RealClimate Climate science from climate scientists... Sun, 28 Dec 2014 19:20:05 +0000 en hourly 1 Absolute temperatures and relative anomalies Tue, 23 Dec 2014 12:14:19 +0000

Most of the images showing the transient changes in global mean temperatures (GMT) over the 20th Century and projections out to the 21st C, show temperature anomalies. An anomaly is the change in temperature relative to a baseline which usually the pre-industrial period, or a more recent climatology (1951-1980, or 1980-1999 etc.). With very few exceptions the changes are almost never shown in terms of absolute temperatures. So why is that?

There are two main reasons. First of all, the observed changes in global mean temperatures are more easily calculated in terms of anomalies (since anomalies have much greater spatial correlation than absolute temperatures). The details are described in the previous link, but the basic issue is that temperature anomalies have a much greater correlation scale (100’s of miles) than absolute temperatures – i.e. if the monthly anomaly in upstate New York is a 2ºC, that is a good estimate for the anomaly from Ohio to Maine, and from Quebec to Maryland, while the absolute temperature would vary far more. That means you need fewer data points to make a good estimate of the global value. The 2\sigma uncertainty in the global mean anomaly on a yearly basis are (with the current network of stations) is around 0.1ºC in contrast that to the estimated uncertainty in the absolute temperature of about 0.5ºC (Jones et al, 1999).

As an aside, people are often confused by the ‘baseline period’ for the anomalies. In general, the baseline is irrelevant to the long-term trends in the temperatures since it just moves the zero line up and down, without changing the shape of the curve. Because of recent warming, baselines closer to the present will have smaller anomalies (i.e. an anomaly based on the 1981-2010 climatology period will have more negative values than the same data aligned to the 1951-1980 period which will have smaller values than those aligned to 1851-1880 etc.). While the baselines must be coherent if you are comparing values from different datasets, the trends are unchanged by the baseline.

Second, the absolute value of the global mean temperature in a free-running coupled climate model is an emergent property of the simulation. It therefore has a spread of values across the multi-model ensemble. Showing the models’ anomalies then makes the coherence of the transient responses clearer. However, the variations in the averages of the model GMT values are quite wide, and indeed, are larger than the changes seen over the last century, and so whether this matters needs to be assessed.

IPCC figure showing both anomalies as a function of time (left) and the absolute temperature in each model for the baseline (right)

Most scientific discussions implicitly assume that these differences aren’t important i.e. the changes in temperature are robust to errors in the base GMT value, which is true, and perhaps more importantly, are focussed on the change of temperature anyway, since that is what impacts will be tied to. To be clear, no particular absolute global temperature provides a risk to society, it is the change in temperature compared to what we’ve been used to that matters.

To get an idea of why this is, we can start with the simplest 1D energy balance equilibrium climate model:

In the illustrated example, with S=240 W/m2 and \lambda=0.769, you get a ground temperature (T_s) of 288 K (~15ºC). For the sake of argument, let’s assume that is the ‘truth’. If you (inaccurately) estimate that \lambda= 0.73, you get T_s=286K – an offset (error) of about 2K. What does that imply for the temperature sensitivity to a forcing? For a forcing of 4 W/m2 (roughly equivalent to doubling CO2), the change in T in the two cases (assuming no feedbacks) is an almost identical 1.2 K. So in this case, the sensitivity of the system is clearly not significantly dependent to small changes in GMT. Including a temperature feedback on \lambda would change the climate sensitivity, but doesn’t much change the impact of a small offset in T_s. [Actually, I think this result can be derived quite generally based just on the idea that climate responses are dominated by the T^4 Planck response while errors in feedbacks have linear impacts on T_s].

Full climate models also include large regional variations in absolute temperature (e.g. ranging from -50 to 30ºC at any one time), and so small offsets in the global mean are almost imperceptible. Here is a zonally averaged mean temperature plot for six model configurations using GISS-E2 that have a range of about 1ºC in their global mean temperature. Note that the difference in the mean is not predictive of the difference in all regions, and while the differences do have noticeable fingerprints in clouds, ice cover etc. the net impact on sensitivity is small (2.6 to 2.7ºC).

We can also broaden this out over the whole CMIP5 ensemble. The next figure shows that the long term trends in temperature under the same scenario (in this case RCP45) are not simply correlated to the mean global temperature, and so, unsurprisingly, looking at the future trends from only the models that do well on the absolute mean doesn’t change very much:

A) Correlation of absolute temperatures with trends in the future across the CMIP5 ensemble. Different colors are for different ensemble members (red is #1, blue is #2, etc.). B) Distribution of trends to 2070 based on different subsets of the models segregated by absolute temperatures or 20th Century trends.

