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Unforced variations: Aug 2019

Filed under: — group @ 31 July 2019

This month’s open thread on climate science topics. Arctic sea ice minimum is upcoming, global temperatures running at (or close) to record levels, heat waves, new reconstructions for the last 2000 years, etc… Surely something there to discuss?

Can planting trees save our climate?

Filed under: — stefan @ 16 July 2019

In recent weeks, a new study by researchers at ETH Zurich has hit the headlines worldwide (Bastin et al. 2019). It is about trees. The researchers asked themselves the question: how much carbon could we store if we planted trees everywhere in the world where the land is not already used for agriculture or cities? Since the leaves of trees extract carbon in the form of carbon dioxide – CO2 – from the air and then release the oxygen – O2 – again, this is a great climate protection measure. The researchers estimated 200 billion tons of carbon could be stored in this way – provided we plant over a trillion trees.

The media impact of the new study was mainly based on the statement in the ETH press release that planting trees could offset two thirds of the man-made CO2 increase in the atmosphere to date. To be able to largely compensate for the consequences of more than two centuries of industrial development with such a simple and hardly controversial measure – that sounds like a dream! And it was immediately welcomed by those who still dream of climate mitigation that doesn’t hurt anyone.

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The International Meeting on Statistical Climatology

Filed under: — rasmus @ 6 July 2019

The weather forecast looks sunny and particularly hot from Sunday to Friday, with afternoon temperatures above 30°C every day, and likely exceeding 35°C by the middle of the week. One consequence is that the poster sessions (Tuesday and Thursday) have been moved to the morning as they will be held outside under a marquee.”


I have never received a notification like this before a conference. And it was then followed up by a warning from the Guardian: ‘Hell is coming’: week-long heatwave begins across Europe.


The heatwave took place and was an appropriate frame for the International meeting on statistical climatology (IMSC), which took place in Toulouse, France (June 24-28). France set a new record-high temperature 45.9°C on June 28th, beating the previous record 44.1°C from 2003 by a wide margin (1.8°C).


One of the topics of this meeting was indeed heatwaves and one buzzword was “event attribution”. It is still difficult to say whether a single event is more likely as a result of climate change because of model inaccuracies when it comes to local and regional details.


Weather and climate events tend to be limited geographically and involve very local processes. Climate models, however, tend to be designed to reproduce more large-scale features, and their output is not exactly the same as observed quantity. Hence, there is often a need for downscaling global climate model results in order to explain such events.


A popular strategy for studying attribution of events is to run two sets of simulations: ‘factual’ (with greenhouse gas forcing) and ‘counterfactual’ (without greenhouse gas forcings) runs for the past, and then compare the results. Another question is how to “frame” the event, as different definitions of an event can give different indicators.


Individual heatwaves are still difficult to attribute to global warming because soil moisture may be affected by irrigation wheras land surface changes and pollution (aerosols) can shift the temperature. These factors are tricky when it comes to modeling and thus have an effect on the precision of the analysis.


Nevertheless, there is little doubt that the emerging pattern of more extremes that we see is a result of the ongoing global warming. Indeed, the results presented at the IMSC provide further support for the link between climate change and extremes (see previous post absence of evidence).


I braved the heat inside the marquee to have a look at the IMSC posters. Several of them presented work on seasonal and decadal forecasting, so both seasonal and decadal prediction still seem to be hot topics within the research community.


A major hurdle facing decadal predictions is to design climate models and give them good enough information so that they are able to predict how temperature and circulation evolve (see past post on decadal predictions). It is hard enough to predict the global mean temperature (link), but regional scales are even more challenging. One question addressed by the posters was whether advanced statistical methods improve the skill when applied to model output.


A wide range of topics was discussed during the IMSC. For instance, how the rate of new record-breaking events (link) can reveal trends in extreme statistics. There was one talk about ocean wave heights and how wave heights are likely to increase as sea-ice retreats. I also learned how severe thunderstorms in the US may be affected by ENSO and climate change.


