EUMETSAT Meteosat-9 Infrared Window (10.8 µm) images (above) showed Category 4 Cyclone Chido as its eye moved across the small island of Mayotte (airport identifier FMCZ) in the Mozambique Channel around 0730 UTC on 14th December 2024 — and went on to make landfall just south of Penba, Mozambique (airport identifier MQPB) around 0400 UTC on 15th December. Chido traversed increasingly warmer sea surface temperatures (source) as it approached Mozambique.

As Cyclone Chido passed over Mayotte, the airport reported wind gusts of 92 kts (106 mph) as the eye approached and 91 kts (105 mph) as the eye departed (below).

Shortly before Chido made landfall in Mozambique, a Synthetic Aperture Radar (SAR) image at 0253 UTC (below) indicated that a derived maximum wind speed of 123.84 knots was present in the SE quadrant of the eyewall (source).

View only this post Read Less

1-minute Mesoscale Domain Sector GOES-18 (GOES-West) Water Vapor (6.9 µm) images (above) showed a mid-tropospheric shortwave trough that was moving inland across central/northern California — along with associated surface warm and cold frontal features on 14th December 2024. Sporadic lightning activity within a few bands of convection was indicated by GLM Flash Points.  Of particular interest was the Tornado Warning (red polygon) that was issued for San Francisco (possibly the first Tornado Warning issued for San Francisco proper?). There were several reports of strong winds across the Bay Area, most notably a gust to 72 knots (83 mph) at San Francisco International Airport.

1-minute GOES-18 Infrared (10.3 µm) images (above) included plots of SPC Storm Reports across the area.

Later in the day, a low-topped thunderstorm produced an EF1-rated tornado at Scotts Valley, the location of which was shown in 1-minute GOES-18 Visible (0.64 µm) and Infrared images (below).

?Preliminary Damage Survey Conducted. EF1 tornado observed in Scotts Valley this afternoon, December 14, 2024. The most severe damage was observed along Mt Hermon Rd. Full info: https://t.co/RQIwRzlVFk #cawx #scottsvalley pic.twitter.com/gs48BsaVrr

— NWS Bay Area ? (@NWSBayArea) December 15, 2024

View only this post Read Less

1-minute Mesoscale Domain Sector GOES-18 (GOES-West) Shortwave Infrared (3.9 µm) images (above) displayed a pronounced thermal signature associated with the Franklin Fire, which began burning just north-northwest Malibu, California around 0644 UTC on 10th December 2024 (or 10:24 PM PST on 9th December). This wildfire was driven by strong Santa Ana winds, which helped it to increase rapidly in size and intensity — in fact, the Franklin Fire began to exhibit 3.9 µm brightness temperatures of 137.88ºC (the saturation temperature of GOES-18 ABI Band 7 detectors) beginning at 0855 UTC (below), which persisted until 0947 UTC.

About 12 minutes after the Franklin Fire began to exhibit a thermal signature on GOES-18 Shortwave Infrared imagery, a RAWS site just east of the wildfire reported a wind gust of 52 mph at 0656 UTC (below). About 2.5 hours later, a RAWS site just northwest of the fire reported a wind gust of 50 mph at 0931 UTC. In addition to the strong winds, relative humidity values at those nearby RAWS sites were generally 10% or less.

Since the Franklin Fire began and rapidly intensified during the nighttime hours, its thermal signature was also apparent in the Near-Infrared 1.61 µm and 2.24 µm spectral bands (below).

1-minute GOES-18 True Color RGB images from the CSPP GeoSphere site (below) revealed several pyrocumulus jumps over the Franklin Fire, in addition to a dense smoke plume drifting offshore.

View only this post Read Less

Fog and Low Clouds are an important hazard with respect to air and surface travel. How can these obstructions to visibility be highlighted from satellite? The toggle above shows the Night Fog Brightness Temperature Difference and the Night Microphysics RGB, popular satellite products to detect regions of fog. Blue regions in the Night Fog brightness temperature difference are regions where clouds with liquid water droplets exist: the brightness temperature difference is much larger than zero because liquid cloud droplets do not emit 3.9 µm energy as a blackbody would, but those same cloud droplets do emit 10.3 µm energy nearly as a blackbody would. The conversion of the radiation sensed by the satellite assumes blackbody emissions, so that the 10.3 µm brightness temperature is close to the cloud-top temperature, but the 3.9 µm brightness temperature (at night) is significantly colder. This brightness temperature is the ‘green’ component to the Night Microphysics RGB: low clouds will show as yellow where the atmosphere is relatively cold (for example over northwest Wisconsin and east-central Colorado) and more of a cyan color where the atmosphere is comparatively warm (central to southwestern Arkansas, for example). Are these the only regions where you might expect fog? What is happening under the high clouds over Oklahoma (depicted as red in the RGB) or the mid-level clouds over Mississippi (purple in the RGB)? One could look at surface observations, as shown below in the toggle, or at webcams, to determine where fog exists. The toggle below shows that fog exists under the high clouds (black enhancement) and under low clouds (blue/cyan enhancement), but the Brightness Temperature Difference field (and the RGB) have very different signals.

---

GOES-R has a level-2 Fog/Low Cloud detection product, IFR Probability. It combines information about clouds (from the satellite) with information about low-level saturation from the Rapid Refresh Model. The toggle below shows IFR Probability fields with observations. The flat solid orange field over central Oklahoma northeastward to Kansas City is a typical look for the field that is driven mainly by model output — this is where high clouds prevent infrared satellite detection of low-level clouds, but because low-level model fields are near saturation, it’s likely that IFR conditions are present (as shown in the observations). The deeper red values over southeast Oklahoma and parts of the Red River valley is more pixelated, reflecting the ability of the satellite to detect low clouds in that region. Note also how the IFR Probability field has little signal over the clouds in southeastern CO — because the Rapid Refresh model there shows no low-level saturation: that cloud is likely stratus that is elevated off the surface.

---

Make sure the satellite-based fog detection product you use is appropriate for the environment, and if possible, verify the satellite estimates with surface observations from airports, or webcams. Use every product available.

View only this post Read Less