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This README describes GOES ABI satellite data and Python code for downloading and visualising the GOES ABI data used to study anthropogenic glaciation of supercooled liquid-water clouds downwind industrial air pollution hot spots.
We studied the glaciation of supercooled liquid-water clouds downwind of a copper smelter in Rouyn-Noranda (Latitude 48.2530°, Longitude -79.0163°), Canada and an oil refinery in Regina (Latitude 50.4849°, Longitude -104.5763°), Canada.

Additional information
Velle Toll velle.toll@ut.ee

This work is funded by the Estonian Research Council grant PRG1726.
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DATASET
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The dataset contains geographical locations and datetimes of occurrence for the events of anthropogenic glaciation of supercooled liquid-water clouds identified in GOES ABI satellite data.
Moreover, Python code used for processing GOES ABI satellite data and creating animations from GOES ABI satellite data for glaciation events are given together with the corresponding animations. 

Creators: Jorma Rahu, Piia Post, Velle Toll
Organisation: University of Tartu
Rights-holder: University of Tartu
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TERMS OF USE
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Copyright 2024 University of Tartu. 
This dataset is licensed by the rights-holder under a Creative Commons Attribution 4.0 International Licence: https://creativecommons.org/licenses/by/4.0/.
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CONTENTS
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The three different records include 
1) GOEAS_ABI_glaciation_cases.csv

Here, 28 anthropogenic glaciation events identified (as seen in GOES ABI satellite data) downwind of the copper smelter in Rouyn-Noranda and 11 anthropogenic glaciation events downwind of the oil refinery in Regina are characterized. 
The columns of data table GOEAS_ABI_glaciation_cases.csv:
location - the studied location/pollution source (Rouyn-Noranda/Regina)
dt_start - the datetimes when glaciation events were first visible 
dt_end - the datetimes when glaciation-induced cloud perturbations were no longer visible
duration - duration of visibility (how long glaciation-induced cloud perturbations were visible in GOES ABI satellite data)
dt_ice - the datetimes when ice clouds in the middle of a supercooled liquid-phase cloud deck were seen in GOES ABI satellite data (not given when ice clouds were not seen)

2) python_code_GOES_ABI_processing.zip

input start_end_dates_NORANDA.txt start_end_dates_REGINA.txt 
give start and end times to download GOES ABI satellite data

scripts $location(ROUYN-NORANDA/REGINA) 
gives Python code to download and visualise GOES ABI data 

download_goes.py uses goes2go to download GOES ABI data to a local server (https://blaylockbk.github.io/goes2go/_build/html/)

We used the Satpy Python library to create composite satellite images from GOES ABI satellite data.
plot_goes.py visualises the following:
3.9microns data | night_microphysics
natural_color | day_microphysics
plot_goes_day.py visualises the following:
cloud_phase_distinction | convection
snow | day_microphysics_abi
plot_goes_night.py visualises the following:
cloudtop | night_microphysics_abi
night_fog | dust

Shell scripts loop over time and call out Python plotting scripts and FFmpeg (https://www.ffmpeg.org/) to create animations.

3) GOEAS_ABI_animations 

naming: videos_$location(Rouyn-Noranda/Regina)*.tar.gz

animations of GOES ABI satellite data in mp4 format 
In all the animations, white pluses mark the location of the air pollution source.

$location
Rouyn-Noranda/Regina
3.9microns data | night_microphysics
natural_color | day_microphysics

$location day
Rouyn-Noranda/Regina day
cloud_phase_distinction | convection
snow | day_microphysics_abi

$location night
Rouyn-Noranda/Regina night
cloudtop | night_microphysics_abi
night_fog | dust
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METHOD and PROCESSING
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We first identified glaciation events using Terra MODIS satellite data and then analysed the temporal evolution of glaciation events for Rouyn-Noranda and Regina, Canada, using GOES ABI satellite data.
https://www.goes-r.gov/spacesegment/abi.html

We used the Satpy Python library to create composite satellite images from GOES ABI satellite data.
https://satpy.readthedocs.io/en/stable/
https://github.com/pytroll/satpy
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