Low-Earth Orbit satellite views of Ian as it formed, and comparisons to Geostationary imagery

September 26th, 2022 |

Polar-orbiting satellites have microwave detectors that give important information about the low-level structure of an evolving tropical cyclone. If high clouds are omnipresent, it can be difficult for an analyst to diagnose storm strength with accuracy. Microwave energy penetrates clouds, however, and low-earth orbit (LEO) observations of microwave frequencies can reveal much about a storm’s structure.


24 September: South of Haiti


Consider the imagery below, showing the cluster of thunderstorms associated with then-Tropical Storm Ian south of Haiti. Based on just the still infrared image (admittedly, this would be easier with an animating image!), where would you place the center? Microwave data — 36.5 GHz and 89 GHz data from GCOM-W1 (from the AOML Direct Broadcast site here) suggest a center in between the top large regions of cold cloud tops in the infrared imagery (the 0900 UTC discussion has a center near 14.7oN, 73.5oW). MIMIC Tropical Cyclone imagery (from this link) for Ian on 24 September (here) can help a user determine where the center is as well.

GOES-16 ABI Band 13 Infrared (10.3 µm) imagery, and GCOM-W1 AMSR-2 Microwave imagery (36.5 and 89.0 GHz), 0620 UTC on 24 September 2022 (Click to enlarge)

25 September: Southwest of Jamaica


One day later, imagery from ABI and GCOM-W1 show a better-defined tropical system at 0700 UTC (Here’s the NHC discussion from 0900 UTC, at which time the center was at 14.9oN, 78.8oW). Even from the still ABI image, one could infer a center based on the spiral bands. Microwave information (36.5 and 89.0 GHz) certainly will increase confidence. Indeed, the low-level microwave signal (i.e., from 36.5 GHz) suggests a center very near the 0900 UTC location. The MIMIC TC animation from 0000 UTC 25 September – 0000 UTC 26 September (link) is showing a stronger signal for a center as well.

GOES-16 ABI Band 13 Infrared (10.3 µm) imagery, and GCOM-W1 AMSR-2 Microwave imagery (36.5 and 89.0 GHz), 0700 UTC on 25 September 2022 (Click to enlarge)

26 September: south of Western Cuba


NOAA-20 ATMS imagery (88 GHz) over Ian, 0606 and 0746 UTC on 26 September 2022 (Click to enlarge)

The LEO coverage on 26 September is a great example of why multiple LEO satellites are vital. The early-morning coverage from NOAA-20 is shown above; the gap between the two satellite passes is in an unfortunate spot for monitoring this tropical cyclone! However, Suomi NPP orbits overlap NOAA-20, and on this day Suomi NPP overflew the center of the storm, as shown below. The cadence was NOAA-20 to the east, 45 minutes later Suomi-NPP over the center, 45 minutes later NOAA-20 to the west. Here is an animation of the three passes. Polar monitoring capabilities will receive a big boost when JPSS-2 (slated to become NOAA-21) is launched (tentatively scheduled for 1 November 2022).

Suomi-NPP ATMS Microwave Imagery, 88.0 GHz, 0656 UTC on 26 September 2022 (Click to enlarge)

Ian at 0700 UTC on 26 September, below, is on the cusp of being upgraded to a hurricane (0600 UTC intermediate advisory), and an animation of the Band 13 imagery (a still image is shown below for comparison to the ATMS imagery) shows the center of rotation even though an eye is not present in the infrared (although one in the microwave).

GOES-16 ABI Band 13 Infrared (10.3 µm) imagery, and Suomi-NPP ATMS Microwave imagery (88.0 GHz), ca. 0700 UTC on 26 September 2022 (Click to enlarge)

ATMS and AMSR2 imagery as shown above are created from passive microwave sensors; that is, the sensors are detecting the microwave imagery emitted by the ocean, land, clouds and atmosphere. Other LEO satellites emit energy (“ping”) in the microwave and listen for a return signal. This leads to both scatterometry (not shown, as from the Advanced Scatterometer — ASCAT — instrument on Metop-B and Metop-C — available here) and Synthetic Aperture Radar imagery (available here for tropical cyclones), and shown below. The image below shows infrared and GLM imagery for then-newly upgraded Hurricane Ian (link). Although a distinct eye is still not present in the infrared imagery, SAR wind data defines an obvious region of reduced winds. Maximum SAR winds in this image are just above 70 knots.

