Flooding in Utah – 26 July 2021
July 29th, 2021 by Dan BikosBy Sheldon Kusselson and Dan Bikos
The North American monsoon has been in full swing during the summer of 2021, bringing much needed moisture to the Southwest.
At times though the abundant moisture has resulted in heavy rain and flash flood events.
See the 4 panel Advected Layer Precipitable Water (ALPW) animation
Upper left: ALPW in the Surface to 850 mb layer
Upper right: ALPW in the 850 to 700 mb layer
Lower-left: ALPW in the 700-500 mb layer
Lower-right: ALPW in the 500-300 mb layer
When viewing this product in the west, keep in mind that data is missing over higher elevations. This effect is easily observed in the Surface to 850 mb layer, and even shows up in localized regions of the 850 to 700 mb layer. The 700-500 mb layer is very useful for the monsoon season with the typically high moisture values observed in mid-levels over regions of higher elevation. The relative maximum in moisture across southern Utah can be easily observed in this layer. The 500-300 mb layer can depicts regions of higher moisture at that level highlighting regions where the moisture is particularly deep which can enhance precipitation efficiency. Compare the animation with the slide above that denotes with arrows the direction moisture plumes are moving in the different layers. Source regions of moisture can be readily identified along with when these moisture layers become vertically aligned leading to a deep moist profile typically associated with excessive precipitation events.
See the 4 panel 700-500 mb ALPW, GOES-16 6.2 um water vapor band and 2 TPW products
Upper left: ALPW in the 850 to 700 mb layer
Upper right: GOES-16 6.2 um (upper-level) water vapor band
Lower-left: Blended TPW product (operational), (missing before 1400 UTC)
Lower-right: Merged (GOES + POES) TPW product (experimental)
Compare the animation of the water vapor imagery with the annotated water vapor image on the slide above that denotes short waves.
Compare the TPW products with the ALPW animation above, how do they complement and supplement each other?
Upper left: ALPW in the 850 to 700 mb layer
Upper right: MRMS composite reflectivity
Lower-left: GOES-16 IR (10.3 um)
Lower-right: GOES-16 upper-level water vapor (6.2 um)
Again, the water vapor imagery depicts the short wave.
Note how the ALPW seems to increase at certain times. If the increase is occurring over a large area, it is likely due to a new polar pass becoming available or a pass with a different sensor.
Detailed information on the flooding in southern Utah
Posted in: Heavy Rain and Flooding Issues, Hydrology, | Comments closed
30 November 2020 Severe Weather Event in the Mid-Atlantic
December 3rd, 2020 by Dan BikosBy Dan Bikos, Sheldon Kusselson and Jorel Torres
On 30 November 2020, a trough affected the Mid-Atlantic region and was responsible for the following severe weather reports:
https://www.spc.noaa.gov/climo/reports/201130_rpts.html
In this blog post, we’ll examine aspects of the synoptic scale setup for this event.
The following GOES-16 low-level water vapor (7.3 micron) animation:
depicts an extra-tropical cyclone moving northeastward. Thunderstorms developed in northeast Virginia around 1800 UTC and moved northeast across Maryland, Delaware, Pennsylvania and New Jersey. These thunderstorms appear to have developed at the nose of a dry slot apparent in the imagery as a region of warmer brightness temperatures. Click on the image below to see the thunderstorms of interest (yellow circle) and approximate boundary of the dry slot over the region of interest (green line):
What role did the dry slot have on the thunderstorms?
