When you hear about the lake effect, you almost always think about the Great Lakes, whose impacts on local weather and climate are well-known across the upper Midwest and into the northeast. It may, then, seem odd to consider a lake effect event in North Dakota. However, if conditions are right, smaller bodies of water can also create lake effect snow.

Lake Sakakawea is a reservoir that was formed in the 1950s when the two-mile long Garrison Dam was built across the Missouri River for flood control and hydroelectric purposes. While it’s the country’s third largest reservoir by volume, its long, narrow shape lends it the form of a very wide river more than a traditional lake.

With a polar air mass plunging southward from Canada, surface temperatures in central North Dakota were very cold on the afternoon of 1 December 2025. Even though it was daytime on the first day of December, surface temperatures were in the single digits and numerous stations had the potential to set new records for lowest daily maximum temperature. This was a sharp contrast to a little over a week earlier; on the 23rd of November, the high temperature at Garrison was 57 F.

Therefore, while the land surface was very cold, the lake was still relatively warm as its large thermal mass inhibited its heat loss. This made for a perfect set up for a lake effect event as the following visible animation from GOES-19 shows. Lake Sakakawea is the dark snake-like form in the middle of the image, and clouds can be streaming to the southeast from the southern portion of the lake. Note that the winds in the region are largely westerly, ensuring enough fetch along the lake to produce the effect.

Recent snows over the region had previously blanketed the area in white, meaning there was very little visible contrast between the clouds and the snow. Since these clouds are also very shallow, they have very little thermal contrast with the surrounding land, and thus the clouds are very difficult to discern using single channel infrared imagery as well. However, certain RGB products are well-suited to discriminating between snow and cloud, as can be seen in this view of the Day Snow-Fog product. Here, the lavender of the low clouds pops against the red of the snow-covered land.

It’s important to note that, as its name suggests, this product can only be used during the day. This is because of its dependence on multiple shortwave channels. At night, the 0.87 and 1.61 micron channels have no reflectance, and the interpretation of the 3.9 micron channel changes from reflectance to emission. These animations were recorded late in the day and wold soon become unreliable for further interpretation. A better product to use after sunset is the Night Microphysics RGB seen below. In this case the land has cooled even further with sunset; the temperature at Garrison on the northeastern edge of the lake dropped to 1 F at the time of this animation. This served to deepen the lake/land temperature gradient and further enhance the lake-induced dynamics.

Throughout this blog post, this has been called a lake effect snow event. However, there is no radar evidence that any precipitation formed from this. This animation from the Bismarck NEXRAD radar covers the area were we’d expect to see snow, but there’s nothing there beyond the expected ground clutter.

However, observers are reporting snow downwind of the lake. That’s visible in the station plots depicted in the GOES-19 animations at the start of this blog post. The asterisk in the station plot for Hazel, ND, indicates that snow was being observed at the same time that one of these lake-enhanced clouds was directly overhead.

So why are weather observers reporting snow when the radar says that it is clear? The answer is simple: lake effect snow events are shallow, and these highly localized lake effect events are even shallower. The radar beam gets higher above the ground the further away you get from the radar because of the tilt of the radar beam and the curvature of the earth. It’s approximately 60 miles from the NEXRAD in Bismarck to the shores of Lake Sakakawea, which means the beam is roughly 4500 feet above the ground at that distance. These shallow clouds easily slip beneath the lowest radar beam and produce snow that is undetected by the radar.

