GOES-R ABI: full-disk, CONUS, mesoscale

The GOES-R series (GOES-16, 17, 18, 19) is NOAA's flagship geostationary weather constellation. From 35,786 km altitude over the equator, each satellite stares continuously at one hemisphere of Earth, producing the highest-cadence operational Earth imagery available to the public — including the 30-second mesoscale refresh that LaunchDetect uses for real-time launch detection.

The GOES-R fleet

The Americas + Atlantic are covered by GOES-19 (East); the Pacific + western US + Hawaiʻi by GOES-18 (West). Combined, they cover from longitude ~160°E to ~10°W. Outside that range, the geometry is too oblique to be useful — that's where JMA Himawari-9 takes over (East Asia and Western Pacific).

The ABI sensor

The Advanced Baseline Imager (ABI) is the primary instrument on every GOES-R satellite. It has 16 spectral bands:

• Bands 1–2 (visible, 0.47 and 0.64 µm) — for clouds, daytime imagery. Band 2 is the "red" channel used in true-color composites.
• Band 3 (veggie, 0.86 µm) — vegetation and aerosol.
• Bands 4–6 (cirrus + SWIR, 1.37–2.24 µm) — thin cirrus, cloud-particle size, snow/ice discrimination.
• Band 7 (shortwave window, 3.9 µm) — the workhorse for thermal hotspot detection. Sensitive to fires, plumes, gas flares, hot industrial sources. The band LaunchDetect uses.
• Bands 8–10 (water vapor, 6.2, 6.9, 7.3 µm) — upper, mid, lower troposphere water vapor.
• Bands 11–13 (longwave window, 8.4, 9.6, 10.3 µm) — cloud-top phase, ozone, "clean" thermal IR.
• Bands 14–15 (longwave window, 11.2, 12.3 µm) — "dirty" thermal IR pair, used for split-window SST retrieval.
• Band 16 (CO₂ longwave, 13.3 µm) — cloud-top temperature, CO₂ absorption.

Three scanning modes

ABI scans Earth in three nested modes simultaneously:

1. Full Disk — the entire Earth hemisphere, every 10 minutes (in Mode 6, current standard). Resolution: 2 km for Band 7 (and most others); 0.5 km for Band 2.
2. CONUS / FullDisk Sectors — fixed sector covering the contiguous United States, every 5 minutes.
3. Mesoscale 1 & 2 — two operator-controllable 1,000 × 1,000 km windows, every 30 seconds. Each mesoscale window is moved by NOAA operators to focus on active weather events — hurricanes, severe convection, and (when an operator agrees to cooperate) active launches.

The 30-second mesoscale cadence is what makes real-time launch detection possible. A Falcon 9 ascent from Vandenberg passes through several mesoscale frames during boost phase; LaunchDetect captures the plume in each.

The data

Every ABI scene is published as a NetCDF file to NOAA's public AWS Open Data bucket within seconds of generation:

s3://noaa-goes18/ABI-L1b-RadM/{year}/{day-of-year}/{hour}/{filename}.nc

For Band 7, mesoscale 1: OR_ABI-L1b-RadM1-M6C07_G18_*.nc. The file is ~3 MB per scene. Open with xarray, netCDF4, or — most conveniently — the satpy library which handles georeferencing automatically.

Where the data lives

GOES-R imagery is one of the few satellite archives that ships live from a public cloud bucket — no login, no rate limit, no quota:

• NOAA AWS Open Data — s3://noaa-goes16, s3://noaa-goes17, s3://noaa-goes18, s3://noaa-goes19. Anonymous (--no-sign-request) reads, region us-east-1. New scenes land ~30 seconds after acquisition. Path structure: <Product>/<Year>/<DOY>/<Hour>/OR_ABI-...-M6C07_G18_s<start>_e<end>_c<create>.nc. DOY is day-of-year (001-366). For mesoscale 1 Band 7 on 2026-05-12 at 18:00 UTC: ABI-L1b-RadM/2026/132/18/OR_ABI-L1b-RadM1-M6C07_G18_*.nc.
• Google Cloud Public Datasets — gs://gcp-public-data-goes-16 through -19. Mirror of the same NOAA archive, useful if your compute is on GCP.
• NOAA CLASS (www.aev.class.noaa.gov) — official NOAA archive UI with full historical backfill. Slower than S3 but covers gaps before AWS coverage began (2017 onward).
• Himawari-9 (JMA, 140.7°E) — for the western Pacific. AWS Open Data at s3://noaa-himawari9. Same NetCDF-ish shape with HSD (Himawari Standard Data) raw format also available. We'll use it in Week 21 for multi-sensor fusion.

For Python, the path of least resistance: s3fs.S3FileSystem(anon=True).glob(...) to discover files, then either xarray.open_dataset with the fsspec backend (streams) or aws s3 cp ... --no-sign-request if you want a local copy. The whole-archive size is petabytes; you almost never want to download all of it. The lab pulls a single ~3 MB mesoscale scene.

The lab

You'll pull a real GOES-18 Band 7 mesoscale scene from s3://noaa-goes18 over the Pacific, open it with satpy, plot it on a map with proper geographic coordinates (handled via Scene.resample()), and identify the geographic coverage area. By the end you'll understand the data shape, units, and georeferencing — preparation for Week 14 where the same data is used for actual plume detection.