GOES-19 today is positioned at 89.5^oW, the test position, but is presently scheduled to drift east to the GOES-East location at 75.2^oW. When on station in early April, it will become the operational GOES-East satellite. CIMSS scientists have been modifying CSPPGeo software to produce products, such as LightningCast probability (available online here, or, for GOES-16/GOES-18 in AWIPS), using GOES-19 data as input. The image above shows LightningCast probabilities from GOES-19 over a True Color image (a new feature of the latest beta). A comparison with GOES-16 (using Day Cloud Phase Distinction) is below. Differences in the fields are most likely due to view angle differences. You can read more on GOES-19 LightningCast probabilities here, and this blog post describes the (first) beta version of the software.

---

The new beta is available for download: https://cimss.ssec.wisc.edu/csppgeo/lightningcast_v1.0b2.html Comments and evaluations are welcome!

View only this post Read Less

5-minute CONUS Sector GOES-16 (GOES-East) Visible images (above) showed the strong winds — associated with the passage of a cold front — which produced widespread areas of blowing dust across parts of southern/eastern New Mexico and western/northern Texas on 03 March 2025. This blowing dust caused marked reductions in visibility — leading to closures of Interstates 10 and 25 near Deming KDMN and Las Cruces KLRU in southern New Mexico, in addition to multiple-vehicle accidents near Roswell KROW.

GOES-16 True Color RGB images from the CSPP GeoSphere site (below) provided a more distinct view of the dense blowing dust, which eventually stretched from northern Mexico to far southeast Colorado and far southwest Kansas. Note the plume of blowing sand whose source region was White Sands National Park in southern New Mexico.

After sunset, GOES-16 Nighttime Microphysics RGB images (below) showed that the leading edge of the airborne dust (highlighted by brighter shades of magenta) advanced as far northward as Nebraska and South Dakota. The Nighttime Microphysics RGB makes use of the 10.3-12.3 µm “Split Window Difference“, which is effective for dust detection.

View only this post Read Less

Sometimes, CIMSS Blog writers get emailed letter, like the one below (anonymized) forwarded along to CIMSS with a request

A long-dormant idea has resurrected itself in my mind, which is to look into the “biomass and carbon impact” (e.g. biomass and carbon knocked down) from some MCS and derecho type events.  We may have talked about this briefly some years ago.  Since we share an interest in NW PA, I thought I would ask if you know of any maps or diagrams that would show the affected area from the July 21, 2003 wind event…..of course it produced the tornado that brought down the Kinzua Bridge, but the event itself was much more widespread....

.....Is there an archived database of satellite imagery that would show the damage in NW Pennsylvania from the 21 July 2003 storm?

 

Your blogger first thought of the MODIS Today website — but those images “only” go back to late 2007. There are data sources that allow a reconstruction of those images, however. The big challenge in accessing MODIS data from long ago is knowing when Terra (or Aqua) overflew northwest Pennsylvania, where the Kinzua Viaduct once stood. The CIMSS Polar Orbit Tracking website (https://www.ssec.wisc.edu/datacenter/polar_orbit_tracks/) includes an archive for satellites, so it’s easy to find where Terra was flying on 19 July, 20 July, 21 July, … , 27 July (and other dates too, of course), allowing someone to identify the times of data needed. I’m looking at series of days because I don’t recall cloud conditions over northwest Pennsylvania from back in 2003! The NASA LAADS website (https://ladsweb.modaps.eosdis.nasa.gov/) contains the level-1b hdf files that can be used to create imagery. (This is also discussed in this blog post for imagery over the Himalayas). For this blog post, I searched for Level-1b files ( https://ladsweb.modaps.eosdis.nasa.gov/missions-and-measurements/science-domain/modis-L0L1/ ) and downloaded hdf files containing data to be displayed with polar2grid software. The data needed to construct true-color imagery include quarter-kilometer data (MOD02QKM), half-kilometer data (MOD02HKM) and georeferencing data (MOD03), as shown at the website below (accessible from this link). Each of those folders will have annual and then daily folders to enter; the daily files are 5-minute granules that are matched to times in the polar orbit tracks at the CIMSS website.

