Strong Santa Ana winds and dry conditions caused multiple fires in Los Angeles area on 7-8 January 2025 (here is a blog post on the Palisades fire, for example). What information on these fires is provided by the Next-Generation Fire System (NGFS) website? The Alerts Dashboard at that site shows the latest Thermal Anomalies; when a previously un-detected fire develops, it is highlighted on that website. Consider the screenshot below, from ca. 0214 UTC on 7 January. Two separate fires are indicated in Los Angeles county; the county name is highlighted in magenta because Los Angeles County is ‘Rank 1’ as shown at the bottom of the page: SPC has highlighted the county as one defined by Extreme Fire Weather criteria, and/or there is a Red Flag warning. In other words, the likelihood of rapid fire growth is present. Other counties listed show less hazardous ranks. For Los Angeles County at 0214 UTC, the oldest detection (of the Palisades fire), from 7h 48 minutes before, occurred with GOES-18 Mesoscale Sector 2; GOES-18 CONUS data detected this fire 5 minutes after that, and GOES-16 CONUS’s detection lagged the GOES-18 Mesoscale sector detection by 16 minutes! The lesson from this: Use a mesoscale sector when possible for fire detection.

At 1439 UTC, the Alerts Dashboard for Los Angeles County shows much more activity, with at least three new thermal anomalies shown. For all the fires, the earliest detection was achieved by the GOES-18 Mesoscale domain (1-minute imagery) sector.

Clicking on the ‘Satellite Imagery’ box for the detection that’s 4 lines down in the image below — GOES-18 Mesoscale Sector 2, from 8h and 26 m before the time of the ‘Last Updated’ time (1439 UTC) yields the display below, NGFS Microphysics imagery centered on the new detection (to become the ‘Hurst’ Fire) between I-210 and I-5 south of Santa Clarita. The very obvious ongoing Palisades fire — near the coast — and the Eaton fire — near Altadena/Pasadena — are present. The focus for the figure below, however, is the newly-developing fire in the center of the image that is circled in the toggle. A user would already know of the two other fires ongoing.

On the right hand side of this display are right/left arrows that let a user step forward and backward with time for up to two hours. The slow toggle below shows the Night Microphysics for this fire at 0610 (no detection), 0611 (first detection), 0615 and 0811 UTC on 8 January. The fire grew rapidly.

Note the link on the side: ‘Open in Real Earth’. When that’s clicked, a new tab appears in your browser with the RealEarth display as shown below. The functionality of RealEarth allows a user to change the start/end times of the images loaded. RealEarth adds flexibility to the times displayed.

If you mouse over a pixel in RealEarth, the data can be probed, and the results at 1031 UTC are shown below for this fire. The land surface and potential fuels for the detected fire are shown in piechart form (this probe feature is also available at the NGFS website).

The RealEarth website makes it relatively simple to zoom out and see how things are changing over a long period of time. The toggle below, showing 0710 and 1710 UTC imagery, shows how the three fires have changed in those 10 hours. All three fires grew in size during these ten hours.

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This is a life-threatening fire event over Los Angeles county. Residents should heed warnings from local officials. For more information, view the NWS Los Angeles website. In particular, very strong winds will lead to rapid fire spread, and inhibit fire-fighting efforts.

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Antonio B. Won Pat International Airport on Guam experienced a record wet 7 January this year when 3.32″ of rain fell, mostly between 1700 UTC/6 January and 0500 UTC/7 January. Himawari-9 Band 13 imagery, above, for the 3 days ending at 0000 UTC 08 January 2025, show a region of thunderstorms approaching the Marianas. A slower animation covering the times of the heavy rainfall is below; the heavy rain was fairly isolated; much of the Marianas remained dry.

A closer look using 10-minute Himawari-9 Infrared images centered on Guam International Airport PGUM (below) showed the series of convective storms that produced the bulk of the record-setting rainfall (plot of surface observations). Cloud-top infrared brightness temperatures briefly reached -80ºC (violet pixels) with one of the convective elements.

It is noteworthy that the Total Precipitable Water value of 63.33 mm (2.49 in) derived from 7 January / 0000 UTC PGUM rawinsonde data exceeded the previous record TPW value of 2.34 in for that date/time (based on SPC climatology).

10-minute Himawari-9 Visible and Infrared images (below) displayed the rapid development of a convective cell which produced a brief period of heavy rain at PGUM as it traversed the island.

The large-scale conditions that allowed the heavy rain were well-forecast. GFS forecasts of the Galvez-Davison Index (GDI) (source) from the forecast started at 1800 UTC on 4 January 2025 are shown below, and they show a narrow tongue of higher values moving over the Marianas that corresponded with the time of the heavy rains.

MIMIC Total Precipitable Water (TPW) fields, below, from 0000 UTC 6 January to 0000 UTC on 8 January 2025, show abundant moisture moving over Guam (at 144^oE Longitude, 13.4^oN Latitude)

The Guam forecast office of the National Weather Service (WFO GUM) receives polar orbiting data from a Direct Broadcast antenna onsite (signals are processed by CSPP software). True-color VIIRS imagery from ca. 0300 UTC on 7 January is shown below, and a line of convection bisecting Guam is apparent.

CSPP also processes microwave imagery, and the computed MIRS estimates of TPW are shown below. The MIRS diagnostics also show the enhanced amount of TPW over the southern Marianas as the rain fell. TPW values dropped quickly by mid-day (UTC) on the 7th (at the end of the animation below).

My thanks to Landon Aydlett, WCM on Guam for alerting me to this wet event, and to Douglas Schumacher, CIMSS, for the Direct Broadcast imagery.

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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 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.

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

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).

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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 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.

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.

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