“Ring” Solar eclipse shadow moving across northern North America

June 10th, 2021 |

Early on June 10th, 2021 there was a solar eclipse for the northern portions of the globe. This was not a total, but annular (or “ring”) solar eclipse. Satellite instruments, such as NOAA’s ABI on GOES-16 (East) can monitor the shadow of the moon as it falls on the Earth. There are several recent examples from December 2020 (South America), June 2020 (southern Asia), December 2019 (central Pacific), July 2019 (southern hemisphere), January 2019 (Asia) and August 2017 (central US).

GOES ABI

The shadow cast on the Earth could be seen from NOAA’s GOES-16 (East) ABI. This included both the visible and near-infrared spectral bands, and the ABI band 7 (at 3.9 micrometers).

A time animation of NOAA’s GOES-16 ABI band 3 (0.86 micrometers) on June 10, 2021.
A time animation of the cooling associated wit the shadow on the Earth’s surface can be seen in this GOES-16 ABI band 7 (3.9 micrometers) animation.
A time animation of the Full Disk view showing the CIMSS true color spectral composite on June 10, 2021. This product does not employ a Rayleigh correction.

There are other similar loops are posted on many web pages, such as this one from UW/SSEC. This page is a collection of those links.

The 10 UTC composite Full Disk GOES-16 image from June 10, 2021.

A larger image of the GOES-16 10 UTC Full Disk composite shown above.

The shadow from the moon could also been seen from NOAA’s GOES-17 (West) ABI on June 10, 2021.

A more zoomed in GOES-17 view.

AWIPS animation (mp4) of the CIMSS Natural Color RGB from both GOES-16 and GOES-17.

The same loop as above, but as an animated gif. Thanks to Scott.

Japan’s AHI

Japan’s AHI near-infared (band 4 centered at 0.86 micrometers) imagery on June 10, 2021.

While it’s subtle, the shadow could also be seen in Japan’s AHI.

HEO (highly elliptical orbit)

A satellite was recently launched by Russia into a highly elliptical orbit (Molniya). The satellite (Arctica) is in a commissioning phase, but some imagery from the 10-band imager of the eclipse shadow was released.

Google translation: An annular happened today #???????? Suns — For the first time in half a century, it was accessible for observation from Russia; it was best seen from Yakutia and Chukotka. Russian satellites #??????? and #???????? were able to capture this astronomical phenomenon from orbit.

Ground-based Image

A image from Chris Draves over Lake Mendota (Madison, WI).

Background

This map of the eclipse path shows where the June 10, 2021, annular and partial solar eclipse will occur. Times are UTC.
Credits: NASA’s Scientific Visualization Studio/Ernie Wright.

Credits

NOAA GOES-16 ABI data are via the University of Wisconsin-Madison SSEC Satellite Data Services. Thanks Scott Bachmeier, CIMSS for the AWIPS animation.

There GOES 2020

January 4th, 2021 |

Daily Full Disk imagery

By animating daily NOAA GOES-16 or GOES-17 ABI Full Disk visible imagery, the year are 2020 can be shown quickly in review. The GOES-16 loops show an 18 UTC image each day of 2020, while GOES-17 shows an image from 21 UTC. The images are Rayleigh-corrected composites. The GOES-16 loop is similar to a loop that includes the Winter Solstice.

Click on the above image for a link to a page with one GOES-16 ABI image for each day of 2020: http://cimss.ssec.wisc.edu/goes/loops/18z_2020_GOES.html.

Other versions as an mp4, from the ABI on GOES-16: small, medium and large. Although it should be noted that all these images are drastically sub-sampled from the higher spatial resolution imagery.

A similar year-long animation, from GOES-17 at 21 UTC daily. This time was chosen for a maximum illumination of the full disk.

Click on the above image for a link to a page with one GOES-17 ABI image for each day of 2020.

Other mp4 versions, as mp4, from the ABI on GOES-17: small and medium.

Daily Regional Views

Year-long, GOES-16 loops at 18 UTC have been generated for other regions, including: the Northeast, Mid-Atlantic, Southeast, Texas and part of the Gulf of Mexico, Central US, Southwest, Northwest and the Midwest. Similar loops from GOES-17 have been generated using images from 21 UTC for both Alaska and Hawaii. These loops begin on January 1, 2020.

Hourly Views of the Midwest

A very large (~800 MB) file, showing a year-long (hourly) GOES-16 file over the Midwest (duration of 14 min) covering 2020. Many features can be seen, including clouds, smoke and snow. Note that this loop is sub-sampled in time by a factor of 12. RGB imagery of the CIMSS (Natural) true color (during the day) and the nighttime cloud microphysics (during the night) are shown.

These images were made with geo2grid s/w, with NOAA GOES data via the UW-Madison, SSEC.

