The EconomistSeptember 21st 2019 891T
he world’s climate scientists are
charged with a difficult task: to create a
crystal ball with which to skry a future that
promises to be hotter than today. But exact-
ly how much hotter depends on innumera-
ble factors, both natural and human. Creat-
ing the crystal ball is thus a two-stage
process. First, you have to build a simula-
crum of how Earth’s climate works. Then,
you try to perturb this simulacrum with
plausible future human actions, to see
what picture appears.
Modern magic being what it is, the crys-
tal balls are actually supercomputers run-
ning programs with 1m or more lines of
code. These programs are models that di-
vide the planet’s atmosphere, ocean and
land surface into grids of cells—many mil-
lions of them. Land cells are flat. Atmo-
sphere and ocean cells are three-dimen-
sional and are stacked in columns to
account for the effects of altitude and
depth. A model calculates what is going on,
physically and chemically, inside each cell,
and how this will affect that cell’s neigh-
bours, both sideways and, if appropriate,
above and below. Then it does it again. And
again. And again.
That is a complicated process. A model’s
code has to represent everything from the
laws of thermodynamics to the intricacies
of how air molecules interact with one an-
other. Running it means performing quad-
rillions of mathematical operations a sec-
ond—hence the need for supercomputers.
And using it to make predictions means
doing this thousands of times, with slight-
ly different inputs on each run, to get a
sense of which outcomes are likely, which
unlikely but possible, and which implausi-
ble in the extreme.
Even so, such models are crude. Mil-
lions of grid cells might sound a lot, but itmeans that an individual cell’s area, seen
from above, is about 10,000 square kilo-
metres, while an air or ocean cell may have
a volume of as much as 100,000km^3. Treat-
ing these enormous areas and volumes as
points misses much detail. Clouds, for in-
stance, present a particular challenge to
modellers. Depending on how they form
and where, they can either warm or cool the
climate. But a cloud is far smaller than even
the smallest grid-cells, so its individual ef-
fect cannot be captured. The same is true of
regional effects caused by things like topo-
graphic features or islands.Uncertainty principals
Building models is also made hard by lack
of knowledge about the ways that carbon—
the central atom in molecules of carbon di-
oxide and methane, the main heat-captur-
ing greenhouse gases other than water va-
pour—moves through the environment.
Understanding Earth’s carbon cycles is cru-
cial to understanding climate change. But
much of that element’s movement is facili-
tated by living organisms, and these are
even more difficult to understand than
physical processes.
Plants absorb carbon from the air dur-
ing photosynthesis and then return it dur-
ing respiration. Animals that eat those
plants also respire. Bacteria and fungi sim-
ilarly break down dead plants and animals
to pillage materials and energy from them,
releasing carbon dioxide and methane intoThe uncertainties of climate change
Throwing the dice
Predicting how the climate will evolve is fiendishly difficult. The greatest source
of uncertainty comes not from science but from human behaviour
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