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    i'm going to give you a an overview of
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    what it is that that we do as a as a
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    group and what we do collectively as
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    scientists to try and understand what
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    we're dealing with with with climate and
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    the climate system and climate change
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    the world is extremely complex and
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    dynamic the patterns that you can see
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    here in these clouds which is not real
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    where this is a computer simulations is
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    not this is this isn't a this is in a on
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    a laptop not on a non a satellite but
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    the patterns that you can see a very
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    similar to the ones that you see in the
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    satellite you can see storms you can see
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    convection you can see waves going
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    through you can see things repeating but
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    not quite right
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    that's the essence of the system that
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    were talking about it's a it's a
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    complicated chaotic dynamic system it
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    never quite repeats and yet all of the
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    processes that are going on the
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    underlying all of the things that are
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    going on with these clouds there
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    understandable there are computable we
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    can go and measure all of those
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    different individual things how do we
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    deal with that the challenge is is one
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    of scale the scales of the climate
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    system range from micrometers for small
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    aerosol particles that are from the
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    nuclei of clouds in the atmosphere all
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    the way out to the size of the planet
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    itself which is about 10 to the 8th
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    meters that's about 14 orders of
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    magnitude that's an enormous scale range
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    in which to encapsulate all the things
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    that are going on and even in time you
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    know you're going from things that are
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    happening on micro second scales to
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    things that are happening over millennia
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    again 14 orders of magnitude an enormous
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    range of scales to comprehend them play
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    everything together that's enormous
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    challenge what you have when you build a
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    model then is-is-is you have some
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    fundamental concerns we don't have
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    infinite computer power right so how
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    does that work well with weather models
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    right the ones that produce the forecast
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    that you see every day
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    the kind that the kind of result physics
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    the things that we can expressly
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    included in these models go from the
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    global scale down to about the
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    50-kilometer scale right that's only a
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    very small part of that huge range of
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    scales that that actually impact of
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    climate and the weather right the stuff
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    that we can resolve the stuff that we
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    can say okay we totally understand that
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    we can put in the exact equations is
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    just that small part all the rest of it
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    is what we call these subscale processes
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    now that stuff is is how a cloud
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    actually forms how rainfall actually
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    comes from a cloud system how
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    evaporation works at other very very
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    small scale and all of those things need
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    to be approximated in some way we need
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    to have some empirical phenomenological
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    approximation to that physics to allow
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    the rest of it to work and that's a real
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    challenge right there's this is this is
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    turbulence this is a small-scale
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    heterogeneity this is small mountains
