12 | ber | Berlin | Germany | 52.52 | 13.41 | 13.9 | 10.2 | 12.5 | 3.7 | 0.8 | 18.7 | 45.4 | 2.92 | 0.8 | 5.5 | 0 | -0.583 | -2.7 | 3.8 | -0.303 | 0 | 0 | 0 | 3.17 | 0 | 5948b8317a004ec3 |
| 2025-10-13 | ber | Berlin | Germany | 52.52 | 13.41 | 14 | 7.6 | 10.9 | 6.4 | 0.1 | 8.8 | 19.1 | 10.36 | 1.41 | 7.1 | 0 | -2.053 | -3.9 | 0.7 | -0.897 | 0 | 0 | 0 | 3.178 | 0 | 148a90ca21b6cb54 |
| 2025-10-14 | ber | Berlin | Germany | 52.52 | 13.41 | 12.7 | 6.8 | 9.9 | 5.9 | 2.3 | 13.6 | 32 | 2.16 | 0.43 | 8.1 | 0 | -2.88 | -5.2 | 0.8 | 1.257 | 0 | 0 | 0 | 3.198 | 0 | 3b7f7e4f87209947 |
- Current
20261006T183310Z-656228788b9c · sha256 656228788b9c…
8,760 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/openmeteo_city_weather_intel/major_city_weather_daily" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/openmeteo_city_weather_intel/major_city_weather_daily").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/openmeteo_city_weather_intel/major_city_weather_daily
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 20261006T183310Z-656228788b9c and its content hash, so readers get exactly the data you used.
Open-Meteo Archive (derived). (2026). Major-city daily weather signals (Open-Meteo, 24 cities) [Data set, snapshot 20261006T183310Z-656228788b9c, sha256 656228788b9c]. Datazimuts. Retrieved 2026-10-07, from https://datazimuts.com/en/datasets/openmeteo_city_weather_intel/major_city_weather_daily?snapshot=20261006T183310Z-656228788b9c
@misc{dz_openmeteo_city_weather_intel_major_city__65622878,
title = {{Major-city daily weather signals (Open-Meteo, 24 cities)}},
author = {{Open-Meteo Archive (derived)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/openmeteo_city_weather_intel/major_city_weather_daily?snapshot=20261006T183310Z-656228788b9c}},
note = {Snapshot 20261006T183310Z-656228788b9c, sha256 656228788b9c28e2d2f56ed213cc9e0304ff783c3d7ac4c519cb889fe257f83b; accessed 2026-10-07}
}Embed a table or a chart
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<iframe src="https://datazimuts.com/embed/chart?dataset=openmeteo_city_weather_intel%2Fmajor_city_weather_daily&lang=en&theme=auto&snapshot=20261006T183310Z-656228788b9c&x=date&y=latitude&agg=avg" title="Major-city daily weather signals (Open-Meteo, 24 cities)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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