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IFS - Forecast Data

Overview

The Integrated Forecasting System (IFS) is the global numerical weather prediction model operated by the European Centre for Medium-Range Weather Forecasts (ECMWF). It provides high-quality weather forecasts up to 15 days ahead and is considered one of the most accurate global forecast systems available.

Data Specifications

  • Provider: ECMWF
  • Frequency: Twice daily (00Z and 12Z runs)
  • Data Latency: Updated every 12 hours
  • Geospatial Resolution: 0.25° (approximately 25 km) for public data; higher resolutions available for member states
  • Forecast Range: Up to 15 days for medium-range; extended to 46 days for monthly forecasts
  • Data Format: GRIB, NetCDF
  • Coverage: Global
  • Ensemble Members: 51 ensemble members (1 control + 50 perturbed)

Variables

Onboarded Variables

The following forecast variables are currently implemented in Riskwolf's data processing pipeline:

Variable Units Description
3-hour precipitation forecasts mm Accumulated precipitation over 3-hour intervals
3-hour temperature forecasts °C 2-meter temperature at 3-hour intervals

Available Variables

Additional forecast variables that can be onboarded from IFS:

  • Wind speed and direction (10-meter and multiple atmospheric levels)
  • Relative and specific humidity
  • Cloud cover (total, high/medium/low levels)
  • Surface pressure and mean sea level pressure
  • Solar radiation (shortwave and longwave)
  • Soil temperature and moisture content
  • Snow cover and snow depth
  • Precipitation type (rain, snow, mixed)
  • Wave height and direction (from coupled ocean model)
  • Geopotential height (multiple pressure levels)
  • Vertical velocity and vorticity
  • Convective available potential energy (CAPE)
  • Wind gusts and surface stress

Key Features

  • State-of-the-art data assimilation system
  • Combined deterministic and ensemble prediction system
  • High performance computing infrastructure
  • Integration of atmospheric, land, ocean and wave models
  • Continuous development and improvement cycle

Use in Parametric Insurance

IFS forecast data is valuable for:

  • Forward-looking risk assessments
  • Early warning systems for weather-related events
  • Proactive risk management
  • Forecast-based parametric trigger mechanisms
  • Pre-emptive claim processing
  • Dynamic pricing models

Data Access

The data is accessible through the ECMWF API, Copernicus Climate Data Store, or through authorized data service providers. Certain datasets are freely available for research and commercial use.

Official Source: ECMWF Open Data

Link verified: ✅ Active (HTTP 200) - Last checked: 2025-09-24