klopfens@bgsu-stu.UUCP (Bruce Klopfenstein) (03/01/90)
I have read with interest the postings so far on retrospective
forecasting. I have another area which I hope prompts some
reactions. William Ascher in his book on Forecasting examined
past technological forecasts for a number of items including
computer capabilities. One of his findings that I found
extremely interesting is that of "assumption drag," the reliance
of previously stated assumptions in spite of empirical evidence
to the contrary.
As a snow lover, I have witnessed this phenomenon in weather
forecasting repeatedly. At 3 PM, the National Weather Service
issues a winter storm warning (not a watch) for that evening with
heavy snow expected. The snow does not develop. By 9 PM, the
updated forecast often will continue with the warning or at least
a forecasting of significant amounts of snow. The following
morning there may be 2 inches of snow on the ground. The same
thing happened here a few days ago. By 9 PM it was completely
clear outside while the forecast had been for a 60% chance of
accumulating snow. The 3 AM forecast on that next day still said
cloudy with snow flurries. It was sunny with very few clouds.
ALthough this is anecdotal evidence, I have witnessed it MANY
times (my attention is heighted by forecasts of snow). I wonder
why the forecasters don't check the local conditions to see that
they contradict the forecast itself. It's as if so much effort
and data went into the forecast, that the forecast is not changed
even in the face of empirical evidence to the contrary.
I don't believe Ascher explains why assumption drag happens (I
may be wrong) but rather that n it simply does happen. Besides the
explanation that so much work went into a forecast that the
author is reticent to change it for that reason alone, the other
(perhaps additional) explanation is that the short-term results
from the environment could be the anomoly, and the forecast
assumptions remain "valid" in the mind of the forecaster.
I wonder how many analogies there are in computer forecasting.
(By the way, no need to explicate weather forecasters--I was just
using that as an example to clarify assumption drag.)
--
Dr. Bruce C. Klopfenstein | klopfens@andy.bgsu.edu
Radio-TV-Film Department | klopfenstein@bgsuopie.bitnet
Bowling Green $tate University | klopfens@bgsuvax.UUCP
Bowling Green, OH 43403 | (419) 372-2138; 352-4818
| fax (419) 372-2300