WindRIX-Style Terrain–Wind Exposure Index (2020–2024)

Overview

This dataset represents the global WindRIX-Style Terrain–Wind Exposure Index, a continuous environmental exposure raster derived from the combined influence of terrain ruggedness, prevailing wind speed, and directional wind exposure for the period 2020–2024.

The WindRIX index was developed to support:

• Atmospheric corrosion assessment
• Chloride deposition modeling
• Coastal exposure analysis
• Environmental severity mapping
• Atmospheric transport studies
• Machine learning applications
• Environmental risk screening

Unlike the traditional WAsP Ruggedness Index (RIX), which was designed primarily for wind energy siting, the WindRIX-Style Terrain–Wind Exposure Index provides a global-scale representation of terrain–wind interaction suitable for environmental and engineering applications.

The dataset is expressed as a continuous unitless index ranging from 0 to 100, where higher values indicate increased terrain-induced wind exposure and environmental forcing.

Units:

• Unitless Index (0–100)

Background

Wind exposure is an important environmental variable influencing atmospheric transport, marine aerosol delivery, chloride deposition, and atmospheric corrosion severity.

The WindRIX framework integrates three primary environmental drivers:

• Terrain Ruggedness
• Mean Wind Speed
• Directional Wind Exposure

By combining terrain complexity with prevailing wind characteristics, the dataset provides a physically meaningful representation of environmental exposure potential.

Higher WindRIX values generally indicate environments characterized by:

• Rugged terrain
• Elevated wind energy
• Windward exposure
• Enhanced atmospheric transport
• Increased chloride delivery potential
• Greater environmental forcing

Lower WindRIX values generally indicate:

• Sheltered terrain
• Flat landscapes
• Reduced wind exposure
• Lower atmospheric transport potential

Modeling Methodology

The WindRIX framework integrates terrain and wind datasets into a continuous environmental exposure index.

Primary inputs include:

• GEBCO 2024 Terrain Elevation Model
• ERA5 Wind Speed
• ERA5 Resultant Wind Direction

The modeling framework incorporates:

Terrain Ruggedness

Terrain Ruggedness Index (TRI) was calculated from the GEBCO elevation model using local elevation variability.

Terrain ruggedness serves as a proxy for:

• Topographic complexity
• Wind acceleration potential
• Flow channeling
• Turbulence generation
• Environmental exposure intensity

Mean Wind Speed

Mean wind speed was derived from ERA5 wind vectors using:

Wind Speed = √(u² + v²)

where:

• u = zonal wind component
• v = meridional wind component

Five-year mean wind speed was calculated for each grid cell.

Directional Wind Exposure

Terrain aspect was compared with prevailing wind direction using a cosine-based angular relationship to evaluate terrain alignment with dominant wind flow.

This component represents:

• Windward exposure
• Terrain sheltering
• Relative atmospheric forcing
• Wind-terrain interaction

Normalization

Each component was normalized to a common scale ranging from 0 to 1:

• Terrain Ruggedness (TRIₙ)
• Wind Speed (WSₙ)
• Directional Exposure (EXPₙ)

WindRIX Calculation

The final index was calculated using a weighted linear model:

The resulting values were scaled to a continuous index ranging from 0 to 100.

Interpretation Guidelines

Higher values generally indicate greater potential for atmospheric transport, environmental exposure, and chloride delivery.

Spatial Resolution

Data Sources

Primary environmental inputs include:

• ERA5 Reanalysis Dataset
• European Centre for Medium-Range Weather Forecasts (ECMWF)
• Copernicus Climate Change Service (C3S)
• GEBCO 2024 Grid

Derived environmental layers include:

• Wind Speed
• Wind Direction
• Bathymetry and Terrain Elevation
• Chloride Deposition
• Atmospheric Corrosion Layers

Intended Applications

This dataset may be used for:

• Atmospheric corrosion assessment
• ISO 9223 environmental characterization
• Chloride deposition modeling
• Coastal exposure analysis
• Environmental severity mapping
• Atmospheric transport studies
• GIS visualization
• Machine learning feature engineering
• Random Forest modeling
• Regression modeling
• Infrastructure exposure assessment
• Environmental risk screening

Related Datasets

Corrosion Layers

• ISO 9223 Steel Corrosion Rate
• ISO 9223 Zinc Corrosion Rate
• ISO 9223 Aluminum Corrosion Rate
• ISO 9223 Copper Corrosion Rate

Supporting Atmospheric Layers

• Mean Chloride Deposition
• Mean Sulfate Deposition
• Mean Annual Temperature
• Mean Relative Humidity
• Time of Wetness (TOW)

Supporting Coastal & Terrain Layers

• Distance to Coast
• Bathymetry 2024 – Terrain Elevation
• WindRIX Terrain–Wind Exposure Index
• Wind Resultant Direction (0–360°)
• Wind Speed

Attribution

Joseph Mazzella
AtmosphericIQ LLC
Engineering Director, Inc.

Dataset Citation

Mazzella, J. (2026). WindRIX-Style Terrain–Wind Exposure Index (2020–2024), Global Raster. AtmosphericIQ LLC / Engineering Director, Inc.

Supporting Dataset Citations

ERA5 Reanalysis

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., et al. (2020). The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146(730), 1999–2049.
https://doi.org/10.1002/qj.3803

Copernicus Climate Data Store

Copernicus Climate Change Service (C3S). ERA5 Hourly Data on Single Levels.
https://cds.climate.copernicus.eu/

GEBCO 2024 Grid

GEBCO Compilation Group. (2024). The GEBCO_2024 Grid — A Continuous Terrain Model of the Global Oceans and Land.
https://www.gebco.net/data-products-gridded-bathymetry-data/gebco2024-grid

GEBCO DOI

GEBCO Compilation Group. (2024). The GEBCO_2024 Grid.
https://doi.org/10.5285/1c44ce99-0a0d-5f4f-e063-7086abc0ea0f

Version Information