Out At The Boundaries

Guest Post by Willis Eschenbach

I’ve heard many times that whereas weather prediction is an “initial-value” problem, climate prediction is a “boundary problem”. I’ve often wondered about this, questions like “what is the boundary?”. I woke up today thinking that I didn’t have an adequately clear understanding of the difference between the two types of problems.

For these kinds of questions I find it’s hard to beat Wolfram Reference, which is a reference to the various functions in the computer program Mathematica. Wolfram is a total genius in my opinion, and the Wolfram site reflects that. Here’s what Wolfram Reference says (emphasis mine):

Introduction to Initial and Boundary Value Problems

DSolve [a Mathematica function] can be used for finding the general solution to a differential equation or system of differential equations. The general solution gives information about the structure of the complete solution space for the problem. However, in practice, one is often interested only in particular solutions that satisfy some conditions related to the area of application. These conditions are usually of two types.

• The solution x(t) and/or its derivatives are required to have specific values at a single point, for example, x(0)=1 and x’(0)=2. Such problems are traditionally called initial value problems (IVPs) because the system is assumed to start evolving from the fixed initial point (in this case, 0).

• The solution x(t) is required to have specific values at a pair of points, for example, x(0)=1 and x(1)=5. These problems are known as boundary value problems (BVPs) because the points 0 and 1 are regarded as boundary points (or edges) of the domain of interest in the application.

The symbolic solution of both IVPs and BVPs requires knowledge of the general solution for the problem. The final step, in which the particular solution is obtained using the initial or boundary values, involves mostly algebraic operations, and is similar for IVPs and for BVPs.

IVPs and BVPs for linear differential equations are solved rather easily since the final algebraic step involves the solution of linear equations. However, if the underlying equations are nonlinear, the solution could have several branches, or the arbitrary constants from the general solution could occur in different arguments of transcendental functions. As a result, it is not always possible to complete the final algebraic step for nonlinear problems. Finally, if the underlying equations have piecewise (that is, discontinuous) coefficients, an IVP naturally breaks up into simpler IVPs over the regions in which the coefficients are continuous.

Now, as I read that, it says that for an initial value problem (IVP) we need to know the initial conditions at the starting time, and for a boundary value problem (BVP) we need to know the future conditions at a particular boundary. For example, suppose we are interested in the future thermal behavior of an iron rod with one end in a ice-water bath. The boundary condition is that the end of the iron rod in the ice-water bath is at 0°C.

So my question is two-fold. IF predicting weather is an IVP and predicting climate is a BVP, then

1) What is the “boundary” in question?, and

2) Once we determine what the boundary is, how do we know the future value of the boundary?

Some investigation finds that for US$48 I can read the following:

Existence and regularity theorems for a free boundary problem governing a simple climate model

Xiangsheng Xua

Abstract

From a class of mean annual, zonally averaged energy–balance climate models of the Budyko‐Sellers type, we arrive at a free boundary problem with the free boundary being the interface between ice‐covered and ice-free areas. Existence and regularity properties are proved for weak solutions of the problem. In particular, the regularity of the free boundary is investigated.

Fortunately, I don’t need to read it to see that the boundary in question is the ice-water interface. Now, that actually seems like it might work, because we know that at any time in the future, the boundary is always at 0°C. Since we know the future temperature values at that boundary, we can treat it as a boundary problem.

But then I continue reading, and I find Dr. Pielke’s excellent work , which says (emphasis mine):

One set of commonly used definitions of weather and climate distinguishes these terms in the context of prediction: weather is considered an initial value problem, while climate is assumed to be a boundary value problem. Another perspective holds that climate and weather prediction are both initial value problems (Palmer 1998). If climate prediction were a boundary value problem, then the simulations of future climate will “forget” the initial values assumed in a model. The assumption that climate prediction is a boundary value problem is used, for example, to justify predicting future climate based on anthropogenic doubling of greenhouse gases. This correspondence proposes that weather prediction is a subset of climate predictions and that both are, therefore, initial value problems in the context of nonlinear geophysical flow. The consequence of climate prediction being an initial value problem is summarized in this correspondence.