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    and small hills and small lakes all of
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    those things have to be squeezed into
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    our approximation of those subscale
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    processes so there's no guarantee that
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    this works right there's no guarantee
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    that this is even a program that will
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    lead to successful predictions and so
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    the test all of this program is whether
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    it does actually produce successful
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    predictions
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    now you might not like the weather
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    forecast that you get you might think
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    that they're terrible but actually
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    they're much much better than they used
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    to be where the models are skillful of
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    producing forecasts three four five six
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    days almost 10 days out in ways that
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    were unforeseen able even 20 years ago
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    now climate models are slightly
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    different beast climate models have to
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    use longer timescales because time is a
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    longer time scale and so that compromise
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    they make is they don't go to quite such
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    fine detail
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    and so back in the nineteen nineties
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    climate models really only occupied that
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    very small part of that of that space
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    now we can go a little bit further so in
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    the 20,000 tens that so the models that
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    were working with now you know we're
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    coming out about the same spatial
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    resolution as the weather models and
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    we're taking up more times you know
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    we're going out for a thousand years and
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    working on the physics at the same
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    potential and yet we still have this
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    large large range of subjects scale
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    processes that we still have to include
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    this is a climate model I this is an old
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    tram or you'll be pleased to know we
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    don't use punch cards anymore it's a
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    single line of Fortran we still do you
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    use for transfer any of the old-timers
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    here who think that that their skills
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    are no longer valid
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    they asked a valid yes you can have a
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    job with each of these colored bands
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    with a single subroutine a single
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    calculation of some physical aspect of
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    the code arm and you would put them into
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    a machine one at a time and if you got
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    them in the wrong order you have to
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    start over again it would take months to
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    produce any output arm and it was a very
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    very clunky thing and so obviously if
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    you have to write out every line using
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    punch cards you don't include or of
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    comments so you know we inherited this
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    code and we're going
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    what does this go do we have no idea
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    anyway so it doesn't quite look like
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    that anymore but the the essence the the
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    idea of what we're doing is directly
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    related to what we did back in the
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    nineteen eighties and in the missus
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    before that 1970 ok so how do we
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    actually go around building a model we
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    do it one piece of the time and i use
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    the a jigsaw analogy by the beginning
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    and I'll kind of work with that a little
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    bit now it's very much like putting
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    together pieces of a jigsaw so this is a
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    piece of the jigsaw it's a picture of
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    arctic sea ice taken from a flight going
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    across the North Pole each of those ice
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    floes that you can barely see there are
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    a few tens of kilometers across and you
