Utility of the SPoRT ADAS During a Complex Weather Pattern

The last day of November brought a very familiar late fall/early winter weather pattern to the Tennessee Valley–very warm (but not very unstable) conditions with tremendous wind shear, abundant (occasionally flooding) rainfall, followed by sharply colder conditions with upstream reports of snow and sleet.

The earliest part of the day was spent watching radar for potential tornadoes.  Everyone was aware of the devastation that struck central Mississippi, but conditions were not expected to be as unstable across north Alabama.  The SPoRT ADAS improved the radar operators’ situational awareness–and thus the decision to issue (or not to issue) warnings–by helping identify the location of the warm front and most unstable air.  Fortunately, the greatest impacts to the region involved heavy rainfall, and little wind damage was reported across the Huntsville CWA.

SPoRT ADAS Dew Point & Wind, 11/30/10 at 6 AM CST/1200 UTC

SPoRT ADAS Dew Point & Wind, 11/30/10 at 6 AM CST/1200 UTC

Later in the morning a new forecast challenge evolved: would any post-frontal precipitation fall in the form of sleet or snow?  Here again the SPoRT ADAS assisted the forecast team.  By using the ADAS temperature and dewpoint fields in concert with observations, forecast models and forecast sounding data, the forecast team decided to include only a slight chance of snow and sleet.  (Fortunately, again, the Huntsville CWA dodged the most active weather and saw little if any wintry precipitation.)

SPoRT ADAS Temperatures, 11/30/10 at 11 AM CST/1700 UTC

SPoRT ADAS Temperatures, 11/30/10 at 11 AM CST/1700 UTC

ADAS depiction of the nocturnal inversion in complex terrain

The early morning hours of October 16, 2010 were clear with calm winds over the Southern Appalachian region, providing an ideal set up for radiative cooling. The ADAS objective analysis of temperatures revealed some interesting temperature profiles that reflected the nocturnal inversion across the complex terrain of East Tennessee and southwest North Carolina.

Topographic image of the Cumberland Plateau, Great Tennessee Valley, and southern Appalachian Mountains, with 09Z suface observations plotted.

ADAS objective analysis of temperature at 09Z October 16, 2010.

The ADAS temperature analysis  at 09Z (image above) shows surface temperatures in the Great Tennessee Valley (about 800-1200 ft MSL) mainly  in the lower 40s. In the foothills of the Great Smoky Mountains and the sheltered valleys of southwest North Carolina (about 1200-1800 ft MSL), the temperatures drop to between 34 and 40 degrees, matching very closely to observations. These lower temperatures at the base of the mountains reflect colder, more dense air sinking down the mountainsides and collecting in the elevated sheltered valleys.

As we move toward higher elevations, temperatures begin increasing sharply at around 2 kft MSL. ADAS temperatures in this warm layer are between 43 and 48 degrees. This creates the appearance of a “ring” of higher temperatures around the Great Smoky Mountains in the image above. Also note how the higher temperatures across the northern Cumberland Plateau correlate very well to the higher terrain of that area (the highest elevations in this area are below 3000 ft MSL).

As we continue above 3000 ft MSL, temperatures decrease to between 43 and 39 degrees. The difference from the ADAS valley temperatures to the higher “mountainside” temperatures is about 10 degrees. This temperature pattern can also be seen by overlaying the ADAS temperature contours with the topography image (image below).

ADAS temperature contoursat 09Z overlaid on a topography image, zoomed in on the Great Smoky Mountains and southwest North Carolina.

The RUC sounding at that same time (image below) showed a strong temperature inversion, with maximum temperatures in the warm nose of 54 degrees, and a surface temperature of 44 degrees. Temperatures in the sounding begin to drop off at about 2800 ft, very close to the same level as shown by ADAS. Though actual temperature values between the RUC and ADAS differ, the temperature difference from the surface to the warm nose is about 10 degrees – the same as show by ADAS.

09Z RUC sounding at TYS. The maximum temperature value at the nose of the inversion is 54 degrees at about 2500 ft MSL.

Some observations of minimum temperatures that morning from across the region reflected this temperature inversion:

McGee-Tyson Airport (TYS) @ 981 ft MSL – 41

Sugarland Center @ 1600 ft MSL – 36

Cades Cove @ 1900 ft MSL – 43

Newfound Gap @ 5000 ft MSL – 36

The benefits of using the ADAS temperature analysis are even more striking when we compare it to the LAPS objective analysis of temperature in the image below.

09Z LAPS objective analysis of temperature.

A Frost Advisory was also in effect on this morning, and ADAS temperature analysis helped to get a better idea of which areas may have received a frost or a freeze.

