To celebrate the 50th anniversary of the GOES-A launch (GOES-A became GOES-1 on reaching geostationary orbit), this blog post contains one or two satellite animations (or images) for each of the 50 states. More on GOES-1 through GOES-19.

There were experimental geostationary imagers (ATS and SMS) that preceded the first GOES. In fact, what was going to be SMS-3 became GOES-1. Learn more about the the history of GOES in these book chapters (chapter 2 and chapter 1.05: Schmit, T.J., Goodman, S.J., Daniels, J., Rachmeler, L.A., 2026. GOES: Past, Present, and Future. In: Liang, S. (Ed.), Comprehensive Remote Sensing, vol. 1. Elsevier, pp. 126–166. https://dx.doi.org/10.1016/B978-0-443-13220-9.00051-2). More on the history of satellites.

Alabama

1-minute GOES-16 Infrared (IR) Window images of severe thunderstorms that produced an EF-3 tornado near Birmingham: https://cimss.ssec.wisc.edu/satellite-blog/images/2021/01/210125_goes16_infrared_spcStormReports_AL_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/39747

GOES-17 visible images showing the tidal motion of ice in Norton Sound: https://cimss.ssec.wisc.edu/satellite-blog/images/2022/02/NORTON_loop_GOES-17_2021149_160059_2021150_015949.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/40991

A low pressure system intensfying over the Gulf of Alaska, depicted by the GOES-17 water vapor band: https://cimss.ssec.wisc.edu/satellite-blog/images/2022/01/WV_PAC_loop_GOES-17_2022012_140032_2022013_130032_faster.mp4

Also see this resuspended volcanic ash example: https://cimss.ssec.wisc.edu/satellite-blog/archives/66940

1-minute GOES-17 Fire Temperature RGB imagery of the Tunnel Fire: https://cimss.ssec.wisc.edu/satellite-blog/images/2022/04/Tunnel_GOES-17_Rad_fire_temperature_abi_2022109_160117_2022111_083035.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/45859

Arkansas

Severe thunderstorms with SPC Storm Reports plotted over 1-minute GOES-16 IR Window imagery: https://cimss.ssec.wisc.edu/satellite-blog/images/2022/04/220411_goes16_infrared_spcStormReports_AR_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/45730

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California

Smoke and thermal signatures of the County Fire as seen in the GOES-16 visible and shortwave infrared window bands: https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2018/07/180630_goes16_visible_shortwave_infrared_County_Fire_CA_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/28722. Fog is also seen in the visible images, while the hottest shortwave IR pixels are colored in red.

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Colorado

Snow cover shown in GOES-16 Visible images and the Land Surface Temperature derived product : https://cimss.ssec.wisc.edu/satellite-blog/images/2024/11/241111_g16_vis_lst_sfcTemp_CO_snow_cover.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/61705

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Connecticut

GOES-16 Visible imagery of severe thunderstorms with SPC Storm Reports over-plotted: https://cimss.ssec.wisc.edu/satellite-blog/images/2021/11/211113_goes16_visible_spcStormReports_NJ_NY_CT_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/43277

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Delaware

Fog as shown in GOES-16 Cloud Thickness derived product and Visible imagery: https://cimss.ssec.wisc.edu/satellite-blog/images/2021/03/210323_goes16_cloudThickness_visible_East_Coast_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/40373

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Florida is home to Cape Canaveral, from where all GOES Satellites were launched. The ABI can be used to view rocket launches, as in this animation showing the GOES-T launch with special GOES-17 30-second Mesoscale Sector scans https://cimss.ssec.wisc.edu/satellite-blog/images/2022/02/800x800_AGOES17_B1_ZOOM_V2_30SEC_animated_2022060_213625_188_2022060_215455_188_X_redo.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/44902

Florida’s location in the tropics means that tropical cyclones frequently affect the state. Sometimes they make landfall in an area where previous storms have occurred, allowing interesting satellite comparisons such as this one between 2022’s Ian and 2004’s Charley: https://cimss.ssec.wisc.edu/satellite-blog/archives/48129. This kind of comparison between different storms has also been done near Jamaica, as shown in this blog post: https://cimss.ssec.wisc.edu/satellite-blog/archives/60196

GOES-R series routine 5-minute scanning allows for precise knowledge of fog‘s increase, as shown in this animation of the Nighttime Microphysics RGB. Note that surface observations show widespread fog in regions where the RGB doesn’t suggest fog (i.e., where the cyan color isn’t present). GOES-R IFR Probability fields, a product that combines satellite information with Rapid Refresh model estimates of low-level saturation, does indicate high probabilities of IFR conditions throughout the observed fog field.