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    can see leads
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    the middle i was the summertime so the
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    ice is breaking up
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    and so there's a lot of physics is going
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    on there right there is the physics of
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    the Sun coming in reflecting off the ice
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    because it's white
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    there's the physics of the of the the
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    heat being absorbed in the ice melting
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    it from the top and is melting from the
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    bottom going on at the same time there's
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    dynamics how each of the ice floes
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    interacts with each other all of those
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    things can be encapsulated measured and
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    put into some kind of formula so here
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    are some of the formulas
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    yeah so physics you know I don't expect
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    you two to look at these your critique
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    these are but this is basically what we
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    do we write down what the boundary
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    conditions are we use calculus we use
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    basic conservation of energy that's
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    that's a big deal and for each of those
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    different things we then take some code
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    and you get lots and lots of lines of
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    code there are some comments now that
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    that's pleasing arm mr. the last bit
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    that there's some melting and we make
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    that one piece into like a component and
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    so okay well when we do see ice that's
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    the piece of code that we're going to
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    use and we can add in lots of different
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    processes so that was the sea-ice
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    process now there's one other processes
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    associated with clouds there's a process
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    associated with radiation and the solar
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    radiation coming through the atmosphere
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    and being absorbed at the different
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    layers of the atmosphere that's one more
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    piece there are other pieces the winds
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    and the way use and other pieces the
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    flow of water through plants the flow of
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    water and rivers back down to the ocean
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    so the point is that each of those bits
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    makes up part of the picture of the
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    climate system now I've left and pieces
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    out because our picture of the timing
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    system is not complete right we don't
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    know everything about the system and yet
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    when we put it all together we end up
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    with a simulation
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    that has all of the emergent properties
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    that we can see in the real world right
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    so these storm systems in the Southern
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    Ocean you can anybody has been to the
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    Southern Ocean knows exactly what they
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    look like or storms in the North
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    Atlantic Kevin can tell you about those
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    tropical cyclones in in the Pacific the
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    convective bands in in the was a couple
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    of tropical cyclones are going to cycle
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    around each other kind of meat
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    yeah now within the code there was no
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    code that says hey do an atmospheric
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    River that hits Oregon there's no code
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    that says do tropical cyclones and make
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    them dance around each other right
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    all of these things are emergent
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    properties that just arise from the fact
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    that the system that you're modeling is
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    chaotic is dynamic and all of the
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    different processes that we put together
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    intersect and interact in ways that you
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    can't predict a priori now just having
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    done that i think is a intellectual
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    endeavor worthy of of of Cato
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    and-and-and Chomsky right trying to
