Some Discussion of the Short Fuse Composite Technique

Some History:

This technique was originally developed in the late 1980s using vector graphic products from the old AFOS ADAP (AFOS Data Analysis Program) developed by Phil Bothwell, now of SPC. Needless to say, there has been considerable change in the quality and quantity of graphical information available since then. However, one of the primary advantages of the technique was that it did *not* include data from any of the numerical models thereby allowing the forecaster to compare the *real* derived fields to the *forecast* derived fields of the models. Often this process helped identify places where the models had gone astray.

Now, some 15 years later, model short term, high resolution forecasts have improved considerably. Scale of measurement considerations aside, the upper level data (temperature, geopotential height, wind vectors...etc) are of sufficient quality that vertically derived fields using real surface data and model forecasts aloft are probably very close to reality. This has allowed the technique to be expanded from the early method so that computations of stability parameters (CAPE and LI) are likely far more accurate than those arrived at by the old ADAP routines. Additionally, many new surface observations are now available over the techinque's domain than were to be had in the 1980s thereby improving resolution of smaller scale surface features. This is the *up* side of the situation.

Invariably, there is a *down* side to the improved accuracy and resolution of the data included in the technique. Largely, that *down* side centers on difficulties with data quality and the objective analysis scheme limitations.

Data Quality:

Let us first consider data quality.  Many automated observations are now available to the analysis routines in LAPS. Unfortunately, they come from a number of different instrument platforms, some of which are poorly sited and all of which suffer from systematic biases that are as yet many undocumented. As a result, objective analysis schemes (hereafter OAs) translate small defects in the data into large variations once derived quantities are calculated, resolved to grid point, and contoured.
Considerable noise has appeared in some of the OA fields from surface based parameters producing undesirable and unrepresentative "bulls eyes" in the contoured fields of derived quantities. Smoothing of the wind vector fields from these disparate observation platforms has helped so eliminate some, but not yet all of that difficulty. Some sites will undoubtably have to be black-listed from the OA routines entirely due to faulty data output. Some sites will only produce poor quality data on occasion so that we are left with the choice to either remove them entirely (thereby losing the quality higher resolution data most of the time) or to accept that there will occasionally be anomalies in the OA contours.

The problem then is knowing when the depictions in the OA fields are real and when they are artifacts of bad observations. A vexing situation to say the least, and not one easily resolved.

OA Scheme Limitations:

I will have Mike address the limitations of the objective analysis schemes when he has time as I am not terribly familiar with the scheme being employed.

Some Caveats:

The original technique was developed using somewhat different though similar fields on the composite charts. Hopefully, the present set of parameters will be a step forward, though we may alter these, too, as we see how they perform in daily use. Of course, your input is solicited insofar as which fields are best, but we will reserve the right to adjust as we see fit and as the science dictates. If there is one thing we are painfully aware of, it is that every forecaster and chaser has their own pet "indicies" so we are going to be a bit stodgy about making wholesale changes in the composite charts to satisfy everyone's personal favorites.

Mike has described on the main page (with the images) a rough approximation of the original "Threat Area" definition. We will no doubt have to adjust this some over time to fit the new parameters being used. In the original paper, some emperical values were arrived at for flux divergence of mixing ratio, lifted index, and "cap". The new iteration of the technique uses a bit different computation for moisture convergence, CAPE as an instability measure and CIN in place of convective "cap".


As a result of the changes in the above paragraph, none of the emperical values found to work with the old technique are still valid and we will have to gradually develop new values to replace them.



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