12 April 2010

If I were in charge?

Carrot eater asked me to consider what I would do if I were in charge of climate research.  I assume that he wasn't going for answers like 'find a different job promptly', which does make the question a little more theoretical.  Although I do have the copy of Nature that prompted his question, I've not read that article.  So these are my own thoughts.

My first thought is the least creative -- pretty much what is already being done in pretty much the proportions it is already being done.  No doubt that I would like to make some adjustments, say more for ice-related work.  But the main lines have gotten to be the main lines because they consistently show up as areas that deliver improvement to our understanding (satellites, paleoclimate) or they consistently show up as areas hampering our understanding (clouds).  Some areas probably get more funding than ideal, or less than ideal, because humans are involved and a particularly good, or bad, field leader can have effects beyond just writing good papers and proposals.

The two that I like for creative work should start as minor niches.  If my intuition is right, they'll grow markedly, at least for a time.  Because if my intuition is right, there's a lot to be learned from here that would be useful.  But it is pretty much just my intuition, so the starting investment shouldn't be huge.

The less exciting already has some work being done, at least in related fields.  Namely, 'no approximations' modeling.  We do know the equations that describe how fluids move, for instance.  We can write programs that carry out those equations accurately.  But once you're examining a volume of fluid larger than a moderately large fish tank (call it 50 gallons, 200 liters), you have to make approximations.  Computers can't deal with the full dynamics for a larger volume than that.  Nevertheless, in the 1950s and 1960s especially, quite a lot was learned about the general circulation of the atmosphere by doing 'dishpan' experiments.  Dishpans can be set back up, and the computers given accurate representations of them.  And then we can see how close the models come to the observations. 

More about the dishpans in a later post; they were a very clever way of approaching the atmosphere.  But here's a modern version's photo:
  and see also the original press release about the memorial lab, from which I got that picture.  I was among the last students Fultz fired up his working lab for.

The more exciting, to me, notion turns on an observation that I find very striking, and very few others in the field find at all interesting.  Makes it a high risk idea -- those other people are awfully smart, good chance they're seeing a flaw that I'm not.  I'll have a little explaining to do, but the short form of the observation is: for something like the global climate surface temperature field, you only need something like 12 numbers.

If you look at our climate models, they have quite a lot more than 12 numbers to them.  They've got at least 6 for every grid cell, and several hundred thousand to several million grid cells.  Tons of numbers, and how many increases every time we run a climate model at better (meaning smaller grid cells) resolution.

Yet 12 or so is, in some sense, 'enough' for temperature.  (Another 12 for pressure, maybe a bit more for each of wind and humidity.)  The sense starts here: if you look at temperatures around the globe, most of what you see is climate -- that the poles are cold and the tropics are hot.  So we subtract out climate in looking at the global temperature field.

After doing that subtraction, you can see that areas that are warmer than usual tend to be fairly large, millions of square km.  Ditto the areas that are cooler than usual.  Continue with that sort of analysis and you also notice that the warm areas are usually balanced off by cold areas elsewhere.  Keep doing it and you see that the same areas tend to be counterbalancing each other.  These are areas that you can look at and know even thousands of km away whether it is warmer or cooler than usual.  The El Nino-Southern Oscillation is the best-known of these patterns.

Once you get rigorous about doing this, which I will be for a later post, you find that if you pick the right areas, once you've chosen about 12, you can put together the entire globe to fairly good accuracy.  This is the root of methods to reconstruct paleoclimate from information sampled from only a modest number of locations around the world.

But I look at it and think, and wonder ... if you can describe something with only 12 numbers, global surface temperatures in this case, then there should be some way to model it with only that many variables.  If only we were clever enough?

So one thing I'd like to see some funding for is these sorts (I'm sure I'm not the only one with such ideas) of basic research ideas.  They're ideas that will probably take a few years to develop, and most will never pan out.  But they're also the ideas that will revolutionize the field if they do pan out.  Current support for science has gotten very short term in its view.  If you can't be sure to publish a paper or three per year from a grant, you are very unlikely to get it.  Fields therefore get very 'play it safe' in what they attempt to do.