The boundaries in the context of climate prediction are the ocean surface and the land surface. If these boundaries are fixed in time, evolve independently of the atmosphere such that their time evolution could be prescribed, or have response times that are much longer than the time period of interest in the climate prediction, than one may conclude that climate prediction is a boundary problem.

So Dr. Pielke says that there is an entirely different boundary in play, the boundary between the atmosphere and the surface.

But then my question is, how would we know the future conditions of that boundary? If it’s a BVP, we have to know future conditions.

Dr. Pielke takes an interesting turn. IF I understand his method in another paper, Seasonal weather prediction as an initial value problem, he shows that the chosen boundary (the atmosphere/surface interface) doesn’t “evolve independently of the atmosphere such that their time evolution could be prescribed” and thus seasonal weather prediction is shown to be an IVP rather than a BVP.

However … he’s using an entirely different boundary than that used by Xiangsheng Xua above. Which one is right? One, both, or neither?

And the underlying problem, of course, is that IF climate is an initial value problem just like weather, given the chaotic nature of both we have little hope of modeling or predicting the future evolution of the climate.

My conclusion from all of this, which I think is shared by Dr. Pielke, is that climate prediction is an initial value problem. I say this in part because I see no difference in “climate” and “weather” in that both seem to be self-similar, non-linear, and chaotic.

This view is also shared by Mandelbrot, as was discussed about a decade ago over at Steve McIntyre’s excellent blog … have we really been at it that long? Mandelbrot analyzed a number of long-term records and found no change in the fractal nature of the records with timespan. In other words, there’s no break between the chaotic nature of the short, medium, and long-term looks at weather.

Now, it’s often argued that weather prediction has gotten much better over the decades … and this is true. But remember, weather prediction is an initial value problem. That means that the more accurately and specifically and finely we can measure the initial conditions, the better our prediction will be. Much of the improvement in our weather predictions is a result of satellites which give us our initial conditions in exquisite detail. And despite all our advances in predictive ability, lots of weekend barbecues still get rained on.

And at the end of the day, I’m left with my initial questions:

• If modeling the future evolution of the climate a boundary problem, what exactly is the boundary?, and

• Having specified the boundary, how can we know the future conditions of the boundary?

Egads … a post without a single graphic … curious.

w.

My Usual Request: If you think something is incorrect, please have the courtesy to quote the exact words that you disagree with so that everyone can understand your objections.

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242 Comments
rabbit
May 25, 2015 3:58 pm

Climate prediction is a boundary value problem if you’ve already decided what the climate will look like at the end of the duration.
Or am I being too cynical?

Theo Goodwin
May 25, 2015 4:14 pm

Much thanks to you, Willis, for a very good discussion of the differences between an IVP and a BVP. More thanks to you for your explanation of Pielke’s claim that climate is an IVP.

Rob Dawg
May 25, 2015 4:16 pm

Living several miles inland from the Pacific Ocean, on a hill, in a valley I can speak with great authority that any boundary being contemplated twixt land and ocean is likely to be so large and/or vague as to render measure/reporting of initial conditions effectively meaningless.

BarryW
May 25, 2015 4:17 pm

I’m surprised. I would think the boundary would really be the space/atmosphere. Land and water are part of the “inside” of the system. At the very least you have to include it along with land and water if you are just considering atmosphere and, if your taking that approach, possibly you should include ice.

JPS
May 25, 2015 4:21 pm

Weather predictions are largely fluid dynamics problems whereas climate prediction is largely a thermodynamics/heat transfer problem. Weather predictions require transient solutions (predictions marching through distinct time steps) and require boundary conditions in both time and space, including an initial value at all gridpoints as well as rules for interacting with boundaries, primarily the land/air interface, i.e. boundary conditions. Climate models, to my knowledge, are largely steady-state solutions for the entire closed system of the earths atmosphere at some future date- the boundary conditions in this case are the interaction between the upper atmosphere and outer space, as well as the atmosphere and the land/sea. In this sense boundary conditions are not actually a set of conditions in the future but a set of rules by which the model operates at the defined boundary.