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    understand exactly what's going on in
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    such a complex system and being
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    successful at doing so is an enormous
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    challenge and i think one we can rightly
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    be proud of but we're not just doing it
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    to understand the system we're doing it
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    because that system can be kicked in
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    many many different ways and right now
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    humans are kicking this system in a very
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    particular way so let's look at some
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    ways in which the system can be kept
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    right so there are waffles in the
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    Earth's orbit these bubbles kind of make
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    a difference on ten thousand two hundred
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    thousand year time scales and a big
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    driver of the of the of the Ice Age
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    cycle that we've been seeing for the
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    past 2.5 million years right so Iceland
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    used to have a lot more ice
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    it's not quite as I see
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    as it used to be and and and it will get
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    messy as well with 10,000 years ago
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    20,000 years ago
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    Iceland was almost completely emaciated
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    right all right yeah and that's due to
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    these bubbles so that's that's a very
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    powerful kick to the system right that's
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    everything changed
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    you know can we understand that ok there
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    are changes because of the Sun the Sun
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    has cycles that has activity and it's
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    over its lifetime of the lifetime of the
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    earth has expanded and become more
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    active by about thirty percent over the
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    last four billion years that has an
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    impact on the climate the set the solar
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    cycles an 11-year cycle have an impact
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    on the climate we need to understand
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    those things volcanoes as have also well
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    aware have an impact on the climate not
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    just locally but they can have a global
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    impact on the climate by the injection
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    of sulfates into the stratosphere
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    changing the albedo of the palette
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    changing the amount of energy coming
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    into the system right so you're getting
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    the idea there are lots of different
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    ways in which we can change the climate
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    right or the system itself can be
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    changed whether its biomass burning
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    ozone depletion land-use change
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    contrails or of course greenhouse gases
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    all of these change the balances and the
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    flows of energy in the system and when
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    you change the balances and flows of
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    energy in the system you change the
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    climate so what we need to understand is
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    whether the simulations that i discussed
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    before where the weather models are the
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    climate models whether they have skill I
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    want to be very clear about this
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    these models are not complete right
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    there were holes in the jigsaw there's
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    whole bunches of things that we have to
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    and empirically fill-in write the word
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    that we can't predict from a priori
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    considerations
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    so why do we think that these things are
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    useful
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    we think that they're useful because
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    they have
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    demonstrated skill skill is I model
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    results skillful if it's better than
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    what you would have had otherwise
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    that's not to say it's perfect it's not
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    to say that there are uncertainties but
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    it's something that's better than what
