GOES-16 ABI and GOES-R CI aid IDSS over the weekend

Once again, NWS Huntsville provided impact-based decision support services (IDSS) for the Panoply Arts Festival in downtown Huntsville.  Since it occurs in late April every year, Panoply has a long history of coping with challenging weather conditions, and NWS Huntsville has staffed the event every year to help with those challenges.  This year was no exception.


Saturday was a summer-like day, with the main forecast challenge being convective initiation from a field of cumulus clouds.  The UAH-developed GOES-R Convective Initiation algorithm output was helpful with this process as it correctly forecast low probabilities for much of the day.


We also decided to look at GOES-16 ABI data to see if it added any value.  In addition to monitoring the low (7.3um) and mid-level (6.9um) water vapor channels on a larger scale, the Red Visible (0.64 micron) was most beneficial.  A mesoscale domain sector was in place over the region at the time, enabling forecasters to easily look for growing cumulus clouds (though there were not many of these).  (Apologies for the quick and small screen captures!)

GOES-16 ABI 0.64um imagery – valid 29 April 2017 1950 UTC

During the mid-afternoon, forecasters staffing the emergency operations center noticed an interesting trend in the visible imagery: areas to the south that were shrouded by thicker cirrus were seeing clearly-suppressed cumulus development, and the cumulus clouds were developing again once the cirrus had passed by. This almost created a “moving shadow” effect.

GOES-16 ABI 0.64um imagery – valid 29 April 2017 2013 UTC

GOES-16 ABI 0.64um imagery – valid 29 April 2017 2029 UTC

The forecasters were able to use this to determine that convective initiation–and thus impacts to Panoply and downtown Huntsville–were very unlikely, since the cirrus clouds were moving into the area.
There is a great deal of promise for IDSS using the new GOES-16 data, particularly once the Geostationary Lightning Mapper begins flowing on a preliminary basis.
Note The GOES-16 data posted on this page are preliminary, non-operational data and are undergoing testing. Users bear all responsibility for inspecting the data prior to use and for the manner in which the data are utilized.

GOES-R CI and Total Lightning Products Prove Useful Again in HUN Operations

Shortly after arriving for my evening shift today, I was called by a representative from an organization hosting an outdoor event in downtown Huntsville.  She was inquiring about the chances for shower or thunderstorm development into the early evening hours during the outdoor event (movie in the park night).  As I have grown quite accustomed to loading the GOES-R CI and total lightning products to be used for situational awareness, especially during the convective season, I referred to those to help with my assessment…in addition to radar data of course.  The image below shows GOES Visible channel imagery overlaid with GOES-R CI, total lightning data, and NLDN (the latter of which may be hard to see).  The location of Huntsville is labeled, and cloud motion is analyzed in the image.  Notice that the GOES-R CI product indicates generally low probabilities of convection in the area of clouds to the northwest (and upstream) of Huntsville.  The blue colors indicated CI probabilities of around 10-40%.

GOES Vis imagery overlaid with GOES-R CI, Total Lightning, and 15-min NLDN, approx. 2015 UTC June 13, 2014

GOES Vis imagery overlaid with GOES-R CI, Total Lightning, and 15-min NLDN, approx. 2015 UTC June 13, 2014

The next image shows lightning data overlaying the GOES Vis imagery…

GOES Vis imagery overlaid with KHTX 0.5 reflectivity (dZB) ~2015 UTC June 13, 2014

GOES Vis imagery overlaid with KHTX 0.5 reflectivity (dZB) ~2015 UTC June 13, 2014


Notice that only a few showers were located to the NW of Huntsville, but the GOES-R CI suggested further development was not likely and the total lightning (available from the North Alabama LMA) suggested these were only showers and thus not electrically active (I had looked over the previous ~20-30 mins).   Notice that lightning activity was relegated mainly to the South and East of the area.  This was a situation in which the GOES-R CI and total lightning data both served to provide a more complete assessment of the situation, allowing for a better forecast for one of our customers.

By the way…my forecast to her?  Well, based on the evidence from the observational imagery/data…I said very small chances for any shower activity, so let the show go on!  No showers ended up impacting the downtown area.

Evaluating Experimental Products at the Hazardous Weather Testbed…

This week I am privileged to be a part of the Experimental Warning Program at the Hazardous Weather Testbed in Norman, OK.  Here, forecasters get a chance to test, in an operational style setting, some of the latest experimental warning products as a part of the GOES-R Proving Ground and Risk Reduction projects.