Charlie
May 25, 2015 4:29 pm

Climate prediction is palm reading. This is the loosest scam ever. As if anybody could control the climate or really cared about their hypothetical great grandchildren. What a bizarre time to exist.

May 25, 2015 4:31 pm

In climate predictions the boundary condition is the change of forcing over time, the most important is considered CO2. f= (5.35 ln ([CO2](t)/[CO2](0)), To test climate software therefore storylines (SRES, RCP) have been introduced. We are led to believe that the previously worst case scenario SRES A1FI is now a business as usual scenario called RCP8.5. These scenario’s are virtually identical, so whilst climate sensitivity is coming down, the previously worst case is now sold as business as usual.
Look, look, be afraid: we are on the RCP8.5 track! Hiding that we are also still on the SRES A1B track (the real business as usual)

Tom
May 25, 2015 4:42 pm

Climate prediction is not a boundary value problem (BVP), irrespective of whether the boundary is time (between now and the end of the century, say), or atmosphere/surface, or ice/water, or anything else. This is because the problems are not well-posed.
Well-posed BVPs have unique solutions that vary continuously with their inputs. No climate projection has ever been shown to be (or claimed to be, as far as I know) a unique solution to a well-posed BVP. This is why ensemble modelling is used: compute a load of things that could be BVP solutions, then take some sort of average.
Well-posed BVPs do get solved all the time in areas like designing wings for aircraft, geophysics and electrostatics. Real science (where there’s a problem if the wings fall off, you drill in the wrong place, or your industrial painting doesn’t work), rather than climate pseudoscience (where observations are never matched to projections).
In summary, whoever said that whereas weather prediction is an “initial-value” problem, climate prediction is a “boundary problem” wasn’t a mathematician.

Bubba Cow
May 25, 2015 4:43 pm

a good day of wondering and quite graphic for our imaginations,
a skill I fear is lost by many who don’t make the efforts to read

JT
May 25, 2015 4:53 pm

I have always been under the impression that when people described the climate problem as a “boundary value” problem it was with respect to the atmosphere/space interface and the principles of conservation of energy and spontaneous increase of entropy. Given that the shortwave flux incoming is known, the long wave flux outgoing must equal it in order to have long term temperature stability and satisfy the principle of conservation of energy; and the difference in entropy between the incoming and outgoing fluxes is determined by the difference in frequency of the fluxes and the transition from parallel incoming flux to radially distributed outgoing flux; so the total work done within the system and the total amount of entropy created within the system must be finite and determinable, assuming no long-term storage of energy is taking place and that there is no other significant source of energy than the solar flux. The resulting climate(s) over the face of the globe are constrained by the energy and entropy gradients available within the system together with the material constitution of the system. In short, what is possible within the system and what is inevitable within the system is determined by what happens at the boundary of the system, given that all the energy available to the system passes through the system without accumulation.

May 25, 2015 5:02 pm

Thanks, Willis.
I agree that Wolfram is a total genius. Dr. Pielke is another one.
I think weather forecasting will be improved by satellite observations. Climate predictions, not so much, because of the chaotic nature of weather, with becomes climate in aggregate form.
I have seen incredible advances in weather forecasting as practiced by Joe Bastardi. Another genius.
The NWS does an acceptable job with 3-days forecasts, the 7-days forecasts, not so much.
The hurricane seasons forecasts by Dr. Philip Klotzbach and Dr. William Gray of Colorado State University, are quite good. NOAA-NWS, not even in the same league.

May 25, 2015 5:07 pm

IPCC & WMO define climate as weather averaged over 30 years. So it’s simply data and statistics, just like at the dog & horse tracks.