Another interesting observation was that so-called “emergent constraints” (and the Cox et al, (2018) paper) are still debated, in addition to methods for separating internal variability from forced climate change. And there is ongoing work on the reconstruction of temperature over the whole globe, making use of all available information and the best statistical methods.


It is probably not so surprising that the data sample from the ARGO floats shows an ongoing warming trend, however, by filling in the spaces with temperature estimates between the floats, the picture becomes less noisy. It seems that a better geographical representation removes a bias that gives an underestimated warming trend.

While most talks were based on statistics, there was one that was mostly physics-based on the transition between weather regimes. Other topics included bias-adjustment (multi-variate), studies of compound events (straining the emergency service), the connection between drought and crop yields, how extreme weather affects health, snow avalanches, precipitation from tropical cyclones, uncertainties, downscaling based on texture analysis, and weather generators. To cover all of these would take more space than I think is appropriate for a blog like this.


One important issue was about data sharing which merits wider attention. The lack of open and free data is still a problem, especially if we want to tackle the World Climate Research Programme’s grand challenges. European and US data are freely available and the Israeli experience indicate that open access is beneficial.

Unforced variations: July 2019

Filed under: — group @ 2 July 2019

This month’s open thread for climate science discussions.

Absence and Evidence

Guest commentary by Michael Tobis, a retired climate scientist. He is a software developer and science writer living in Ottawa, Ontario.

A recent opinion piece by economist Ross McKitrick in the Financial Post, which attracted considerable attention in Canada, carried the provocative headline “This scientist proved climate change isn’t causing extreme weather – so politicians attacked”.

In fact, the scientist referenced in the headline, Roger Pielke Jr., proved no such thing. He examined some data, but he did not find compelling evidence regarding whether or not human influence is causing or influencing extreme events.

Should such a commonplace failure be broadly promoted as a decisive result that merits public interest?

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Koonin’s case for yet another review of climate science

We watch long YouTube videos so you don’t have to.

In the seemingly endless deliberations on whether there should be a ‘red team’ exercise to review various climate science reports, Scott Waldman reported last week that the original architect of the idea, Steve Koonin, had given a talk on touching on the topic at Purdue University in Indiana last month. Since the talk is online, I thought it might be worth a viewing.

[Spoiler alert. It wasn’t].

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Unforced Variations vs Forced Responses?

Guest commentary by Karsten Haustein, U. Oxford, and Peter Jacobs (George Mason University).

One of the perennial issues in climate research is how big a role internal climate variability plays on decadal to longer timescales. A large role would increase the uncertainty on the attribution of recent trends to human causes, while a small role would tighten that attribution. There have been a number of attempts to quantify this over the years, and we have just published a new study (Haustein et al, 2019) in the Journal of Climate addressing this question.

Using a simplified climate model, we find that we can reproduce temperature observations since 1850 and proxy-data since 1500 with high accuracy. Our results suggest that multidecadal ocean oscillations are only a minor contributing factor in the global mean surface temperature evolution (GMST) over that time. The basic results were covered in excellent articles in CarbonBrief and Science Magazine, but this post will try and go a little deeper into what we found.

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  1. K. Haustein, F.E.L. Otto, V. Venema, P. Jacobs, K. Cowtan, Z. Hausfather, R.G. Way, B. White, A. Subramanian, and A.P. Schurer, "A Limited Role for Unforced Internal Variability in Twentieth-Century Warming", Journal of Climate, vol. 32, pp. 4893-4917, 2019.

Unforced Variations: June 2019

Filed under: — group @ 3 June 2019

This month’s open thread for climate science discussions. Remember discussion about climate solutions can be found here.

Forced responses: May 2019

Filed under: — group @ 2 May 2019

A bimonthly open thread on climate solutions and policies. If you want to discuss climate science, please use the Unforced Variations thread instead.

Unforced variations: May 2019

Filed under: — group @ 2 May 2019

This month’s open thread about climate science topics. For discussions about solutions and policy, please use the Forced Responses open thread.