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Georgia

SPC Storm Reports plotted on 1-minute GOES-16 Visible imagery of severe thunderstorms: https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2019/03/190303_goes16_visible_spcStormReports_AL_GA_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/32150

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Hawaii

Derived multi-spectral Volcanic Ash Probability https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2022/11/GOES17AshProbability_0906_1301_28Nov_2022.gif (or https://cimss.ssec.wisc.edu/satellite-blog/images/2025/10/GOES17AshProbability_0906_1301_28Nov_2022.mp4) via https://cimss.ssec.wisc.edu/satellite-blog/archives/48881 Automated, multi-spectral derived products are key to be able to monitor such phenomena in realtime.

Also see GOES-18 imagery of the deadly Lahaina, Maui wildfire:  https://cimss.ssec.wisc.edu/satellite-blog/images/2023/08/230808_230809_goes18_shortwaveInfrared_HI_anim.mp4

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Idaho

Wildfire smoke as seen in this CIMSS True Color RGB imagery: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/ID_GOES-17_RadC_cimss_true_color_2022252_140117_2022253_015617.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/47831

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Illinois

GOES continuously monitors the Earth and its atmosphere. When something new and unexpected occurs, GOES imagery or products can help with situational awareness. Consider, for example, this Chemtool facility fire in northern Illinois in 2021. GOES-16 Near-Infrared imagery identified the (dark) smoke plume’s transport and areal extent. This was also a case where both GOES satellites (East and West) were useful; although GOES-East gave a better view of the smoke plume, that dense smoke plume masked the view of the fire thermal signature. GOES-West however had a continuous view of the fire and could be used to determine how the fire intensity might be changing in time. https://cimss.ssec.wisc.edu/satellite-blog/images/2021/06/GOES-16_RadC_C03_2021165_120000_2021165_192500.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/41094

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Indiana

During arctic outbreaks, northwest Indiana frequently experiences lake effect snow bands. Multi-spectral RGB imagery from GOES-East can highlight which cloud bands are most likely to produce heavy snow. GOES-16 Cloud Phase Distinction RGB images: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/01/MI_GOES-16_RadC_cloud_phase_distinction_2024019_140117_2024019_220117.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/56535

Aircraft “hole punch” (or cavum) clouds https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2017/12/171221_goes16_visible_snow-ice_IL_IN_hole_punch_clouds_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/26446 GOES Visible imagery is on the top panel, while Near-IR Snow/Ice imagery is on the bottom panel.

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Iowa

One of the most powerful derechos of the 2020s formed over western Iowa on 10 August 2020 and then moved eastward (Here’s a summary from the Quad Cities NWS; Cedar Rapids was particularly hard-hit; WFO IND noted the anniversary). A CIMSS Satellite Blog post: https://cimss.ssec.wisc.edu/satellite-blog/archives/37938 includes 1-minute imagery and plots of SPC Storm Reports of the system as it crossed Iowa. https://cimss.ssec.wisc.edu/satellite-blog/images/2020/08/200810_goes16_visible_spcStormReports_Midwest_Derecho_anim.mp4

Here is an animated gif version of the above animation. There are several other CIMSS Satellite Blog posts on Derechos.

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Kansas

In addition to severe severe thunderstorms, the Spring season will often bring agricultural burning that can be monitored very closely from GOES, as shown in this blog post. These agricultural burns can also show up in the Next Generation Fire System events dashboard here.

