Helios draws on a comprehensive, globally distributed network of meteorological, satellite, and reanalysis datasets to power our climate-driven models and risk forecasts. Our system is designed to ensure high-resolution, high-frequency coverage across all major agricultural regions—providing both historical context and near real-time monitoring.
Global Climate Data Sources We Use
We incorporate data from leading national and international meteorological agencies, including:
Weather Station & Observational Networks
These sources provide sub-hourly to daily observations from on-the-ground infrastructure:
Integrated Surface Database (ISD) – Global network of weather stations reporting hourly data
MADIS – NOAA’s sensor fusion system for ASOS, AWOS, METAR, and mesonet stations
GHCN-D (Global Historical Climate Network – Daily) – Historical daily summaries from weather stations worldwide
SNOTEL – Snow telemetry data from mountainous agricultural regions
Maritime Weather Data – Buoy and ship-based weather observations
Deutscher Wetterdienst (DWD) – Germany’s national meteorological service
Integrated Mesonet Systems – High-resolution regional networks
Reanalysis & Forecast Models
These models blend satellite data, surface observations, and physical modeling to reconstruct past and current atmospheric conditions:
ERA5 – The ECMWF’s flagship reanalysis model, created by the Copernicus Climate Change Service
MERRA-2 – NASA’s Modern-Era Retrospective analysis system
NOAA GFS & HRRR – Global and high-resolution regional forecasts
ICON – High-resolution weather model by DWD
IFS & AIFS (ECMWF) – Medium- to long-range forecasting systems
ARPEGE & AROME (Météo-France) – High-resolution models for Europe and Africa
GEM (Canada), MSM & GSM (Japan), GRAPES (China), ACCESS-G (Australia) – National-level weather prediction systems
COSMO 2I & 5M (Italy’s ARPAE) – Regional forecasting for Southern Europe
MET Nordic – Data from Scandinavian national weather services
How This Data Powers Helios Forecasts
Coverage: Our climate infrastructure spans 14 million hexagons globally, providing granular coverage even in historically under-observed regions.
Frequency: We ingest data daily or sub-hourly, depending on the source, and update forecasts nightly.
Standardization: Data is normalized and integrated into predefined climate profiles, enabling consistent comparisons across time and geographies.
Anomaly Detection: These inputs power our proprietary algorithms that detect and classify events like droughts, floods, unseasonal temperature spikes, and other risks that impact crop supply and pricing.
This diverse set of sources gives Helios the ability to:
Monitor real-world crop-growing conditions at a daily and regional level
Compare current anomalies against multi-decade baselines
Power WA%R™ and pricing forecasts that reflect true environmental stress
Reduce dependency on a single country’s reporting or model bias