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Industry use case
Researchers
The provenance trail your methods section needs.
Academic and applied researchers use PastClimate's ECMWF ERA5-based normals as a documented, citation-ready baseline: a fixed 0.25° grid, full processing provenance, and dated extreme-value records — without re-deriving climatology from raw reanalysis files yourself.
How PastClimate helps
Documented provenance
Every figure traces to a model version, 0.25° grid resolution and processing lineage — the detail a methods section or data-availability statement asks for.
Climatological baselines
Monthly and day-of-year normals, plus dated extreme-value records, computed once and returned identically on every query.
Reproducible citation
A formatted citation block ties your numbers to an exact dataset version, so a co-author or reviewer can trace them back.
Cross-region comparison
One global reanalysis source and one grid convention, so comparing countries isn't confounded by mismatched national datasets.
The report
Research-Grade Normals & Provenance Pack
Academic researchers, grad students and applied scientists who need a documented historical-weather baseline for a study.
Sample report snapshot
Research-Grade Normals & Provenance Pack
Real data for Sydney, Australia · 10 years on file
10
Years of continuous hourly record
18.5°C
Annual mean temperature
134.2mm
Wettest day on record
on 2020-02-09
1697 kWh/m²
Annual solar irradiance
In your report
- Monthly and day-of-year climatological normals (10-20 years, ERA5 reanalysis, 0.25° grid) via API, for baseline comparisons
- Dated extreme-value records (hottest, coldest, wettest, windiest day) for citing local extremes with an exact occurrence date
- A provenance document: source reanalysis dataset, grid resolution, model version, processing steps
- Single-date daily/hourly CSV or API pulls, and a citation block formatted for a references list
Coming soon
- Bulk multi-year raw daily/hourly series export (today's API is single-date range-GETs, not a bulk pull)
- Batch export across many locations in a single API call
- Formal uncertainty/bias-correction documentation against station observations
Curated for researchers
Paid features on PastClimate most teams in this industry reach for first.
Climate trends
Multi-year warming/cooling trend for a city.
proWeather anomalies
How this year compares to the historical baseline.
proCompare cities
Side-by-side monthly normals for two cities.
pro