Severe thunderstorms: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/05/240519_goes16_visibleInfraredSandwichRGB_localStormReports_KS_2_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/59341

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Kentucky

Thunderstorms that produced heavy rainfall and flooding in July 2022, as seen by GOES-16: https://cimss.ssec.wisc.edu/satellite-blog/images/2022/07/220727_220728_goes16_infrared_surfacePlots_KY_flooding_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/47406

A river valley fog example: https://cimss.ssec.wisc.edu/satellite-blog/archives/42165

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Louisiana

Hurricane Katrina in August of 2005, as seen by GOES-12: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/logoLL_logoLR_GOES12_Katrina_loop_GOES-12_2005235_001500_2005242_034500.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/19402

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Maine

Wildfire smoke as seen in two of the GOES-16 spectral bands — Visible and Near-Infrared Cirrus: https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2017/08/170817_goes16_visible_cirrus_Canadian_smoke_anim.mp4 (Preliminary, Non-operational) via https://cimss.ssec.wisc.edu/satellite-blog/archives/24736

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Maryland

Winter storm via the GOES-16 Cloud Type RGB: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/02/240213_goes16_dayCloudTypeRGB_Northeast_US_snow_cover_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/57171

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Massachusetts

GOES-16 Set of Nor’ Easters: https://cimss.ssec.wisc.edu/goes/abi/youtube/loops/20_1080x1920_AGOES16_B1_SHCS_FD_FOUREASTER_2018_loop_59s.mp4

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Michigan

Bore over Lake Superior in GOES-16 Visible imagery: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/RedVisLakeSuperiorFog-20170710_101218_194718anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/24420

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Minnesota

The GOES-R series routine 5-minute scanning allowed for timely monitoring of snow melt over southwest Minnesota in early December 2021, as shown in the animation below — see this CIMSS Satellite Blog post. The animation shows Band 2 (Visible, 0.64 µm), True Color RGB imagery, the Day Cloud Phase Distinction RGB, and the Day Snow/Fog RGB. You can view the mp4 below, or an animated gif.

Blowing snow example: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/GOES-19_RadC_blowing_snow_2024339_142117_2024339_220117.gif via https://cimss.ssec.wisc.edu/satellite-blog/archives/61934

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Mississippi

Severe thunderstorms https://cimss.ssec.wisc.edu/satellite-blog/images/2024/04/240410_goes16_visible_spcStormReports_TX_LA_MS_AL_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/58370

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Missouri

Severe convection as seen by 1-minute Mesoscale Sector GOES-16 Visible and Infrared imagery: https://cimss.ssec.wisc.edu/satellite-blog/images/2023/05/230506_goes16_visible_infrared_localStormReports_MO_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/52201

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Montana

30-second GOES-18 Visible imagery of severe thunderstorms https://cimss.ssec.wisc.edu/satellite-blog/images/2022/07/220709_goes18_visible_spcStormReports_MT_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/47146

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Nebraska

Haboob over Nebraska in May 2022 https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/NE_GOES-16_RadC_cimss_true_color_2022132_150117_2022132_235617.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/46385

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Nevada

Cherrywood Fire from May 2021 as seen by GOES-17 in 4-panels: https://cimss.ssec.wisc.edu/satellite-blog/images/2021/05/210520_goes17_shortwaveInfrared_visible_goes16_firePower_fireTemperature_Cherrywood_Fire_NV_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/40926

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New Hampshire

Mountain waves and banner clouds in October 2018 as seen by GOES-16: https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2018/10/181025_goes16_waterVapor_Northeast_US_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/30441

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New Jersey

Special (research) GOES-14 Super Storm Sandy in 2012: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/logos_GOES14_SRSOR_B1_2012299_174500_2012304_224500_UTC.mp4 More on Hurricane Sandy and SRSOR imagery which was used to prepare users for the eventual routine GOES-R ABI 1-minute imagery.

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New Mexico

GOES data are helpful in identifying regions of blowing dust that can occur either with strong low pressure systems or with thunderstorm outflow. For example, this GOES-18 animation (https://cimss.ssec.wisc.edu/satellite-blog/images/2024/06/Haboob_GOES-18_RadM1_cimss_true_color_night_dust_2024171_210030_2024172_035927.mp4) shows dust caused by a thunderstorm downdraft moving westward across New Mexico (for more information, see this CIMSS Satellite Blog post: https://cimss.ssec.wisc.edu/satellite-blog/archives/60275 .