One of the more useful observational products to assess atmospheric water vapor in 4 dimensions is the Advected Layered Precipitable Water (ALPW) product which makes use of microwave instruments on several polar orbiting satellites. Water vapor is retrieved without the use of NWP output in the retrieval, short-term NWP output wind information is used only to advect the retrieved moisture fields. A loop of ALPW looks like this:
Upper-left panel: Surface to 850 mb Precipitable Water
Upper-right panel: 850 to 700 mb Precipitable Water
Lower-left panel: 700 to 500 mb Precipitable Water
Lower-right panel: 500 to 300 mb Precipitable Water
The loop goes back to 1800 UTC the previous day so that we may view how the moisture fields are changing in time. At low-levels, areas of higher moisture indicate the warm sector with moisture advection northward ahead of the developing cyclone. As we get higher into the atmosphere we see indications of the upper low in northern Texas / Oklahoma with drier air on its southern / southwest flank wrapping cyclonically around it on the eastern flank:
Subsidence within the dry slot would account for dry air at mid- to upper levels, but are there other sources of dry air?
Next, we’ll consider this 4 panel animation:
Upper-left: GFS 700-500 mb lapse rate
Upper-right: ALPW product in the 700 to 500 mb layer
Lower-left: GOES-16 7.3 micron imagery
Lower-right: ALPW product in the 850 to 700 mb layer
Early in the loop, during the daytime hours of November 29 we see a rather obvious region of steeper mid-level lapse rates in Arizona and northwest Mexico. The evening sounding from Tucson, AZ:
Shows a deep well-mixed layer with very steep (nearly dry-adiabatic) mid-level lapse rates. In the GOES 7.3 micron imagery we see very warm brightness temperatures since the weighting function peaks around 600-700 mb, within the well mixed warm / dry air mass. The ALPW product in the 700-500 mb layer shows this as a very dry air mass as well. The animation indicates that this air mass advected eastward towards Texas, so we may suspect some portion of the dry air observed further east may have come from the Elevated Mixed Layer (EML) across Arizona and northern Mexico. Next we’ll look at soundings to assess this.
The 00Z soundings from Del Rio, TX:
and Corpus Christi, TX:
depict dry air at mid-levels, as well as very steep mid-level lapse rates characteristic of what you may expect with an EML as we observed in the Tucson sounding.
The animation appears to show the dry air mass moving from Arizona into Texas and Louisiana combining with the developing trough where you’d expect to see a subsidence signal (mid-level drying). In fact a sounding north of the EML plume as indicated by the steeper mid-level lapse rates in the GFS at Fort Worth, TX:
shows the dry air mass at mid-levels, but not the steeper mid-level lapse rates like we observe further south in Texas, much like you would associate with being in a subsidence region of a developing trough. The dry air mass we observe on satellite images appears to be a combination of both the subsidence region of a developing extra-tropical cyclone and an EML with origins over Arizona / northern Mexico. The EML is of particular note since the steeper mid-level lapse rates may lead to a more favorable environment for severe thunderstorms. Click on this image to compare the above 00Z sounding sites with the imagery at the corresponding time:
Next, let’s assess November 30 12Z soundings, we’ll be referring to the following sounding sites (corresponding imagery from 12Z is shown):
Was the EML evident in the Nov. 30 12Z soundings?
Yes, in Atlanta, GA:
and also in Tallahassee, FL:
Note that the region of warmer brightness temperatures in the GOES 7.3 micron band and drier air mass in the ALPW 700-500 mb layer is not quite to central North Carolina at 12Z:
The mid-level dry air mass had not yet arrived at sounding time, however without an 18Z RAOB is there another way to assess the air mass at Greensboro, NC (GSO)?
Yes, NUCAPS provides soundings (except no wind data) around 18Z, here is the NUCAPS sounding at that time a little southeast of Greensboro, NC within the dry mid-level air mass:
We can see that the mid-level dry air mass has moved through Greensboro, and the mid-level lapse rates are quite steep (7.5 degrees C per km), this is confirmation of the mid-level lapse rates caused by a combination of the EML and being in the subsidence region of the extra-tropical cyclone.
Compare the 12Z Greensboro sounding with the 18Z NUCAPS sounding near Greensboro
Note that low-level features such as sharp capping inversions may not be adequately resolved with NUCAPS soundings, however that is not an issue here since we are assessing mid-level drying and lapse rates.
