Historical Weather API
Access high-resolution historical weather data — cleaned, gap-filled, and sourced from weather stations, satellite and radar imagery, and reanalysis datasets including the ERA5.
The Historical Weather API allows you to quickly retrieve accurate, high resolution historical weather data for any location in the world. Our curated weather data is backed by over 120,000 weather stations as well as high resolution gridded weather datasets such as the ERA-5 re-analysis, and global satellite / doppler radar. Data retrieved from our API is gap-free (minimal missing data) due to its application of advanced machine learning, and statistical backfilling techniques.
Use daily, hourly, or sub-hourly endpoints based on your temporal resolution requirements.
- Gap-filled and quality-controlled historical data.
- Daily, hourly, and 15-minute interval variants.
- Designed for analytics, training, and validation workloads.
Frequently Asked Questions
What data sources are used in the Historical Weather API?
Historical weather responses are built from a multi-source dataset that can include station observations, RTMA, radar, satellite precipitation estimates, ERA5, CAMS, GHCN, and other global sources. The exact mix depends on location, time, and source availability.
Read help articleWhy does historical data sometimes change?
Historical records can be revised as higher-quality source data arrives after the first response. We recommend checking `revision_status` and `revision_version`, and retrieving updated data if your analysis requires research-quality values. For most users, "interim" data is adequate.
Read help articleHow does Weatherbit combine multiple historical data sources?
We prefer nearby ground-truth station data when it is available and high quality, then blend in other datasets to improve spatial completeness and reduce gaps. As station distance or quality changes, the source selection can shift accordingly.
Read help articleWhat spatial resolution should I expect from historical data?
Historical weather coverage typically ranges from about 1 to 13 km, depending on nearby stations and the source mix available for that location.
Read help articleWhen is data valid, and how are accumulated values computed?
Unless a field is documented otherwise, values are valid at the timestamp shown in the response. Accumulated fields such as precipitation and snowfall represent the aggregate for the interval from that timestamp, to the next timestamp. The same applies to averages, max/mins, etc.
Read help articleWhat does the `solar_rad` field represent?
The solar radiation field is an estimated surface solar flux value that accounts for cloud cover, surface albedo, and atmospheric effects. Alternatively, GHI/DNI/DHI values are clear-sky values which do not account for these.
Read help articleWhy do large historical requests need to be broken into smaller calls?
Historical API access is designed around chunked retrieval, so larger time ranges should be split into smaller windows such as monthly requests. This is expected behavior and is how bulk retrieval is meant to be handled.
Read help articleAvailable Fields
| Field | Granularity | Sources |
|---|---|---|
| Temperature | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Apparent temperature | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Dew point | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Relative humidity | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Sea level pressure | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Station pressure | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Wind speed | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Wind direction | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Wind gust | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Visibility | hourly, subhourly | RTMA, stations, ERA5 |
| Precipitation accumulation | daily, hourly | stations, IMERG, MRMS, ERA5 |
| Precipitation rate | subhourly | stations, IMERG, MRMS, ERA5 |
| Snowfall accumulation | daily, hourly | RTMA, stations, ERA5 |
| Snowfall rate | subhourly | RTMA, stations, ERA5 |
| Snow depth | daily | RTMA, stations, ERA5 |
| Cloud cover | daily, hourly, subhourly | stations, satellite, ERA5 |
| Weather conditions | hourly, subhourly | RTMA, stations, ERA5 |
| UV index | daily, hourly, subhourly | RTMA, stations, ERA5 |
| Solar radiation | daily, hourly, subhourly | RTMA, stations, ERA5 |
| GHI / DNI / DHI | daily, hourly, subhourly | RTMA, stations, ERA5 |
Location Retrieval Methods
- Latitude / longitude
- City name
- Weather station ID
- Airport ICAO code
- Postal (zip) code
Advantages
Advanced Historical Precipitation: Historical rain and snowfall fields are derived from radar, multi-sensor satellite, and rain gauge datasets.
Augmented Weather Station Data: Combines station observations with high-resolution reanalysis and satellite-derived fields for remote or sparse-coverage regions.
Pinpoint Accuracy: Average spatial resolution is typically 1-13 KM depending on region.
Sub-Hourly, Hourly, and Daily Data: Historical weather is available at 15-minute, hourly, and daily intervals over long time ranges.
Gap-Free Data for AI/ML: Backfilling and quality-control methods target near-complete data coverage for model development and validation.
Available APIs
- Daily Historical API: backfilled daily observations with broad field coverage, including min/max temperature, precipitation, snow depth/snowfall, UV, and solar metrics.
- Hourly Historical API: detailed hourly time series for backtesting and analytics, including temperature, precipitation, snowfall estimate, UV, conditions, and wind fields.
- Sub-Hourly Historical API: 15-minute interval history for event-level analysis with high temporal granularity.
- Historical Lightning API: point-based lightning observations for event investigations and safety analytics.
- Climate Normals API: 30-year climate averages for long-term weather context.