Friday, February 19, 2016

Water Vapor, Water Vapor Everywhere and It All Absorbs in Air

Elementary quantum mechanics quickly shows that harmonic oscillators (shown by the dotted line in the figure to the right) can only absorb or emit light associated with a transition between neighboring quantum levels such as between v = 0 and 1.  To the extent that molecular vibrational motion is harmonic, this is an absolute rule. Oh yes, there also has to be a change in the dipole moment between the two levels of the transition which explains why homonuclear diatomics (N2 , O2, H2) don't absorb in the infrared. However, molecular vibrational motion (loosely defined as the relative motion of the atoms in a molecule relative to each other) is not quite harmonic (shown by the solid line), and the vibrational selection rule is not absolute in transitions between distant vibrational levels.

Multiquantum changing transitions are weak, but they can be observed, both in the laboratory and the atmosphere.  Karl-Heinz Gericke at Uni-Braunschweig has an on line molecular spectroscopy textbook that goes into detail. Of course, for polyatomic molecules there is more than a single vibrational level and there are transitions that involve not only mutiquantum changes in a single vibrational stack, but also combinations of these changes.

Water vapor, as a triatomic non-linear molecule has three vibrational modes and tens of thousands of observed lines.  Starting about 2000 a major effort was made to explore the quantum states and spectra of water vapor, extending from the near IR into the visible which involved many people and a remarkable mutually supportive set of experimental measurements and theoretical calculations.

As emphasized already in Parts I and II, a distinguishing feature of the present series of IUPAC-sponsored spectroscopic studies is the joint utilization of all available experimental and the best theoretical line (transition) and energy-level data, with a long-term aim of creating complete linelists for all water isotopologues. While determination of a complete linelist is outside the scope of present-day experiments, it can be determined by means of sophisticated first-principles quantum chemical computations. Studies on the spectroscopic networks of water isotopologues  also revealed that a large number of energy levels participate in some transitions strong enough to be observable. Thus, although only a small portion of all the allowed transitions will ever be observed experimentally, it seems likely that the majority of energy levels will eventually be connected to observed transitions. For the time being, as experimental line positions have a higher accuracy than those yielded by even the most advanced computations, complete line lists will necessarily contain a mixture of accurate experimental data and less accurate computational data. MARVEL-type efforts (a) replace as many computed lines as possible with their experimental counterparts, (b) validate and ideally reduce the uncertainty with which a transition has been determined, and (c) facilitate the assignment of experimental spectra. Unlike line positions, the overwhelming majority of one-photon, temperature-dependent absorption and emission intensities can be computed with an accuracy matching or even exceeding most of the measurements. Thus, the availability of first-principles intensities, based on computed and perhaps empirically adjusted potential energy surfaces (PES) and dipole moment surfaces (DMS)  greatly helps in the assignment and labeling of experimental absorption or emission spectra.
What does this have to do with the climate?  The transmission of sunlight through the atmosphere in the near infrared (between say 0.7 and 1.5 microns), is limited by the absorption of water vapor and we now know with precision where each of the lines is, how strong each is at any temperature and what transitions they correspond to.  The figure below shows the absorption through the entire atmosphere.  For comparison on a strong CO2 bending mode line a photon might travel a few meters before being absorbed, On one of these near IR lines, the average distance traveled before absorption might be a kilometer or more, so these lines are comparatively weak, but not vanishing.

A key predictions of climate models and common sense is that increased surface temperature will drive a positive feedback by increasing the water vapor content of the atmosphere, resulting in more rain, or if the bunnies prefer, precipitation.  This strengthening of the hydrological cycle on the front end depends on faster evaporation driven by warming of the surface, and on the back end by the lapse rate which cools the atmosphere at altitude and results in condensation.  Anything which warms the atmosphere where precipitation forms weakens the hydrological cycle but until relatively recently good line by line calculations were limited by the data.  Of course complex climate models which extend beyond radiative transfer cannot include all of this detail and rather parameterize  enables the calculations to take slightly less time than the age of the universe.  Each model in the CIMP5 ensemble is different on this account.

In an article in Nature (with an introduction by Steven Sherwood) deAngelis, Qu, Zelinka and Hall consider the effect of the NIR absorption by water vapor in the atmosphere on precip.
Using an ensemble of climate models, here we show that such models tend to underestimate the sensitivity of solar absorption to variations in atmospheric water vapour, leading to an underestimation in the shortwave absorption increase and an overestimation in the precipitation increase.  This sensitivity also varies considerably among models due to differences in radiative transfer parameterization, explaining a substantial portion of model spread in the precipitation response.
CIMP5 models find an increase of 1-3% in the cycle per degree kelvin surface warming, while this may appear small, it is a factor of three and a difference in the ensemble average of ~35%.   The parameterization varies from reasonably in agreement with observation (HadGEM2-ES, ACCESS1.3, GFDL-CM3) to way out (GISS-E2-R/H).

Basically, the path from bad to good is temporal, with more modern, and complex parameterizations performing better, and older schemes such as those based on the International Satellite Cloud Climatology Project, flux data set showing the worst agreement.  Sherwood concludes that
It is remarkable for a paper not only to identify a useful link between observable behaviour in today's climate and a crucial aspect of global climate change, provigind a physical explanation, but also to trace that link back to a specific scheme within models.  Such links, sometimes called emergent constraints, are now a hot topic in efforts to narrow the known uncertainty (model spread) in predictions of global warming.  They should take centre stage in any efforts to 'weight' the predictions of some models over others.  But most emergent constraints reported so far either lack a clear physical explanation or fail to significantly narrow the uncertainty, either because the relationship is insufficiently strong or because there are not enough relevant observations to exploit it.  DeAngelis and colleagues provide an example of what such efforts should aspire to.
DeAngelis et al is a major step forward, but as Sherwood says,
Their result is impressive, but its value for our understanding of climate change is more theoretical than practical.  The main impacts from global warming will depend on regional changes in the amount and intermittency of precipitation, rathe than theon the global, time averaged amount.
As the modelers incorporate this work into their models, and they are doing so, it will be interesting to see how it plays out on a regional basis.


Aaron said...

What happens in clouds?

Fernando Leanme said...

I agree with the comment that the real deal comes in the simulation of small scale regions. My experience running dynamic models has been that very small sectors can go nuts and spiral into absurd states which misrepresent nature. I used to call them "reality leaks". What was even worse was the way some "simulator pilots" avoided the proper use of post processing and visualizing the model outputs to see if they made any sense. I've seen presentations of really lousy model results as if they were reality. Nauseating.

DrTskoul said...

It is up to the experience of the modeler to discern those states ....

Chase S said...

Mr. Rabett, weird times up here. My group is fine for awhile, but the State has decided to decapitate those programs "unworthy" of oil money. Surprisingly, our Mutual Friend has come out strongly against the same person he supported in the great wood smoke air pollution bonanza a year ago.