GOES-East ABI Band 13 Infrared imagery (10.3 µm), GLM 1-minute aggregate Total Optical Energy (TOE) and RSAT-2 SAR Winds over Ian, 1110 UTC on 26 September 2022 (Click to enlarge)

VIIRS and ATMS imagery of Hurricane Ian on 27 September is here. For the latest information on Hurricane Ian, please refer to the National Hurricane Center. People in southern (and especially southwestern) Florida should be paying very close attention to this storm.

Hurricane Darby in the East Pacific Ocean

July 11th, 2022 |

GOES-17 “Red” Visible (0.64 µm, top) and “Clean” Infrared Window (10.35 µm, bottom) images [click to play animated GIF | MP4]

1-minute Mesoscale Domain Sector GOES-17 (GOES-West) “Red” Visible (0.64 µm) and “Clean” Infrared Window (10.35 µm) images (above) showed the evolution of the eye of Hurricane Darby as it moved westward across the East Pacific Ocean on 11 July 2022. Mesovortices were evident within the eye, along with a stadium effect eye structure — as Darby ended its period of rapid intensification and leveled off as a Category 4 storm (ADT | SATCON). Darby was moving through an environment of low wind shear and across relatively warm water (SST | OHC), factors which favored intensification.

A NOAA-20 VIIRS Infrared Window (11.45 µm) image from RealEarth (below) revealed an arc of slightly colder cloud tops (shades of white within dark black) in the northern portion of the eyewall.

NOAA-20 VIIRS Infrared Window (11.45 µm ) image at 2129 UTC [click to enlarge]

A NOAA-20 ATMS Microwave (183 GHz) image from the CIMSS Tropical Cyclones site (below) also showed the compact eye, along with a band of precipitation spiraling northward.

NOAA-20 ATMS Microwave (183 GHz) image at 2129 UTC [click to enlarge]

Satellite detection of ice

February 25th, 2022 |

A colder-than-normal February over the western Great Lakes (through the 27th, Duluth is 10o F below normal; Marquette is 5o F below normal; Green Day is 2o F below normal; Cleveland is 1o F below normal) has fostered a growth in ice cover over the Lakes (This figure, from here, for example). How can satellites detect that ice, especially for a region where winter-time cloudiness is notorious? In general, there are two different ways to detect ice: Visible/Infrared imagery and Microwave imagery. The toggle above shows Advanced Technology Microwave Sounder (ATMS) ice detection (using MiRS algorithms and data from Suomi-NPP (1807 UTC) and NOAA-20 (1859 UTC)) over the Great Lakes on 25 February 2022. (These data come from the Direct Broadcast antenna at CIMSS, and are processed using CSPP to produce AWIPS-ready tiles that are available via an LDM feed). A big challenge with this field is the very large ATMS footprint. Note that these sea-ice concentration values are quantitative: values change based on how much ice is within the footprint but are also dependent on view angle.

VIIRS data (as shown at the VIIRS Today website, for example) can also be used to infer regions of ice in a qualitative sense, as shown below. The true color imagery shows possible ice features over the lakes. It’s a challenge, however, to use a single VIIRS image to distinguish (mostly) stationary ice from (usually) moving clouds. Multispectral VIIRS imagery means (via the use below of the 2.25 µm M11 band) ice features are cyan colored and can be qualitatively distinguished from clouds. Consider, for example, the color difference in the False Color image between the clouds over eastern Lake Superior (white in both True- and False-Color) and near-shore ice over southern and eastern Lake Superior (white in the True-Color and cyan in the False-Color). There are also VIIRS-based Ice Concentration products that can be computed in clear skies.