Moving on to the time of the severe thunderstorms, we analyze the GOES visible (0.64 micron) imagery:
Cloud coverage was quite extensive during the morning hours over the region that experienced severe weather which likely limited the overall severe threat, however there was a narrow region of clearing that developed that allowed for sufficient insolation and thus destabilization that contributed to the severe thunderstorms.
Posted in: Severe Weather, | Comments closed
ALPW depiction of many tropical cyclones & disturbances – September 14, 2020
September 15th, 2020 by Dan BikosBy Sheldon Kusselson
Posted in: Tropical Cyclones, | Comments closed
ALPW depiction of mid-level dry air associated with Tropical Storm Isaias
August 21st, 2020 by Dan BikosBy Sheldon Kusselson
Loop of ALPW 700-500 mb layer over a long time period
Posted in: Severe Weather, Tornadoes, Tropical Cyclones, | Comments closed
Impacts of Water Vapor on Satellite Dust Detection of the 16-17 February 2020 Saharan Air Layer Dust Event over the Eastern Atlantic
August 4th, 2020 by Dan BikosLewis Grasso1, Dan Bikos1, Jorel Torres1, John Forsythe1, Heather Q. Cronk1, Curtis J. Seaman1, Emily Berndt2
1Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO
2NASA Marshall Space Flight Center, Short-term Prediction Research and Transition Center, Huntsville, AL
In the afternoon of 16 February 2020 a dust layer moved off western Africa. A loop of GeoColor imagery from ABI on GOES-16 exhibits the dust layer, which is typically part of a Saharan Air Layer (SAL), that moved westward over the eastern Atlantic Ocean. At approximately 15:40 UTC 16 February 2020, CALIPSO moved northward over the SAL; a green line segment in Fig. 1a indicates the ground track of the CALIPSO satellite. Data from CALIOP, the primary sensor onboard CALIPSO, was used to produce a Vertical Feature Mask (VFM), also shown in Fig. 1b. As seen in the VFM, the primary constituent was dust and is indicated in the VFM as a yellow shading, from the surface to about 3.0 km.
Figure 1: (a) GeoColor imagery diagnosed from ABI on GOES-16 valid at 1540 UTC 16 February 2020 along with a portion of the ground track (green line segment) of CALIPSO from 1530 UTC to 1543 UTC 16 February 2020. (b) Dust, in yellow, is displayed in the vertical feature mask from CALIOP.
Annotations are placed on GeoColor imagery valid 17:50 UTC 16 February 2020 that distinguish between a northern dust region (NDR) and a southern dust region (SDR), see Fig. 2. A black oval is used to indicate the NDR while a horizontal, black, dashed line segment denotes the SDR in the figure.
Figure 2: GeoColor imagery diagnosed from ABI on GOES-16, valid 1750 UTC 16 February 2020, along with the following annotations: A black oval bounds dust in the NDR while the horizontal, black, dashed line highlights dust in the SDR. Within the black oval are additional annotations in red. Further the letters A (upper left portion of the figure), B, and C appear. All annotations are used for comparison purposes with Fig. 3.
A companion image to Fig. 2 is Fig. 3, which displays the ABI infrared channel difference, Tb(10.35 um) – Tb(12.3 um)
Figure 3: Channel difference, Tb(10.35 µm) – Tb(12.3 µm) (˚C), from ABI on GOES-16 valid at 1750 UTC 16 February 2020. Annotations are the same as in Fig. 2. Dust is indicated by the blue and purple colors within the black oval in the northern dust region. There was a lack of a dust signal in the southern dust region.
