Weather Hourly
Hourly weather by city worldwide from Open-Meteo.
weather_hourly — the dataset name to pass to the Obscura API.
What one row means
One hour of observed surface weather (temperature, humidity, precipitation, wind, pressure, cloud cover) for one GeoNames city (pop > 15000), fetched from the Open-Meteo ERA5 archive API. Full-fidelity hourly history; daily aggregates are sampled from the `weather_daily_sampled` VIEW rather than stored separately.
One row per (location, event_time).
Point-in-time availability
Every Obscura dataset carries available_date: the calendar day the publisher made the row
available, day-of, with no session rounding. It is the one column a backtest filters on, and it means the
same thing on every dataset in the catalog.
For weather_hourly: snapshot: available_date = synced_at::date, the day this row was actually fetched and upserted by the collector (the Open-Meteo archive API has a ~2-day publication lag, so this is the honest capture date, not the observed hour's own date).
Refresh cadence
Obscura refreshes weather_hourly every 6 hours — the most frequent scheduled job that re-collects or re-exports it. This is Obscura's own pipeline cadence, not the upstream publisher's release schedule; when a row became public is recorded per row in available_date.
Schema — 12 columns
The full public column list for weather_hourly, with the meaning of every field. The same
schema is served unauthenticated at https://api.obscura.trade/v1/catalog/weather_hourly.
| Column | Type | Description |
|---|---|---|
| location | text · not null | GeoNames city key formatted "{asciiname}, {ISO country_code}" (worldwide-unique); identifies the fixed lat/lon point this hourly series was fetched for. |
| event_time | timestamp with time zone · not null | UTC timestamp of the observed hour, parsed from the Open-Meteo archive response's `hourly.time` array. |
| latitude | double precision · not null | Fixed city-centroid latitude in decimal degrees (GeoNames cities15000.txt), constant across every row for a given location. |
| longitude | double precision · not null | Fixed city-centroid longitude in decimal degrees (GeoNames cities15000.txt), constant across every row for a given location. |
| elevation | double precision | Grid-cell elevation in meters above sea level for the ERA5 cell sampled (Open-Meteo response envelope `elevation`, e.g. 27.0); constant per location, not derivable from stored lat/lon without a DEM. |
| temp_c | double precision | 2-meter air temperature in degrees Celsius for this hour (Open-Meteo `hourly.temperature_2m`). |
| humidity_pct | double precision | 2-meter relative humidity, percent 0-100 (Open-Meteo `hourly.relative_humidity_2m`). |
| precip_mm | double precision | Total hourly precipitation in millimeters, rain + showers + snow water-equivalent (Open-Meteo `hourly.precipitation`). |
| wind_kph | double precision | 10-meter wind speed in km/h, Open-Meteo's default unit (Open-Meteo `hourly.wind_speed_10m`). |
| pressure_hpa | double precision | Surface-level (station-level, not sea-level-reduced) atmospheric pressure in hectopascals (Open-Meteo `hourly.surface_pressure`). |
| cloud_pct | double precision | Total cloud cover, percent 0-100 (Open-Meteo `hourly.cloud_cover`). |
| available_date | date | PUBLIC-availability date = synced_at::date (the day this row was fetched and upserted). DB-generated STORED column, read-only; the point-in-time column to filter/join on — NEVER the observed hour's own date. |
Access weather_hourly
Two delivery paths, one identifier. Both require an Obscura account and an active subscription; the catalog entry and the schema above are public.
import obscura
client = obscura.Client("obs_live_…")
df = client.query(
dataset="weather_hourly",
start="2024-01-01",
)Create a free account Browse all 95 datasets
Frequently asked questions
What is in the weather_hourly dataset?
Hourly weather by city worldwide from Open-Meteo. One hour of observed surface weather (temperature, humidity, precipitation, wind, pressure, cloud cover) for one GeoNames city (pop > 15000), fetched from the Open-Meteo ERA5 archive API. Full-fidelity hourly history; daily aggregates are sampled from the `weather_daily_sampled` VIEW rather than stored separately.
How do I avoid look-ahead bias with weather_hourly?
Filter on weather_hourly.available_date, the day the publisher made the row public. For this dataset that date is derived as follows — snapshot: available_date = synced_at::date, the day this row was actually fetched and upserted by the collector (the Open-Meteo archive API has a ~2-day publication lag, so this is the honest capture date, not the observed hour's own date). A query of the form WHERE available_date <= '<as-of date>' never sees a row before it existed.
In what formats can I get weather_hourly?
As a Parquet bulk export (POST https://api.obscura.trade/v1/download) or as JSON from the typed query API (POST https://api.obscura.trade/v1/query), both with dataset="weather_hourly". The column schema is public at https://api.obscura.trade/v1/catalog/weather_hourly.
How often is weather_hourly updated?
Obscura refreshes weather_hourly on a every 6 hours schedule — that is the most frequent scheduled job that re-collects or re-exports the table. It is Obscura's own pipeline cadence, not the upstream publisher's release schedule; when the publisher makes a row available is described by the availability rule above, and is recorded per row in available_date.