Author Archives: niclewis

Emergent constraints on climate sensitivity in global climate models, Part 1

Their nature and assessment of their validity A guest post by Nic Lewis There have been quite a number of papers published in recent years concerning “emergent constraints” on equilibrium climate sensitivity (ECS) in comprehensive global climate models (GCMs), of both the current (CMIP5) and previous (CMIP3) generations. The range of ECS values in GCMs […]

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 […]

Reply to Patrick Brown’s response to my article commenting on his Nature paper

Introduction I thank Patrick Brown for his detailed response (also here) to statistical issues that I raised in my critique “Brown and Caldeira: A closer look shows global warming will not be greater than we thought” of his and Ken Caldeira’s recent paper (BC17).[1] The provision of more detailed information than was given in BC17, and […]

Brown and Caldeira: A closer look shows global warming will not be greater than we thought

A guest post by Nic Lewis Introduction Last week a paper predicting greater than expected global warming, by scientists Patrick Brown and Ken Caldeira, was published by Nature.[1]  The paper (henceforth referred to as BC17) says in its abstract: “Across-model relationships between currently observable attributes of the climate system and the simulated magnitude of future […]

Does a new paper really reconcile instrumental and model-based climate sensitivity estimates?

A guest post by Nic Lewis A new paper in Science Advances by Cristian Proistosescu and Peter Huybers “Slow climate mode reconciles historical and model-based estimates of climate sensitivity” (hereafter PH17) claims that accounting for the decline in feedback strength over time that occurs in most CMIP5 coupled global climate models (GCMs), brings observationally-based climate […]

The effect of Atlantic internal variability on TCR estimation – an unfinished study

A guest article by Frank Bosse (posted by Nic Lewis) A recent paper by the authors Stolpe, Medhaug and Knutti (thereafter S. 17) deals with a longstanding question: By how much are the Global Mean Surface Temperatures (GMST) influenced by the internal variability of the Atlantic (AMV/AMO) and the Pacific (PMV/PDO/IPO)? The authors analyze the […]

How dependent are GISTEMP trends on the gridding radius used?

A guest post by Nic Lewis Introduction Global surface temperature (GMST) changes and trends derived from the standard GISTEMP[1] record over its full 1880-2016 length exceed those per the HadCRUT4.5 and NOAA4.0.1 records, by 4% and 7% respectively.  Part of these differences will be due to use of different land and (in the case of […]

Was early onset industrial-era warming anthropogenic, as Abram et al. claim?

A guest post by Nic Lewis Introduction A recent PAGES 2k Consortium paper in Nature,[i] Abram et al., that claims human-induced, greenhouse gas driven warming commenced circa 180 years ago,[ii] has been attracting some attention. The study arrives at its start dates by using a change-point analysis method, SiZer, to assess when the most recent […]

Are energy budget TCR estimates biased low, as Richardson et al (2016) claim?

A guest post by Nic Lewis   Introduction and Summary In a recently published paper (REA16),[1] Mark Richardson et al. claim that recent observation-based energy budget estimates of the Earth’s transient climate response (TCR) are biased substantially low, with the true value some 24% higher. This claim is based purely on simulations by CMIP5 climate […]

Objective Bayesian parameter estimation: Incorporating prior information

A guest article by Nic Lewis Introduction In a recent article I discussed Bayesian parameter inference in the context of radiocarbon dating. I compared Subjective Bayesian methodology based on a known probability distribution, from which one or more values were drawn at random, with an Objective Bayesian approach using a noninformative prior that produced results […]