Image 1.  An NWS forecaster evaluates the Convective Initiation (CI) product at the HWT.

Image 1. An NWS forecaster evaluates the Convective Initiation (CI) product at the Hazardous Weather Testbed.


This GOES-R product, being evaluated by the NWS forecaster in the image above,  is created by researchers at UAH, but transitioned to operations by the SPoRT team.  The CI, which is a probabilistic tool, can alert forecasters to areas where convective initiation is likely or unlikely, in about a 0-2 hour window.  During the evaluation today, the product has performed favorably over a rapidly developing cumulus field in north central Texas.  The forecaster above noted large probabilities for convective initiation, which subsequently verified.  Yesterday, results with the CI were more mixed, with CI performing generally well late in the afternoon and early evening with lower based convection, but suffering earlier in the day with high-based convection (generally over 700 mb).

The next image below showcases a feature of the Tracking Meteogram (TM) tool, developed collaboratively by researchers at NASA SPoRT and the NWS Meteorological Development Lab.  Here, the tool also demonstrates success of the CI, which showed high probabilities for convective initiation before the cell showed corresponding rapid increases in reflectivity.  Although the TM tool is still undergoing some changes and development, feedback here at the HWT has been instrumental in some necessary updates this week before the tool moves on to the Operations Proving Ground later this month.

GOES-R CI, GOES Visible, and NEXRAD reflectivity left pane, with meteograms of each parameter as tracked by the Tracking Meteogram tool.

Image 2.  GOES-R CI, GOES Visible, and NEXRAD reflectivity (left), with meteograms of each parameter (right) as tracked by the Tracking Meteogram tool.  Notice the increase in CI (over 90%) before reflectivity values near 40 dbZ were present with this cell.







UAH GOES-R Convective Initiation Product at NWS Huntsville – August 24th

On Saturday, August 24th, small convective cells developed across parts of northern Alabama and southern Tennessee during the late afternoon and evening hours.  The cells did offer the chance to make some evaluation of the UAH GOES-R CI product.  In image 1 below, notice that a small, but intense cell was located in SW Lincoln County, TN.  Other smaller cells were located in NW Madison County, AL and in NE and central Limestone County, AL.  Other cells can also be seen in the far northern part of this particular image, in Middle Tennessee.  CI values were 40-50% downstream (to the west, in this case) in the Lincoln/Giles/Limestone/Madison cells.  Meanwhile, CI values were around 50-60% near the very small, light cell in south central Limestone County.  Unfortunately, a lot of “clutter” also existed in the imagery from this event.  So, some of the smaller, lighter cells may be more difficult to detect.

Image 1.  GOES-R CI overlaid by KHTX 0.5 degree reflectivity (dBZ), valid 2115 UTC Aug 24, 2013

Image 1. GOES-R CI overlaid by KHTX 0.5 degree reflectivity (dBZ), valid 2115 UTC Aug 24, 2013

In the next available CI product update, at approx 2132 UTC, CI values had increased downstream of the convection in Lincoln/Giles/Limestone Counties.  Notice the 60-70% values there now, indicating a stronger likelihood of convective initiation of clouds that had developed along outflow from the cell in Lincoln County, TN.  Farther to the south, CI values of 50-60% and 60-70% had appeared along the border of Madison/Limestone Counties, where no cells were yet readily apparent.

Image 2.

Image 2.  GOES-R CI overlaid by KHTX 0.5 degree reflectivity (dBZ), valid 2132 UTC Aug 24, 2013

A little later at 2145 UTC, cells can now be seen developing in the area of previous high CI probability, in eastern Limestone County.  The cell in SE Giles and SW Lincoln Counties, in the same area that also exhibited high CI values in the previous image has also developed further, with over 50 dBZ reflectivities indicated by KHTX.  Also, notice a cell in far NW Jackson County that developed during the previous 15 minutes.  However, CI values were not present for this cell, and I was perplexed by this apparent miss initially.  Or was there really a “miss” by the algorithm?…we’ll get to that in a minute.

