This website works best with a newer web browser such as Chrome, Firefox, Safari or Microsoft Edge. Internet Explorer is not supported by this website.

Palisades Fire in Southern California

1-minute Mesoscale Domain Sector GOES-18 (GOES-West) Shortwave Infrared (3.9 µm) along with Red Visible (0.64 µm) + Fire Mask derived product images (above) displayed a pronounced thermal signature associated with the Palisades Fire located between Malibu and Santa Monica in Los Angeles County, California on 7th January 2025. The 3.9 µm infrared brightness temperatures at... Read More

1-minute GOES-18 Shortwave Infrared (3.9 µm) images (left) and Red Visible (0.64 µm) + Fire Mask derived product (right), with 15-minute METAR surface reports plotted in yellow, from 1801 UTC on 7th January to 0000 UTC on 8th January; Interstate highways are plotted in red [click to play MP4 animation]

1-minute Mesoscale Domain Sector GOES-18 (GOES-West) Shortwave Infrared (3.9 µm) along with Red Visible (0.64 µm) + Fire Mask derived product images (above) displayed a pronounced thermal signature associated with the Palisades Fire located between Malibu and Santa Monica in Los Angeles County, California on 7th January 2025. The 3.9 µm infrared brightness temperatures at the fire origin location began to increase at 1824 UTC, then rapidly increased in intensity and areal coverage for the next several hours as the wildfire exhibited extreme behavior (due to dry fuels and strong Santa Ana winds). The increase in 3.9 µm infrared brightness temperatures at the 1824 UTC fire start time can be seen within the red box below (the NGFS-identified fire start time was 1825 UTC).

1-minute GOES-18 Shortwave Infrared (3.9 µm) images (left) and Red Visible (0.64 µm) + Fire Mask derived product (right), from 1822-1826 UTC on 7th January; Interstate highways are plotted in red [click to enlarge]

1-minute GOES-18 True Color RGB images from the CSPP GeoSphere site (below) showed the offshore transport of smoke from the Palisades Fire — and a few pyrocumulus jumps in the vicinity the wildfire were seen later in the day.

1-minute GOES-18 True Color RGB images, from 1824 UTC on 7th January to 0000 UTC on 8th January [click to play MP4 animation]

===== 8th January Update =====

1-minute GOES-18 Shortwave Infrared (3.9 µm) images (left) and Red Visible (0.64 µm) + Fire Mask derived product (right), from 0000-1200 UTC on 8th January [click to play MP4 animation]

During the subsequent nighttime hours, 1-minute GOES-18 Shortwave Infrared and Fire Mask images (above) showed the Palisades Fire thermal signature as it expanded westward toward Malibu. At 0500 UTC the peak wind gust at Burbank (KBUR) was 73 kts or 84 mph — and at 0545 UTC the peak wind gusts were 58 kts or 67 mph at Van Nuys (KVNY) and 51 kts or 59 mph at Santa Monica (KSMO). According to CAL FIRE updates, during the 12-hour period from 0000-1200 UTC on 8th January the fire more than doubled in size (growing from 1262 acres to 2921 acres).

View only this post Read Less

LightningCast applied to new sensors

GOES-19 is slated to become the next operational GOES-East in April. Despite being trained on GOES-16 data, CIMSS and NOAA scientists have been busy evaluating the AI lightning-prediction model, LightningCast, on GOES-19 output to prepare for the operational transition and see how adaptable the model is.Overall, the LightningCast output on... Read More

GOES-19 is slated to become the next operational GOES-East in April. Despite being trained on GOES-16 data, CIMSS and NOAA scientists have been busy evaluating the AI lightning-prediction model, LightningCast, on GOES-19 output to prepare for the operational transition and see how adaptable the model is.

LightningCast probabilities (contours) GOES-19 ABI day-cloud-phase-distinction RGB (background) and GOES-19 GLM flash-extent density for cold frontal convection over Arkansas and northeast Texas.
Animation of GOES-19 LightningCast predictions and GLM flash-extent density for some thunderstorms off the east coast of Mexico.

Overall, the LightningCast output on GOES-19 looks to be in-line with performance on GOES-16. There are still some data-quality issues that the ABI imagery team is working on to fix, and once resolved, we can quantitatively compare LightningCast output from the two satellites more accurately.

In Europe, the Meteosat Third Generation (MTG) satellite, Meteosat-12, recently became operational. We have been able to get LightningCast to run on data from Meteosat-12’s Flexible Combined Imager (FCI), with surprisingly good results. We say “surprisingly,” because we expected that the differences between ABI’s and FCI’s spectral response functions and differences in channel resolutions would generate poor lightning predictions, since the model was trained on data only from GOES. On the contrary, the predictions look reasonable considering they are applied to FCI data with no re-training or fine-tuning. The animation below shows the sequence of LightningCast predictions, FCI day-cloud-phase-distinction RGB (background), and MTG’s Lightning Imager (LI) flash-extent density (foreground), over a scene in south eastern Africa, over the countries of Mozambique and Zimbabwe.