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    you had before with the weather forecast
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    you could stick your finger in the air
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    and predict what the weather is going to
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    be tomorrow based on just persistence of
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    the weather today that probably doesn't
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    work very well here but it works quite
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    well in New York but we can do better
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    than that with models right weather
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    models a skillful despite the fact that
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    there was that whole range of things
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    that we had to empirically include and
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    so we need to demonstrate that climate
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    models are skillful at estimating the
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    changes to the climate when you kick
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    that system in all of the different
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    myriad ways that that system can be
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    kicked
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    okay so is that true is there are the
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    models skillful so well they know
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    volcanoes are a current topic of
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    interest in in Iceland I said well
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    actually not not anymore right we're
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    done with the volcanoes right so that's
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    it for the next week right
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    remember no more volcanoes ok
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    all models skillful with respect to big
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    volcanic forces so the large big volcano
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    that we had that had a global impact was
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    magnitude but went off in june nineteen
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    ninety one arm and this is a graph of
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    how much stuff basically there was in
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    the stratosphere are from the main
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    eruption and then it took like three or
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    four years for all that stuff to kind of
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    fall out of the atmosphere
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    ok so this is actually quite a large
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    amount of stuff right on the amount of
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    stuff that that is there that's the
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    technical term stuff and got some people
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    pay attention okay
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    the amount of stuff that was there cause
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    the radiation to be from the Sun to be
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    significantly less than it was right
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    because each of those little particles
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    is white and so when the Sun shines on a
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    white particle it reflects back to space
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    and that reduces the total amount of
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    energy coming in the amount of energy
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    going out was pretty much the same and
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    so you have less energy coming into the
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    system right so basic conservation of
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    energy suggest that that would lead to a
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    cooling of the planet but by how much
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    how much should the planet call with a 3
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    watt per meter squared energy imbalance
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    over a few years you have to do the
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    calculation and the climate models allow
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    you to do that calculation so what do
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    they suggest well what they suggested
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    are the the little thin lines that you
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    can see there's a bit of noise because
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    of the different weather and each of
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    those models and then the red line there
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    is what actually happened
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    so the models were able to estimate
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    quite precisely the rate at which this
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    the climate called because of this
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    forcing and we know that is better than
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    what we could just worked out by doing a
  • 16:29 - 16:32
    calculation on the back of the envelope
  • 16:30 - 16:35
    and in fact the first time that we did
  • 16:32 - 16:40
    that calculation we did it in October
  • 16:35 - 16:42
    1991 and made this prediction before any
  • 16:40 - 16:45
    of those changes had actually occurred
  • 16:42 - 16:47
    the model was skillful and it wasn't
  • 16:45 - 16:50
    just fearful estimating the global
  • 16:47 - 16:51
    cooling which you know kind of my energy
  • 16:50 - 16:55
    balance arguments you might argue was
  • 16:51 - 16:58
    the easy part but it was also skillful
  • 16:55 - 17:02
    at predicting that in the wintertime you
  • 16:58 - 17:04
    got a strange pattern in Europe where
  • 17:02 - 17:06
