Groundhogs Have Dueling Predictions About When Spring Will Get Here
  • 2 years ago
Groundhogs , Have Dueling Predictions , About When Spring Will Get Here.
Once a year, Americans ask groundhogs to predict
the end of winter, and this year, two of the furry
forecasters had differing predictions. .
NPR reports that Pennsylvania's
Punxsutawney Phil failed to see his shadow,
which would mean six more weeks of winter. .
NPR reports that Pennsylvania's
Punxsutawney Phil failed to see his shadow,
which would mean six more weeks of winter. .
However, Staten Island Chuck, otherwise
known as Charles G. Hogg, saw his shadow,
which would mean an early spring. .
However, Staten Island Chuck, otherwise
known as Charles G. Hogg, saw his shadow,
which would mean an early spring. .
Last year, the two forecasting rodents
had the same differing predictions. .
The result, was an unseasonably
cold February and a warmer March, .
The result, was an unseasonably
cold February and a warmer March, .
... which means that, in a way,
both groundhogs were right. .
Despite this, NPR reports that as a species, groundhogs are not the most reliable meteorologists, according to recent research. .
Last summer, a study looked at 530 different groundhog predictions across 33 locations. .
The study found that groundhogs
were right exactly 50% of the time.
Using a novel phenological indicator
of spring, this study determined,
without a shadow of a doubt,
that groundhog prognosticating
abilities for the arrival of spring
are no better than chance, Researchers, American Meteorological
Society publication, via NPR.
Some standouts from the study include:.
Connecticut's Essex Ed and New Jersey's
Stonewall Jackson were accurate
with their predictions over 70% of the time.
Connecticut's Essex Ed and New Jersey's
Stonewall Jackson were accurate
with their predictions over 70% of the time.
However, Ohio's Buckeye Chuck
and New York's Dunkirk Dave ended up
being wrong more than 70% of the time. .
However, Ohio's Buckeye Chuck
and New York's Dunkirk Dave ended up
being wrong more than 70% of the time.