Image 3.  GOES-R CI overlaid with KHTX 0.5 reflectivity (dBZ), valid 2145 UTC August 24 2013

Image 3. GOES-R CI overlaid with KHTX 0.5 reflectivity (dBZ), valid 2145 UTC Aug 24, 2013

In the latest image I have available from that event, CI values remained high with the cells mainly in Giles and Limestone Counties.  Meanwhile, the cell in far western Jackson County was moving into eastern Madison County.  However, notice the faint yellow colors that appear in eastern Madison County, to the west of that cell.  Since the radar data were loaded last, and overlaid the CI product, the CI values were being covered by the large amount of clutter in the radar.  Initially, a cell that I thought had been missed by the CI algorithm, may not have been.

Image 4. UAH GOES-R CI overlaid by KHTX 0.5 reflectivity (dBZ), valid 2202 UTC Aug 24, 2013

Image 4. UAH GOES-R CI overlaid by KHTX 0.5 reflectivity (dBZ), valid 2202 UTC Aug 24, 2013

Below is a zoomed image from the area in question above.  Notice the few yellow colors from the CI product in far western Jackson County, mostly hidden by the overlaid KHTX radar data and clutter, indicating 60-70% probability for convective initiation.

Image 5.

Image 5.  Zoom of image 1 over Jackson and Madison Counties


This next image is a zoom of image 4, which better shows some of the underlying CI values (here, yellow colors indicating 60-70% probabilities of convective initiation) in eastern Madison County at 2202 UTC.

Image 6.

Image 6.  Zoom of image 4 over Jackson and Madison Counties. 

In this case, the UAH GOES-R CI values performed well overall in predicting the likelihood for convective initiation.  Cells developed in locations where CI values were typically 50% or greater.  In the case of the cell that moved from Lincoln County into Giles County however…I’m not sure this was more a case of cell propagation than it was actual cell development from storm-scale outflow.

Another take-away item from this event though and a lesson-learned, is the appropriate viewing strategy in AWIPS II.  AWIPS II allows for the loading of multiple data sets and imagery.  Thus, one has to be careful as imagery that are initially loaded may be covered by following imagery.  True, I did have another pane that combined the CI with GOES-East Vis imagery, and then IR imagery once low light conditions made that necessary.  I also had a pane with CI imagery alone.  But, my focus had switched to the CI and radar data at this point, since cells were developing quickly.  However, when incorporating radar with CI imagery, it is probably best to overlay the radar imagery with CI values, when trying to make a proper assessment of CI.


GOES-R Convective Initiation Evaluation Underway at Several NWS Offices…

An evaluation of the GOES-R CI product, which was created by researchers at the University of Alabama-Huntsville (UAH), is currently being conducted at several offices in the Southern Region of the NWS, including here at WFO Huntsville.  SPoRT has worked with the UAH team to transition the GOES-R CI product into the Advanced Weather Interactive Processing System (AWIPS) at some of our collaborative offices.  Importantly, this allows for the overlay of other data sets, including radar, satellite and surface or upper-air analyses, which can add context to the CI data.  The evaluation period officially kicked off Monday, August 19th and will continue through the end of September.  During that time, forecasters at NWS offices in Albuquerque, Melbourne, Miami, Corpus Christi, in addition to Huntsville will be providing analysis of the GOES-R CI product and filling out surveys pertaining to its operational utility.  Huntsville is unique in this assessment, in that we are the only office with AWIPS II participating in the evaluation.

The GOES-R CI product is intended to provide forecasters with probabilities of 0-2 hour convective intiation of cloud objects observed in the visible and IR bands of the GOES-East and GOES-West satellites, and serves as a proxy to future GOES-R capabilities.  This product has undergone improvements in recent years based on user feedback, and now incorporates NWP model data (RAP), while outputting a probabilistic value, rather than the binary or strength-of-signal values from prior years.  The product is expected to show operational benefit, in particular, for assessing downstream locations most susceptible to convective activity, and allowing timely forecast updates for airports and/or outdoor venues.

The HUN WFO is glad to be a part of this evaluation and we hope to provide valuable feedback for the GOES-R CI product developers.

UAH GOES-R CI and GOES-East visible imagery, regional view in AWIPS II at WFO Huntsville.  Product valid 1402 to 1445 UTC August 21, 2013.

UAH GOES-R CI and GOES-East visible imagery, regional view in AWIPS II at WFO Huntsville. Product loop valid 1402 to 1445 UTC August 21, 2013.