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Cato Institute Lists 14 Low Climate Sensitivity Papers

26.09.2014
26.09.2014 11:09 Age: 2 yrs

The important new paper in Climate Dynamics published yesterday which details robust observational data based research on the warming effect of CO2 is the 14th paper to conclude that so called climate sensitivity is at the lower end of IPCC estimates, according to a list collated by US right wing climate sceptic think tank the Cato Institute. Here we provide abstracts of, and links to, all those papers.

Click to enlarge. From the CATO Institute feature. Figure 1. Climate sensitivity estimates from new research beginning in 2011 (colored), compared with the assessed range given in the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5) and the collection of climate models used in the IPCC AR5. The “likely” (greater than a 66% likelihood of occurrence)range in the IPCC Assessment is indicated by the gray bar. The arrows indicate the 5 to 95 percent confidence bounds for each estimate along with the best estimate (median of each probability density function; or the mean of multiple estimates; colored vertical line). Ring et al. (2012) present four estimates of the climate sensitivity and the red box encompasses those estimates. The right-hand side of the IPCC AR5 range is actually the 90% upper bound (the IPCC does not actually state the value for the upper 95 percent confidence bound of their estimate). Spencer and Braswell (2013) produce a single ECS value best-matched to ocean heat content observations and internal radiative forcing. Courtesy: CATO Institute.

 

New research published in the journal Climate Dynamics yesterday (25 September 2014) was the 14th paper to conclude that the warming effect of CO2 is less than has been assumed, according to the Cato Institute, a right wing climate sceptic US think tank.

The new paper (report here) by independent UK-based climate researcher Nicholas Lewis and professor Judith Curry of the School of Earth and Atmospheric Sciences at the Georgia Institute of Technology, derives estimates of the warming effect of CO22 compared with similar estimates which use forcings diagnosed from simulations by such models.

This is the latest in a series of papers to highlight the possibility that IPCC climate sensitivity estimates may be too high. Most of the sensitivities estimated in these papers are 40% below the average climate sensitivity of the models used by the IPCC, according to a feature on the Cato website co-authored by climate scientist and Cato director Patrick Michaels.

Below we reproduce the Cato feature that lists these papers and then below that we also reproduce the abstracts from, and links to, all 14 papers on lower climate sensitivity.

Cato Feature

Here is the Cato Institute feature reproduced from its website:

September 25, 2014 5:09PM

The Collection of Evidence for a Low Climate Sensitivity Continues to Grow

By Patrick J. Michaels and Paul C. "Chip" Knappenberger References:End of CATO feature.

Abstracts Links and Citations

 

Here are abstracts, citations and links to all these papers:

 

Aldrin, M., et al., 2012.

Bayesian estimation of climate sensitivity based on a simple climate model fitted to observations of hemispheric temperature and global ocean heat content. Environmetrics, doi: 10.1002/env.2140.

Abstract


Read the abstract and get the paper here.

Annan, J.D., and J.C Hargreaves, 2011.

Abstract


Read the abstract and get the paper here.

Hargreaves, J.C., et al., 2012.

Can the Last Glacial Maximum constrain climate sensitivity? Geophysical Research Letters, 39, L24702, doi: 10.1029/2012GL053872

Abstract

here.

Lewis, N. 2013.

An objective Bayesian, improved approach for applying optimal fingerprint techniques to estimate climate sensitivity. Journal of Climate, doi: 10.1175/JCLI-D-12-00473.1.

Abstract

here.

Lewis, N. and J.A. Curry, C., 2014.

here.

Our report here.

Lindzen, R.S., and Y-S. Choi, 2011.

Abstract


Get the abstract and read the paper here.

Loehle, C., 2014.

A minimal model for estimating climate sensitivity. Ecological Modelling, 276, 80-84.

Abstract

here.

Our report here.

Masters, T., 2013.

Observational estimates of climate sensitivity from changes in the rate of ocean heat uptake and comparison to CMIP5  models. Climate Dynamics, doi:101007/s00382-013-1770-4

Abstract

here.

McKitrick, R., 2014.