May 25, 2015 5:25 pm

Solar energy makes it through the atmosphere (other than ozone and clouds and sulfur dioxide from volcanoes and some other more minor intercepters 15% may be making it through) and then it mostly gets absorbed by the surface liquid and solid surfaces (less how much gets reflected by those liquid and solid surfaces which is another 20% of the 75% that makes it through).
After that, it is supposed to get simpler. But now we have a number of boundary problems to deal with. How does the gaseous atmosphere interact with those liquid and solid surfaces. We are talking about a tirillion, trillion, trillion, trillion molecules. How much energy in the terms of 10^27 joules do those solid and liquid surfaces already hold. What happens if a small 10^23 joules radiation forcing changes when the surfaces are already holding 10^27 joules. Atmospheric windows, water vapor etc.
I mean, that is all a very big boundary problem which sounds impossible to solve in my opinion.

rpielke
May 25, 2015 5:42 pm

Willis – This is a very important topic; thanks for posting on it. For another perspective, see this paper by Shaun Lovejoy –
Lovejoy, S., 2013: What is Climate?: EOS, 94, No. 1, 1 January 2013, p1-2. http://onlinelibrary.wiley.com/doi/10.1002/2013EO010001/pdf
His more recent work seeks to ferret out the human part where he assumes the climate models accurately replicate the natural climate system as well as that the human role is dominated by CO2. Both of those assumptions are, in my view, wrong.
However, his basic analysis on the chaotic character of the climate system is correct. It is an initial value problem (or to be more precise an initial-boundary value problem as some components of the climate system are nearly invariant on multi-decadal time scales (e.g. terrain).
This paper of ours might be of use on this subject:
Rial, J., R.A. Pielke Sr., M. Beniston, M. Claussen, J. Canadell, P. Cox, H. Held, N. de Noblet-Ducoudre, R. Prinn, J. Reynolds, and J.D. Salas, 2004: Nonlinearities, feedbacks and critical thresholds within the Earth’s climate system. Climatic Change, 65, 11-38. http://pielkeclimatesci.wordpress.com/files/2009/10/r-260.pdf
See also my posts
https://pielkeclimatesci.wordpress.com/2011/01/23/recommended-reading-on-whether-climate-is-an-initial-value-problem/
https://pielkeclimatesci.wordpress.com/2006/12/22/further-comments-demonstrating-that-climate-prediction-is-an-initial-value-problem/
https://pielkeclimatesci.wordpress.com/2011/04/29/climate-science-myths-and-misconceptions-post-4-on-climate-prediction-as-an-boundary-value-problem/
https://pielkeclimatesci.wordpress.com/2006/10/27/the-consequences-of-nonlinearities-in-the-earths-climate-system/
[there are more posts, but this will provide examples of why climate is not just a boundary value problem as the IPCC and others assume.
Roger Sr.

John Phillips
May 25, 2015 5:46 pm

I cannot answer your questions, but can add something related to your excellent post. The weather is mathematically chaotic, and so even a very small difference in assumed initial conditions can result in a very large difference in the weather forecast. The way they (weather forecasters) have greatly improved weather forecasts in recent years is to use ensembles of initial conditions and run many weather forecasts and then throw out the outliers. The problem is, even with small errors in current atmospheric conditions like barometer readings, humidity, etc., or even small inaccuracies in the extrapolation of that data from weather station points across areas, large deviations from reality may result in forecast models because of the chaotic property of the weather.

Roy Spencer
May 25, 2015 5:55 pm

The boundary value referred to is the changing IR cooling of the climate system due to increasing co2.

Admin
May 25, 2015 5:55 pm

It might be an issue of the scale on which the prediction is made.
If you are trying to predict climate for the next 100 years, its unlikely the land / sea boundary will change very much, probably even the ice cover / ice free boundary won’t change very much.
But if you are trying to built a climate model which can handle 10s or 100s of millions of years, there will be substantial changes over this period to the land / sea distribution.
Trying to build a special case climate model which can handle the next 100 years, is probably a different class of problem to trying to build a general climate model which can accurately replicate climate change over millions of years – though without understanding of the general case, its difficult to see how you could create a reliable special case model, without a lot of empirical tuning (say 100 years worth 😉 ).

May 25, 2015 6:01 pm

Wilis, brilliant exposition.
From a Mathematica user, never failed yet even if some is unsolvable.

dmh
May 25, 2015 6:05 pm

The symbolic solution of both IVPs and BVPs requires knowledge of the general solution for the problem.
Do we have the requisite knowledge of the general solution to know?

