Probabilistic tropical cyclone model
Example: Raster return period maps showing tropical cyclone wind speeds using Generalized Extreme Value (GEV) statistical analysis.
Step-by-step guidance
1. Dataset-level metadata
Select the following values when describing your dataset:
Risk data type:
hazardTitle: “Probabilistic tropical cyclone wind hazard maps for [region]”
Description: Brief description of the modeling approach and GEV analysis methodology
Publisher: Organization or research institution that produced the model
License: Appropriate license
2. Resources
Add resources for each return period map:
Format:
geotiffornetcdfSpatial resolution: Resolution in meters or degrees (e.g., 1000m, 0.01 degrees)
Coordinate reference system:
EPSG:4326or appropriate projected CRS
You may have multiple resources for different return periods (e.g., 10-year, 50-year, 100-year, 500-year).
3. Hazard metadata
Under the Hazard section:
Event sets
Analysis type:
probabilisticCalculation method:
simulatedorstatisticalEvent count: Number of return period scenarios included
Occurrence range: Range description (e.g., “1/10 to 1/500 years”)
Hazards (within the event set)
Hazard type:
windProcesses:
tropical_cycloneIntensity measure:
v_ect(3s):kph(3-second gust wind speed in km/h) orv_ect(1m):mph(1-minute sustained wind in mph)
4. Statistical analysis
Add information about the extreme value analysis:
Statistical method: Select
GEV(Generalized Extreme Value)Return periods: List the return periods available (e.g., 10, 25, 50, 100, 250, 500 years)
5. Spatial coverage
Define the geographic extent:
Scale:
nationalorregionalCountries: Select applicable ISO 3166-1 alpha-3 country codes
Bounding box: Specify coordinates of the model domain
Key considerations
Each raster file typically represents one return period
Ensure intensity measures are clearly specified with units
GEV analysis parameters (location, scale, shape) may be documented in additional details