So, small (a degree or so) variations in the global mean don’t impact the global sensitivity in either toy models, single GCMs or the multi-model ensemble. But since there are reasonable estimates of the real world GMT, it is a fair enough question to ask why the models have more spread than the observational uncertainty.

As mentioned above, the main problem is that the global mean temperature is very much an emergent property. That means that it is a function of almost all the different aspects of the model (radiation, fluxes, ocean physics, clouds etc.), and any specific discrepancy is not obviously tied to any one cause. Indeed, since there are many feedbacks in the system, a small error somewhere can produce large effects somewhere else. When developing a model then, it is far more useful to focus on errors in more specific sub-systems where further analysis might lead to improvements in that specific process (which might also have a knock on effect on temperatures). There is also an issue of practicality – knowing what the equilibrium temperature of a coupled model will be takes hundreds of simulated years of “spin-up”, which can take months of real time to compute. Looking at errors in cloud physics, or boundary layer mixing or ice albedo can be done using atmosphere-only simulations which take less than a day to run. It is therefore perhaps inevitable that the bounds of ‘acceptable’ mean temperatures in models is broader than the observational accuracy.

However, while we can conclude that using anomalies in global mean temperature is reasonable, that conclusion does not necessarily follow for more regional temperature diagnostics or for different variables. For instance, working in anomalies is not as useful for metrics that are bounded, like rainfall. Imagine that models on average overestimate rainfall in an arid part of the world. Perhaps they have 0.5 mm/day on average where the real world has 0.3 mm/day. In the projections, the models suggest that the the rainfall decreases by 0.4 mm/day – but if that anomaly was naively applied to the real world, you’d end up with an (obviously wrong) prediction of negative rainfall. Similar problems can arise with sea ice extent changes.

Another problem arises if people try and combine the (uncertain) absolute values with the (less uncertain) anomalies to create a seemingly precise absolute temperature time series. Recently a WMO press release seemed to suggest that the 2014 temperatures were 14.00ºC plus the 0.57ºC anomaly. Given the different uncertainties though, adding these two numbers is misleading – since the errors on 14.57ºC would be ±0.5ºC as well, making a bit of a mockery of the last couple of significant figures.

So to conclude, it is not a priori obvious that looking at anomalies in general is sensible. But the evidence across a range of models shows that this is reasonable for the global mean temperatures and their projections. For different metrics, more care may need to be taken.


  1. P.D. Jones, M. New, D.E. Parker, S. Martin, and I.G. Rigor, "Surface air temperature and its changes over the past 150 years", Rev. Geophys., vol. 37, pp. 173, 1999.
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Clarity on Antarctic sea ice. Fri, 19 Dec 2014 09:08:33 +0000

I’ve always been a skeptic when it comes to Antarctic sea ice. I’m not referring here to the tiresome (and incorrect) claim that the expansion of sea ice around Antarctica somehow cancels out the dramatic losses of sea ice in the Arctic (NB: polar bears don’t really care if there is sea ice in Antarctica or not). Rather, I’m referring to the idea that the observation of Antarctic sea ice expansion represents a major conundrum in our understanding of the climate system, something one hears even from knowledgeable commentators. In this post, I’ll try to provide some clarity on this subject, with some basic background and discussion of a couple of important recent papers.

In general, Antarctic sea ice forms near the coastline, where upwelling waters cool to the atmosphere. It melts when the winds and currents push it into areas of warmer water to the north. In the summer, it melts pretty much all the way back to the coast. An efficient way to form lots of Antarctic sea ice during the autumn growth season is to have strong winds that push the ice away from the coastline. Pushing sea ice away leaves open water that can lose heat to the atmosphere, creating more sea ice. The persistent circumpolar westerlies are critical in pushing ice toward the north, into warmer waters. (Owing to the Coriolis effect, westerly winds cause northward-flowing surface ocean currents in the Southern Hemisphere).