New GIS Utility Allows Forecasters to Identify Observations Used for SPoRT ADAS Analysis

A real-time capability that will allow forecasters to see exactly which observations for each analysis variable go into the hourly SPoRT ADAS product has been developed.  This new utility will allow WFO partners to more easily identify exactly which of the observations within their County Warning Area are being used in the analysis and will assist in determining additional stations for blacklisting, which is important to maintaining analysis fidelity.  Information from the observation input files is used to determine which stations (and which variables at each station) are available for assimilation into the SPoRT ADAS analysis.  Then, information about the internal SPoRT ADAS quality control is taken into account to discard some of the available observations in the observation list.  The internal quality control performs a neighbor check, a check against the background field, and a check against an observation from the previous hour.  Finally, the blacklisted stations that have been identified by SPoRT WFO partners are removed from the observation list.  The final list is used to produce a KML file that can be downloaded from the SPoRT website under the “Real-Time Data” –> “SPoRT ADAS” tab.  The figure below shows a screen capture of the temperature analysis on this page from 1900 UTC on 30 August 2010.  The KML files for each analysis variable can be downloaded by clicking the appropriate link below the heading “View Observation Locations”.

Screen capture of Real-Time Data --> SPoRT ADAS showing links to new KML files of observation locations

Clicking on one of the links allows the user to open the file using Google Earth (or another GIS application of the users choosing).  When one of the KML files is opened in Google Earth, users can view an overview of the entire domain to see the distribution of the observations.  The figure below shows the distribution of temperature observations from the 1900 UTC analysis on 30 August 2010.

Full domain view of all temperature observations from the 1900 UTC SPoRT ADAS analyis on 30 August 2010. METAR stations are in red, mesonet stations are in green, and buoy/ship stations are in blue.

In the figure, red paddles denote METAR stations, green paddles denote mesonet stations, and blue paddles denote buoy/ship stations.  Using the pan and zoom features in Google Earth, users can get a closer look at individual stations within a cluster of many observations such as those around larger cities.  In addition, each station contains information about the station name, time, and the value of the actual observations so users can better understand exactly what is going into the analysis.  Clicking on an individual station brings this information to the screen in a pop-up window as shown below.

Zoomed in domain over the Huntsville, AL County Warning Area of temperature observations from the 1900 UTC SPoRT ADAS analysis on 30 August 2010. By clicking on a station, the user can display information about the station name, time, and value of the observation.

SPoRT ADAS as a Forecasting Tool

0600 UTC SPoRT ADAS Dewpoint Analysis

0600 UTC SPoRT ADAS Dewpoint Analysis

The SPoRT ADAS assisted in an unusually-challenging dewpoint forecast on August 8.  A cold front had come through north Alabama the previous day, causing dew point temperatures around the area to fall into the lower 60s (and even upper 50s in a few spots as diurnal mixing took hold).  Dewpoint temperatures to the south remained in the mid 70s.  There was some moisture recovery behind the front that evening, but the front had stalled out just south of the WFO HUN forecast area and was beginning to retreat northward.  Early on the midnight shift, we suspected that the front had actually pushed into the forecast area based on the widely-spaced observations in Tupelo, MS, and Haleyville, AL.  The just-in 0600 UTC SPoRT ADAS analysis helped confirm this suspicion, which improved our situational awareness and changed the short-term forecast thinking rather significantly.

Since nearly all of the forecast models kept the Huntsville forecast area unseasonably dry for another 24 to 36 hours, the forecast grids did not reflect this impinging moisture.  The 0600 UTC analysis further proved its worth when trying to adjust the near-term grids to fit this new paradigm.  The analysis was used first to determine which forecast model fit the current conditions most closely; Huntsville’s GFE configuration includes a display of all available model data for each of the main forecast parameters, so the ADAS helped me select and adjust dewpoint grids from the 13-km RUC for the 0900 and 1200 UTC time periods.  The 0600 UTC ADAS dewpoint grid was then copied into the forecast grids and intermediate grids were interpolated, allowing some of the “ground-truth” data to be directly incorporated into the near-term forecast.

As mentioned earlier, the new frontal positioning changed the forecast in other ways, including the addition of enhanced wording for heat index concerns in northwest Alabama, and convincing us that a slight chance of showers would be needed over part of the region.  (Indeed, it turned out that moisture continued pushing further north through the morning, and we were too conservative with rain chances!)

0900 UTC Dewpoint Forecast -- AFTER SPoRT ADAS

0900 UTC Dewpoint Forecast -- AFTER SPoRT ADAS

0900 UTC Dewpoint Forecast -- BEFORE SPoRT ADAS

0900 UTC Dewpoint Forecast -- BEFORE SPoRT ADAS

Importance of Blacklisting Stations in SPoRT ADAS

The SPoRT ADAS produces a high-resolution surface analysis of temperature, dew point, relative humidity, and winds and has been very beneficial to some of SPoRT partnering offices.  One of the advantages of the SPoRT ADAS system is it’s flexible, user-defined quality control whereby forecasters can identify questionable observations and request that they be removed from the analysis for one or all of the analysis variables.

