Transparent methodology, trusted data sources, and sophisticated algorithms delivering accurate climate insights for your planning needs.
Climocast combines multiple authoritative climate datasets to provide the most accurate historical weather information.
National Centers for Environmental Information provides ground-truth weather observations from thousands of stations across North America, Caribbean, and Europe.
Used for bias correction and validation of ERA5 reanalysis data
ECMWF's 5th generation reanalysis provides hourly global weather estimates through sophisticated modeling and data assimilation at 0.1° resolution (~11 km).
Complete hourly coverage, gap-filling, and consistency across all locations
National Hurricane Center's database tracks historical tropical cyclone activity with 6-hourly positions, intensity, and wind radii for comprehensive storm risk assessment.
Hurricane risk analysis for coastal and Caribbean locations
NCEI and HURDAT2 are maintained by NOAA, ensuring rigorous quality control and long-term data continuity. ERA5 is produced by ECMWF, the European Centre for Medium-Range Weather Forecasts.
All three datasets are extensively documented in scientific literature and used by researchers worldwide for climate analysis.
NCEI provides accurate point observations, ERA5 ensures complete hourly coverage, and HURDAT2 adds tropical cyclone context for risk assessment.
All datasets are freely available, allowing independent verification of our processing methods and results.
Two decades (1995-2024) provides the optimal balance between statistical significance and climate relevance.
20 years includes multiple El Niño and La Niña cycles, droughts, wet periods, and heat waves—ensuring you're not planning based on a statistical outlier.
Using only recent data ensures our statistics reflect current climate conditions rather than outdated patterns from 50+ years ago.
Post-1995 data benefits from improved weather station networks, better quality control, and consistent observation protocols.
Not all climate stations have equal data quality for the 20-year period. We assess the available observations for each station and use that information to determine the degree of bias correction to apply to the ERA5 reanalysis data.
| Tier | Data Quality | Completeness | Processing Method |
|---|---|---|---|
| Tier 1 | Excellent | ≥90% | Full bias correction with high-quality station data |
| Tier 2 | Good | 75-89% | Standard bias correction with good station data |
| Tier 3 | Fair | 50-74% | Limited bias correction with selective station data |
| Tier 4 | Poor | 25-49% | Minimal bias correction, ERA5-dominant |
| Tier 5 | Very Poor | <25% | ERA5-only (no bias correction) |
Completeness measures what percentage of the expected 20 years × 365 days = 7,300 daily observations are present in the station record. A station with 90% completeness has approximately 6,570 daily observations.
Data Quality is assessed based on completeness, data consistency, temporal coverage, and absence of suspicious patterns or gaps.
Tier Assignment is determined algorithmically during preprocessing based on both completeness percentage and quality confidence scores. Each location's tier is documented in its data confidence metadata.
How we combine information from a global atmospheric reanalysis model and ground observations to create hourly reports of typical weather conditions.
ERA5 is a global atmospheric reanalysis model that provides complete coverage of the entire planet at hourly resolution. However, because it's a model rather than direct measurements, it can have systematic errors in specific locations—especially near coasts, mountains, or urban areas where local geography affects weather.
Our solution: Use NCEI station observations as "ground truth" to calculate correction factors for ERA5 data, then apply those corrections to produce the most accurate possible hourly climate information.
For Tier 5 locations with insufficient station data (<25% completeness or <5 observations for the date), we use raw ERA5 temperatures without bias correction.
In these cases, the data confidence metadata clearly indicates "ERA5-only mode" so users understand the data source and limitations. While less precise than bias-corrected data, raw ERA5 is still valuable for general planning purposes.
Three levels of precipitation risk defined.
Measurable precipitation—enough to be detected but may not impact outdoor activities.
Enough to get noticeably wet without cover—outdoor events become uncomfortable.
Significant rainfall that will substantially impact outdoor events—equivalent to 6+ hours of steady light rain.
Our 0-100 comfort score translates complex weather conditions into a simple, actionable metric for outdoor event planning.
Combined with humidity to calculate heat index (how hot it feels).
Higher humidity increases apparent temperature and reduces evaporative cooling.
Most outdoor events (weddings, corporate gatherings, sports) occur during daylight hours when comfort matters most. We specifically analyze the noon-7PM window to provide relevant comfort metrics for event planning.
What you should know about our data and its appropriate use cases.