Search Results for: Cloud positive feedback

Cloud Super-Parameterization and Low Climate Sensitivity

“Superparameterization” is described by the Climate Process Team on Low-Latitude Cloud Feedbacks on Climate Sensitivity in an online meeting report (Bretherton, 2006) as: a recently developed form of global modeling in which the parameterized moist physics in each grid column of an AGCM is replaced by a small cloud-resolving model (CRM). It holds the promise […]

AR4: "Now-Classic" Results on Cloud Uncertainty are "Unsettling"

AR4 (chapter 1 on the History of Climate Science) contains the remarkable statement: The strong effect of cloud processes on climate model sensitivities to greenhouse gases was emphasized further through a now-classic set of General Circulation Model (GCM) experiments, carried out by Senior and Mitchell (1993). They produced global average surface temperature changes (due to […]

Spencer on Cloud Feedback

Roy Spencer has an interesting post on cloud feedback at Pielke Sr (which doesn’t permit comments.) He observes: On August 8, 2007, I posted here a guest blog entry on the possibility that our observational estimates of feedbacks might be biased in the positive direction. Danny Braswell and I built a simple time-dependent energy balance […]

Water Vapor Feedback

In response to an inquiry to Scott Saleska, Dan Kirk-Davidoff, a prominent expert in the field, has sent the following suggestions: Soden and Held 2006, An Assessment of Climate Feedbacks in Coupled Ocean—Atmosphere Models, J. Climate 19:3354, DOI: 10.1175/JCLI3799.1 reviews the relative role of various feedbacks in the IPCC AR4 runs. Held and Soden, “Water […]

Water Vapor and Cloud Feedbacks

Is anyone interested in starting a separate thread on water vapor and cloud feedbacks? While it is of some relevance to the hurricane/global warming topic, the relevance is indirect and this topic certainly has enough scientific meat for its own thread (provided people are sufficiently interested. Comment by Judith Curry “¢’‚¬? 17 September 2006 @ […]

Emergent constraints on climate sensitivity in global climate models, Part 2

The four constraints that Caldwell assessed as credible A guest post by Nic Lewis In Part 1 of this article the nature and validity of emergent constraints[i] on equilibrium climate sensitivity (ECS) in GCMs were discussed, drawing mainly on the analysis and assessment of 19 such constraints in Caldwell et al (2018; henceforth Caldwell),[ii] who […]

Marvel et al.’s new paper on estimating climate sensitivity from observations

A guest post by Nic Lewis Introduction and summary Recently a new model-based paper on climate sensitivity was published by Kate Marvel, Gavin Schmidt (the head of NASA GISS) and others, titled ‘Internal variability and disequilibrium confound estimates of climate sensitivity from observations’.[1] It appears to me that the novel part of its analysis is […]

Marvel et al.: Implications of forcing efficacies for climate sensitivity estimates – update

A guest article by Nicholas Lewis Introduction In a recent article I discussed the December 2015 Marvel et al.[1] paper, which contends that estimates of the transient climate response (TCR) and equilibrium climate sensitivity (ECS) derived from recent observations of changes in global mean surface temperature (GMST) are biased low. Marvel et al. reached this […]

Appraising Marvel et al.: Implications of forcing efficacies for climate sensitivity estimates

A guest article by Nicholas Lewis Note: This is a long article: a summary is available here. Introduction In a recent paper[1], NASA scientists led by Kate Marvel and Gavin Schmidt derive the global mean surface temperature (GMST) response of the GISS-E2-R climate model to different types of forcing. They do this by simulations over […]

Pitfalls in climate sensitivity estimation: Part 3

A guest post by Nicholas Lewis In Part 1 I introduced the talk I gave at Ringberg 2015, explained why it focussed on estimation based on warming over the instrumental period, and covered problems relating to aerosol forcing and bias caused by the influence of the AMO. In Part 2 I dealt with poor Bayesian […]