NUCAPS fields across an upper tropospheric front

January 20th, 2021 |

GOES-16 ABI Airmass RGB, Band 10 and Band 8 (7.34 µm and 6.19 µm, respectively), and GOES-16 Airmass RGB overlain with NUCAPS sounding availability plots, 0801 UTC oni 20 January 2021 (click to enlarge)

The AirMass RGB from GOES-16 at 0800 UTC on 20 January 2021 showed a distinct color change across central Missouri, from red to green.  The enhanced red coloring suggests a large difference in water vapor brightness temperatures.  The toggle above (including an image with NUCAPS* sounding points), shows structures in the water vapor imagery consistent with an upper tropospheric front.

Water Vapor and Airmass RGB imagery fields are useful because they be compared to model fields of the tropopause, and similarities in model fields and satellite imagery lend credence to the idea that the model initialization is accurate.  Compare the Airmass RGB and the Rapid Refresh mapping of the pressure on the 1.5 PVU surface below.  There is good spatial correlation between model and satellite fields.

GOES-16 Airmass RGB and Rapid Refresh model field of Pressure on the 1.5 PVU surface, 0800 UTC 20 January 2021 (Click to enlarge)

How do vertical profiles from NUCAPS vary across the tropopause fold?  The animation below shows six different profile in Missouri and Arkansas, spanning the reddish region of the airmass RGB.

GOES-16 Airmass RGB image with selected NUCAPS profiles, as indicated. (Click to enlarge)

A more efficient way to view information from NUCAPS is to view gridded fields.  Polar2Grid is used to transform the vertical profile to horizontal fields at the individual NUCAPS pressure levels (and then vertical interpolation moves those fields to standard levels).  The animations below show gridded values that are all in agreement with the presence of a tropopause fold where the Airmass RGB and model fields suggest.  Gridded temperature and moisture can be combined in many ways.  Gridded Ozone is also available in AWIPS (some of these fields were created using the Product Browser).

Ozone from NUCAPS, below, does show an enhancement, as expected, in the region where the tropopause fold is suggested by the airmass RGB.

NUCAPS-derived ozone anomalies, ca. 0800 UTC on 20 January 2021 (Click to enlarge)

The gridded NUCAPS tropopause level, shown below, can also be inferred from the individual profiles shown above.

Gridded NUCAPS Tropopause level, ca. 0800 UTC on 20 January 2021 (click to enlarge)

Note how the lapse rates show relatively less stable air (in the mid-troposphere) in the region of the tropopause fold.

Gridded 500-700 mb Lapse rates, ca. 0800 UTC on 20 January 2021 (click to enlarge)

Mixing ratio shows dry mid- and upper-tropospheric air, in the region of the tropopause fold, as might be expected from the GOES-16 water vapor imagery.

Gridded NUCAPS esimates of 300-700 mb mixing ratio, ca. 0800 UTC on 20 January 2021 (Click to enlarge)

In general, NUCAPS data can be used to augment other satellite and model data to better understand the thermodynamic structure of the atmosphere.  For more information on NUCAPS profiles, refer to this training video.

*The careful reader will note that the timestamp of the NUCAPS Sounding Availability plot, 0753 UTC, is different from the GOES-16 imagery.  Why?  The NUCAPS Sounding Availability plot is timestamped (approximately) when NOAA-20 initially overflies North American airspace.  NOAA-20 was flying over Missouri shortly after 0800 UTC, as shown in this plot (from this website).  Gridded NUCAPS fields are timestamped when NOAA-20 is overhead.

CIMSS GeoSphere website is now active

January 13th, 2021 |

CSPP GeoSphere page showing True-Color (and Nighttime Microphysics) Imagery at 1730 UTC on 13 January 2021 (Click to enlarge)

The CIMSS CSPP-Powered GeoSphere site is now available.  This site allows quick access to GOES-16 imagery via Cloud-friendly, flexible (and configurable) software.  Data are accessed from the GOES Re-Broadcast (GRB) downloaded via antenna at CIMSS/SSEC.  Significant effort was made to reduce latency.  For example,  GOES-16 Mesoscale Sectors load within about a minute of their being downloaded, CONUS sectors load within about 8 minutes, and Full-Disk imagery loads within 20 minutes.  In addition to the individual bands (1-16), a sharpened True-Color (Daytime) and Nighttime Microphysics (Nighttime) product is available.  The data are tiled and only tiles that are needed for the present view are loaded.  In addition to still images, animations can be displayed, and a user can choose how many images are in the loop (up to 30), and what the time-step (i.e., ‘Pattern Stride’) is.  Users can also share urls so that others can view the same animation.  For example, the image above was created with this url.  Individual frames can be downloaded via a left-click on the image.  There is at present no method to download animations directly.

More information on this site is available in this recorded presentation created from this PowerPoint.

