Turbulence probability is an aviation tool created (using machine learning techniques) at CIMSS to diagnose the likelihood of Moderate Or Greater (MOG) turbulence at least once during a 10-minute period. The image above shows the 1455 UTC MOG Turbulence Probability along with pilot reports (PIREPS) of turbulence, taken from this website. Turbulence Probability fields are also in AWIPS, and the 1500 UTC image is shown below.

There are frequently features in the water vapor imagery (or in visible, or near-infrared, imagery during the day) that have a known association with turbulence. The turbulence probability field is toggled below with the 6.19 µm upper-level water vapor infrared imagery, and beneath that with the 1.38 µm “cirrus band” near-infrared imagery. Striated features that are apparent in, for example, this event from 28 February, are not obvious.

MOG Turbulence Probability also includes information from the GFS: temperature, height, and winds from 850 mb to 50 mb! (Such GFS fields are especially important when using GOES-17 data during times when the Loop Heat Pipe malfunctions leads to data loss over the Pacific.) The toggles below show the relationship between the Turbulence Probability and upper-tropospheric stability (as diagnosed by the 400-300 mb lapse rate), and the also the pressure on the 1.5 PVU surface. Turbulence is occurring just Equatorward of a slope in the tropopause, in a region of weak stability.

GOES Data can also be used to diagnose wind speeds in the upper-troposphere. Peak winds in the 350-450 mb layer, shown in a toggle below with the MOG Turbulence Probability, are 100-120 knots from southeastern North Dakota into northwestern Wisconsin.

How did this potential for turbulence (and strong winds) affect air traffic? Consider the path of one late-morning flight, Delta Flight 867 from Minneapolis to Seattle. Its path is shown below for February 28th, and for March 2nd, courtesy of FlightAware. The 2 March flight was diverted south to avoid the strong winds and potential for turbulence.

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You might ask: Why are the upper-tropospheric lapse rates shown? The reason is because they align the use of the 6.19 µm imagery. The (new and improved!!) CIMSS Weighting Function page shows that at 1200 UTC, much of the signal in the upper-level water vapor imagery (in brown in the plot below) around Minneapolis was coming from the 300-400 mb layer. A plot using GFS data at 45^o N, 95^o W, shows a similar distribution.

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AWIPS imagery in this blog post was created using the NOAA/NESDIS TOWR-S AWIPS Cloud Instance.

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GOES-T was launched from the Kennedy Space Center in Florida at 2138 UTC on 01 March 2022 — and distinct reflectance and/or thermal signatures of the Atlas V rocket launch were evident in 30-second images from all 16 ABI spectral bands of GOES-16 (GOES-East) (above).

One of the more interesting aspects was the long trail of superheated air + water vapor in the wake of the Atlas V booster engines, which could be seen drifting slowly northward in GOES-16 Shortwave Infrared (Band 07, 3.9 µm) and Upper-level Water Vapor (Band 09, 6.2 µm) images (below). The warmest 3.9 µm Shortwave Infrared brightness temperature sensed by GOES-16 was 38.78ºC at 2139 UTC.

30-second scan were also available from GOES-17 (GOES-West) — reflectance and/or thermal signatures were also evident in imagery from all 16 of those ABI spectral bands (below). The warmest 3.9 µm Shortwave Infrared brightness temperature sensed by GOES-17 was 38.58ºC at 2139 UTC. 

A comparison of “Red” Visible (0.64 µm) images from GOES-17 and GOES-16 is shown below — and as in the 16-band examples above, the images are displayed in the native projection of each satellite (in other words, they are not re-mapped to a common map projection). Due to the much higher oblique viewing angle from GOES-17, parallax made the rocket condensation plume appear much longer (and extend farther to the east).

However, a toggle between GOES-16 and GOES-17 Shortwave Infrared images at 21:38:55 UTC (below) — both displayed in a common map projection — revealed the large eastward displacement of the Atlas V rocket booster engine thermal signature with GOES-17 (the parallax shift magnitude was 35 km).

The Atlas V rocket’s rapid rate of ascent was apparent when looking at the first 1 minute (at 30-second intervals) of GOES-16 True Color RGB images visualized using CSPP GeoSphere (below).

GOES-16 Plume RGB imagery (below) is an effective product that aids in the identification of both the rocket condensation plume and the booster engine thermal signature.

 

True Color RGB images from GOES-16 (above) and GOES-17 (below) highlighted the rocket condensation plume. 

Additional imagery and information on the GOES-T launch can be found on the Satellite Liaison Blog.

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The image above (from 2100 UTC on 28 February 2022) and below (from 0930 UTC on 1 March 2022) toggle between low-level estimates of 1000-mb dewpoint and GOES-16 IFR Probability fields. Is there a general relationship between the two? At first blush, it does seem like the IFR Probability fields are affected by the strong gradient in low-level temperature, where the dewpoint drops from the teens (^oC, grey/blue to cyan in the enhancement) to the single digits (purple and white in the enhancement). Note that SSTs in the region where the 1000-mb dewpoints are in the single digits are between 10 and 14 C at both ~2100 UTC 28 February and ~0930 UTC 1 March (ACSPO SSTs at the link are derived from Direct Broadcast data from CIMSS and are available via an LDM feed).

The toggle below compares gridded NUCAPS estimates of 1000-mb relative humidity with Low IFR Probability fields. There again seems to be a relationship. How robust that relationship is is to be determined. This is the first in a series of blog posts that compares these two fields, as part of a way of better forecasting fog over the oceans.

AWIPS imagery in this blog post was created using the NOAA/NESDIS TOWR-S AWIPS Cloud Instance.

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GOES-16 (GOES-East) “Red” Visible (0.64 µm), Near-Infrared “Cirrus” (1.37 µm), Mid-level Water Vapor (6.9 µm) and “Clean” Infrared Window (10.3 µm) images (above) displayed a pattern of transverse cloud banding over parts of the Upper Midwest on 28 February 2022.  This type of transverse banding is often a signature of an enhanced potential of middle- to high-altitude turbulence — so not surprisingly, there were several pilot reports of light to moderate turbulence in the vicinity of these cloud bands.

A closer view of the transverse banding over Minnesota and Wisconsin at 2301 UTC is shown below.

Hourly GOES-16 Near-Infrared “Cirrus” images with contours of RAP40 model Maximum Wind isotachs (below) indicated that this pattern of transverse banding was occurring within the left exit region of an anomalously-strong anticyclonically-curved upper tropospheric jet streak — consistent with the findings of a study by Trier and Sharman.

Such transverse banding cloud features are frequently observed around the periphery of decaying MCSs (for example, July 2020 , June 2018 and July 2016) and in the vicinity of strong upper-tropospheric jet streaks (for example, February 2020 and March 2016).

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