Animation of Meteosat-12 LightningCast predictions and LI flash-extent density for thunderstorms off in Mozambique and Zimbabwe.

There are still some data quality issues with FCI (e.g., co-registration errors) and LI, but the predictions look reasonable for a first application to the new sensor. In this scene, there is over-prediction in the maritime region and under-prediction for some regions with lightning initiation. But we believe that with fine-tuning methods on a limited amount of FCI and LI data, LightningCast will perform well with MTG data without a significant re-training.

For users who want to run LightningCast on these sensors, the CSPP-Geo LightningCast package will soon have a patch that will enable it work fully with GOES-19, and an update is planned for full support of MTG data, though the date is not known at this time.

H/T: LightningCast software has made substantial use of the Satpy library to read and visualize data from geostationary satellites such GOES-R, MTG, and Himawari.

View only this post Read Less

Using Day Cloud Phase Distinction RGB fields to identify precipitating Lake-Effect snow bands

GOES-16 Day Cloud Phase Distinction RGB imagery at 1801 UTC on 6 January 2025, above, show evidence (in greenish yellow) of a glaciated band of cloudiness that is a Lake Effect snow band that deposited from 3-6″ over extreme southeast Wisconsin, in Kenosha and Racine counties. The toggle with the radar emphasizes how Day... Read More

GOES-16 Day Cloud Phase Distinction and Composite Reflectivity, 1801 UTC on 6 January 2025 (Click to enlarge)

GOES-16 Day Cloud Phase Distinction RGB imagery at 1801 UTC on 6 January 2025, above, show evidence (in greenish yellow) of a glaciated band of cloudiness that is a Lake Effect snow band that deposited from 3-6″ over extreme southeast Wisconsin, in Kenosha and Racine counties. The toggle with the radar emphasizes how Day Cloud Phase Distinction can be used (in daytime) to highlight precipitating lake-effect snow bands. Visible imagery at the same time is shown below. The character of the precipitating clouds is different, and that might help you identify the precipitating clouds from the non-precipitating ones.

GOES-16 Band 2 Visible (0.64 µm) imagery, 1801 UTC on 6 January 2025 (Click to enlarge)

The use of Day Cloud Phase Distinction to highlight precipitating clouds has been discussed before on this blog, here and here and here, for example.

View only this post Read Less

Disturbed weather near the Samoan Islands

Hourly GOES-18 infrared imagery (10.3 µm), above, shows the development of strong convection to the south of the Samoan Islands during the morning hours of 6 January (on American Samoa) or 7 January (Independent Samoa). Is this the start of a tropical system? Total Precipitable Water (MIMIC TPW) imagery from microwave data,... Read More

GOES-18 Clean Window infrared (Band 13, 10.3 µm) imagery, 0000 UTC on 5 January 2025 through 1500 UTC 6 January 2025 (Click to enlarge)

Hourly GOES-18 infrared imagery (10.3 µm), above, shows the development of strong convection to the south of the Samoan Islands during the morning hours of 6 January (on American Samoa) or 7 January (Independent Samoa). Is this the start of a tropical system? Total Precipitable Water (MIMIC TPW) imagery from microwave data, below (TPW estimates from GOES-18 require clear skies that aren’t occurring during this time in the domain shown), show the rich moisture of the South Pacific Convergence Zone sagging south through the Samoan Islands. GFS model winds that are used to construct hourly MIMIC TPW fields suggest, perhaps, the beginnings of a cyclone circulation as well.

MIMIC Total Precipitable Water estimates, 1500 UTC 5 January – 1400 UTC 6 January 2025 (Click to enlarge)

Scatterometry winds can be used to determine the presence of a low-level circulation center. The plots below, from this site, show MetopB / MetopC / OSCAT3 scatterometry for 05/06 January. The challenge, as always is that overpasses miss: the final MetopB overpass in the animation, for example, misses the circulation entirely. It is sampled, however, by MetopB, MetopC and OSCAT3 between 2000 and 0000 UTC on 5/6 January when the circulation was near 178oW, 16oS.

Scatterometry over the South Pacific from Matop B (20238 UTC), MetopC (2133 UTC) on 5 january and from OSCAT3 (0010 UTC), MetopB (0907 UTC) and MetopC (1004 UTC) on 6 January 2024 (Click to enlarge)

The RSMC (Regional Specialized Meteorological Center) in Fiji notes that the system may strengthen slowly; that discussion is shown below.

Tropical Disturbance Summary from Fiji RSMC, 0900 UTC on 6 January 2024 (Click to enlarge)

Although SSTs are warm, the region of favorable deep layer shear (shown below from 0000 UTC and 1200 UTC 6 January 2024 from this source) is very narrow, and it shrinks during the 12 hours shown.

Deep Layer Shear (850-200 mb) at 0000 UTC (left) and 1200 UTC (right), 6 january 2024 (Click to enlarge)

View only this post Read Less