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Sensible Questions on Climate Sensitivity

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Guest Commentary by Cristian Proistosescu, Peter Huybers and Kyle Armour

tl;dr 

Two recent papers help bridge a seeming gap between estimates of climate sensitivity from models and from observations of the global energy budget. Recognizing that equilibrium climate sensitivity cannot be directly observed because Earth’s energy balance is a long way from equilibrium, the studies instead focus on what can be inferred about climate sensitivity from historical trends. Calculating a climate sensitivity from the simulations that is directly comparable with that observed shows both are consistent. Crucial questions remain, however, regarding how climate sensitivity will evolve in the future.

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Observations, Reanalyses and the Elusive Absolute Global Mean Temperature

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One of the most common questions that arises from analyses of the global surface temperature data sets is why they are almost always plotted as anomalies and not as absolute temperatures.

There are two very basic answers: First, looking at changes in data gets rid of biases at individual stations that don’t change in time (such as station location), and second, for surface temperatures at least, the correlation scale for anomalies is much larger (100’s km) than for absolute temperatures. The combination of these factors means it’s much easier to interpolate anomalies and estimate the global mean, than it would be if you were averaging absolute temperatures. This was explained many years ago (and again here).

Of course, the absolute temperature does matter in many situations (the freezing point of ice, emitted radiation, convection, health and ecosystem impacts, etc.) and so it’s worth calculating as well – even at the global scale. However, and this is important, because of the biases and the difficulty in interpolating, the estimates of the global mean absolute temperature are not as accurate as the year to year changes.

This means we need to very careful in combining these two analyses – and unfortunately, historically, we haven’t been and that is a continuing problem.

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Climate Sensitivity Estimates and Corrections

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You need to be careful in inferring climate sensitivity from observations.

Two climate sensitivity stories this week – both related to how careful you need to be before you can infer constraints from observational data. (You can brush up on the background and definitions here). Both cases – a “Brief Comment Arising” in Nature (that I led) and a new paper from Proistosescu and Huybers (2017) – examine basic assumptions underlying previously published estimates of climate sensitivity and find them wanting.

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References

  1. C. Proistosescu, and P.J. Huybers, "Slow climate mode reconciles historical and model-based estimates of climate sensitivity", Science Advances, vol. 3, 2017. http://dx.doi.org/10.1126/sciadv.1602821

Snow Water Ice and Water and Adaptive Actions for a Changing Arctic

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The Arctic is changing fast, and the Arctic Council recently commissioned the Arctic Monitoring and Assessment Programme (AMAP) to write two new reports on the state of the Arctic cryosphere (snow, water, and ice) and how the people and the ecosystems in the Arctic can live with these changes.

The two reports have now just been published and are called Snow Water Ice and Permafrost in the Arctic Update (SWIPA-update) and Adaptive Actions for a Changing Arctic (AACA).

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Judy Curry’s attribution non-argument

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Following on from the ‘interesting’ House Science Committee hearing two weeks ago, there was an excellent rebuttal curated by ClimateFeedback of the unsupported and often-times misleading claims from the majority witnesses. In response, Judy Curry has (yet again) declared herself unconvinced by the evidence for a dominant role for human forcing of recent climate changes. And as before she fails to give any quantitative argument to support her contention that human drivers are not the dominant cause of recent trends.

Her reasoning consists of a small number of plausible sounding, but ultimately unconvincing issues that are nonetheless worth diving into. She summarizes her claims in the following comment:

… They use models that are tuned to the period of interest, which should disqualify them from be used in attribution study for the same period (circular reasoning, and all that). The attribution studies fail to account for the large multi-decadal (and longer) oscillations in the ocean, which have been estimated to account for 20% to 40% to 50% to 100% of the recent warming. The models fail to account for solar indirect effects that have been hypothesized to be important. And finally, the CMIP5 climate models used values of aerosol forcing that are now thought to be far too large.

These claims are either wrong or simply don’t have the implications she claims. Let’s go through them one more time.

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Model projections and observations comparison page

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We should have done this ages ago, but better late than never!

We have set up a permanent page to host all of the model projection-observation comparisons that we have monitored over the years. This includes comparisons to early predictions for global mean surface temperature from the 1980’s as well as more complete projections from the CMIP3 and CMIP5. The aim is to maintain this annually, or more often if new datasets or versions become relevant.

We are also happy to get advice on stylistic choices or variations that might make the graphs easier to comprehend or be more accurate – feel free to suggest them in the comments below (since the page itself will be updated over time, it doesn’t have comments associated with it).

If there are additional comparisons you are aware of that you think would be useful to include, please point to the model and observational data set(s) and we’ll try and include that too. We should have the Arctic sea ice trends up shortly for instance.

The underestimated danger of a breakdown of the Gulf Stream System

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A new model simulation of the Gulf Stream System shows a breakdown of the gigantic overturning circulating in the Atlantic after a CO2 doubling.

A new study in Science Advances by Wei Liu and colleagues at the Scripps Institution of Oceanography in San Diego and the University of Wisconsin-Madison has important implications for the future stability of the overturning circulation in the Atlantic Ocean. They applied a correction to the freshwater fluxes in the Atlantic, in order to better reproduce the salt concentration of ocean waters there. This correction changes the overall salt budget for the Atlantic, also changing the stability of the model’s ocean circulation in future climate change. The Atlantic ocean circulation is relatively stable in the uncorrected model, only declining by about 20% in response to a CO2 doubling, but in the corrected model version it breaks down completely in the centuries following a CO2 doubling, with dramatic consequences for the climate of the Northern Hemisphere. [Read more…] about The underestimated danger of a breakdown of the Gulf Stream System

Tuning in to climate models

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There is an interesting news article ($) in Science this week by Paul Voosen on the increasing amount of transparency on climate model tuning. (Full disclosure, I spoke to him a couple of times for this article and I’m working on tuning description paper for the US climate modeling centers). The main points of the article are worth highlighting here, even if a few of the characterizations are slightly off.

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Q & A about the Gulf Stream System slowdown and the Atlantic ‘cold blob’

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Last weekend, in Reykjavik the Arctic Circle Assembly was held, the large annual conference on all aspects of the Arctic. A topic of this year was: What’s going on in the North Atlantic? This referred to the conspicuous ‘cold blob’ in the subpolar Atlantic, on which there were lectures and a panel discussion (Reykjavik University had invited me to give one of the talks). Here I want to provide a brief overview of the issues discussed.

What is the ‘cold blob’?

This refers to exceptionally cold water in the subpolar Atlantic south of Greenland. In our paper last year we have shown it like this (see also our RealClimate post about it):

fig1a_new

Fig. 1 Linear temperature trends from 1901 to 2013 according to NASA data. Source: Rahmstorf et al, Nature Climate Change 2015.

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