This CIMSS Satellite Blog post (https://cimss.ssec.wisc.edu/satellite-blog/archives/64237 ) shows dust moving northeastward across New Mexico in response to the circulation around a strong low pressure system. Here’s the animation: https://cimss.ssec.wisc.edu/satellite-blog/images/2025/04/250417_goes19_trueColorRGB_dustRGB_NM_TX_blowing_dust_anim.mp4

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New York

A heavy rain event over NYC in September 2023: https://cimss.ssec.wisc.edu/satellite-blog/archives/54772 that was also a Forecast Decision Training Division (FDTD) Webinar ( https://rammb2.cira.colostate.edu/training/visit/satellite_webinar/fdtd_webinar/2024-01-10/ and https://www.youtube.com/watch?v=8v9qUynltyc ) as well as a Satellite Book Club presentation (https://www.youtube.com/watch?v=KuO-xsy3S-s&list=PLJzZC8w9vPV1NSHVBtMqOEP0VxlDmh5WA&index=61).

An example of river valley fog and snow cover is shown above: https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2018/04/180501_goes16_visible_snow_ice_NY_Catskills_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/27893

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North Carolina

Tropical Storm Ophelia in September 2023: https://cimss.ssec.wisc.edu/satellite-blog/images/2023/09/230922_goes16_visible_infared_TS_Ophelia_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/54632

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North Dakota

An annual possibility along North Dakota’s eastern border is flooding from the Red River of the North. Satellite information is vital to monitor such inundations. Combined ABI/VIIRS products (available at this website) allow for the monitoring, as shown here: https://cimss.ssec.wisc.edu/satellite-blog/archives/45947 ; SAR data can also be used for very high-spatial resolution flood monitoring: https://cimss.ssec.wisc.edu/satellite-blog/archives/46140 . Multi-spectral data are very important when monitoring floods, especially observations at 0.87 and/or 1.61 micrometers (an early example with MODIS data: https://cimss.ssec.wisc.edu/satellite-blog/archives/7894).

Light snow from lake effect clouds as seen in GOES-19 Day Cloud Phase Distinction RGB imagery: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/11/241125_goes19_dayCloudPhaseDistinctionRGB_ND_lake_effect_clouds_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/61872

Satellite observations of blowing snow in very cold airmasses (when visibility restrictions from blowing snow can rapidly become life-threatening) are very important over North Dakota — one example is shown in this CIMSS Satellite Blog post: https://cimss.ssec.wisc.edu/satellite-blog/archives/44612 ; Note that for this case, Blizzard Warnings were modified based on the Satellite Observations, as detailed in this Satellite Liaison Blog post: https://satelliteliaisonblog.wordpress.com/2022/02/11/more-northern-plains-blowing-snow/

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Ohio

Cleveland is an active port on Lake Erie. GOES data can be used to monitor ship tracks as they move through lake ice, as shown in the animation (https://cimss.ssec.wisc.edu/satellite-blog/images/2022/02/220215_goes16_visible_Lake_Erie_ship_track_anim.mp4“), from this blog post: https://cimss.ssec.wisc.edu/satellite-blog/archives/44646“.

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Oklahoma

Grass fires (hottest pixels colored red to yellow) and smoke plumes https://cimss.ssec.wisc.edu/goes/abi/youtube/loops/17_ABI_BAND7_13_FIRE_COMBO_OK_loop_2017065_170029_2017066_045929_fast.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/23297

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Oregon

Wildfire smoke as seen in CIMSS True Color RGB imagery: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/OR_GOES-17_RadC_cimss_true_color_2022252_140117_2022253_015617.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/47831

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Pennsylvania

Pennsylvania’s many river-filled valleys are common areas for fog development. The high temporal resolution of GOES-R (as shown in the animation below from a special observing session with GOES-14) means you can observe the dissipation to the closest minute.

https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2014/08/GOES14_VIS_18August2014loop.gif as in this blog post.

