DOI: 10.5281/zenodo.17962930
title: DARK AR Detection Catalog (ERA5, 1979–2023)

description: This dataset provides yearly binary atmospheric-river (AR) masks derived from the ERA5 reanalysis, produced using the DARK (formerly Buffet v1.0) detection algorithm.Although originally developed with a polar (Antarctic) focus, the implementation operates globally on the full ERA5 grid.All outputs follow ARTMIP Tier-1 conventions, including variable naming, attributes, dimensions, CF metadata, and filename structure.



Method

Input field





ERA5 vertically integrated water vapor flux components:viwve (eastward) and viwvn (northward)




Data source: ERA5 reanalysis (ECMWF), typically 6-hourly fields.



Overview of the steps





Rolling seasonal threshold (98th percentile baseline)For each leap day-of-year (1–366), compute a 15-day rolling climatology of Integrated Vapor Transport (IVT) and extract the 98th percentile.Non-leap years are mapped to leap-year DOYs by shifting days ≥ 29 Feb (+1).The 98th-percentile field is precomputed from 1979–2023.




Exceedance maskA grid cell is marked 1 if the local IVT exceeds its day-of-year threshold; otherwise 0.




Area filtering (< 20 000 km²)Connected regions are identified using 8-connectivity and periodic longitude boundaries (dateline continuity).Components with total area < 20 000 km² are removed.Grid-cell areas are computed on WGS-84 using geocentric radius and local Δlat/Δlon.




Length filtering (< 2 000 km)Each connected component is skeletonized and represented as a graph.The endpoint-to-endpoint path best aligned with the principal component axis is selected, extended to the edges, and smoothed using a B-spline.Sub-grid geodesic segment lengths (WGS-84) are summed; components shorter than 2 000 km are discarded.




Output assemblyEach yearly NetCDF file contains the binary field ar_binary_tag(time, lat, lon) with values 1 = AR and 0 = no AR.





Files & Format

One NetCDF file per year:







 



ERA5.ar_tag.DARK.<freq>.<YYYYMMDD-YYYYMMDD>.nc



where <freq> is inferred from input ERA5 temporal resolution (e.g. 6hourly).



Variables








Variable
Type
Description




ar_binary_tag(time, lat, lon)
byte
1 = AR, 0 = no AR






Attributes:





description = "binary indicator of atmospheric river"




scheme = "DARK"




version = "1.0"




credits = "Developed by Victoire Buffet, Vincent Favier, and Benjamin Pohl"



Coordinates:





time — CF-compliant (minutes since <year>-01-01 00:00:00, calendar = "standard", axis = "T")




lat — degrees_north (axis = "Y")




lon — degrees_east (axis = "X")



Compression: NetCDF-4 deflate (zlib=True, complevel=1, shuffle=True); time unlimited.



Spatial / Temporal Coverage





Spatial: Global ERA5 native 0.25° × 0.25° grid.(Algorithm tuned for polar ARs but operates globally.)




Temporal: 1979 – 2023, using ERA5 6-hourly timesteps.





Parameters (defaults)





Rolling window: 15 days




Percentile: 98th




Minimum area: 20 000 km²




Minimum length: 2 000 km





Reproducibility

Inputs





ERA5 u/v flux files:vertical_integral_of_eastward_water_vapour_flux_{year}.ncvertical_integral_of_northward_water_vapour_flux_{year}.nc




Percentile baseline:percentile_98_IVT_rolling_15D_era5.nc (1979–2023)



Outputs





Yearly AR masks:ERA5.ar_tag.DARK.6hourly.YYYYMMDD-YYYYMMDD.nc



Software





Python ≥ 3.11




Key libraries: xarray, numpy, scipy, scikit-image, geopy, networkx, matplotlib




Geodesic distances computed with geopy (WGS-84)




NetCDF written CF-1.6-compliant using netCDF4





Credits

Developed by Victoire Buffet, Vincent Favier, and Benjamin Pohlat Institut des Géosciences de l’Environnement (Grenoble) and Biogéosciences (Dijon).



Keywords

Atmospheric Rivers; ERA5; ARTMIP; IVT; Antarctic; Polar Meteorology; Reanalysis; Climate Diagnostics



Related Material





ARTMIP format and Tier-1 conventions




ERA5 reanalysis documentation