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Data Sources

Riskwolf platform uses multiple weather data types based on the suitability of use-case to provide desired precision and minimal basis risk:

  • Gridded Data: Gridded data refers to weather information that is organized in a grid format, with regularly spaced data points across a geographic area. This data is typically obtained through advanced numerical weather prediction models that divide the region into grid cells and provide weather variables for each cell. Gridded data offers a comprehensive view of weather conditions across a large area, allowing for detailed analysis and forecasting. It is commonly used in weather modeling, climate studies, and risk assessment.
  • Weather Station Data: Weather station data is collected from ground-based weather stations that are strategically located to monitor local weather conditions. These stations measure various weather variables such as temperature, precipitation, wind speed, humidity, and air pressure. Weather station data provides detailed, localized information and is essential for day-to-day weather monitoring and forecasting. It is widely used in agriculture, aviation, and meteorological research.
  • Satellite Data: Satellite data involves observations of the Earth's atmosphere, cloud cover, and surface conditions from space-based satellites. These satellites capture images and collect data using various sensors, including visible, infrared, and microwave sensors. Satellite data provides a wide-scale perspective of weather patterns, cloud cover, and atmospheric conditions over large areas. It is particularly useful for monitoring tropical cyclones, cloud tracking, and studying long-term climate patterns.
  • Reanalysis Data: Reanalysis data combines historical weather observations from various sources, including weather stations, satellites, buoys, and other data collection platforms. These observations are assimilated into numerical weather models to create a comprehensive and consistent dataset spanning several decades. Reanalysis data allows for a detailed understanding of past weather patterns, climate variability, and long-term trends. It is valuable for climate research, trend analysis, and studying the impacts of climate change.

Available Datasets

The following table summarizes key datasets available for parametric insurance design:

Risk Type Data Source Provider Frequency Data Latency Geospatial Resolution Variables Status Data exploration Pricing Monitoring Documentation
Weather ERA5-Land ECMWF via Copernicus CDS Hourly (aggregated to daily) ~7 days 0.1° (9 km) Daily precipitation, min/max temperature, temperature fluctuation, snowfall Active ✅ ✅ ✅ Details
Weather IFS - Forecast ECMWF Twice daily (00Z/12Z) Updated every 12 hours 0.25° (25 km) 3-hour precipitation forecasts, 3-hour temperature forecasts Active ✅ Details
Weather IMD Gridded Rainfall India Meteorological Dept. Daily ~3 days 0.25° (25 km) Daily rainfall Active ✅ ✅ ✅ Details
Weather IMD Gridded Temperature India Meteorological Dept. Daily ~3 days 0.5° (50 km) Daily min/max temperature Active ✅ ✅ ✅ Details
Weather CHIRPS Climate Hazards Center Daily ~3 weeks 0.05° (5 km) Daily precipitation Active ✅ ✅ ✅ Details
Tropical Storm IBTrACS NOAA Event-based / Monthly 2-5 days post-event Storm track data Maximum 6-hour wind speeds Active ✅ ✅ ✅ Details
Disaster Events GDACS Copernicus & UN OCHA Event-based Real-time to 4 days Multi-hazard events Multi-hazard events (storms, earthquakes, floods, wildfires, droughts, volcanoes) Active ✅ Details
Earthquake USGS EHP USGS Real-time/Daily Minutes to 1 day Event-based Earthquake events, peak ground acceleration, magnitude Not Active ✅ Details
Wildfire NIFC WFIGS National Interagency Fire Center Real-time Minutes to hours Event-based Wildfire perimeters Not Active ✅ Details
Severe Weather NOAA SPC NOAA Storm Prediction Center Real-time/Daily Minutes to hours Event-based Live events (tornado, hail, wind), forecast probabilities, categorical forecasts Not Active ✅ Details

Planned Weather & Climate Data Sources

The following data sources are planned for future implementation:

Risk Type Data Source Provider Key Features Status
Weather IMERG NASA High-resolution satellite precipitation Planned
Weather BOM SILO Australian Bureau of Meteorology Australia-specific climate data Planned
Weather MERRA-2 NASA Global reanalysis with aerosol data Planned

Administrative Boundary Sources

Risk Type Data Source Provider Key Features Status Documentation
Geographic Reference GADM Database of Global Administrative Areas Administrative levels 0-5, global coverage Active Available via Data Extraction System
Geographic Reference GeoBoundaries Open-source boundaries project Open-source administrative boundaries Active Available via Data Extraction System

Data Integration & Processing

For information about how these data sources are collected, processed, and integrated into Riskwolf's platform, see:

For detailed technical specifications of individual data sources, refer to the documentation links in the tables above.