Snow squalls https://cimss.ssec.wisc.edu/satellite-blog/images/2022/02/220219_goes16_dayCloudPhaseDistinctionRGB_PA_snow_squalls_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/44742

Also see: https://cimss.ssec.wisc.edu/satellite-blog/archives/45461

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Rhode Island

This animation https://www.ssec.wisc.edu/~scottl/data/GOES-16_ABI_RadC_C02_20210607_1501_to_2356_RhodeTLanim.gif (See more at this blog post https://cimss.ssec.wisc.edu/satellite-blog/archives/41031) shows the evolution of fog moving over Block Island. Of particular note, especially to sailors, is the development of overlapping waves downwind of Block Island. Note also how this imagery can be used to pinpoint where over southern Rhode Island beaches you might be disappointed by the weather on this day! Snow during a Nor’easter: https://cimss.ssec.wisc.edu/satellite-blog/images/2020/12/201216_201217_goes16_waterVapor_Noreaster_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/39306

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South Carolina

South Carolina was visited by a swarm of tornadoes before sunrise on 13 April 2020 (SPC Storm Reports) as a strong cold front moved through the state. The animation below shows GOES-16 Mesoscale Sector 1-minute imagery. Most of the tornadoes occurred between 0900 and 1000 UTC. A large-scale view of this system is shown below. The forecast office in Columbia (WFO CAE) published a Storyboard on this event.

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South Dakota

“River effect” clouds during an arctic outbreak: https://cimss.ssec.wisc.edu/satellite-blog/images/2024/01/240113_goes16_daySnowFogRGB_SD_river_effect_snow_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/56436

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Tennessee

GOES-16 Visible and Infrared images (with GLM lightning observations) of severe thunderstorms https://cimss.ssec.wisc.edu/satellite-blog/images/2024/05/240508_goes16_visible_infrared_glmFlashExtentDensity_warningPolygons_TN_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/59059

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Texas

West Texas can be a prime wildfire environment, and GOES-R’s fine temporal scanning abilities allows for precise monitoring of the evolution of fires. That kind of information is vital to ensure the safety of those responding to the fire. An excellent example is the Smokehouse Creek fire in 2024: https://cimss.ssec.wisc.edu/satellite-blog/archives/57431, the largest fire in areal extent in Texas history; it burned more than 1600 square miles, an area larger than the state of Rhode Island.

Texas has a long Gulf coastline, and tropical cyclones are a common occurrence. Hurricane Harvey, in 2017, was an early example of a tropical system being monitored with Geostationary Lightning Mapper data, as shown in this blog post: https://cimss.ssec.wisc.edu/satellite-blog/archives/24841 . Harvey’s effects on SE Texas were also monitored via VIIRS’ Day Night Band sensor on Suomi-NPP: https://cimss.ssec.wisc.edu/satellite-blog/archives/24924. A similar Day Night Band comparison with Hurricane Beryl in 2024 is shown in this National Weather Association short course: https://rammb2.cira.colostate.edu/training/2024-nwa-satellite-workshop/

GOES-16 images showing splitting convection in 2018: https://cimss.ssec.wisc.edu/goes/abi/youtube/loops/04_ABI_BAND2_SPLIT_loop_2018084_200104_2018085_012904_17s.mp4

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Utah

30-second imagery from GOES-17, to monitor the development of convection during a radar outage: https://cimss.ssec.wisc.edu/satellite-blog/images/2022/06/220623_goes17_visible_UT_CO_KGJT_radar_outage_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/46981

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Vermont

Wave clouds and snow squalls https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/VT_GOES-16_RadC_cloud_phase_distinction_2022058_123117_2022058_222617.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/44873

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Virginia

Rocket Plume and Shadow https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2019/11/WALLOPS_Vis_loop.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/34945

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Washington

Preliminary, Non-operational GOES-16 Fog advection https://cimss.ssec.wisc.edu/satellite-blog/images/2024/12/Fog_GOES-16_RadC_day_snow_fog_2017140_173207_2017141_032707.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/23981

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West Virginia

Snow cover https://cimss.ssec.wisc.edu/satellite-blog/images/2021/01/210128_goes16_visible_daySnowFogRGB_dayCloudPhaseDistinctionRGB_VA_NC_snow_cover_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/39766

