Have You Noticed?
By Ross Pomeroy
Included in RealClear
Science on December 23, 2022
People routinely make
snide jokes about the inaccuracy of weather forecasts. It's a status quo that irks
MIT Professor Emeritus Kerry A. Emanuel and Penn State Professors Richard Alley
and Fuqing Zhang, because, as the trio of experts in atmospheric science and
geoscience noted in a paper published to the journal Science in 2018, those
jokesters "wouldn’t dream of planning an outdoor activity without first
checking the weather forecast."
Moreover, the forecasts
they mock have drastically improved in accuracy over the past few decades and
continue to do so.
"Modern 72-hour
predictions of hurricane tracks are more accurate than 24-hour forecasts just
40 years ago," they wrote. "A modern five-day forecast is as accurate
as a one-day forecast in 1980, and useful forecasts now reach 9-10 days into
the future," they added.
So though the weather
prediction jokes continue, they are growing more and more unfounded every year.
Three key developments
enabled weather forecasting's giant leap forward, the authors said,
"Better and more extensive observations, better and much faster numerical
prediction models, and vastly improved methods of assimilating observations
into models." The improved observations have come from the proliferation
of advanced weather satellites in Earth's orbit, including the incredible
lineup of Geostationary Operational Environmental Satellites (GOES), operated
by the National Oceanic and Atmospheric Administration (NOAA), and the European
Space Agency's Meteosat satellites. Moreover, much faster computers have
allowed for more advanced and detailed models.
The simple passing of
time has also fed weather forecasting's advance. Each day, week, month, and
year, reams of data are collected and fed into prediction models, which are
then adjusted accordingly, granting more and more precision as additional data
arrives. The Earth is a system, and the more we monitor that system, the better
we can foresee its future.
Still, there are hard
limits to predicting
the weather, the authors said. "The details of weather cannot be
predicted accurately, even in principle, much beyond roughly two weeks."
The good news, they
added, is there's still a lot of room for refinement within that time frame.
Flood forecasts for coastal storms still need work, as do predictions of sea
ice extent in the Arctic and the movements of smoke from increasingly frequent
wildfires.
Meteorology will also
have a massive role in a future renewable-centered power grid.
"As renewables
come to play an increasing role in power systems, forecasting the availability
of sun, wind, and river flow will take on increased importance, as will
forecasts of energy demand, a large part of which is driven by weather,"
the authors wrote.
But for weather
prediction to keep improving, there needs to be a steady stream of monetary
investment and human effort, they assert. Data collection needs to continue
apace from the ground, sky, and space. Machine learning and neural networks
need to be crafted and applied within earth sciences, particularly to learn
more about intricate physical processes like cloud-aerosol interactions that
still aren't well understood. Governments also need to pay for supercomputing
infrastructure to run increasingly advanced weather prediction models.
"With strategic
investments, the future of weather forecasting and related environmental services
is bright," Emanuel, Alley, and Zhang concluded.
This article was originally published
at Big Think.
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