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" <s.sal...@ed.ac.uk> 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<rob...@envsci.rutgers.edu> 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: rob...@envsci.rutgers.edu >>> New Brunswick, NJ 08901-8551 USA http://envsci.rutgers.edu/~robock >>> -- You received this message because you are subscribed to the Google Groups "geoengineering" group. To post to this group, send email to geoengineer...@googlegroups.com. To unsubscribe from this group, send email to geoengineering+unsubscr...@googlegroups.com. For more options, visit this group at http://groups.google.com/group/geoengineering?hl=en.
