Models Knew Monster Storm Was No Certainty
Despite hype, 'Groundhogzilla' was never close to sure bet
In his recent post Andrew Freedman justifiably criticizes the hyping last week and into the weekend by AccuWeather, a Pennsylvania-based private forecasting company, of a potential major east coast snowstorm this past Monday, Groundhog Day. The hype manifested itself in eye-catching headlines that did nothing to acknowledge the ever-present uncertainties in any weather forecast, especially one so complicated. It was a classic case of "cherry picking" the data that supported a significant storm and ignoring all else.
With the benefit of hindsight we know the certainty of a "monster storm" or "Groundhogzilla" -- both terms used in an AccuWeather news release -- was unjustifiable, seeing as the storm dumped a grand total of a dusting to a few inches on the mid-Atlantic and Northeast. But we knew this before the fact, too.
Keep reading for more on the disconnect between AccuWeather's forecast and what computer weather models were predicting...
At times toward the end of last week there was a consensus among the computer models meteorologists use to help predict the weather, which go by acronyms such as "GFS," "ECMWF" and "UKMET," that the AccuWeather forecast could come true. But, there were also times when these models fluctuated wildly, showing a big snowstorm on one run and virtually no snow at all on a run six or 12 hours later (most models are run every six or 12 hours). The fluctuations were enough to drive forecasters batty and send snow lovers on a roller coaster of emotions that alternated between periods of optimism (exaggerated by wishful thinking?) and pessimism (tempered by wishful thinking?).
AccuWeather placed its bets squarely on the big-snow horse, and now finds itself having to eat a very large slice of "humble pie." Importantly, though, I believe that by in large the blame here does not lie with AccuWeather's forecasters, who are no doubt aware and mindful of forecast uncertainties and the pitfalls of overconfidence and hype, but rather the policy dictates of management -- not unlike the relationship between some TV meteorologists and station management.
Nevertheless, it must be emphasized that up until late Saturday and early Sunday there was a very realistic possibility of AccuWeather hitting a home run. -- sometimes even blind squirrels find an acorn. Had the storm occurred as AccuWeather had predicted, you'd likely never hear the end of AccuWeather claims about how wonderfully skillful it had been -- rather than acknowledge the role of old fashion good luck.
The truth is that in a situation as complicated as this particular storm, the basic set of weather models mentioned above is totally inadequate to sample the much larger number of equally possible forecasts.
Models make predictions by, first, processing measurements of the initial state of the atmosphere -- current temperature, wind, pressure, humidity and other data collected across the country and around the world. Then, using mathematical formulas that model the physics and dynamics of the atmosphere, they predict how the atmosphere will evolve over time from its initial state. Equally plausible sets of uncertainties in the initial conditions and/or differences in the algorithms from model to model will produce an array of equally plausible forecasts. Differences between any two forecasts might be too small to be consequential, or large enough to be the difference between a blizzard, drenching rains or a sunny day.
This range of possibilities is an expression of the inevitable uncertainties in all weather forecasts. And, no forecast should be considered complete without conveying that uncertainty, either probabilistically or with some explicit measure of forecast confidence. It all goes back to those pesky butterflies of chaos theory, which inevitably will come back to haunt those who choose to ignore them.
Generating a more complete picture of the full range of possible forecasts is the basis for ensemble forecasting, where a single model is run up to 50 times, each time with a set of slightly different initial conditions (to account for possible inaccuracies in the measured initial conditions). Each of these runs is known as an ensemble member, and together the ensemble members provide a reasonably good portrayal of possible outcomes (e.g., storm track and intensity) and their relative likelihood. The more members that show a given scenario -- for example, a storm hugging the coast and producing significant snows, or instead a storm tracking too far off the coast to produce meaningful precipitation -- the greater the chance that scenario will pan out (at least in theory).
My appraisal of all available ensemble forecasts indicates that from the middle of last week, when the first signal of a realistic possibility for a significant snowstorm became apparent, there was never more than a 50/50 chance of it actually occurring. The chances markedly decreased to less than 10% from Sunday onward. Conversely, an offshore track of a relatively weak low-pressure area -- as turned out to be the case -- was always included in the array of possibilities, and became a 90% plus possibility by Sunday.
Bottom line: There was never a scientifically sound basis to hype the inevitability of a significant snowstorm with this weather system. To their credit CWG and most other weather providers never did.
Note: It was a different system that ended up burying localized areas with an unanticipated 8-12"+ of snow Tuesday night into Wednesday in parts of New Jersey and Pennsylvania, including the Philadelphia area.
| February 6, 2009; 11:00 AM ET
Categories: Tracton, Winter Storms
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