last January 25th people in New York
City were panicking the media spoke of a
snowpocalypse that was coming and it
never happened while several inches of
snow did occur in the city there were
erroneous forecasts that talked about
two to three feet of snow in less than a
day
based on those forecasts the subways and
much of the city infrastructure were
closed people in general are skeptical
of weather forecasts they see the hype
in the media they get conflicting
reports from a number of different
sources some forecasts may be simply too
vague or they'll remember all of the
missed forecasts in any new warning is
simply like the boy who cried wolf but
the reality is that better information
was available for that snowstorm in fact
that's what my team and I are working on
to develop better tools and these better
tools for forecasting can save lives and
save money so take a look at this map of
the New York City metropolitan area this
was a weather forecast that we generated
over two days before the snow even
started to fall the dark colors over the
city show only that several inches of
snow were to happen and the areas to the
east over Long Island where you see it
more white that's where the heavy snow
would occur and that is actually what
happened so why would we need this level
of precision it's because weather
forecasts really matter it can affect
thousands of people and mean millions of
dollars so for example from 1970 to 2012
there were over 7,000 weather-related
disasters around the
over a million people lost their lives
from that from those events and that was
mostly in the developing world
in the developed world there were over
two trillion dollars worth of economic
impact better weather forecasts could
help to mitigate those types of those
types of impacts so the challenge is how
do we go from this common skepticism
that weather forecasts are always wrong
to a level of trust well it's about
relying on the science so on our planet
energy from the Sun drives weather if we
understand how the energy interacts in
our atmosphere we can determine how the
wind flows over the surface how clouds
form where and when storms would occur
the next thing we have to do is we
introduce mathematics to model the
physics and effectively that's the
bridge between the science and weather
forecasting so some of you may see these
equations and think this is the sort of
scary math but scientists like myself
will solve equations like these on a
supercomputer to create predictions in
three dimensions of temperature wind and
precipitation the next thing we have to
do is leverage advances in computing so
that forecast that I showed you for the
correct snowfall in New York City a few
years ago that would have taken days to
compute on a large system but today we
can compute a forecast like that in
under an hour on a relatively modest
computer so now we have two ingredients
where we understand that we can produce
precise forecasts and we can produce
them quickly but how do we know if the
forecasts are even right and how can we
improve our models this is where we
leverage additional advances in
technology such as spacecraft in orbit
or advances in weather stations and
maybe even the sensors on our
mark phones the idea is that all of
these sensors give us information about
weather and in fact each and every day
we are collecting or generating hundreds
of terabytes of data about the weather
on our planet and that's millions of
times more data compared to a few
decades ago so now we have sort of three
ingredients to improve weather forecasts
we have improvements in the sciences
advances in computing and advances in
the collection of data one of the
problems is that these advances are not
used in an optimal way and often we see
problems with even data being shared and
this is why the weather forecasts that
you commonly see are not reliable but we
actually know how to solve that problem
and it's really about using those
ingredients in a different way in a
manner that can produce forecasts that
are more useful so what we do is that we
start by focusing on a particular
geography or an application this is a
forecast of a set of thunderstorms
rather than saying 50% chance of
thundershowers tomorrow we're actually
showing predictions of the individual
storm cells that you can see as cyan or
turquoise colored surfaces they're
inside 3-dimensional predictions of the
clouds this also can tell us where and
when it will rain so what that means is
that we can tell the difference in
weather from one neighborhood to the
next tomorrow so as amazing as this kind
of capability is it really is not enough
what we have to be able to do is predict
the impact of weather and by predicting
the impact of weather that means that we
can move from smear Lee a weather
forecast to a weather forecast that's
actionable or in other words as one of
my former bosses once said you don't get
points for predicting rain you get
points for building
ARC's so if we apply this principle we
can do some very valuable things for
example we can predict how much
electricity we can really produce from
wind turbines and solar panels to reduce
our reliance on fossil fuels we can
predict when storms will make the
electricity go out and when the power
will be restored and we're actually
doing this today we use data coming from
utilities that tell us about their past
performance and their infrastructure and
more and we ingest those into our models
which we correlate with weather but we
can apply these same ideas elsewhere
we're already been helping farmers to
produce more food and to reduce the
amount of water and energy they use
these kinds of techniques can also help
reduce flight delays that airlines have
due to weather we've had the privilege
of being able to build on advances in
science and technology to create a new
set of forecasting methods due to the
laws of physics we can never be perfect
but there's so much more that we can do
and for me this has really been the most
rewarding because it's actually an
opportunity to really help people it's
not that often that in one's career that
they really have the chance to create
new technology and new ideas that can
have a positive influence on people's
lives or livelihoods or even to help the
mayor of a large city to know with
confidence whether when that Blizzard
will hit and how bad it will be thank
you