Severe Weather in southeast Texas

January 6th, 2021 |

GOES-16 Day Cloud Phase Distinction RGB, 1646-2136 UTC on 6 January 2021, along with surface METARs (Click to animate)

The Storm Prediction Center in Norman issued a Slight Risk (click for map, from here) of severe weather over portions of southeast TX on 6 January 2021. The Day Cloud Phase Distinction RGB, shown above (click the image to animate) shows a developing line of convection stretching through the SLGT RSK area (The tallest convective cloud tops acquire a yellowish tint as they glaciate; lower clouds are blue/green/cyan).  The Day Cloud Phase Distinction RGB also allows for easy visualization of vertical wind shear:  the high cirriform clouds (orange and red) move in a distinctly different direction than the low cumuliform clouds (blue and green).  A Severe Thunderstorm Watch (Watch #2 on the year) was issued at 1900 UTC (Click here for Radar image that accompanied the watch issuance).  How could various satellite-based (or satellite-influenced) products be used to anticipate and to quantify the likelihood of severe weather during the day?

Polar Hyperspectral Sounding (PHS) data (from CrIS on Suomi NPP/NOAA-20 or from IASI on MetOp, for example) can augment Advanced Baseline Imager (ABI) data from GOES-16 (or GOES-17) to allow for better initialization of moisture fields in models. PHS data are linked to ABI information at the time of the polar orbiting overpass, and that relationship is carried forward in time. This data fusion process (PHSnABI) combines the excellent spectral resolution of the PHS with the superior spatial and temporal resolution of the ABI. When those data are used to initialize a model, it is frequently the case that the better moisture distribution within the PHSnABI fields leads to a more refined forecast of convection. (See this website for more information and for current model fields) Was that true on this day?

The toggles below show data from models runs initialized at 1400 and 1500 UTC, with model fields at 1800, 2000 and 2200 UTC. Lifted Index fields are shown with data from a Rapid Refresh-type simulation (that is, with no incorporation of fused PHSnABI data) identified as ‘RAP’ in the label; with data from a Single Data Assimilation (‘SDA’) system; and with data from a Continuous Data Assimilation (‘CDA’) system.

The CDA model system does appear best at simulating the timing of the convection that moves through southeast Texas (if one can use simulated Lifted Index as a proxy for the leading edge of convection).

Lifted Index at 1800 UTC from Models (RAP, SDA, and CDA) initialized at 1400 UTC (Click to enlarge)

Lifted Index at 1800 UTC from RAP, SDA and CDA models initialized at 1500 UTC (Click to enlarge)

Lifted Index at 2000 UTC from RAP, SDA and CDA models initialized at 1400 UTC (Click to enlarge)

Lifted Index at 2000 UTC from RAP, SDA and CDA models initialized at 1500 UTC (Click to enlarge)

Lifted Index at 2200 UTC from RAP, SDA and CDA models initialized at 1400 UTC (Click to enlarge)

Lifted Index at 2200 UTC from RAP, SDA and CDA models initialized at 1500 UTC (Click to enlarge)

NOAA-20 VIIRS imagery at 1823 UTC: 1.61 µm, True Color and False Color (Click to enlarge)

NOAA-20 overflew the convection at 1823 UTC, and the imagery above was processed at the Direct Broadcast site at CIMSS. (It is available for AWIPS via an LDM feed, and also as imagery for one week at this website; data for other days is here). VIIRS I3 (1.61 µm), True-Color and False-Color imagery from VIIRS all show a well-developed convective system at 1823 UTC.

As the convective event is unfolding, NUCAPS profiles derived from NOAA-20 can be used to diagnose the thermodynamic state of the atmosphere.  The toggle below shows 5 different profiles over southeastern Texas (along a line to the west of Galveston Bay) at ca. 1830 UTC.  The green points are NUCAPS profiles for which the infrared retrieval has converged to a solution.  A general decrease in stability (and increase in moisture) is apparent for profiles closer to the convection.  The red point (a profile for which the infrared and microwave retrieval both failed) is included as well.

NUCAPS profiles at select points as indicated over southeast Texas, 1830 UTC on 6 January 2021 (Click to enlarge)

A simpler, faster way to view the thermodynamic fields within NUCAPS profiles is to use gridded fields.  NUCAPS data are gridded onto constant pressure surfaces (using Polar2Grid software). The Total Totals Index field, below, shows a corridor of instability inland over southeast Texas with values exceeding 50.

Total Totals index from gridded NOAA-20 NUCAPS values, ca. 1830 UTC (Click to enlarge)

During the actual convective outbreak, NOAA/CIMSS ProbSevere (available online here) offers a data-driven way to highlight the radar echoes most likely to be producing severe weather in the next 60 minutes. The animation below shows values at 15-minute timesteps (for simplicity); ProbSevere values can change every 2 minutes, however. Use ProbSevere in combination with radar scanning to increase confidence in warning issuance.

NOAA/CIMSS ProbSevere, every 15 minutes, 1715 – 2300 UTC on 6 January 2021 (Click to enlarge)

Severe Weather reports(source) for 6 January are shown below.