The importance of the winds in controlling Antarctic sea ice leads to the obvious idea that changing winds can explain the increase that has been observed over the last several decades. There has indeed been a substantial increase in the circumpolar westerlies; this is very well established from observations and is associated with the oft-discussed increase in the “Southern Annular Mode” (SAM) index2. Averaged over the year, the SAM index has increased nearly monotonically since the 1970s (e.g., Marshall et al., 2003). This has led to a fairly simple logic in explaining the recent sea ice increase: the westerly winds have increased, so sea ice has increased too. Furthermore, there is good evidence that the increasing westerlies are a response to anthropogenic climate forcing from CO2 and other greenhouse gas increases in the troposphere, along with ozone declines in the stratosphere (Thompson and Solomon, 2002; Thompson et al., 2011). This would suggest that the observed increase in Antarctic sea ice extent is anthropogenic in origin, just like the Arctic sea ice decline, but for very different reasons. In short, reduced ozone in the stratosphere, and increased CO2 in the troposphere — both climate forcings that are unequivocally anthropogenic — cause increased westerly winds, which cause Antarctic sea ice to expand.

Of course, it’s not that simple. For one thing, the average increase of Antarctic sea ice is actually a small number that is the difference of two big numbers — modest increases over a large area, mostly in the Eastern Hemisphere, and very large decreases over a smaller area in the Western Hemisphere. The map below, showing change in the length of the sea ice season over the last 30 years, illustrates this point well. In spite of the average increase, there are very rapid declines in the Bellingshausen and Amundsen Seas, comparable to sea ice declines in the Arctic. Furthermore, the only season is which there is a significant trend in the westerlies is austral summer. There is a weak positive trend in fall, but both spring and winter show no trend; the SAM trends in these seasons may even be slightly negative, depending on which data are used (Ding et al., 2012). Yet the pattern of sea ice change is quite similar in all seasons: decreasing along the Pacific coast of West Antarctica, and increasing around most of East Antarctica, and in the Ross and Weddell Seas.

Trend in the length of the sea ice season, 1979-2010. Blue and purple areas show areas where sea ice is declining, orange and red where it is increasing. Source: Maksym et al., 2012</a

Trend in the length of the sea ice season, 1979-2010. Blue and purple areas show areas where sea ice is declining, orange and red where it is increasing. Source: Maksym et al., 2012

On top of these subtleties, confusion about the role of the winds has arisen because some of the prominent modeling studies that have examined the relationship between the westerly winds and Antarctic sea ice have come up with results that appear to be in direct opposition to the observations. When fully coupled climate models are run with increased CO2 and decreased stratospheric ozone, the westerly winds increase as has been observed, but sea ice decreases around most of Antarctica. For example, Bitz and Polvani, 2012 found that the pattern of trends is the mirror image of the observations, with increases, rather than decreases in the Amundsen and Bellingshausen Seas.

Annual mean response of sea ice concentration to ozone depletion in a fully coupled climate model (CCSM3, and 1° resolution). Thick black contour shows the marks the winter edge (15% concentration); thin black lines show areas where the change is statistically significant. Note that in this figure, red means a decrease in sea ice. Source: Bitz and Polvani, 2012, Figure 1d.

Annual mean response of sea ice concentration to ozone depletion in a fully coupled climate model (CCSM3, and 1° resolution). Thick black contour shows the marks the winter edge (15% concentration); thin black lines show areas where the change is statistically significant. Note that in this figure, red means a decrease in sea ice. Source: Bitz and Polvani, 2012, Figure 1d.

So what’s really going on? One idea is that changes in ocean stratification might be important. There has been a huge increase in the amount of fresh water getting into the Southern Ocean from melting glaciers, especially in the Amundsen Sea (see, e.g., the latest data from Sutterly et al., 2014). Fresh water forms a sort of buoyant lid on the ocean, limiting the ability of heat from the warmer water below to get to the sea ice and melt it. A study by Bintanja et al. (2013) showed that it was a least plausible that this explains the Antarctic sea ice change. A basic problem, though, is that the greatest discharge of meltwater is occurring in the Amundsen Sea, exactly where sea ice is declining, so while this probably is part of the story, I doubt it’s very dominant.

As it turns out, comparing observations with the results of model experiments like those of Bitz and Polvani (2012) is misleading. Most such experiments are equilibrium experiments: What’s done is to run a model under “preindustrial” conditions, and then to run it again with reduced ozone and increased CO2, and to look at the difference. This provide a measure of what will eventually happen (at least in the model) after many decades or centuries. But when you look at the transient response to changes in the circumpolar winds, as Marshall et al (2014) have done, it turns out that two important things happen. The winds tend to push the sea ice boundary northward, as we would have expected. But the winds push the surface ocean northward too, and cause a slow rise in the isopycnal surfaces (surfaces of constant density). This brings relatively warm deep water closer to the surface, eventually melting sea ice after a period of a few decades, countering the initial increase in sea ice. These results explain why equilibrium model calculations find sea ice decreasing in response to ozone forced changes in the circumpolar winds, and also why observations show the opposite. Not enough time has passed for the equilibrium response to be manifested. These results suggest that some time in the next few decades, there will reverse, and average sea ice will begin to decline.