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Wisconsin

GOES data continuously monitors the evolution of the atmosphere, and machine learning tools have been developed (at CIMSS, CIRA and elsewhere) to help forecasters (in the National Weather Service and elsewhere) anticipate the development of lightning. One of the more important channels that fosters the ability of satellite data to anticipate lightning is GOES-R’s Band 5 (that is, observations at 1.61) that can highlight phase changes during the day based on changes in reflectivity from clouds made up of water droplets vs. clouds made up of ice crystals. Both the Day Cloud Phase Distinction and Day Cloud Type RGBs include band 5 for that reason. LightningCast probabilities, plotted below on top of Day Cloud Phase Distinction RGB imagery, shows a slow increase in lightning possibilities in advance of a GLM observation at the end of the animation (See more, including this animated gif https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2024/07/G16DCPD_LtgCast_GLMFED-20240716_1616_to_1931anim.gif at this CIMSS satellite blog post https://cimss.ssec.wisc.edu/satellite-blog/archives/60337 )

In 2018, fire at a refinery in Superior Wisconsin was captured by GOES-East (and JPSS) satellite imagery. GOES imagery allows Emergency Managers to determine where any evacuations might have to occur. A CIMSS Satellite Blog post on this event is here: https://cimss.ssec.wisc.edu/satellite-blog/archives/27868. The response of WFO Duluth to this event was discussed at the FDTD Satellite Applications webinar here https://rammb2.cira.colostate.edu/training/visit/satellite_webinar/fdtd_webinar/2019-07-17/ and on YouTube here: https://www.youtube.com/watch?v=h4BImH-zJio

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Wyoming

Hail Swath produced by a severe thunderstom: https://cimss.ssec.wisc.edu/satellite-blog/images/2023/07/230711_goes16_nighttimeMicrophysicsRGB_WY_SD_anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/53389

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Other

Washington, D. C.

Severe weather: https://cimss.ssec.wisc.edu/satellite-blog/images/2025/10/PSv3Readout5July2022_2000_to_2200step.mp4 https://cimss.ssec.wisc.edu/satellite-blog/images/2025/10/G16B13-20220705_2001_to_2256anim.mp4 via https://cimss.ssec.wisc.edu/satellite-blog/archives/47110

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Puerto Rico

Hurricane Maria https://cimss.ssec.wisc.edu/satellite-blog/wp-content/uploads/sites/5/2017/09/GOES16_RedVis-20170920_1017_1117anim.gif via https://cimss.ssec.wisc.edu/satellite-blog/archives/25338

American Samoa

Flash flooding example: https://cimss.ssec.wisc.edu/satellite-blog/archives/59796

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H/T

Both McIDAS-X and Geo2Grid (as well as AWIPS) software was used in generating these images, using data via the UW/SSEC Data Services. More about GOES-16. Thanks to CIMSS Satellite Blog contributors Scott Bachmeier and Tim Schmit, in addition to Mat Gunshor and Alexa Ross. Credit to Bill Bellon for coding up the map.

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1-minute Mesoscale Domain Sector GOES-19 (GOES-East) images from all 16 ABI spectral bands (above) showed thermal signatures of SpaceX Starship Test Flight 11 — launched from Starbase in South Texas at 2323 UTC on 13 October 2025.

A thermal signature of the Super Heavy stage 1 booster rocket was apparent in Near-Infrared (Bands 04-06) and Infrared (Bands 07-16) spectral bands at 2125 UTC (below).

After separation from the stage 2 Starship, the stage 1 Super Heavy performed a boostback burn in order to descend and make a soft landing in the Gulf of Mexico (just off the Texas coast) — a thermal signature of the boostback burn was seen in Bands 05-07 at 2329 UTC (below).

A larger-scale stepped sequence of 1-minute GOES-19 images from all 16 ABI spectral bands is shown below.

In a toggle between two GOES-19 Upper-level Water Vapor images (below), the change in appearance of the Starship’s superheated water vapor trail changed from a more linear shape at 2327 UTC (at lower altitudes of 50-70 km in the Stratosphere, where the atmosphere had more density and ambient pressure) to a “boomerang” shape at 2329 UTC (at higher altitudes of 70-100 km, where the atmosphere within the Mesosphere and Thermosphere had much less density and ambient pressure, allowing the water vapor trail to expand outward).

A toggle between GOES-19 Shortwave Infrared and Upper-level Water Vapor images at 2330 UTC (below) revealed a cluster of hotter pixels (darker shade of red) at the leading edge of the water vapor trail (darker shades blue).

