Dataset of manually identified contrails in GOES ABI and VIIRS satellite imagery

1 Dataset of manually identified contrails in GOES ABI and VIIRS satellite imagery Paper: The findings from this data are presented in Euchenhofer, M. V., et al. Contrail observation limitations using geostationary satellites. Manuscript under review, Geophysical Research Letters, 2025. Authors: Marlene V. Euchenhofer1,*, Prashanth Prakash1, Sydney A. Parke1,*, Sebastian D. Eastham2, Ian Waitz1 1 Department of Aeronautics and Astronautics, Massachusetts Institute of Technology, Cambridge, MA, USA. 2 Department of Aeronautics, Imperial College London, London, UK. * Authors contributing to curation of dataset. Overview: This dataset includes the investigated false-color images (subdir. false_color_images), the generated contrail shapefiles as labelled in each image (subdir. contrail_labels), the derived binary masks showing all “contrail pixels” in an image (subdir. contrail_masks), and derived quantities (see second table below) grouped by images for each individual contrail label (subdir. contrail_geometric_properties). Description: A dataset of manually labelled contrails identified in respective infrared false-color (“ash”) imagery from GOES-16 ABI Advanced Baseline Imager, 2 km spatial resolution at nadir) and VIIRS (Visible Infrared Imaging Radiometer Suite, 750m spatial resolution at nadir) onboard different LEO satellites (SUOMI-NPP, NOAA-20, NOAA-21). The satellite data for the GOES-ABI imagery has been downloaded from Amazon Web Services (AWS , https://noaa-goes16.s3.amazonaws.com/index.html#ABI-L2-MCMIPC/). The data used is the Level 2 Cloud and Moisture Imagery product MCMIP for the CONUS region, more specifically the channels 11, 14, and 15. The data is regridded to a regular 0.02°x0.02° degree grid. 2 NOAA data is not copyrighted and not restricted with regards to use or redistribution (https://registry.opendata.aws/collab/noaa/). The satellite data for the VIIRS imagery has been downloaded from the NASA Earthdata archive (https://www.earthdata.nasa.gov/), where the data is product is provided on a regular lat-lon grid of about 500 m resolution, in form of two NetCDF (.nc) files from which a GeoTIFF raster image was generated using the polar2grid python package (version 3.0.2), using the following command: polar2grid -r viirs_l1b -w geotiff -p ash -f *.nc NASA data is not copyrighted and not restricted with regards to use or redistribution (https://www.earthdata.nasa.gov/engage/open-data-services-software-policies/data-useguidance). Example format of dataset: The dataset consists of 1,667 and 7,731 individually identified contrails in ABI and VIIRS false-color imagery of twelve scenes, respectively. The false-color images are provided as GeoTIFF rasters. Labels were generated by two trained individuals as shapefile layer polygons using the open-source geographic information system QGIS Quantum geographic information system). For each scene there is a binary mask on the native image grid that highlights all identified contrail pixels and is provided in form of another GeoTIFF. All of this data can be opened and viewed using GS software. Additionally, parquet files that describe the geometry of each contrail label, including derived quantities, are provided and can be read using the geopandas package. Contrail labels and contrail geometries are grouped by the 24 images (with two images capturing the same scene but from different imagers) in which they were identified and stored as shapefiles including supporting files. Additional information on the investigated scenes can be found in the Supplementary Information to the above-mentioned paper. Files and variables: All files exist for each scene described by a time string in the following format: time_str format: YYYYY-mm-ddTHHMM 3 File name Description clipped_goes_abi_image_{time_str}.tif GOES ABI false-color image on regular latitudelongitude grid clipped_viirs_image_{time_str}.tif VIIRS false-color image on regular latitudelongitude grid contrail_labels_w_ids_goes_abi_{time_str}.dbf GOES ABI contrail labels in attribute format contrail_labels_w_ids_goes_abi_{time_str}.prj Projection description of GOES ABI contrail labels contrail_labels_w_ids_goes_abi_{time_str}.shp GOES ABI contrail labels in shape format (actual geometry) contrail_labels_w_ids_goes_abi_{time_str}.shx GOES ABI contrail labels in shape index format contrail_labels_w_ids_viirs_{time_str}.dbf VIIRS contrail labels in attribute format contrail_labels_w_ids_viirs_{time_str}.prj Projection description of VIIRS contrail labels contrail_labels_w_ids_viirs_{time_str}.shp VIIRS contrail labels in shape format (actual geometry) contrail_labels_w_ids_viirs_{time_str}.shx VIIRS contrail labels in shape index format mask_clipped_alpha_goes_abi_{time_str}.tif GOES ABI binary contrail mask mask_clipped_alpha_viirs_{time_str}.tif VIIRS binary contrail mask contrails_geometric_properties_goes_abi_{time_str}.parquet ABI contrail geometries and derived quantities contrails_geometric_properties_viirs_{time_str}.parquet VIIRS contrail geometries and derived quantities 4 The following table describes the variables in the parquet files that contain the contrail geometries and derived quantities. Variable name Description id Contrail identifier outlining scene id (1 through 12), imager type (A or V), and number of contrail in image geometry Polygon describing outline of contrail centerline Linear approximation of contrail length Distance between endpoints of centerline area Area covered by contrail polygon effective width Approximated width of contrail, derived from area and length area (downsampled) Area covered by downsampled contrail (only defined for VIIRS contrails) effective width (downsampled) Approximated width of downsampled contrail, derived from area (downsampled) and length (only defined for VIIRS contrails) Grants/funding: This research was partially funded by the U.S. Federal Aviation Administration Office of Environment and Energy through ASCENT, the FAA Center of Excellence for Alternative Jet Fuels and the Environment, Project 78 through FAA Award Number 13-C-AJFE-MIT under the supervision of Kenisha V. Ford and Nicole Didyk-Wells. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the FAA.