    you actually get winter warming after a
  • 17:04 - 17:09
    big volcano and that turns out to be a
  • 17:06 - 17:11
    dynamic response changes in the winds
  • 17:09 - 17:14
    that are affected by the temperature
  • 17:11 - 17:18
    changes our loft that actually push more
  • 17:14 - 17:20
    warm water over more warm air over over
  • 17:18 - 17:21
    Europe during the wintertime and that is
  • 17:20 - 17:24
    also captured by the model and the
  • 17:21 - 17:26
    models are skillful even with the
  • 17:24 - 17:29
    dynamics and the radiation and the
  • 17:26 - 17:30
    temperature there are lots of other
  • 17:29 - 17:32
    example
  • 17:30 - 17:34
    solar cycles you know we can measure and
  • 17:32 - 17:36
    calculate the change in ozone in the
  • 17:34 - 17:38
    stratosphere because of this change in
  • 17:36 - 17:42
    the sun with models are skillful because
  • 17:38 - 17:44
    of that in overall changes those wobbles
  • 17:42 - 17:46
    in the Earth's orbit like even 6,000
  • 17:44 - 17:48
    years ago they were relatively important
  • 17:46 - 17:51
    and we can look at that difference and
  • 17:48 - 17:53
    the models are skillful estimating how
  • 17:51 - 17:55
    the northern hemisphere temperatures got
  • 17:53 - 17:58
    better because our change because of
  • 17:55 - 18:02
    that ok
  • 17:58 - 18:03
    the response to the ice sheets 20,000
  • 18:02 - 18:04
    years ago the models are successful are
  • 18:03 - 18:06
    getting that right
  • 18:04 - 18:08
    the 20th century multi-decade all trends
  • 18:06 - 18:11
    were successful getting that right
  • 18:08 - 18:12
    models are skillful even bizarre things
  • 18:11 - 18:15
    that have happened to the climate about
  • 18:12 - 18:18
    8,000 years ago there was a huge great
  • 18:15 - 18:19
    lake that covered most of Manitoba and
  • 18:18 - 18:21
    Ontario much larger than all of the
  • 18:19 - 18:25
    great lakes that exists right now and it
  • 18:21 - 18:28
    was kept in place by the remnant by the
  • 18:25 - 18:30
    remnant ice sheet that was kind of
  • 18:28 - 18:33
    standing over hudson bay about 8,000
  • 18:30 - 18:35
    years ago that I sheet finally broke and
  • 18:33 - 18:38
    all of that water that was kept in that
  • 18:35 - 18:39
    Lake rushed into hudson bay and into the
  • 18:38 - 18:42
    labrador sea and into the North Atlantic
  • 18:39 - 18:44
    around here and at that same time there
  • 18:42 - 18:46
    is evidence of a cooling event that
  • 18:44 - 18:48
    happened in the Greenland ice cause in
  • 18:46 - 18:50
    Europe and in Newfoundland and all
  • 18:48 - 18:52
    around here and I'm sure that they would
  • 18:50 - 18:55
    a nice and have been affected as well
  • 18:52 - 18:58
    the models are skillful at responding to
  • 18:55 - 19:01
    that water going in by changing the
  • 18:58 - 19:02
    circulation in the in the ocean and by
  • 19:01 - 19:03
    changing the temperatures in the
  • 19:02 - 19:06
    rainfall patterns associated with that
  • 19:03 - 19:08
    the models are skillful across a whole
  • 19:06 - 19:09
    range of different ways that we can kick
  • 19:08 - 19:14
    that system
  • 19:09 - 19:18
    ok
  • 19:14 - 19:21
    and that system is complicated and
  • 19:18 - 19:24
    global right this is a simulation again
  • 19:21 - 19:25
    of tiny little atmospheric particles and
  • 19:24 - 19:29
    all the different kinds of particles
  • 19:25 - 19:32
    that you can have these orange swirls
  • 19:29 - 19:33
    are dust coming from the Sahara Desert
  • 19:32 - 19:36
    and you can see them affecting the
  • 19:33 - 19:38
    climate and affecting a deposition of
  • 19:36 - 19:41
    stuff all the way across the Atlantic
  • 19:38 - 19:43
    the white wispy parts over over Europe
  • 19:41 - 19:45
    you can see that's atmospheric pollution
  • 19:43 - 19:47
    sulfates right and you can see that
  • 19:45 - 19:51
    what's happens in Europe does not stay
  • 19:47 - 19:53
    in Europe the green and the Reds
  • 19:51 - 19:55
    indicate where there is our where there
  • 19:53 - 19:57
    are fires and whether its biomass
  • 19:55 - 19:58
    burning and where is organic carbon and
  • 19:57 - 20:01
    black carbon being put into the
  • 19:58 - 20:03
    atmosphere and again these things don't
  • 20:01 - 20:05
    just stay where they are stuck there
  • 20:03 - 20:08
    they started you can see the pollution
  • 20:05 - 20:12
    over China that again does not just stay
  • 20:08 - 20:15
    in China the blue dots associated with
  • 20:12 - 20:18
    the big tropical storms are associated
  • 20:15 - 20:21
    with sea salt particles so as the winds
  • 20:18 - 20:23
    whip up the waves small particles of sea
  • 20:21 - 20:26
    salt which are a key element in the
  • 20:23 - 20:28
    production of low-level clouds you can
  • 20:26 - 20:32
    see them again in the in the Southern
  • 20:28 - 20:36
    Ocean all of these things are connected
  • 20:32 - 20:38
    and important and we can answer now with
  • 20:36 - 20:40
    the click with the with the computer
  • 20:38 - 20:42
    models that we have we can answer
  • 20:40 - 20:44
    questions that associate that are
  • 20:42 - 20:48
    associated with all of those things
  • 20:44 - 20:53
    how does pollution change climate and
  • 20:48 - 20:56
    air quality all at the same time I love
  • 20:53 - 20:57
    this but this this animation that they
  • 20:56 - 21:00
    they did a really nice job here this is
  • 20:57 - 21:01
    my colleagues at NASA Goddard Space
  • 21:00 - 21:04
    Flight Center and now there's another
  • 21:01 - 21:06
    volcano in Madagascar that just went off
  • 21:04 - 21:08
    and so you can include all thoughts of
  • 21:06 - 21:11
    things in these models and answer all
  • 21:08 - 21:15
    sorts of actually quite subtle and
  • 21:11 - 21:20
    interesting nuance questions
  • 21:15 - 21:23
    how things work over the 20th century
  • 21:20 - 21:26
    when we've seen an amount of global
  • 21:23 - 21:29
    warming right so is this is a model
  • 21:26 - 21:31
    simulation this is the observations you
  • 21:29 - 21:33
    can see the patterns of whether you know
  • 21:31 - 21:36
    they're not correlated the weather isn't
  • 21:33 - 21:38
    predictable 50 years in advance but the
  • 21:36 - 21:40
    emerging patterns have changed that you
  • 21:38 - 21:42
    see towards the end of the 20th century
  • 21:40 - 21:45
    and that we end up where we are today
  • 21:42 - 21:48
    those patterns are predictable they are
  • 21:45 - 21:50
    predicted by the models the models are
  • 21:48 - 21:52
    skillful at getting these patterns right
  • 21:50 - 21:54
    this warming in the Arctic compared to
  • 21:52 - 21:55
    the Antarctic the warming over land
  • 21:54 - 21:58
    compared to the ocean the warming in the
  • 21:55 - 22:04
    North versus the woman in the south
  • 21:58 - 22:07
    these are skillful models but then let's
  • 22:04 - 22:09
    think about the real reason why we need
  • 22:07 - 22:13