A dust signal is evident in the NDR with negative to near zero values of the channel difference. In sharp contrast, the SDR is void of a dust signal with values of the channel difference near 3˚C in Fig. 3. In addition, the red oval in Fig. 2 surrounds thick dust, which is coincident with a strong dust signal in Fig 3. Southwest of the red dashed contour in Fig. 2, dust appears thin, which was a region with a weak dust signal in Fig. 3. In the northwest portion of Figs. 2 and 3 the letter A is used to highlight the sharp boundary of low-level liquid clouds as opposed to the diffuse boundary of dust, despite the same channel difference color. That is, different features in Fig. 2 may have similar values of the channel difference in Fig. 3. Further, the letter B denotes locations of thin cirrus along the western portions of the horizontal, black, dashed line segment of the SDR. Although the letter C identifies a region with a similar channel difference color as thin cirrus in Fig. 3, a comparison of the region C in Figs. 2 and 3 reveal clear skies.
Imagery from VIIRS on NOAA-20 at 1510 UTC 16 February 2020 is displayed in Fig. 4.
Figure 4: Data from VIIRS on NOAA-20 valid at approximately 1510 UTC 16 February 2020 showing (a) True-Color, as opposed to GOES-16 ABI GeoColor, imagery and (b) VIIRS channel difference, Tb(10.76 µm) – Tb(12.01 µm), with the same color table shown in Fig. 3.
Note the similarity of patterns in True-Color imagery from VIIRS (Fig. 4a) and the channel difference (Fig. 4b) compared to those from ABI in Figs. 2 and 3. One unanswered question is why does dust in the NDR and SDR (Fig. 2) have such a different appearance in the channel difference (Fig. 3).
Values of the total precipitable water (TPW) from the GFS analysis are superimposed on GeoColor imagery, both valid at 1800 UTC 16 February 2020 (Fig. 5). As illustrated in the figure, values of TPW varied between 0.5 inches to 0.75 inches in the NDR; in contrast, TPW values increased significantly to near 1.5 inches in the SDR.
Figure 5: TPW (in) from the GFS analysis plotted on a GeoColor image derived from GOES-16 ABI; all data is valid at 1800 UTC 16 February 2020.
Values of the TPW from the GFS analysis were also superimposed on the ABI channel difference (Fig. 6), valid at the same time as Fig. 5.
Figure 6: Same as Fig. 5, except TPW (in) is plotted on the GOES-16 ABI Tb(10.35 µm) – Tb(12.3 µm) channel difference (˚C).
One striking feature in Fig. 6 is the clear link between low values of TPW (0.5-075 inches) and a dust signal in the NDR as opposed to high values of TPW (1.0-2.0 inches) an a lack of a dust signal in the SDR.
Satellite retrievals of Advected Layer Precipitable Water (ALPW) retrieved from microwave instruments, valid 0300 UTC 17 February 2020, are displayed in Fig. 7.
Figure 7: Advected Layer Precipitable Water product (in) for the surface to 850 hPa layer valid at 0300 UTC 17 February 2020.
As seen in the figure, the NDR was characterized has having the lowest values of LPW, from the surface to 850 hPa. Values increased sharply in the SDR where a dust signal was absent in ABI channel difference images.
Values of TPW diagnosed or computed from retrieved NUCAPS soundings, valid 03:30 17 February 2020, are shown in Fig. 8. Similar to the patterns in Fig. 7, values of TPW were the lowest over the NDR and largest over the SDR.
Figure 8: Gridded NUCAPS TPW (mm) valid at 0333 UTC 17 February 2020, which represents the time of the granule in the image.
Observations of the water vapor field for this dust event allows for the development of a hypothesis. Based on GFS analysis and satellite retrievals of water vapor, dust is detected/masked when water vapor content in the atmosphere is low/high. That is, when water vapor values are low enough infrared channel differences, and dust products, will detect a dust signal. However, when water vapor content is above a critical value the channel difference will be dominated by a water vapor signal, thus masking dust.
One beneficial consequence of infrared channel differencing of dust in a dry environment is the ability to track dust layers when the sun sets. During the night, GeoColor imagery will be unable to reveal dust layers as a result of the loss of reflection of solar energy off dust. Figure 9 is an animation of the channel difference, which allows a forecaster to follow the nocturnal morphology of dust.
