Comments on: AGU Day 3 part C: How good are predictions from climate models?

By: I never said that! | Serendipity

I never said that! | Serendipity — Wed, 01 Sep 2010 15:37:22 +0000

[...] earth system models, the workhorses of climate science, appear to have very few bugs, and produce remarkably good simulations of past climate. One of the most important success factors is that the code is written by the scientists [...]

By: AGU 2010 session on Software Engineering for Climate Modeling | Serendipity

AGU 2010 session on Software Engineering for Climate Modeling | Serendipity — Fri, 06 Aug 2010 18:43:15 +0000

[...] Methodologies of Climate Model Confirmation and Interpretation (this was my favourite session last [...]

By: Tracking down the uncertainties in weather and climate prediction | Serendipity

Tue, 06 Jul 2010 22:44:36 +0000

[...] There is a big concern here about how to communicate this. Does this mean the science is going backwards – that we know less now than we did five years ago (imagine the sort of hay that some of the crazier parts of the blogosphere will make of that)? Well, there has been all sorts of progress in the past five years, much of it to do with understanding the uncertainties. And one result is the realization that the previous generations of models have under-represented uncertainty in the physical climate system – i.e. the previous projections for future climate change were more precise than they should have been. The implications are very serious for policymaking, not because there is any weaker case now for action, but precisely the opposite – the case for urgent action is stronger because the risks are worse, and good policy must be based on sound risk assessment. A bigger model spread means there’s now a bigger risk of more extreme climate responses to anthropogenic emissions. This problem was discussed at a fascinating session at the AGU meeting last year on validating model uncertainty, which I blogged at length. [...]

By: Leave Science interpretation to Scientists: Media and Popular Opinion do not Invalidate Climate Science « Remove the Walls

Tue, 16 Mar 2010 04:37:14 +0000

[...] Ms. Madil states: ‘evidence shows us that in recent years there haven been fewer droughts, hurricanes and heat waves than in earlier decades’. Climate science is clear that it is not the frequency of these events that is important. It is location and severity. Climate models quiet accurately predict the changes in rainfall and temperature. Hence climate change. Any specific location may get cooler, warmer, drier or wetter. The trend, however, will be greater global rainfall and temperatures. [20,21]. Although climate models are often attacked as inaccurate, they actual perform reasonably well considering the complexities of climate modelling – one of the most difficult in science. [22]. [...]

By: jstults

jstults — Fri, 05 Feb 2010 18:50:04 +0000

“how can we get the requested runs out of the way quickly so that we can get back to doing our science”. Fundamentally, there is a significant gap between the needs of planners and policymakers for detailed climate forecasts (preferably with the uncertainties quantified), and the kinds of science that the climate models support.

This is why in more mature fields there is usually a significant division of labor between the people doing the science (publishing on new methods / techniques / parameterizations) and the people 'using the models in anger' (doing forecasts). The numerical weather prediction community is a good example of this. Most engineering fields where models of similar complexity / fidelity are used to support decision making are a good example of this.

Sure, climate scientists do mention robustness of the ensemble of models in simulating 20th Century climate as evidence of correctness, but only as part of a much larger collection of arguments about validity.

You're right, comparing models as a form of verification (or heaven forbid, as a form of validation) is building castles in the sand.

the question is how fast will model accuracy tail off once we enter new climate regimes?

Pretty quick. Thanks for your write-up, I think if the current research was presented this way (where uncertainties in predictive capability are honestly addressed) more often, rather than the treatment things get in the popular press, we would be much better off.

By: Climate Science is an Experimental Science | Serendipity

Climate Science is an Experimental Science | Serendipity — Wed, 03 Feb 2010 15:45:45 +0000

[...] fact, predictions of future climate are really only a by-product of climate science. The science itself concentrates on improving our understanding of the processes [...]

By: Exploiting Spatial Memory: Code Canvas | Serendipity

Exploiting Spatial Memory: Code Canvas | Serendipity — Tue, 26 Jan 2010 14:50:13 +0000

[...] methodological choices by the climate scientists, which are entrenched in their design choices, and eventually become inscrutable. And when the code gets old, we lose access to these decisions. I suggested we need a kind of [...]

By: Positive Water-Vapor Feedback | Water Clean and Pure

Positive Water-Vapor Feedback | Water Clean and Pure — Tue, 19 Jan 2010 22:22:52 +0000

[...] AGU Day 3 part C: How good are predictions from climate models … [...]

By: Initial value vs. boundary value problems | Serendipity

Initial value vs. boundary value problems | Serendipity — Sun, 17 Jan 2010 02:28:57 +0000

[...] models have also improved in accuracy steadily over the last few decades. We can now use the known forcings over the last [...]

By: Alicia Grubb

Alicia Grubb — Wed, 13 Jan 2010 19:09:47 +0000

"The main message from Lenny’s talk is if we fail to communicate clearly the limits of today’s climate models for quantitative decision-making, we risk the credibility of tomorrow’s climate science and science-based policy in general." I approve of this message. Was there a quotable quote from his talk that said this? [Here's the verbatim quote from his abstract: "It is suggested that failure to clearly communicate the limits of today’s climate model in providing quantitative decision relevant climate information to today’s users of climate information, would risk the credibility of tomorrow’s climate science and science based policy more generally." (I think he meant 'models' plural) - Steve]