    models right and then this this comes
  • 22:09 - 22:15
    from a rebuttal that the two scientists
  • 22:13 - 22:18
    wrote when somebody you know they talked
  • 22:15 - 22:20
    about modeling of of future tropical
  • 22:18 - 22:22
    cyclones and somebody wrote a response
  • 22:20 - 22:24
    to them they say well why are you
  • 22:22 - 22:28
    looking observations and they responded
  • 22:24 - 22:30
    i think quite finally what if we had
  • 22:28 - 22:33
    observations of the future we obviously
  • 22:30 - 22:37
    would trust them more than models but
  • 22:33 - 22:40
    unfortunately observations of the future
  • 22:37 - 22:43
    and not available at this time and
  • 22:40 - 22:45
    that's funny but it's actually the real
  • 22:43 - 22:49
    reason why we build models we want to
  • 22:45 - 22:51
    have predictive capability of situations
  • 22:49 - 22:54
    where we don't yet have any observations
  • 22:51 - 22:56
    so that we can make plans accordingly
  • 22:54 - 22:58
    whether it's a weather forecast whether
  • 22:56 - 23:00
    it's a climate forecasts whether it's an
  • 22:58 - 23:04
    economic projection which we could get
  • 23:00 - 23:07
    into is as well but Sir what we want our
  • 23:04 - 23:10
    is an ability to make informed decisions
  • 23:07 - 23:12
    about the future right so predictable
  • 23:10 - 23:16
    lity and predicting the future is the
  • 23:12 - 23:17
    absolute fundamental reason why we're
  • 23:16 - 23:18
    looking at models right that's what
  • 23:17 - 23:21
    science is all about making predictions
  • 23:18 - 23:23
    testing your theories adapting them
  • 23:21 - 23:27
    making them better making them more
  • 23:23 - 23:28
    predictive so what does the future hold
  • 23:27 - 23:31
    what we have
  • 23:28 - 23:35
    in the future of course our choices and
  • 23:31 - 23:38
    we don't have to fall down one
  • 23:35 - 23:40
    particular line the economic an economy
  • 23:38 - 23:42
    technology how we structure societies
  • 23:40 - 23:45
    these things are not written in stone
  • 23:42 - 23:51
    we have choices society has choices you
  • 23:45 - 23:53
    individuals have choices and these
  • 23:51 - 23:56
    aren't you know completely accurate
  • 23:53 - 23:58
    labels we don't know really what will
  • 23:56 - 24:02
    happen if we just continue as we go
  • 23:58 - 24:04
    along this is an estimate of that we
  • 24:02 - 24:06
    have a pretty good idea of what it would
  • 24:04 - 24:09
    take to bring everything kind of back
  • 24:06 - 24:13
    down to the level that it was you know
  • 24:09 - 24:17
    at the beginning of this century this
  • 24:13 - 24:18
    aggressive mitigation i am kevin will
  • 24:17 - 24:22
    tell you this is not going to happen
  • 24:18 - 24:25
    this is the under two-degree world that
  • 24:22 - 24:26
    people talk about sometimes business as
  • 24:25 - 24:30
    usual
  • 24:26 - 24:31
    that's a 56 degree world that's a
  • 24:30 - 24:33
    totally different planet
  • 24:31 - 24:35
    remember how different the ice age was
  • 24:33 - 24:37
    to today
  • 24:35 - 24:39
    well that is just as different but in
  • 24:37 - 24:42
    the opposite direction the ice age was a
  • 24:39 - 24:45
    different planet different organization
  • 24:42 - 24:48
    of ecosystems where people lived where
  • 24:45 - 24:50
    things live where things grew the same
  • 24:48 - 24:54
    will be true for the business-as-usual
  • 24:50 - 24:58
    planet where were more likely to end up
  • 24:54 - 25:01
    in my opinion is some effort serious
  • 24:58 - 25:03
    mitigation not today not tomorrow maybe
  • 25:01 - 25:05
    in the next 10 years 20 years 30 is
  • 25:03 - 25:09
    armed and now I'll still be a planet
  • 25:05 - 25:11
    that has significantly warmer
  • 25:09 - 25:14
    temperatures particularly on land
  • 25:11 - 25:17
    particularly in the North particularly
  • 25:14 - 25:20
    in the Arctic this will be a radically
  • 25:17 - 25:23
    different planet as well but exactly how
  • 25:20 - 25:26
    different is still to be determined but
  • 25:23 - 25:31
    the choices are really ours to make
  • 25:26 - 25:34
    now I'm a scientist and and I spend my
  • 25:31 - 25:36
    time working on those small scale
  • 25:34 - 25:37
    processes and the encapsulation of all
  • 25:36 - 25:39
    of that physics that you store in those
  • 25:37 - 25:42
    animations
  • 25:39 - 25:48
    and these projections these predictions
  • 25:42 - 25:51
    put us in a very odd position and it was
  • 25:48 - 25:57
    very clearly encapsulated by showed
  • 25:51 - 26:00
    Rowland who are was the one of the the
  • 25:57 - 26:02
    chemists who discovered the reactions
  • 26:00 - 26:04
    that led to ozone depletion and some of
  • 26:02 - 26:06
    you here will remember spray cans and
  • 26:04 - 26:09
    freon and the Montreal Protocol and how
  • 26:06 - 26:13
    that was negotiated and how that changed
  • 26:09 - 26:16
    so sure Roland understood quite clearly
  • 26:13 - 26:18
    the consequences of having made
  • 26:16 - 26:22
    scientific discoveries that have
  • 26:18 - 26:25
    real-world implications and he said in
  • 26:22 - 26:27
    an interview what's the use of having
  • 26:25 - 26:31
    developed a science well enough to make
  • 26:27 - 26:33
    predictions if in the end all willing to
  • 26:31 - 26:37
    do is stand around and wait for them to
  • 26:33 - 26:41
    come true and that's really the dilemma
  • 26:37 - 26:45
    that people like me fais do we just
  • 26:41 - 26:47
    continue to make predictions or do we go
  • 26:45 - 26:50
    out and tell people about what these
  • 26:47 - 26:52
    predictions mean do we go and help
  • 26:50 - 26:54
    people work out what they should do
  • 26:52 - 26:57
    about the energy system i'm not an
  • 26:54 - 26:59
    expert in energy systems you know should
  • 26:57 - 27:01
    we use nuclear power should be used
  • 26:59 - 27:01
    geothermal power should we do this
  • 27:01 - 27:04
    should we do that
  • 27:01 - 27:08
    those are decisions that are not up to
  • 27:04 - 27:12
    me though I would like to think that the
  • 27:08 - 27:15
    information that we produce informs the
  • 27:12 - 27:17
    decisions that you make individually and
  • 27:15 - 27:23
    that you make as a city or as a country
  • 27:17 - 27:29
    and as the world and I don't know what
  • 27:23 - 27:34
    our future will hold arm but i'm i'm
  • 27:29 - 27:37
    hopeful that whatever future we choose
  • 27:34 - 27:43
    it's an informed future so thank you
  • 27:37 - 27:43
    very much
Title:
Long blank video (1:46:39)
Description:

I created this video with the YouTube Video Editor (http://www.youtube.com/editor) by duplicating several times the one in http://www.youtube.com/watch?v=IFbc7LWUL8g . This one too is completely empty: no images, no audio. It is uploaded here for experimental reuses in closed captioning platforms. Obviously, it is in the public domain, even though YT does not offer this licensing option.