1-minute GOES-19 Rocket Plume RGB images created using Geo2Grid (below) provided a single product to visualize the initial 2323 UTC launch thermal anomaly (pink), the Super Heavy and Starship water vapor plumes (brighter shades of green) and the slow westward drift of the Super Heavy launch condensation cloud (darker shades of red).

1-minute GOES-19 True Color RGB images from the CSPP GeoSphere site (below) showed the Super Heavy rocket booster condensation cloud as it slowly drifted westward over South Texas — along with the smaller condensation cloud from the Super Heavy booster as it later made its landing off the Texas coast.

The 2 condensation clouds are highlighted on the 2335 UTC GOES-19 True Color RGB image (below).

A plot of rawinsonde data from Brownsville, Texas (KBRO) (below) showed easterly winds throughout the entire mid/upper troposphere and lower stratosphere — which explained the westward drift of the Super Heavy booster condensation cloud after launch.

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10-minute Full Disk scan GOES-18 (GOES-West) Mid-level Water Vapor images (above) showed the remnants of Typhoon Halong (North Pacific surface analyses) as it entered the Bering Sea late in the day on 11 October, re-intensified to a Hurricane Force low pressure (Alaska surface analyses) then eventually moved inland across far western and northwestern Alaska later in the day on 12 October 2025 (crossing the Seward Peninsula after 1600 UTC, then traversing the far western North Slope after 2100 UTC).

Notable peak wind gusts (below) included 80 kts (92 mph) at St. George (PAPB) in the Bering Sea at 0615 UTC, 75 kts (86 mph) at Cape Newingham (PAEH) along the southwest coast of Alaska at 0915 UTC, 87 kts (100 mph) at Toksook Bay (PAOO) along the southwest coast of Alaska at 1135 UTC and 70 kts (81 mph) at St. Michael (PAMK) farther inland just south of Norton Sound at 1829 UTC.

A toggle between Suomi-NPP VIIRS Infrared Window and Day/Night Band images at 1424 UTC (below) showed the remnants of Typhoon Halong as it was centered over Norton Sound, south of the Seward Peninsula.

A mid-tropospheric dry slot (shades of yellow) was evident in GOES-18 Water Vapor imagery as it progressed northeast across the Bering Sea (0400 UTC image) — the downward transfer of momentum could have been a factor in producing some of the stronger wind gusts at the surface, as was suggested by a plot of rawinsonde data at Nome PAOM (located on the southern coast of the Seward Peninsula).

More details on this event are available here, here and here.

The remnants of Typhoon Halong appear to have potentially set a local ERA5 record (1950-2024) for lowest MSLP for the month of October:

— Tomer Burg (@burgwx.bsky.social) 2025-10-13T01:11:06.134Z

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Due to a lack of radar coverage over American Samoa, WSO Pago Pago requested a 1-minute Mesoscale Domain Sector over the islands to monitor convective development and the potential for flash flooding. GOES-18 (GOES-West) Clean Infrared Window (10.3 µm) images (above) showed rain showers that developed in the general vicinity of the American Samoa island of Tutuila (where Pago Pago International Airport NSTU is located) on 09 October 2025. GLM Flash Points indicated that intermittent lightning occurred very near the island of Tutuila — although no thunderstorms or lightning were explicitly reported during that particular 10-hour period at NSTU. The northwest-to-southeast orientated band of deep convection was aligned along a trough of low pressure that was located across the islands.

A Flash Flood Warning was issued at 0335 UTC (25 minutes prior to the start of the animation shown above), which was valid until 0700 UTC — 0.60″ of rainfall was recorded during the 6-hour period ending at 0600 UTC, but there no reports of flooding on Tutuila that were received by WSO Pago Pago.

GOES-18 Total Precipitable Water derived product values in the vicinity of American Samoa were generally in the 2.0-2.4 inch range — and a toggle between Pago Pago rawinsonde data at 0000 UTC and 1200 UTC (below) indicated that Precipitable Water (PW) increased from 2.19 inches to 2.40 inches during that 12-hour period. In addition, after 1200 UTC the coldest cloud-top infrared brightness temperatures associated with some of the rain showers and thunderstorms across the region were around -80ºC (darker shades of purple embedded within brighter white areas) — which represented a small overshoot of the Most Unstable (MU) air parcel’s Equilibrium Level (EL).

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