Furthermore, there’s a whole lot more going on with the winds than just “increased westerlies”. In the areas where the big sea ice losses have occurred, the concept of “circumpolar westerlies” isn’t very relevant. A far more important measure of wind variability in the Amundsen and Bellingshausen Seas is the Amundsen Sea Low (ASL).5 The ASL describes the average location of storms systems the bring heat and moisture into West Antarctica. Changes in the ASL may occur for myriad reasons, but one big hammer that can make it ring is the propagation of atmospheric planetary wave arising out of the tropics, more-or-or less associated with ENSO (El Niño-Southern Oscillation) variability. It’s been clear for many years that ENSO variability play a significant role in sea ice variability in those regions, and recent work shows that this can explain the trends pretty well too (e.g. Yuan and Li, 2008; Stammerjohn et al., 2008). Not incidentally, the adjacent land areas of the Antarctic Peninsula and the West Antarctic Ice Sheet have warmed significantly over the last few decades (Steig et al, 2009; Orsi et al., 2013Bromwich et al, 2013), and those changes can also be attributed largely to tropical climate variability (Schneider and Steig, 2008; Ding et al., 2011; Schneider et al., 2012; Steig et al., 2013). The cause of temperature and sea ice change is the same: more warm air is being steered into West Antarctica, and the atmospheric flow tends to push sea ice against the continent, keeping it from expanding.

So, do we get the right answer if we take into account all of the wind changes that have occurred over the last few decades? The answer is yes. This is nicely illustrated in a study by Holland and Kwok (2012), who showed that wind, ice motion, and ice concentration changes match each other remarkably well. Where the wind has been increasingly northward, concentrations are increasing; where wind and ice motion changes are toward the continent, ice concentrations are decreasing. And this year, Holland et al. (2014), showed that when they drive an ocean and sea ice model with observed winds — not just increased westerlies, but the full range of wind changes, as calculated by the ECMWF (European Center for Medium Range Weather Forecasting) –- they correctly simulate the overall expansion of sea ice, and they also get the pattern of changes pretty much spot-on. To be sure, the authors note that not all the details are explained, and they highlight the possibly greater importance of thermodynamic consideration (i.e. ocean temperature/stratification) in some areas than in others.  Also, the period they study (1992-2010 only) is pretty short.  The results are nevertheless pretty compelling. Just like the observations, the calculations show large decreases in the Amundsen and Bellinghausen seas, but increases nearly everywhere else.7

Modeled (top) vs. observed (bottom) sea ice concentration changes.  Source: Holland et al., 2014.

Modeled (top) vs. observed (bottom) sea ice changes. Source: Holland et al. (2014).

Taken as a whole, these results show that there is no significant contradiction between our understanding of Antarctic sea ice and the observation that it is, in average, expanding. We can explain sea ice trends in the Antarctic rather well if we take into account the full range of changes in winds that have occurred. The average expansion of Antarctic sea ice was not anticipated, but it hardly represents any sort of existential threat to our fundamental understanding of the climate system as a whole. It’s merely an interesting scientific challenge.

Not incidentally, changing winds also have a lot to do with what’s been happening to the Antarctic ice sheet (meaning the land-based glaciers, distinct from the sea ice). I’ll have another post on that later this month, or in the New Year.

For a more in-depth version of this post, see Climate Change National Forum / Making Sense of Antarctic Sea Ice Changes.

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AGU 2014 Sun, 14 Dec 2014 18:23:51 +0000

Once more unto the breach!

Fall AGU this year will be (as last year)

…the largest Earth Science conference on the planet, and is where you will get previews of new science results, get a sense of what other experts think about current topics, and indulge in the more social side of being a scientist.

The full scientific program is available for searching here.

Poster hall sans posters #AGU14

A photo posted by American Geophysical Union (@americangeophysicalunion) on

As in recent years, there will be a lot of live streaming of key sessions and high profile lectures, and continuous twitter commentary (follow the hashtag #AGU14), that give people not attending to get a sense of what’s going on. Some of us (including Mike) are attending and will try and give some highlights as the week goes along.