Update Jan 14, 2012: As I tried to explain in the comments to irate/baffled/amused viewers. I uploaded this video for a purely instrumental purpose: seeing how online collaborative subtitling/captioning instruments can be diverted to collaboratively translate normal texts, and to then export the translation, as you would export the file of translated subtitles.
Of course, you can also collaboratively translate on a wiki page, but the advantage of doing it in a subtitling app is that the original text above the translated part cannot get deleted: this makes revision easier.

I started toying with this 2 and half years ago with DotSUB: see http://etcjournal.com/2009/04/05/collaborative-text-translation-with-dotsub/ . But the problems with DotSUB for that are that a) it does not allow you to have subtitles longer that what its programmers deemed suitable; b) subtitles HAVE to be time-coded and can only be exported in time-coded formats, and it's a bore to have to delete all the time codes if what you want is just a plain text translation of a normal text.
So I decided to try again with Universal Subtitles, where you can transcribe without time-coding. and where you can translate the "non time-coded" transcript, and export the translation as a .txt file.
So I used this irritating blank video to create http://www.universalsubtitles.org/en/videos/xHZzawTR9MLF/ , to which I added, as if it were a transcript of the video, Cory Doctorow's "Constitutional Crisis" short story (1). And then I started to translate it in Italian in the http://www.universalsubtitles.org/en/videos/xHZzawTR9MLF/it/222759/ subpage: click on "Edit Subtitles" if you wish to see the translation interface.
That's all this empty video is about: just a means to create a translating interface for a text that is just a text.

Update Nov. 7, 2012 Changes to the Amara software made it impossible to re-use the already used "subtitle sets": I therefore asked for the deletion of the above-mentioned page, and made a new one in http://www.universalsubtitles.org/en/videos/69iJjyH8euXi/info/long-blank-video-14639/ .

(1) from his "With a Little Help" collection, whose text can be bought in print or downloaded under a , under a http://creativecommons.org/licenses/by-nc-sa/3.0/ license as a digital file from http://craphound.com/walh/e-book/browse-all-versions
----
Update March 5, 2012:
As people inexplicably continue to view this empty video, I'm annotating it with links to real videos of interest. So far:
- Say NO to ACTA: http://www.youtube.com/watch?v=citzRjwk-sQ
- " Se la mafia... Il mulo de Paniz" http://www.youtube.com/watch?v=yG8m7-pMJ_c (see description for interesting links)
- "Listening is learning" http://www.youtube.com/watch?v=o67wV-MhlY8
- V4B - Video4Blind ("Ho scelto il Costa di Lecce! (V4B)" http://youtu.be/K_BidSCokLc

(June 16, 2012)
And now: Don't Leave Me Out, with subs so far in English, French, German, Hebrew and Italian: http://youtu.be/w91A_nB4rx0 .
The video can be subtitled into further languages at http://www.universalsubtitles.org/en/videos/zBpewNm5P8GV/info/dont-leave-me-out/ .

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Video Language:
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01:46:39
Retired user edited English, British subtitles for Sandbox
Dutes D edited English, British subtitles for Sandbox
Dutes D edited English, British subtitles for Sandbox
Mattis Skjevling edited English, British subtitles for Sandbox
Claude Almansi edited English, British subtitles for Sandbox
Adam Tait edited English, British subtitles for Sandbox
Adam Tait edited English, British subtitles for Sandbox
Adam Tait edited English, British subtitles for Sandbox
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