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Long-range weather forecasts take little skill, Marijuana doesn’t kill brain cells (probably)
Q:
How accurate are the long-term (10 to 15 day) weather forecasts on the Internet
(such as AccuWeather and The Weather Channel)? Seems to me they are little
better than wild guesses after the first couple of days. (Lanney, Sandia
Park, New Mexico)
 South of Dimmitt, Texas. 1995. The lead time for tornado
warnings has more than doubled in the last decade with improved radar and
satellite images. [National Oceanic and Atmospheric Administration
(NOAA)/National Severe Storms Laboratory]
A: This is one hard question. And I’m not the only one who has
had trouble. Who could better determine the facts than the weather folk
themselves? Yet, in 1997, National Severe Storms of the NOAA stated,
"Information on the quality of public weather forecasts is difficult if not
impossible to obtain." Amen.
In 1998, the American Meteorological Society, (AMS) analyzed
how well forecasters predict weather. Weathermen use various "skill" systems to
score forecasts, where "skill" has a technical meaning: The skill score is the
percentage improvement of the forecasts compared with historical climate
records. The AMS found:
- Extended forecasts (beyond Day 14) show no skill. "No
verifiable skill exists or is likely to exist for forecasting day-to-day
weather changes beyond two weeks. Claims to the contrary should be viewed with
skepticism."
- Long-term forecasts (Day 7 to 14) demonstrate little skill.
John Q Public could do as well simply checking what the long-term average
weather is for that date.
- Short-term forecasts (Days 1 to 7) are better. Temperature
predictions show "considerable skill on day 3, with skill decreasing with time
until generally only marginal skill remains by day 7."
The 1998 AMS report, however, needs updating to reflect
accelerating improvement in forecasts, says Bob McDavitt, a meteorologist and
weather ambassador at MetService in New Zealand. McDavitt finds "useful skill"
out to about Day 7 now.
A forecast is simply an extrapolation from present conditions,
based on a weather model. The mathematical model uses atmospheric-physics theory
to predict the weather. Past weather patterns contribute to the picture, as do
current observations. "We gather data, extract a pattern, experiment with the
results (up to100 times), and publish the output of these experiments — the
weather forecast," says McDavitt.
Most people find the results useful, even for extended
forecasts. The National Weather Service (NWS) asked folks in Buffalo, New York
what they thought of the NWS extended forecast. Of the 500 that responded, most
said "good" — a remarkable achievement, considering what weather entails.
Real weather mixes chaos with pattern. Moreover, no model
can include the myriad possibilities inherent in chaos — it’s too vast. An
iceberg calves off Greenland’s coast. That chaotic event affects Burma’s weather
and throws the Burma forecast off, a bit.
The National Severe Storms of the NOAA, however, has useful
hints for we who struggle with forecast uncertainties. Which — of the various
TV, newspaper, and Internet forecasts — to believe?
- If all the forecasts agree, they are much more likely to be
correct than if they disagree.
Average the predictions. The AMS found, for example, that
the average of all forecasted maximum temperatures (for day 2 and beyond) has
a lower error than that of any individual forecast.
Finally, an encouraging word: forecasting skill on Day 5 has
more than doubled since the late 1970s. Forecasts improve as weathermen use
bigger smarter computers to calculate model predictions in greater detail. The
models better reflect reality, as we better understand the physics of weather.
Observations are more timely and comprehensive, as we see more with ever-growing
networks of radar, satellites, and automated equipment.
Further Reading:
American
Meteorological Society (AMS): Weather Analysis and Forecasting, 1998
The
New Zealand Windsurfer Online: To catch the wind by Bob McDavitt
National Severe Storms of the NOAA: Verification of public weather forecasts
available via the media by Harold E. Brooks, Arthur Witt, and Michael D. Eilts
Wind & Weather, weather instruments: Barometer for $60
National Severe
Storms Laboratory: Weather numerical modeling
National
Weather Service Forecast Office in Buffalo, New York: Perceived accuracy
Q: Does marijuana kill brain cells?
(Jason, Chicago, Illinois)
A:
Probably not in humans. At least, marijuana does not kill neurons (nerve cells)
in monkey brains, according to two studies.
 Marijuana [Utah State Government, press release]
By "brain cells," I assume you mean neurons and not other
brain cells, such as, glial cells. These cells actually outnumber neurons — yet
only support brain structure, digest dead neurons, and insulate neurons.
One 1991 study, conducted by
William Slikker,
Jr. of the National Center for Toxicological Research in Arkansas examined
64 rhesus monkeys. Slikker exposed half of these monkeys to marijuana smoke
daily or weekly for a year. The other (by Gordon T. Pryor and Charles Rebert at
SRI International in Menlo Park, California) studied over 30 rhesus monkeys in
1992. Pryor subjected half his monkeys to marijuana smoke one to three times a
day for 6 to 12 months.
A few months after the monkeys quit inhaling the drug, the
experimenters examined the monkeys’ brains. They found no evidence of structural
or neurochemical changes in the brains.
Further Reading:
William Slikker, Jr. et al, "Chronic Marijuana Smoke Exposure
in the Rhesus Monkey," Fundamental and Applied Toxicology 17: 321-32 (1991)
"Chronic Marijuana Smoke Exposure in the Rhesus Monkey II:
Effects on Progressive Ratio and Conditioned Position Responding", by Merle
Paule, et al, Journal of Pharmacology and Experimental Therapeutics,
#260, 1992, pgs. 213-222.
Society for Neuroscience: Brain briefings — The brain’s stash
Utah State
Government: Marijuana identification
(Answered Aug. 27, 2004)
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