Day 207 files (that is, 26 July 2003) that include Kinzua are shown below. Here are the MODIS paths on that day; note the location of 1630 and 1635 UTC on that map!

MOD02HKM.A2003207.1630.061.2017194224505.hdf
MOD02HKM.A2003207.1635.061.2017194225024.hdf
MOD02QKM.A2003207.1630.061.2017194224505.hdf
MOD02QKM.A2003207.1635.061.2017194225024.hdf
MOD03.A2003207.1630.061.2017194181034.hdf
MOD03.A2003207.1635.061.2017194180729.hdf

I downloaded the data from LAADS for multiple days. To display the imagery, polar2grid (free unix-based software from CIMSS available here) is used. First, a geographic location is established for polar2grid:

./p2g_grid_helper.sh Kinzua -78.6 41.8 250 -250 1120 840 > Kinzua.yaml

That polar2grid command creates gridding information for an 1120×840 grid centered at 41.8^oN, 78.6^oW with 250-m resolution in the n-s and e-w directions. The polar2grid command to create a true_color image and then to place borders, coastlines, and a lat/lon grid are shown below.

./polar2grid.sh -r modis -w geotiff -p true_color -g Kinzua --grid-configs ./Kinzua.yaml -f /path/to/downloadedfiles/Kinzua/206/*.hdf ./add_coastlines.sh --add-borders --borders-resolution f --add-coastlines --coastlines-resolution f --add-grid --grid-D 1.0 1.0 --grid-d 1.0 1.0 --grid-text-size 12 terra_modis_true_color_20030726_??????_Kinzua.tif

The imagery created is below.

An animation from 19-27 July 2003 is shown below. An abundance of clouds is obvious. Perhaps days later in July, or in August, will show clearer skies! Still, a difference field between 19 and 25 July (that is, before and after the Kinzua destruction) might show something. A toggle between those two dates is at the bottom of this blog post.

---

Thanks to Kathy Strabala, SSEC/CIMSS, for reminding me about the LAADS data source. A next step for anyone wanting to look at that region would be to access Landsat data and hope for clearer skies.

View only this post Read Less

Very cold air over the Great Lakes on 17 February helped lead to the development of one long Lake-Effect Snow (LES) band that stretched from the Upper Peninsula of Michigan east-southeastward to Lake Huron then over the Bruce Peninsula and into eastern Lake Ontario and on to the Tug Hill Plateau over upstate New York. Surface observations show surface winds converging into the line: west-southwest winds over southwestern Ontario just south of the band and west-northwest winds just to the north of the band. In the RGB, the LES band clouds are orange/yellow in color. The cold snow-covered land surface is green, as are ice-covered regions on the Great Lakes (for example: Green Bay and the North Channel of Lake Huron). Low clouds (that probably aren’t supporting significant precipitation) are cyan or periwinkle in color.

Microwave sounder data (from, for example, ATMS on Suomi-NPP, NOAA-20 and NOAA-21 or AMSU-A/-B on NOAA-19) can be used to estimate snow fall rates, and this information is available online here. (Click here for a Quick Guide) Snowfall rates for this event are shown below. The LES snow band is obvious from Lake Superior east-southeastward into upstate New York, and strongest snowfall rates are just downwind of Lake Ontario. As the cold air sweeps from Canada southeastward across Lakes Superior, Huron and Ontario, it is warmed and moistened at the lowest levels (that is, it is destabilized) by the open waters of the Great Lakes. Once the band reaches the Tug Hill plateau, it has been prepped by the lakes upstream to unleash a torrent of snow.

Merged snowfall rate, shown below, combines MRMS radar observations with satellite-based microwave estimates of snowfall rate. As you see, the radar observations show a considerably thinner snow band. Even though the microwave footprint has a larger horizontal scale than the LES snow band, the microwave signal is large enough to show where snow is falling. A user must combine the microwave estimate of snow fall rate with their knowledge of the size of the LES — based on infrared satellite imagery, or on surface observations — to use the microwave snowfall rate estimates most effectively.

View only this post Read Less