# WindRIX-Style Terrain–Wind Exposure Index ERA5 (`windrix_style_2020_2024_ERA5`) — EDIS AI Agent Dataset View

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## 1. Dataset Metadata
- **Raster Name**: WindRIX-Style Terrain–Wind Exposure Index ERA5
- **Slug**: `windrix_style_2020_2024_ERA5`
- **Units**: `Unitless (0–100 index)`
- **Spatial Extent**: UL(90.0026808, -179.9963784) to LR(-90.0026808, 180.0053616)
- **Summary**: 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.
- **Included in Flagship Map Package**: `Global_ISO9223_2020_2024_LE_V4` (`GET https://secure.engineeringdirector.com/api/bundles/Global_ISO9223_2020_2024_LE_V4/point_query`)

### Color Table & Value Breaks
- `(0.39, (0.0, 0.0, 139.0))`
- `(0.7010000000000001, (0.0, 10.0, 145.1))`
- `(1.012, (0.0, 20.0, 151.2))`
- `(1.323, (0.0, 30.0, 157.3))`
- `(1.634, (0.0, 40.0, 163.4))`
- `(1.9449999999999998, (0.0, 50.0, 169.5))`
- `(2.2560000000000002, (0.0, 60.0, 175.6))`
- `(2.567, (0.0, 70.0, 181.7))`
- `(2.878, (0.0, 80.0, 187.8))`
- `(3.189, (0.0, 90.0, 193.9))`
- `(3.5, (0.0, 100.0, 200.0))`
- `(3.5, (0.0, 100.0, 200.0))`

# 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:

| Component | Weight |
|---|---|
| Terrain Ruggedness | 50% |
| Wind Speed | 30% |
| Directional Exposure | 20% |

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

---

## Interpretation Guidelines

| WindRIX Value | Interpretation |
|---|---|
| 0–20 | Minimal Exposure |
| 20–40 | Low Exposure |
| 40–60 | Moderate Exposure |
| 60–80 | High Exposure |
| 80–100 | Very High Exposure |

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

---

## Spatial Resolution

| Property | Value |
|---|---|
| Coverage | Global |
| Resolution | ~1 km |
| Coordinate System | WGS 84 |
| EPSG Code | 4326 |
| Temporal Coverage | 2020–2024 |

---

## Data Sources

Primary environmental inputs include:

- [ERA5 Reanalysis Dataset](https://cds.climate.copernicus.eu/)
- [European Centre for Medium-Range Weather Forecasts (ECMWF)](https://www.ecmwf.int/)
- [Copernicus Climate Change Service (C3S)](https://climate.copernicus.eu/)
- [GEBCO 2024 Grid](https://www.gebco.net/data-products-gridded-bathymetry-data/gebco2024-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](https://secure.engineeringdirector.com/public/map/ISO9223_Steel_2020_2024_1km)
- [ISO 9223 Zinc Corrosion Rate](https://secure.engineeringdirector.com/public/map/ISO9223_zinc_2020_2024_1km)
- [ISO 9223 Aluminum Corrosion Rate](https://secure.engineeringdirector.com/public/map/ISO9223_Aluminum_2020_2024_1km)
- [ISO 9223 Copper Corrosion Rate](https://secure.engineeringdirector.com/public/map/ISO9223_Copper_2020_2024_1km)

### Supporting Atmospheric Layers

- [Mean Chloride Deposition](https://secure.engineeringdirector.com/public/map/ISO9223_Chlorides_2020_2024_1km)
- [Mean Sulfate Deposition](https://secure.engineeringdirector.com/public/map/ISO9223_Sulfates_2020_2024_1km)
- [Mean Annual Temperature](https://secure.engineeringdirector.com/public/map/ISO9223_Temp_2020_2024_1km)
- [Mean Relative Humidity](https://secure.engineeringdirector.com/public/map/ISO9223_Humidity_2020_2024_1km)
- [Time of Wetness (TOW)](https://secure.engineeringdirector.com/public/map/tow_global_2020_2024_ERA5)

### Supporting Coastal & Terrain Layers

- [Distance to Coast](https://secure.engineeringdirector.com/public/map/Distance_to_Coast_2013_1km)
- [Bathymetry 2024 – Terrain Elevation](https://secure.engineeringdirector.com/public/map/Bathymetry_2024_1km)
- [WindRIX Terrain–Wind Exposure Index](https://secure.engineeringdirector.com/public/map/windrix_style_2020_2024_ERA5)
- [Wind Resultant Direction (0–360°)](https://secure.engineeringdirector.com/public/map/Wind_Degree_Direction_2020_2024_ERA5)
- [Wind Speed](https://secure.engineeringdirector.com/public/map/wind_speed_2020_2024_ERA5)

---

## 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

| Property | Value |
|---|---|
| Dataset Name | WindRIX-Style Terrain–Wind Exposure Index |
| Dataset Version | 1.0 |
| Publication Year | 2026 |
| Author | Joseph Mazzella |
| Organization | AtmosphericIQ LLC / Engineering Director, Inc. |
| Temporal Coverage | 2020–2024 |
| Resolution | ~1 km |
| Coordinate System | WGS 84 (EPSG:4326) |
| Value Range | 0–100 |
| Data Type | Continuous Raster |
| Index Type | Terrain–Wind Exposure Index |
| Primary Inputs | Terrain Ruggedness, Wind Speed, Wind Direction |

---

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