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On 28 November 2025, large regions of standing waves were present throughout the eastern seaboard. When air flows across mountainous regions it gets forced upward by orographic lift. The air cools as it rises due to adiabatic expansion. If the environment is largely stable, the upward motion is inhibited as the ascending air parcels find themselves too warm for the environment and so the air starts to sink. As it sinks, it warms due to adiabatic compression and eventually starts rising. This process can repeat itself many times as the air races hundreds of kilometers downstream of the initial range. While most commonly associated with the Rocky Mountains, they can occur over other, shorter landforms like the Appalachians. If the air is sufficiently moist, this can manifest itself as a series of parallel cloud bands, as can be seen in the GOES-19 True Color view. Note the ridged clouds that are particularly noticeable in Pennsylvania and Virginia. At the tops of these waves, when the air is at its coldest, condensation occurs. At the bottom, the cloud droplets evaporate as the air is warmed, leading to clear skies in between the ridges.

However, what if there’s not enough moisture for condensation to happen? Can these waves still be seen? If you’re looking using a water vapor channel, then the answer is yes. Look at the following animation of the 7.34 micron (low level water vapor) band from GOES-19. Note now in eastern Virginia and North Carolina, even though skies are clear the same wave pattern is visible. There’s even a particularly interesting feature in central Virginia where eastward-moving flow is creating its own waves that are intersecting with the westward flow over the Appalachian Mountains which is creating wave interference.

These events matter because these mountain waves are a significant cause of clear air turbulence (CAT). Turbulence associated with convection is easier for aircraft pilots and flight planners to identify and avoid since it is found in the vicinity of deep, moist convection. CAT, on the other hand, is not visible to the naked eye at standard visible wavelengths, but water vapor imagery can help pilots avoid these situations.

It’s important to note that the Channel 10 (7.34 micron) channel shown above is largely sensitive to low level water vapor. The waves depicted here are unlikely to disturb aviation too much as they are occurring at a level where most planes are just passing through on their way up to cruising altitudes or down to airports. However, these waves are still visible on the upper level water vapor channel, Channel 6 (6.19 microns).

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A EUMETSAT Meteosat-10 False Color RGB product from the NOAA/CIMSS Volcanic Cloud Monitoring site (above) showed the signature of a large volcanic cloud following the explosive eruption of Hayli Gubbi in Ethiopia, which began around 0830 UTC on 23 November 2025. Since this False Color RGB product uses the 8.7 µm spectral band (which is sensitive to SO₂ absorption) in its green component, shades of green exhibited by much of the larger eastward-moving cloud indicated a mixture of volcanic ash and SO₂ — while the shades of pink exhibited by the smaller northwest-moving cloud indicated that it was composed primarily of ash.

Sentinel-5P #TROPOMI measurements at ~11:00 UTC show most of the SO? emissions from #HayliGubbi spreading east in the upper troposphere. Plume contains ~44 kilotons of SO? (~0.04 Tg).

— Prof. Simon Carn (@simoncarn.bsky.social) 2025-11-23T17:53:45.223Z

A radiometrically retrieved Meteosat-10 Volcanic Ash Height product (below) indicated that maximum ash heights associated with the larger eastward-moving cloud were in the 18-20 km range — while the smaller northwest-moving cloud had ash heights generally in the 3-5 km range.

A Volcanic Ash Height product derived using higher-spatial-resolution VIIRS data from NOAA-21, Suomi-NPP and NOAA-20 (below) indicated that maximum ash heights of the larger cloud were in the 16-18 km range — which were closer to the height values listed in volcanic ash advisories (FL450 = 13.7 km; FL500 = 15.2 km) from the Toulouse VAAC.

A Meteosat-10 Ash Loading derived product (below) indicated that loading was quite high within the larger eastward-moving cloud, and generally low to moderate within the smaller northwest-moving cloud.

A Meteosat-10 Ash Effective Radius product (below) depicted the presence of larger ash particles within the higher-altitude cloud, in contrast to smaller ash particles within the lower-altitude cloud.

A toggle between Low-level (700-850 hPa) and High-level (200-700 hPa) Deep Layer Mean Wind or “Environmental Steering Product” (source) at 0900 UTC on 23 November (below) showed lower-tropospheric southeasterly winds and upper-tropospheric westerly winds that were responsible for the transport of the 2 different volcanic clouds.

