so I started out 28 years ago
just imagine forecast information came
in the form of paper piles of paper it
limited the amount of information that
we could could look at we’ve seen things
now in the models that we’re actually in
some ways learning and confirming using
other information observation satellite
data so things have changed enormously
in my career today forecasters can rely
on a vast array of weather sensors on
the ground at sea in the air and even
space this information is fed into
computer models that build on our deep
knowledge of environmental physics the
atmosphere is basically a fluid just
like water fish tank and fluids are
defined by mathematical equations in
terms of their structure and how they
would evolve with time
so we go for the major terms in an
equation and then we put them into a
computer model we try to get a solution
of how the atmosphere will evolve dr.
Willey LaPenta is the director of NOAA’s
nine Weather Prediction centers when a
tornado is forming or a hurricane is
brewing the accuracy of his models can
be a matter of life and death but
because there are so many variables in
the atmosphere no model spits out the
right prediction every time NOAA
compensates by running their models
dozens of times introducing random
variations and the data the result is a
cluster of possible futures called a
none sambal so let’s just say that my
pipe was a hurricane track ok so I put
once you see the ball roll you see a
roll a certain way okay that’s one piece
of information
so an in samba means you would do that
many times over maybe 20 times maybe 40
times
and the thing is every time you put it
down and stroke it something changes so
then if the trajectories of the balls
are very close to each other that means
you either have a very good model or
there’s a high level predictability in
that hurricane track or both these are
called spaghetti plots and it’s
essentially just deterministic guidance
overlaid with a bunch of ensemble
guidance so you can really see a lot of
information on one screen when they’re
closer together you know you have higher
confidence in your forecast you know
there’s more certainty in your forecast
and then as you go out in time solutions
begin to diverge we become more
uncertain about the forecast and really
just the slightest difference can make a
huge change in the forecast
[Music]
just imagine forecast information came
in the form of paper piles of paper it
limited the amount of information that
we could could look at we’ve seen things
now in the models that we’re actually in
some ways learning and confirming using
other information observation satellite
data so things have changed enormously
in my career today forecasters can rely
on a vast array of weather sensors on
the ground at sea in the air and even
space this information is fed into
computer models that build on our deep
knowledge of environmental physics the
atmosphere is basically a fluid just
like water fish tank and fluids are
defined by mathematical equations in
terms of their structure and how they
would evolve with time
so we go for the major terms in an
equation and then we put them into a
computer model we try to get a solution
of how the atmosphere will evolve dr.
Willey LaPenta is the director of NOAA’s
nine Weather Prediction centers when a
tornado is forming or a hurricane is
brewing the accuracy of his models can
be a matter of life and death but
because there are so many variables in
the atmosphere no model spits out the
right prediction every time NOAA
compensates by running their models
dozens of times introducing random
variations and the data the result is a
cluster of possible futures called a
none sambal so let’s just say that my
pipe was a hurricane track ok so I put
once you see the ball roll you see a
roll a certain way okay that’s one piece
of information
so an in samba means you would do that
many times over maybe 20 times maybe 40
times
and the thing is every time you put it
down and stroke it something changes so
then if the trajectories of the balls
are very close to each other that means
you either have a very good model or
there’s a high level predictability in
that hurricane track or both these are
called spaghetti plots and it’s
essentially just deterministic guidance
overlaid with a bunch of ensemble
guidance so you can really see a lot of
information on one screen when they’re
closer together you know you have higher
confidence in your forecast you know
there’s more certainty in your forecast
and then as you go out in time solutions
begin to diverge we become more
uncertain about the forecast and really
just the slightest difference can make a
huge change in the forecast
[Music]
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