SPC Storm Reports from 6 January 2021 (Click to enlarge)

Stereoscopic imagery and cloud top heights

December 11th, 2020 |

GOES-16 (left) and GOES-17 (right) visible imagery (0.64 µm) at 1800 UTC, 11 December 2020 (Click to enlarge)

This blog has featured numerous blog posts that use visible imagery from two Geostationary Platforms (e.g., GOES-16/GOES-17 ; Himawari-8/GEOKOMPSAT-2).  Different cloud heights can be perceived in that imagery (for those who have mastered the art of crossing their eyes!).

GOES-R-type satellites also produce a Level 2 Product:  Cloud Top Height.  Can that product be used in concert with the Stereoscopic imagery to quantify the height differences seen in visible imagery?  The image above was created using Geo2Grid and ImageMagick: Geo2Grid to create the GOES-16 (left) and GOES-17 (right) visible imagery, ImageMagick to paste them together.  The GOES-R data (Full Disk in this case) have been remapped to a common projection. The scripts that does this sits below. (Click here to view Geo2Grid documentation).

../ SWUSStereo -115.0 34.0 2000 -2000 960 720 > $GEO2GRID_HOME/SWStereo.conf
../ -r abi_l1b -w geotiff -p C02 -g SWUSStereo --grid-configs $GEO2GRID_HOME/SWStereo.conf --method nearest -f /arcdata/goes_restricted/grb/goes17/2020/2020_12_11_346/abi/L1b/RadF/OR_ABI*G17_s2020346180*.nc
../ -r abi_l1b -w geotiff -p C02 -g SWUSStereo --grid-configs $GEO2GRID_HOME/SWStereo.conf --method nearest -f /arcdata/goes_restricted/grb/goes16/2020/2020_12_11_346/abi/L1b/RadF/OR_ABI*G16_s2020346180*.nc
../ --add-borders --borders-resolution=h --borders-outline='black' --add-coastlines --coastlines-outline='blue' --coastlines-resolution=h --add-grid --grid-text-size 12 --grid-d 10.0 10.0 --grid-D 10.0 10.0 GOES-17_ABI_RadF_C02_20201211_180???_SWUSStereo.tif
../ --add-borders --borders-resolution=h --borders-outline='black' --add-coastlines --coastlines-outline='blue' --coastlines-resolution=h --add-grid --grid-text-size 12 --grid-d 10.0 10.0 --grid-D 10.0 10.0 GOES-16_ABI_RadF_C02_20201211_180???_SWUSStereo.tif
convert GOES-16_ABI_RadF_C02_20201211_180???_SWUSStereo.png GOES-17_ABI_RadF_C02_20201211_180???_SWUSStereo.png +append GOES-1617Stereo_ABI_RadF_C02_20201211_1800_SWUSStereo.png

Unfortunately, Geo2Grid doesn’t (yet!) display Level 2 products. But AWIPS does. A somewhat later Stereoscopic image (1941 UTC on 11 December) is shown below. GOES-R data (CONUS and PACUS in this case) are shown in a common projection, with GOES-16 shown on the left and GOES-17 shown on the right.

GOES-16 (left) and GOES-17 (right) visible imagery (0.64 µm) at 1941 UTC, 11 December 2020 (Click to enlarge)

Can quantitative information from the Cloud Top Height Level 2 product, shown below, be easily incorporated into stereoscopic imagery?

GOES-16 Cloud Top Heights, 1941 UTC on 11 December 2020 (Click to enlarge)

First, I tried making side-by-side imagery with GOES-16 Visible and GOES-16 Cloud Top Heights. That is shown below.  Cross your eyes to combine the information.  Although one may be able to view something here — by aligning the state boundaries, your blogger did not find this side-by-side view useful — except in the conventional sense, seeing features in the visible to the left and corresponding information in the Level 2 product on the right.

GOES-16 Visible (0.64 µm) imagery (left) and GOES-16 Cloud Top Height (Right), 1941 UTC on 11 December 2020 (Click to enlarge)

Including the Cloud Top imagery to the right of the stereoscopic pair, however, did allow for a simple (although, perhaps, headache-inducing) comparison between the perceived height differences in the visible imagery and the quantitative differences in the Level 2 product.  If I had GOES-17 Cloud Heights, I would include those to the left of the visible pairs.

GOES-16 Visible (0.64 µm) imagery (left), GOES-17 VIsible (0.64 µm) imagery (center) and GOES-16 Cloud Top Height (Right), 1941 UTC on 11 December 2020 (Click to enlarge)

Perhaps the solution lies in color-enhancing the visible imagery based on the cloud top height.  That is work for the future.

The Sandwich Product in AWIPS, a combination of visible imagery — proving texture — and infrared imagery providing color is one way to color the visible imagery based on cloud-top brightness temperatures (as a proxy for height).  A 2.5-hour animation of the Sandwich product is shown below. It does provide an interesting way to view heights of clouds!

GOES-16 (Left) and GOES-17 (Right) Sandwich RGB Product, 1716 – 1941 UTC on 11 December 2020 (Click to animate)