===== 24 November Update =====

10-minute Full Disk scan JMA Himawari-8 Air Mass RGB images created using Geo2Grid (above) showed a signature of the SO₂-rich volcanic cloud as it emerged from over the northern Arabian Sea and moved northeast across parts of Pakistan, India, Nepal and finally the Tibet region of southwestern China on 24 November (2130 UTC Toulouse VAAC final advisory). Since the red component of the Air Mass RGB uses the 7.3 µm spectral band — which is also sensitive to SO₂ absorption — the Hayli Gubbi volcanic cloud appeared as brighter shades of magenta.

===== 26 November Update =====

The leading edge of the SO₂-rich Hayli Gubbi volcanic cloud (brighter shades of magenta) eventually began to appear along the western limb of GOES-18 (GOES-West) Air Mass RGB images on 26 November (above), as the volcanic cloud started to move eastward across the North Pacific Ocean (east of Japan).

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The residents of American Samoa found themselves in the early morning hours of 20 November 2025, as strong maritime convection moved into the region. There is no radar in the area, so satellite observations are critical for operational awareness and nowcasting. The Band 13 infrared view on GOES-18 showed a large array of vigorous convective storms stretching east-west across the near-equatorial Pacific.

While this product gives a solid qualitative view of where deep, moist convection is taking place, additional products can also further inform as to the intensity of the storms. One of these is the Day Convection RGB. The recipe for this product is designed to show red when clouds are high and green where cloud droplets are large. The combination of high clouds and large droplets is found in deep convective plumes, while the combination of red and green produces yellow. The following animation shows that relationship in action. You might note that this loop spans the sunrise. Since the product relies heavily on near-infrared and visible reflectance, it can only be used during the day. The lack of yellow at the start of the loop does not mean that there is no deep convection. Instead, it just means that the 3.9 minus 10.3 micron brightness temperature difference which comprises the green channel of this image in very small at night (unless something is on fire).

With no radar, satellites have to step in and help fill the gap. The GREMLIN product is a machine-learning retrieval of rainfall from satellite brightness temperature observations, designed to mimic the radars that forecasters find so familiar. The following loop is from GREMLIN as displayed on AWIPS for roughtly the same time as the previous animations. Note the pulses of yellow over and around the island of Tutuilia, corresponding with rain rates of 40 mm/hr (more than 1.5 inches per hour).

Satellites can also help judge the convective instability of the atmosphere. NUCAPS-retrieved thermodynamic profiles from polar-orbiting hyperspectral infrared and microwave sounding instruments provide valuable information about the atmosphere’s thermodynamic state. Since NUCAPS retrieves dozens of profiles simultaneously, it’s possible to analyze the profiles like a three-dimensional cube, taking horizontal slices and seeing how key parameters change horizontally as well as vertically. The next image shows the 850-500 mb lapse rate over the central Pacific as calculated by NUCAPS and displayed in AWIPS. The NUCAPS availability parameter is plotted on top as an array of red, blue, or green dots. The values in the middle of the convection are untrustworthy as neither the infrared nor the microwave sounders can penetrate the convective cores. Still, the reliable locations show lapse rates approaching 6 C/km. In the tropics, the moist adiabatic lapse rate is less than it is in the tropics as more latent heat lease means a slower lapse rate. Therefore, the observed lapse rates can still indicate instability

Clicking on any of the dots in AWIPS brings up the sounding and its associated stability indices. For one green dot near Pago Pago, American Samoa, the environment is clearly moderately unstable with CAPEs in the mid-to-upper 1000s and effectively no CIN to restrain convection.

This just continues a trend of record-setting precipitation in American Samoa, which has previously been discussed on the blog. The chart below shows the accumulated precipitation for so far in 2025 (blue), the wettest year before now (2020, magenta), and normal (brown). Already in 2025, the total rainfall has exceeded every single year save one despite still having a month to go.

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