Alastair said...

The idea that the climate state can be summed up with twelve numbers is very interesting.

What are these twelve numbers? Do they include the state of ENSO, the PDO, NAO and AO?

If so, that explains why they cannot be used for deep paleo climate research, since they are all related to oceans, some of which have only existed for 100 Ma.

However, IMHO, that is the way to go. Since weather is a Chaotic system, climate must be too. Thus investigating climate in more and more detail is like a dog chasing its tail. What need to do is forget more and more detailed computer models and concentrate instead on the big picture.

Now, with so much specialisation, it would be impossible to get a grant that would fund such a project, so I doubt that anyone is investigating it :-(

Just the job for an amateur like me!

Cheers, Alastair.

Thomas Palm said...

I suspect that global ground observations probably get less funding than optimal. The old, boring job of collecting data is just less sexy than building a fancy satellite or computer (not to mention that there are big companies lobbying for the chance to build things like that).

Launching "Goresat" should be high on the agenda too, since it is already built.

Robert Grumbine said...

They're numbers related to ENSO, PDO, NAO, AAO, and the like. Don't hang on to exactly 12 being the figure. My real point is that it's a small number, vs. what we do in the climate models so far.

As to a job for an amateur ... you're likely right. Less so on grounds of specialization than because funding agencies are skewing towards safe projects.

But there are a lot of amateurs out there!

Traditional in situ observations are definitely an area I'd like to see more given to. One reason that many US surface weather observing stations are poorly sited is that the money to relocate them and improve them was cut in the mid to late 1990s.

Resurrecting the ocean weather ship program would be a different one in this vein. Far less expensive than a satellite, but gives data in places we otherwise almost never see (too far from land, too heavily clouded -- blocking many satellite instruments).

carrot eater said...

Not sure where you're going with the 12. If the temperature anomaly field can be more or less specified using 12 well-located points, that's surely useful for reconstructing paleoclimate.

But I don't understand how this is useful for modeling. In order to use one point to infer the condition of a larger area, you need to have a good handle on different circulation patterns. And in order to have that handle, I'd think you'd need a finer grid than just those 12 points.

To restate, I can see how the reduction can be helpful when working with sparse measurement data, but I don't see where you're headed in terms of simplifying a model.

jyyh said...

Hello, the simpler model for NH has been attempted (don't know how it performs). Various indexes and their values (descriptions elsewhere thereabouts) may be found @ ftp://ftp.cpc.ncep.noaa.gov/wd52dg/data/indices/tele_index.nh . I'm also quite interested of this sort of evaluation of climate, since it is way more approachable for me than the more accurately calculated grid-models. I don't know if someone has done similar pattern searches for SH, but would be interested on those too (I'd imagine one of the indices would be the variation in the formation of bottom water around Antarctica, which could possibly be calculated of some surface circulation data), but what else? Also some "choke points" (such as Bering strait currents, their warmth, and direction) related to weather phenomena could be included in such a model. Then also add the possible orographic rains on mountain chains effecting rains on nearby areas. I'm afraid that high level of skill in multidimensional vector algebra is needed to produce such a model.

Bayesian Bouffant, FCD said...

Had I been present at the creation, I would have given some useful hints for the better ordering of the universe.

- Alfonso the Wise

EliRabett said...

Having sat in on a number of panel reviews looking for the next great thing, Eli is not so sure that is the way to go.

Maybe the best way is to provide some base funding to soft money types, maybe a month a year, e.g. if someone is supporting 11 months salary on grants and contracts, the agencies should toss a month extra at them and tell them to use it to do exciting stuff.

Faculty essentially have this cushion from their 9 month salary.

James Annan said...

I'm interested in a cite for 12 numbers. Or indeed any cite related to this topic...