Suomi-NPP VIIRS True- and False-Color imagery over the Great Lakes, 1806 UTC on 25 February 2022 (Click to enlarge)

For cloudy regions, Advanced Baseline Imagery can be used to create estimates of Ice Surface Temperature and Ice Concentration. Quantitative estimates such as these give more information than the qualitative estimates shown above. These estimates at present are only created hourly; in partly-cloudy regions, that cadence is sufficient to give lake-wide quantitative estimates of ice coverage and temperature. CONUS imagery — with a 5-minute time cadence — and mesoscale sectors — with 1-minute cadences — can be used to monitor (in a qualitative sense) how ice is moving (as shown link, for example). High temporal-resolution imagery is important because ice sheets can change rapidly under strong winds, as shown in this tweet. At high latitudes, there are also ways of monitoring ice motion via polar orbiters (link).

GOES-16 Estimates of Ice Surface Temperatures, 1800 and 1900 UTC on 25 February 2022 (Click to enlarge)
GOES-16 Estimates of Ice Concentration, 1800 and 1900 UTC on 25 February 2022 (Click to enlarge)

A much higher-resolution method of viewing ice (again, in a qualitative, not quantitative sense) in regions of both clear and cloudy skies, day or night, is through the use of Synthetic Aperture Radar (SAR). Data are available for each Great Lake at this link. Imagery for each Lake over the past days is available there, albeit infrequently (usually around 0000 and 1200 UTC only) and over small domains. This qualitative imagery, however, is very high-resolution and gives very impressive details. Imagery over Lake Erie is shown below.

RCM estimates of Lake Erie Ice, 24-27 February 2022 (Click to — greatly! — enlarge)

VIIRS and ABI give both qualitative (false-color, visible imagery) and quantitative (ice concentration and ice temperature) depictions of ice over the lakes — or over coastal waters around Alaska. Microwave data also gives quantitative estimates (ice concentrations with large microwave footprints) and qualitative estimates (SAR data). Use all products to create a clear picture of ice coverage.

Ozone and the airmass RGB

December 13th, 2021 |
GOES_17 airmass RGB, 2200 UTC on 12 December 2021 (Click to enlarge)

A GOES-17 airmass RGB, above, shows a strong feature in the Gulf of Alaska. It’s common to associate the orange and purple regions within that polar feature (that is accompanied by cloud features consistent with very cold air aloft) with enhanced ozone. What products are available online to gauge the amount of ozone?

The OMPS instrument on board NOAA-20 (and on Suomi-NPP) senses in the ultraviolet (from 250-310 nm) to compute ozone concentration. (For more information on OMPS, refer to this document) The figure below, taken from this Finnish website, shows ozone concentration for the 24 hours ending at 0110 UTC on 13 December. A distinct maximum is apparent over the Gulf of Alaska. Note the northern terminus of the observations that are related to the time of year: there is little Sun north of 60 N. The data for this were downloaded from the Direct Broadcast site at GINA at the University of Alaska-Fairbanks. OMPS data are also available (from Suomi-NPP) at NASA Worldview.

To determine the time of the data in the image below, consult the NOAA-20 orbital paths here. This image (from that site) shows a NOAA-20 ascending overpass between 2235 and 2245 UTC over the Gulf of Alaska.

Daily Composite of Ozone concentration for the 24 hours ending 0111 UTC on 13 December 2021 (click to enlarge)

NOAA-20 also carries the Cross-track Infrared Sounder (CrIS) and Advanced Technology Microwave Sounder (ATMS) instruments that are used to create NUCAPS vertical profiles; one of the trace gases retrieved in this way is ozone. The distribution of ozone (with values in regions where it was dark) from NUCAPS is shown below (from this website maintained by SPoRT), and it corresponds roughly with the OMPS estimates shown above.

Gridded NUCAPS estimates of ozone, 2217 UTC on 12 December 2021 (Click to enlarge)

Conclusion: The assumption that upper-tropospheric ozone values are large in regions where the airmass RGB is tinted red or purple is a good assumption, especially if other structures in the RGB — such as cumulus cloud development in the cold air — reinforce the idea that an intrusion of stratospheric air is occurring. The strong storm that this lowered tropopause is supporting is accompanied by a moist feed of air moving into central California, as shown below by MIMIC total precipitable water fields.

Total Precipitable Water, 2200 UTC on 12 December 2021 (Click to enlarge)

Gridded NUCAPS fields are being tested within RealEarth, as shown below. They should be generally available soon.

RealEarth Gridded NUCAPS estimates of ozone, 2217 UTC on 12 December 2021 (Click to enlarge)