# Comments On Real Climate’s Post “FAQ on climate models: Part II”

Real Climate has a weblog titled “FAQ on climate models: Part II”.

Climate Science has a response to several of the questions that are posed there as well as questions for Gavin Schmidt [who wrote the Real Climate Q&A].  Climate Science has already posted on Part I of the Real Climate FAQs; see

which Gavin has either not seen, or cared to respond to. In either case, he continues to incorrectly communicate important aspects of modeling on Real Climate.

Q & A by Gavin Schmidt

• What are parameterisations?
• Some physics in the real world, that is necessary for a climate model to work, is only known empirically. Or perhaps the theory only really applies at scales much smaller than the model grid size. This physics needs to be ‘parameterised’ i.e. a formulation is used that captures the phenomenology of the process and its sensitivity to change but without going into all of the very small scale details. These parameterisationsare approximations to the phenomena that we wish to model, but which work at the scales the models actually resolve. A simple example is the radiation code – instead of using a line-by-line code which would resolve the absorption at over 10,000 individual wavelengths, a GCM generally uses a broad-band approximation (with 30 to 50 bands) which gives very close to the same results as a full calculation. Another example is the formula for the evaporation from the ocean as a function of the large-scale humidity, temperature and wind-speed. This is really a highly turbulent phenomena, but there are good approximations that give the net evaporation as a function of the large scale (‘bulk’) conditions. In some parameterisations, the functional form is reasonably well known, but the values of specific coefficients might not be. In these cases, the parameterisations are ‘tuned’ to reproduce the observed processes as much as possible.

The only basic physics in the models are the pressure gradient force, advection and the acceleration due to gravity. These are the only physics in which there are no tunable coefficients. Climate models are engineering codes and not fundamental physics. If Gavin concludes otherwise, he should provide examples of any parametrization that does not use tunable empirically derived coefficients.  Also, he should provide examples of where the “functional form” is reasonably well known. This is true for a few types of processes, such as turbulence very near the surface, and for clear sky long- and short-wave radiative fluxes, but is not true for most other parametrizations.

The detailed form of the parameterizations of the atmospheric part of climate models is presented in

Pielke, R.A., Sr., 2002: Mesoscale meteorological modeling. 2nd Edition, Academic Press, San Diego, CA, 676 pp.

Request: Gavin should document the number of parameters used in each of the parameterizations used in the GISS model (or refer us to papers where this appears).

Q & A by Gavin Schmidt

• How are the parameterisations evaluated?
• In at least two ways. At the process scale, and at the emergent phenomena scale. For instance, taking one of the two examples mentioned above, the radiation code can be tested against field measurements at specific times and places where the composition of the atmosphere is known alongside a line-by-line code. It would need to capture the variations seen over time (the daily cycle, weather, cloudiness etc.). This is a test at the level of the actual process being parameterised and is a necessary component in all parameterisations. The more important tests occur when we examine how the parameterisation impacts larger-scale or emergent phenomena. Does changing the evaporation improve the patterns of precipitation? the match of the specific humidity field to observations? etc. This can be an exhaustive set of tests but again are mostly necessary. Note that most ‘tunings’ are done at the process level. Only those that can’t be constrained using direct observations of the phenomena are available for tuning to get better large scale climate features. As mentioned in the previous post, there are only a handful of such parameters that get used in practice.

The statement by Gavin that

“The more important tests occur when we examine how the parameterisation impacts larger-scale or emergent phenomena”

is not correct. Both the process and emergent scales must be accurately modeled. How can the emergent scale be represented skillfully unless the process scale is accurate?

Regarding the statement by Gavin that, with respect to emergent scales,

“As mentioned in the previous post, there are only a handful of such parameters that get used in practice”

Request: Gavin should tell us what are the handful of such parameters used in the GISS model.

Q & A by Gavin Schmidt

What are the differences between climate models and weather models?

“Conceptually they are very similar, but in practice they are used very differently. Weather models use as much data as there is available to start off close to the current weather situation and then use their knowledge of physics to step forward in time. This has good skill for a few days and some skill for a little longer. Because they are run for short periods of time only, they tend to have much higher resolution and more detailed physics than climate models (but note that the Hadley Centre for instance, uses the same model for climate and weather purposes). Weather models develop in ways that improve the short term predictions, though the impact for long term statistics or the climatology needs to be assessed independently. Curiously, the best weather models often have a much worse climatology than the best climate models. There are many current attempts to improve the short-term predictability in climate models in line with the best weather models, though it is unclear what impact that will have on projections.”

Weather models are different from climate models for two main reasons. Weather models focus on the atmospheric part of the climate system and, very importantly, use observed values of temperature, humidity, and winds (and other weather variables, such as cloud information) within the atmosphere as initial conditions. Skill in weather prediction is lost when the memory of these initial conditions is lost.

Gavin’s claim thatCuriously, the best weather models often have a much worse climatology than the best climate models”, is an odd statement, since the weather models use real world observed data! This claim needs to be supported by referring us to peer reviewed studies.

Moreover, as written earlier in my response, weather and climate models are both engineering code in which, of the physical, biological and chemical processes within climate models, only the pressure gradient force, advection and gravity are fundamental physics. All other physical, chemical and biological processes are parameterized.

In order to insure that the dynamics of the atmospheric weather features are accurately predicted (which tests the representation of the pressure gradient force and advection, and of the parameterizations, within the models), the climate models should be run in the weather prediction mode. To my knowledge, the GISS model, and most of the IPCC models, have not completed such an engineering test.

Request: Gavin should tell us why not, or if GISS has completed such a test, provide us the relevant reports or research articles.

I will also post the url of this weblog on Real Climate. If Gavin is interested in a constructive scientific exchange, he will welcome this debate, and respond accordingly.

Update: Here is the comment I submitted to be posted on Real Climate

“Gavin – I have posted a weblog which questions several of your answers [http://climatesci.org/2009/01/20/comments-on-real-climates-post-faq-on-climate-models-part-ii/]. I would be glad to post as a guest weblog your responses on Climate Science. Roger”

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