Brian Carcione at the Huntsville WFO recently identified two stations in DeKalb County (denoted by “X”s in the figures) as having dew point reports that were consistently over 80F when dew points in the rest of their CWA did not exceed 72F.  The top figure shows the SPoRT ADAS dew point analysis when no blacklisting is applied.  For this analysis, the dew point over DeKalb County is over 80F and approaches 90F in some areas!  Not only does the analysis change in the area around the questionable observations, but the larger, unrealistic-looking dew points spread over much of northeastern Alabama (partially due to there being no other observations in that region).  When these two observations are blacklisted, the new quality-controlled dew point analysis produces more realistic-looking fields with similar range across most of northern Alabama (bottom figure).

SPoRT ADAS dew point analysis from 1700 UTC on 27 July 2010 for no blacklist (top) and with blacklisted stations (bottom)

This example highlights the need for forecasters to actively participate in the blacklisting process for the SPoRT ADAS.  If you know of a station in your CWA that is consistently producing unrealistic looking temperature, moisture, or wind observations, please contact SPoRT to have your stations added to the blacklist.  The process to add stations is simple and should take only a few minutes, so please send in as many of the observations from your region that you think should not be included.  Together, we can make this a great surface analysis!

Using the SPoRT ADAS for Short-Term Forecast Updates

Forecast Temperature for 2300 UTC on 26 May

Forecast Temperature for 2300 UTC on 26 May

Summertime convection poses a number of forecasting challenges in the southeastern United States.  Many of the challenges surround threat assessment and warning decision-making (a post for another day), but these “pop-up” showers and thunderstorms can also wreak havoc on temperature forecasts by introducing rain-cooled air and additional cloud cover.  Fortunately, the SPoRT ADAS is proving to be very beneficial when it comes to short-term temperature updates.

This particular example dates from May 26.  During the late afternoon and evening hours, a cluster of showers and thunderstorms developed in northeast Alabama and propagated westward due to outflow boundary motion.  A quick glance at the SPoRT ADAS temperature analysis for 2300 UTC/6 PM CDT indicated that the thunderstorms had significantly lowered temperatures over the eastern portion of the Huntsville forecast area, detail which the original forecast grid could not incorporate.  The SPoRT ADAS also picked up on increased heating across northwest Alabama.

SPoRT ADAS Temperature for 2300 UTC on 26 May

SPoRT ADAS Temperature for 2300 UTC on 26 May

Since NWS Huntsville ingests the SPoRT ADAS into GFE, it was easy to incorporate the analysis grids into the forecast and adjust accordingly (aided by a smart tool dedicated to copying analysis data into the forecast).  Using the ADAS in this particular case meant the temperature forecast more accurately indicated nearly steady overnight temperatures across northeast Alabama early on, then eventually across much of the Huntsville forecast area.

Improved Timeliness and Yield of SPoRT ADAS Product

Based on feedback from the 2010 SPoRT/NWS Partnership Workshop, SPoRT has improved the timeliness and yield of the SPoRT ADAS product to improve its utility in the operational environment.  No changes have been made to the product itself (i.e. the same observations and background field are used); however, the analysis processing have been augmented with the changes outlined below.  Now, the SPoRT ADAS product will be available in partnering offices’ AWIPS systems at around 25 past each hour.  Increased timeliness will allow the operational forecasters to better use the product for initializing their gridded forecasts.  Increased yield will allow for greater utility for grid verification.

The timeliness is improved by implementation of the following:

  • 2-hr RUC background field is now obtained and processed prior to the analysis run time.
  • Analyses are sent directly to the SPoRT LDM server rather than being rerouted due to firewall issues.
  • New cluster head node is slightly more efficient in computation than the previous cluster head node.

The yield is improved by implementation of the following:

  • Dynamic preprocessing of observations and analysis files based on available data.
  • Bug fix in METAR preprocessing script that periodically miscounted cloud levels leading to analysis input error.

The image below is the first ADAS image–from 1500 UTC on 7 April 2010–to be sent using the new scripts.

First SPoRT ADAS Analysis distributed to WFOs using augmented scripts to improve timeliness and yield.

Each NWS WFO can provide additional enhancements to the product by pinpointing observations in the MADIS data sets that they know have a consistent bias.  The SPoRT ADAS has a dynamic blacklisting system by which observations that are questionable only during one part of the day  (e.g. a poorly placed mesonet site that is placed in a shady location that consistently reports lower temperatures) can be removed from the analysis.  Thus, forecasters should communicate their subjective assessments of observation data quality within their CWA to SPoRT for incorporation into the SPoRT ADAS objective analysis.