Mean Annual Time of Wetness (TOW) (2020–2024)

Overview

This dataset represents the global mean annual Time of Wetness (TOW) derived from hourly ERA5 reanalysis data for the period 2020–2024.

Time of Wetness is one of the most important environmental variables influencing:

• Atmospheric corrosion
• Electrolyte formation
• Moisture persistence
• Corrosion cell activity
• Chloride retention
• Material durability

The raster represents estimated long-term mean annual wetness conditions at approximately 1 km spatial resolution.

Units:

• Hours per year (hr/year)

Background

Time of Wetness (TOW) is a core environmental parameter within the ISO 9223 atmospheric corrosivity framework and represents the cumulative duration during which environmental conditions are favorable for corrosion processes.

TOW is directly associated with:

• Surface moisture persistence
• Electrolyte formation
• Atmospheric conductivity
• Corrosion initiation
• Corrosion propagation
• Atmospheric corrosivity classification

ISO 9223 defines Time of Wetness as the cumulative duration during which:

• Relative Humidity (RH) > 80%
• Air Temperature (T) > 0°C

Higher TOW values generally indicate increased atmospheric corrosion potential, particularly when combined with elevated chloride deposition, sulfate deposition, and pollutant exposure.

This dataset was developed to provide global TOW estimates suitable for corrosion engineering, environmental modeling, and GIS-based exposure assessment.

Modeling Methodology

The TOW framework utilizes hourly ERA5 climate reanalysis data to evaluate wetness conditions at each grid cell.

Primary inputs include:

• ERA5 2-meter air temperature (t2m)
• ERA5 2-meter dew point temperature (d2m)

The modeling framework incorporates:

Relative Humidity Calculation

Relative humidity was calculated using the Magnus equation from hourly temperature and dew point temperature observations.

Wetness Criteria

An hour was classified as "wet" when:

• Relative Humidity > 80%
• Air Temperature > 0°C

Annual Aggregation

Hourly wetness occurrences were summed for each year:

• 2020
• 2021
• 2022
• 2023
• 2024

Multi-Year Averaging

The final raster represents the mean annual Time of Wetness calculated from the five-year average of annual TOW values.

The resulting framework provides globally consistent wetness estimates suitable for atmospheric corrosion and environmental exposure applications.

Interpretation Guidelines

Higher TOW values generally indicate increased atmospheric corrosion potential due to longer periods of electrolyte persistence on exposed surfaces.

Spatial Resolution

Data Sources

Primary environmental inputs include:

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

Derived environmental layers include:

• Temperature
• Relative Humidity
• Atmospheric Corrosion Layers
• Environmental Exposure Layers

Intended Applications

This dataset may be used for:

• Atmospheric corrosion assessment
• ISO 9223 modeling
• Corrosion risk screening
• Materials durability studies
• Infrastructure asset management
• Environmental exposure analysis
• Climate-based engineering assessments
• GIS visualization
• Enterprise API workflows

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

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). Mean Annual Time of Wetness (TOW), 2020–2024 (derived from ERA5 hourly reanalysis data). 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/

ECMWF

European Centre for Medium-Range Weather Forecasts (ECMWF). ERA5 Reanalysis Dataset.
https://www.ecmwf.int/

ISO 9223 Standard

ISO 9223:2012. Corrosion of metals and alloys — Corrosivity of atmospheres — Classification, determination and estimation.
https://www.iso.org/standard/53499.html

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