Dear Mike,
Thanks for the update on the models. This makes an even stronger case
for model experiments before we go out into the field. We really need
to understand what the potential reactions will be to cloud seeding so
we can guard against dangers and so that we can design field experiments
that have the potential to teach us about how the system works. I can
see no argument to hurry up and go spray salt into clouds now without a
sound theoretical background to guide where and for how long to spray,
to guarantee that you will be able to measure a signal and test all the
potential benefits and risks. Current arguments to go do this as soon
as possible lack such modeling backgrounds, that I know of.
Alan
Alan Robock, Professor II (Distinguished Professor)
Editor, Reviews of Geophysics
Director, Meteorology Undergraduate Program
Department of Environmental Sciences Phone: +1-732-932-9800 x6222
Rutgers University Fax: +1-732-932-8644
14 College Farm Road E-mail: [email protected]
New Brunswick, NJ 08901-8551 USA http://envsci.rutgers.edu/~robock
On 9/29/2010 12:13 PM, Mike MacCracken wrote:
Yesterday I got to visit the NOAA lab in Boulder and, among other things,
get to see the simulations being done by their 15 km resolution icosahedral
grid simulation model with a finite volume numerical scheme. Other physics
is from the plug-in packages that are available and used in other GCMs. They
are running 10 day forecasts twice a day, and the results certainly look
quite good--better resolution really does help make things appear, at least
with respect to viewing of satellite movies of how the real world is
looking. And they are now getting to explore addition of the smaller scale
aspects not now represented in GCMs (at some point, the heat emissions from
energy use will become important for urban regions; reasonable up slope and
down slope flows; etc.)
With respect to the proposed experiments, it is true that the weather is
chaotic (that is, changing the least significant bits in the initialization
of the model does over a couple of weeks lead to randomly correlated
weather), and that is what Alan is talking about for the weather time scales
(for climate scales, that requires longer simulations and experiments). But,
at the high resolutions that will soon be available (they are aiming in 1-2
years for 4 km non-hydrostatic model, depending on timing of next generation
of graphical processors), my guess is that it is going to be possible to
explore the types of changes in weather that might result as a consequence
of the early cloud brightening field experiments. It will likely require an
ensemble set of simulations (things already being explored in simulations
with and without aerosols, etc.).
As these models get more and more refined and seem to simulate more and more
phenomena that have previously been considered part of the variability [we
should really be saying unexplained instead of natural (even chaotic)
variability until we really get to better models], there will be more and
more capabilities to determine the significance of the changes in models,
and by thoughtful planning of the experiments, in the observations.
Mike
On 9/29/10 5:16 AM, "Stephen Salter"<[email protected]> wrote:
Hi All
Alan says that climate signals will be drowned out by chaotic climate
variations. Both the papers that I pointed to in my email of 24
September were about picking up small signals from large, random
variations. The second paper suggests that a 20 year run of the
pseudo-random stimulus idea might be able to detect changes which are
one or two percent of the root mean square of the natural variation. I
am still hoping for suggestions.
If I knew a bit more about chaos I would like to argue whether or not
the climate is chaotic or we are just ignorant about climate. The best
scientists and philosophers used to think that planetary motions, the
behaviour of chemical elements and the incidence of infectious illnesses
were chaotic. Believing that something is chaotic is an excellent way
of never discovering useful things about it.
Stephen
Emeritus Professor of Engineering Design
Institute for Energy Systems
School of Engineering
Mayfield Road
University of Edinburgh EH9 3JL
Scotland
Tel +44 131 650 5704
Mobile 07795 203 195
www.see.ed.ac.uk/~shs
On 28/09/2010 20:44, Douglas MacMynowski wrote:
Alan - I doubt there's any real disagreement here, but just a
clarification; climate variability/noise is irrelevant to the question
of whether some form of SRM can be tested, but of course critical to
the question of how long it would take to detect a signal. If the
goal is to estimate changes on a global scale, that will take decades
and significant forcing levels (we have a paper under review on this
subject that puts numbers on that trade-off). Other than the moral
hazard, I see no basic difference between testing this, and any other
experiment in any other field of engineering or science. Clearly with
one Earth, I agree with learning everything we can with computer
testing first, but if we ever did want to do this in full-scale, I'd
rather start small and learn something rather than just turning it on
and hoping for the best.
doug
On Sep 27, 11:44 am, Alan Robock<[email protected]> wrote:
Dear Ken,
I think you are being rather picky with words. In any case, I never
said it cannot be tested. I said it cannot be fully tested in a
real-world in situ experiment without full-scale implementation, because
the climate signal will be drowned out by chaotic climate variations and
because injecting into a pristine stratosphere cannot test injecting
into an existing cloud. Of course computers can be used for testing.
That is what I do, and I advocate much more of it. The statement below
refers to in situ experimentation.
Alan
Alan Robock, Professor II (Distinguished Professor)
Editor, Reviews of Geophysics
Director, Meteorology Undergraduate Program
Department of Environmental Sciences Phone: +1-732-932-9800 x6222
Rutgers University Fax: +1-732-932-8644
14 College Farm Road E-mail: [email protected]
New Brunswick, NJ 08901-8551 USA http://envsci.rutgers.edu/~robock
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