Real Climate Misunderstanding Of Climate Models December 1, 2008Posted by honestclimate in Discussions.
Tags: climate change, global warming, Roger Pielke Sr
Real Climate Misunderstanding Of Climate Models
By Roger Pielke Sr
From Climate Science
Real Climate has introduced a weblog titled FAQ on climate models. There are quite a few issues that can be raised with their answers, but I will focus on just one here. It is their answer to the question “What is tuning”. They write
“What is tuning?
We are still a long way from being able to simulate the climate with a true first principles calculation. While many basic aspects of physics can be included (conservation of mass, energy etc.), many need to be approximated for reasons of efficiency or resolutions (i.e. the equations of motion need estimates of sub-gridscale turbulent effects, radiative transfer codes approximate the line-by-line calculations using band averaging), and still others are only known empirically (the formula for how fast clouds turn to rain for instance). With these approximations and empirical formulae, there is often a tunable parameter or two that can be varied in order to improve the match to whatever observations exist. Adjusting these values is described as tuning and falls into two categories. First, there is the tuning in a single formula in order for that formula to best match the observed values of that specific relationship. This happens most frequently when new parameterisations are being developed.
Secondly, there are tuning parameters that control aspects of the emergent system. Gravity wave drag parameters are not very constrained by data, and so are often tuned to improve the climatology of stratospheric zonal winds. The threshold relative humidity for making clouds is tuned often to get the most realistic cloud cover and global albedo. Surprisingly, there are very few of these (maybe a half dozen) that are used in adjusting the models to match the data. It is important to note that these exercises are done with the mean climate (including the seasonal cycle and some internal variability) – and once set they are kept fixed for any perturbation experiment.”
They make the following remarkable claims:
1. “With these approximations and empirical formulae, there is often a tunable parameter or two that can be varied in order to improve the match to whatever observations exist.”
First, there are always tunable parameters within each parameterization, and there are always quite a few more than one or two.
In my class on modeling, the students have documented the number of tunable parameter for a range of parameterizations, and 10 and more are common for each individual parameterization (e.g. see the class powerpoint presentations at ATOC 7500 for my most recent class).
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