Using GOES ABI and deep learning to nowcast lightning

September 2nd, 2020 |

NOAA and CIMSS are developing a product that uses a deep-learning model to recognize complex patterns in weather satellite imagery to predict the probability of lightning in the short term. Deep learning is a branch of machine learning based on artificial neural networks, which have the ability to automatically learn targeted features in the data by approximating how humans learn.

A convolutional neural network (CNN) was trained on over 23,000 images of GOES-16 Advanced Baseline Imager (ABI) data to predict the probability of lightning, within any given ABI pixel, in the next 60 minutes. The CNN was trained using 118 days of data collected between May and August of 2018. Images of GOES Geostationary Lightning Mapper (GLM) flash-extent density (created with glmtools) were used as the source of lightning observations. Note that GLM is an optical sensor that observes both in-cloud and cloud-to-ground lightning.

The CNN currently uses four ABI channels: band 2 (0.64-µm), band 5 (1.6-µm), band 13 (10.3-µm), and band 15 (12.3-µm). Bands 2 and 5 are only utilized under sunlit conditions. Utilization of additional channels and time sequences of images is under investigation. The model uses a semantic image segmentation architecture to assign the probability of lighting in the next 60 minutes to each pixel in the image. The model is very computationally efficient, only needing 30 seconds to process the ABI CONUS domain and 3 seconds to process an ABI mesoscale domain using multithreading on a 40-CPU linux server.

Currently, the model only utilizes satellite radiances. Thus, it can be applied to nearly any spatial domain covered by the ABI or an ABI-like sensor (e.g. AHI). Based on near-real-time testing, the model routinely nowcasts lightning initiation with 10-30 minutes of lead-time. We expect the skill and lead-time will increase as new predictors (e.g. more ABI fields, NWP, radar where available) are added to the model.

Below are a sampling of recent examples. The base images are 0.64-µm reflectance, with GLM-derived flash-extent density overlaid as filled semi-transparent polygons. The flash-extent density is the accumulated number of flashes within the previous 5 minutes. The CNN-derived probabilities are displayed as contours at select levels (near-real-time output is available through RealEarth).

The overall objective is to improve lightning nowcasts in support of aviation, mariners, and outdoor events/activities. Beyond improving the CNN, our work will focus on packaging the output into actionable information for forecasters and other decision makers.

A cold front in Iowa

 

Thunderstorm development on sea-breeze boundaries in Florida and the Bahamas

 

Diurnally and orographically forced storms in the Southwest U.S. and Rocky Mountains

 

Storms in central Oklahoma, on the edge of Hurricane Laura’s cloud shield

 

A couple of examples over the Northeast U.S.

 

A boundary of convection on the southern bank of Lake Ontario

 

Storms in a warm sector in IL/IN/OH, perhaps along an outflow boundary

 

Southeast U.S. offshore region

The background image in this example transitions from 10.3-µm brightness temperature to 0.64-µm reflectance, while the flash-extent density enhancement also changes, in an attempt to enhance contrast.

Supercells in the Southeast

May 6th, 2020 |

A cold front with ample moisture and instability ahead of it spawned numerous strong storms in the Southeast U.S. yesterday; particularly one long-lived supercell in South Carolina. A convolutional neural network model (CNN) was deployed in realtime on the 1-min GOES-16 mesoscale sector imagery. The model produces an “Intense Convection Probability” (ICP). The inputs for the model are the GOES-16 ABI 0.64 µm reflectance, 10.3 µm brightness temperature, and GLM flash extent density. It was trained to identify “intense” convection as humans do, associating features with intense convection such as strong overshooting tops, thermal couplets (“cold-U/V”), above anvil cirrus plumes (AACP), and strong cores of total lightning.

The animation below shows the ICP contours overlaid ABI 0.64 µm + 10.3 µm sandwich imagery, annotated with preliminary severe storm reports.


The long-lived supercell in South Carolina exhibited AACP and cold-U features, and produced numerous severe wind and hail reports (up to the size of tennis balls). While the NOAA/CIMSS ProbSevere models handled this storm well, the ICP ramped up on a couple of severe storms in northern Georgia before ProbSevere did. ICP for these cells exceeded 90% 15-18 min before ProbWind reached 50%. The ICP may be able to provide additional lead time and confidence to ProbSevere guidance for certain storms, utilizing spectral and electrical information from geostationary satellites. Incorporating ICP into ProbSevere is an active area of current research.

ProbSevere storm contours and MRMS MergedReflectivity for storms in GA and SC. The main or “inner” ProbSevere contour is shaded by the probability of any severe weather, while the outer contour is shaded by the probability of tornado, which appeared when that value was at least 3%, in this example.


An accumulation of ProbSevere storm centroids (white to pink squares, 50% --> 100%), NWS severe weather warnings, and SPC severe local storm reports from 12Z on May 5th to 12Z on May 6th [click to enlarge]

An accumulation of ProbSevere storm centroids (white to pink squares, 50% –> 100%), NWS severe weather warnings, and SPC severe local storm reports from 12Z on May 5th to 12Z on May 6th [click to enlarge]