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

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

Filed under: — gavin @ 18 April 2017

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

Filed under: — gavin @ 11 April 2017

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

Filed under: — stefan @ 4 January 2017

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. More »

Tuning in to climate models

Filed under: — gavin @ 30 October 2016

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’

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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The Snyder Sensitivity Situation

Filed under: — gavin @ 26 September 2016

Nature published a great new reconstruction of global temperatures over the past 2 million years today. Snyder (2016) uses 61 temperature reconstructions from 59 globally diverse sediment cores and a correlation structure from model simulations of the last glacial maximum to estimate (with uncertainties) the history of global temperature back through the last few dozen ice ages cycles. There are multiple real things to discuss about this – the methodology, the relatively small number of cores being used (compared to what could have been analyzed), the age modeling etc. – and many interesting applications – constraints on polar amplification, the mid-Pleistocene transition, the duration and nature of previous interglacials – but unfortunately, the bulk of the attention will be paid to a specific (erroneous) claim about Earth System Sensitivity (ESS) that made it into the abstract and was the lead conclusion in the press release.

The paper claims that ESS is ~9ºC and that this implies that the long term committed warming from today’s CO2 levels is a further 3-7ºC. This is simply wrong.

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References

  1. C.W. Snyder, "Evolution of global temperature over the past two million years", Nature, vol. 538, pp. 226-228, 2016. http://dx.doi.org/10.1038/nature19798

Do regional climate models add value compared to global models?

2016-05-20 10.08.17

Global climate models (GCM) are designed to simulate earth’s climate over the entire planet, but they have a limitation when it comes to describing local details due to heavy computational demands. There is a nice TED talk by Gavin that explains how climate models work.

We need to apply downscaling to compute the local details. Downscaling may be done through empirical-statistical downscaling (ESD) or regional climate models (RCMs) with a much finer grid. Both take the crude (low-resolution) solution provided by the GCMs and include finer topographical details (boundary conditions) to calculate more detailed information. However, does more details translate to a better representation of the world?

The question of “added value” was an important topic at the International Conference on Regional Climate conference hosted by CORDEX of the World Climate Research Programme (WCRP). The take-home message was mixed on whether RCMs provide a better description of local climatic conditions than the coarser GCMs.

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Comparing models to the satellite datasets

How should one make graphics that appropriately compare models and observations? There are basically two key points (explored in more depth here) – comparisons should be ‘like with like’, and different sources of uncertainty should be clear, whether uncertainties are related to ‘weather’ and/or structural uncertainty in either the observations or the models. There are unfortunately many graphics going around that fail to do this properly, and some prominent ones are associated with satellite temperatures made by John Christy. This post explains exactly why these graphs are misleading and how more honest presentations of the comparison allow for more informed discussions of why and how these records are changing and differ from models.
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Millennia of sea-level change

How has global sea level changed in the past millennia? And how will it change in this century and in the coming millennia? What part do humans play? Several new papers provide new insights.

2500 years of past sea level variations

This week, a paper will appear in the Proceedings of the National Academy of Sciences (PNAS) with the first global statistical analysis of numerous individual studies of the history of sea level over the last 2500 years (Kopp et al. 2016 – I am one of the authors). Such data on past sea level changes before the start of tide gauge measurements can be obtained from drill cores in coastal sediments. By now there are enough local data curves from different parts of the world to create a global sea level curve.

Let’s right away look at the main result. The new global sea level history looks like this:

Kopp2016_Fig1a+sat

Fig. 1 Reconstruction of the global sea-level evolution based on proxy data from different parts of the world. The red line at the end (not included in the paper) illustrates the further global increase since 2000 by 5-6 cm from satellite data. More »

References

  1. R.E. Kopp, A.C. Kemp, K. Bittermann, B.P. Horton, J.P. Donnelly, W.R. Gehrels, C.C. Hay, J.X. Mitrovica, E.D. Morrow, and S. Rahmstorf, "Temperature-driven global sea-level variability in the Common Era", Proceedings of the National Academy of Sciences, vol. 113, pp. E1434-E1441, 2016. http://dx.doi.org/10.1073/pnas.1517056113