I’ve just been reading “How well do we understand and evaluate climate change feedback processes”, by Bony et.al. (2006) which appears in the Journal of Climate.) While I’ve delved into GCM cloud physics in the past, I’ve never really taken the trouble (beyond this) to get into cloud feedbacks in the climate sense, I’ve been happy to accept the received wisdom that cloud feedbacks are the dominant uncertainty in climate sensitivity, but that most folks (Lindzen apart) believe that despite their uncertainty, the sign at least is very probably positive, that is to enhance the affect of increasing CO2 on surface temperature.

This post is by way of notes from half a day following my nose down the rabbit hole, because for various reasons, I need to educate myself on the issue.

Storm intensity and Frequency

(Nothing to do with why I wanted to read the paper, but something I’ve been interested in for a while.)

Bony et al have an interesting figure which is actually a figure from an earlier paper by Carnell and Senior (1998), which got a mention in the TAR.

Image: IMAGE: static/2009/12/14/Bony.png

As far as I can tell, this paper is close to the basis (see something like 90 citations) of the oft repeated statement that we expect storms to be less frequent but more intense in a future climate.

There have obviously been many follow up papers with other models, including for example, Leckebush and Ulbrich 2004) who in an analysis of GCMS and RCMs found (according to their abstract):

  • Although the overall number of modelled tracks is underestimated in the control period of the global model’s simulation with present-day greenhouse gas forcing, compared to reanalysis data, realistic patterns of the track density over the investigation area are simulated.
  • Changes occur in particular with respect to the A2 scenario for extreme cyclone systems, while for B2 the changes are less pronounced. Especially over western parts of Central Europe, the track density of extreme cyclones increases for A2, accompanied by a tendency towards more intense systems. With respect to the A2 scenario, a tendency towards more extreme wind events caused by deepening cyclones is identified for several regions of Western Europe such as Spain, France, United Kingdom or Germany.
  • Additionally, the climate change signal in the regional climate model (RCM) HadRM3H is analysed. In accordance with the signal of the wind speed changes in the GCM simulation, the RCM reveals an increase of the 95th percentile of the daily maximum wind speed over extended parts of Western Europe related to the areas of increased track density of extreme cyclones under the A2 scenario. Changes with respect to the SRES B2 scenario are similar in their structure, but less pronounced in their amplitude.

A bit of googling resulted in an interesting powerpoint by Ruth McDonald which reviews a lot of similar studies … and then I managed to get hold of Lambert and Fyfe, 2006, which has an analysis making the same point using a CMIP3 multi-model ensemble:

Image: IMAGE: static/2009/12/14/LamFyf.png

Key changes in clouds in a future climate

(This is what I was after):

  • Several analyses show no consensus in the global response to clouds and cloud radiative forcing to a given climatic perturbation.
  • Two analyses showed that the global cloud feedback is positive in all models, but there are large intermodel differences in the magnitude of the feedback.
  • The frequencies of occurrence of different cloud types (both observed and moeled) are highly unequal and so the behaviour of certain clouds may matter more than that of others in explaining the range of feedbacks.
  • Several studies show that the responses of deep convective clouds and of low level clouds differ among GCMs.
  • Changes in the water content of different types of clouds also differ among GCMs …
  • Differences in cloud feedbacks in areas dominated by low-top cloud responses make the largest contribution to the variance in the global feedbacks, with
    • in the tropics, the response differs most between models in subsidence regions (which is consistent with low cloud anyway)
    • the large fraction of the earth covered with this type of cloud being an important contributor …

At the same time however, we have reference to Zhang et al, 2005 which took me off on another riff, but that’s a topic for another day.

Cloud Physics Parameterisations

(this is what I remain most interested in, science-wise, should I ever get any time to do any science myself ever again ….)

One of the things I’m looking forward to getting out out of metafor is a decent summary of what the current state of play in cloud parameterisations is in GCMs … I’ve been out of it for just long enough that it’s hard to get back in … a souped up version of the following table (for just three models, from Wyant. et.al.2006) for all the CMIP5 models should be just the ticket:

Image: IMAGE: static/2009/12/14/WyantParam.png

Papers I now want to read

For these I could only read the abstracts, due to the paucity of support for climate science in my institutional library (which is great for high energy physics, apparently, but crap for climate) … I’m glad that I could get to most of the others via self-archived pdfs (yes, I could get to some via our library subscription!)

  • Uncertainty in Projections of UK Climate Change Resulting from Regional Model Formulation, Rowell, 2006
  • Changes in mid-latitude variability due to increasing greenhouse gases and sulphate aerosols, Carnell and Senior, 1998

(Note that the figures and table have been downgraded in quality by removal of information, consistent with my fair use policy.)