DirkH
May 25, 2015 6:23 pm

“One set of commonly used definitions of weather and climate distinguishes these terms in the context of prediction: weather is considered an initial value problem, while climate is assumed to be a boundary value problem. Another perspective holds that climate and weather prediction are both initial value problems (Palmer 1998). If climate prediction were a boundary value problem, then the simulations of future climate will “forget” the initial values assumed in a model. ”
That’s all meaningless waffling. As long as they define climate as a 30 year average of weather, it’s the same thing, only run through a lowpass filter. An average is just a lowpass filter. So it’s the same problem. You wanna know what the climate in 2100 is; run a weather model for 85 years and run a 30 year average over it.
They are just waffling to sidestep the tiny issue that weather prediction beyond 10 days is impossible. Too bad for them.
And, an average is a weak low pass filter, and, a chaotic nonlinear system will shift energy from high to low and from low to high frequencies as it is NONLINEAR. So you will have chaos in the low frequencies as well, rendering the entire modeling enterprise predictive-skill-less.

Donb
May 25, 2015 6:35 pm

Beware, beware, their computer models,
their society chairs.
Weave a challenge around them thrice,
And advertise by whom they’re led,
For they on research funds have fed,
And drunk the milk of UN advice
with apologies to Samuel Coleridge

masInt branch 4 C3I in is
May 25, 2015 6:42 pm

How would a dog define climate?
How can a creature, Homo Sapiens Sapiens who has existed less than 0.004 of 1 percent of Earth History define climate?
Answer: Not with any respect to or by any definition of Hell.

H.R.
May 25, 2015 6:51 pm

How can climate be a boundary value problem if climate is the average of weather, which is an initial value problem?
Time can’t be the boundary. I don’t see any boundary to the climate of my mid-west USA location or any other location, given enough time. After my neighborhood has put the glacial/interglacial cycles in the rearview mirror, the climate in my neck of the woods could become desert, Mediterranean, tropical; who knows? Now that’s just my regional climate. What will the global climate be, if there is such a beastie; snowball earth, a lava lamp?

Aran
May 25, 2015 6:54 pm

Weather predictions require the exact weather conditions as a starting point. I.e. they take the most recent measurements, put them on a grid (with as small a mesh as practically possible) and let a supercomputer calculate how the system will progress step by step.
Climate predictions don’t care whether or not it rains today or not. The goal is to predict the long-term average and then it does not matter whether your starting point happens to be a cold autumn day or an extreme heat wave or whatever. Much more important are the factors that keep things stable in the long term. These are the boundaries that are referred to. It may be a bit of a confusing term, since you shouldn’t so much think of them as boundaries in space or time, but rather as the constants or constraints that the system is subjected to (constraints would probably be a better term imho). For instance the average power the earth receives from the sun, the rotational speed of the earth, et cetera. So basically all the factors that the determine what the average conditions will be irrespective of the extremes that may happen from time to time.
I find this a pretty good explanation (also gives a good explanation of forcings and feedback):
http://www.easterbrook.ca/steve/2010/01/initial-value-vs-boundary-value-problems/

May 25, 2015 6:56 pm

Saying climate/weather is a “XYZ problem” is like saying the national debt is an “addition/subtraction problem”. The labels “IVP” and “BVP” merely characterize the constraints on various parameters for solving the ‘primitive equations’ in the mathematical systems used to model these systems. But that is not a complete characterization of weather/climate analysis and forecasting.
These labels don’t convey any information about the probabilistic aspects of the problems. They also don’t convey any notion of the actual physics of weather and climate. Moreover, the full details of weather at every point of time and space would be too complex for the kinds of models we currently use to try understand, explain and predict these phenomena.
I think the problem of weather/climate prediction can be more completely characterized as a Bayesian inference process, where the observations and forecasts are probability distributions. Yes, numerical methods are applied to solve differential equations, but overall it is more like an application of Bayes Theorem and recursive Bayesian estimation.
http://en.wikipedia.org/wiki/Data_assimilation

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