HAC-Robust Measurement of the Duration of a Trendless Subsample in a Global Climate Time Series. Open Journal of Statistics, 4, 527-535. doi: 10.4236/ojs.2014.47050.

Abstract

The IPCC has drawn attention to an apparent leveling-off of globally-averaged temperatures over the past 15 years or so. Measuring the duration of the hiatus has implications for determining if the underlying trend has changed, and for evaluating climate models. Here, I propose a method for estimating the duration of the hiatus that is robust to unknown forms of heteroskedasticity and autocorrelation (HAC) in the temperature series and to cherry-picking of endpoints. For the specific case of global average temperatures I also add the requirement of spatial consistency between hemispheres. The method makes use of the Vogelsang-Franses (2005) HAC-robust trend variance estimator which is valid as long as the underlying series is trend stationary, which is the case for the data used herein. Application of the method shows that there is now a trendless interval of 19 years duration at the end of the HadCRUT4 surface temperature series, and of 16 - 26 years in the lower troposphere. Use of a simple AR1 trend model suggests a shorter hiatus of 14 - 20 years but is likely unreliable.

Get the abstract and read the paper here.

Our report here.

Michaels. P.J. et al., 2002.

Revised 21st century temperature projections. Climate Research, 23, 1-9.

Abstract


Get the abstract and read the paper here.

Otto, A. et al 2013.

Energy budget constraints on climate response. Nature Geoscience, 6, 415-416.

Abstract

The rate of global mean warming has been lower over the past decade than previously. It has been

argued that this observation might require a downwards revision of estimates of equilibrium climate sensitivity, that is, the long-term (equilibrium) temperature response to a doubling of atmospheric

CO2 concentrations. Using up-to-date data on radiative forcing, global mean surface temperature and total heat uptake in the Earth system, we find that the global energy budget implies a range of values for the equilibrium climate sensitivity that is in agreement with earlier estimates, within

the limits of uncertainty. The energy budget of the most recent decade does, however, indicate a lower range of values for the more policy-relevant transient climate response (the temperature increase at the point of doubling of the atmospheric CO2 concentration following a linear ramp

of increasing greenhouse gas forcing) than the range obtained by either analysing the energy budget of earlier decades or current climate model simulations.

Get the abstract and read the paper here.

Ring, M.J., et al., 2012.

Causes of the global warming observed since the 19th century. Atmospheric and Climate Sciences, 2, 401-415, doi: 10.4236/acs.2012.24035.

Abstract


Get the abstract and read the paper here.

Schmittner,  A., et al. 2011.

Abstract

Assessing the impact of future anthropogenic carbon emissions is currently impeded by uncertainties in our knowledge of equilibrium climate sensitivity to atmospheric carbon dioxide doubling. Previous studies suggest 3 kelvin (K) as the best estimate, 2 to 4.5 K as the 66% probability range, and nonzero probabilities for much higher values, the latter implying a small chance of high-impact climate changes that would be difficult to avoid. Here, combining extensive sea and land surface temperature reconstructions from the Last Glacial Maximum with climate model simulations, we estimate a lower median (2.3 K) and reduced uncertainty (1.7 to 2.6 K as the 66% probability range, which can be widened using alternate assumptions or data subsets). Assuming that paleoclimatic constraints apply to the future, as predicted by our model, these results imply a lower probability of imminent extreme climatic change than previously thought.

Get the abstract and read the paper here.

Skeie,  R. B., T. Berntsen, M. Aldrin, M. Holden, and G. Myhre, 2014.

Abstract


Get the abstract and read the paper here.

Spencer, R. W., and W. D. Braswell, 2013.

The role of ENSO in global ocean temperature changes during 1955-2011 simulated with a 1D climate model. Asia-Pacific Journal of Atmospheric Science, doi:10.1007/s13143-014-0011-z.

Abstract

here.

Our report here.

van Hateren, J.H., 2012.

A fractal climate response function can simulate global average temperature trends of the modern era and the past millennium. Climate Dynamics,  doi: 10.1007/s00382-012-1375-3.

Abstract

here.

Sources

Cato Institute here.

Our report on the new Lewis and Curry Climate Dynamics paper here.