Some obvious highlights (that will be live-streamed) are the Bjerknes lecture from Brian Hoskins about the Hadley Cell (Tues. 8am), Ulrike Lohmann on clouds in the Charney lecture (Tues. 9am). The Hydroclimatic extremes session on Wednesday morning is being live-streamed and should be very apropos given recent discussions. Peter de Menocal is giving the Emiliani lecture (Wed. 10:20am) on the connections between paleo-climate and human evolution. Not related to climate so much, the sessions on the Rosetta/Philae science will also be viewable (Wednesday). The Lorenz lecture is being given by Demetris Koutsoyiannis a hydrologist whose work on climate statistics has been commented on here before. The Schnieder and Tyndall lectures are being given by Chris Field and Kelly Redmond on Thursday afternoon.

Another interesting presentation is from the group behind “Climate Feedback” – which is a new initiative to help annotate climate science related journalism on Thursday evening (6:30 pm onwards, including a hackathon!). There are also a couple of “SWIRLs” (connected presentations and sessions) on Characterising Uncertainty and Global change: Science Literacy, Societal Impacts, and Response Strategies that should give a broad range of perspectives on the topics.

As was available last year, AGU and the Climate Science Legal Defense Fund have organised a facility for individual consultations with a lawyer (by appointment via for people either who have found themselves involved in legal proceedings associated with their science or people who are just interested in what they might need to be prepared for.

There are obviously many individual presentations that will be of interest, but too many to list here. Feel free to add suggestions in the comments.

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Ten Years of RealClimate: Where now? Sun, 14 Dec 2014 18:23:18 +0000

rc10The landscape for science blogging, the public discourse on climate and our own roles in the scientific community have all changed radically over the last 10 years. Blogging is no longer something that stands apart from professional communications, the mainstream media or new online start-ups. The diversity of voices online has also increased widely: scientists blogging and interacting directly with the public via Twitter and Facebook are much more prevalent than in 2004. The conversations have also changed, and (for the most part) have become more nuanced. And a bunch of early career researchers with enthusiasm, time to spare and things to say, have morphed into institute directors and administrators with lots of new pressures. Obviously, blogging frequency has decreased in the last year or so in response to these pressures and this raises the question: where does RealClimate go now?

Is RealClimate’s mission ‘Climate science from climate scientists’ still needed? There are successful sites about climate science that aren’t run by scientists, but that nevertheless do a good job in providing pointers to the mainstream science, most notably, Climate Central and Carbon Brief, and there are many climate scientists who are on Twitter (over 250 via this list curated by Tamsin Edwards). Lots of climate scientists are blogging for themselves (including some RC folk): Ed Hawkins and guests at Climate Lab Book, Tamsin Edwards, Doug McNeall, Simon Donner, Isaac Held, Jules Hargreaves and James Annan, Jim Bouldin, Sophie Lewis, Georg Hoffmann, Anders Levermann, Kate Marvel and Judy Curry, or who occasionally contribute to the bigger sites such as HuffPo or Slate (Micheal Mann, Ray Pierrehumbert) or the Conversation (Australian, UK, and US editions). The Climate Change National Forum (CCNF) has a wide roster of US-based climate scientists and an expanding mandate. However, none of these efforts duplicate RealClimate in terms of reach or content or community.

We therefore feel that RealClimate still has a role, albeit one that is not tied solely to the current list of contributors. Consequently we need to find ways to transition the site into something that is more of an institution rather than just somewhere we blog. This is undoubtedly a challenge and we will need help to do this successfully. Different directions are possible – increasing use of outside content (cross-posting good pieces by climate scientists elsewhere?), a wider focus to include climate impacts, more of a journal club etc. But while those are possibilities to discuss, we really think we should start with…

A clean slate

A number of us – Gavin, Mike, Ray P. and Ray B. – will be stepping away from an active role in running the blog in 2015. They’ll still contribute occasional guest posts and interact in the comments, but the day-to-day roles will be passed on. Though they will continue posting on Twitter (which requires a little less overhead): @ClimateOfGavin, @MichaelEMann, @Climatebook and @raybradleyUMass. Stefan, Eric, David and Rasmus will continue to contribute, though perhaps not at the same rate. This will leave some holes in the roster, and so we are making a…

Call for proposals

Specifically, we are putting out an open call for climate scientists to join the RealClimate team. We are looking for early career researchers who have a desire to explain the science and engage with the public who want to be part of a group that makes that a little easier. You should be an active researcher in a climate-related field (including impacts), at postdoc level or beyond, and have an enthusiasm to explain the science quite generally, not just about your own research. You might already have your own blog, or you might just want to give blogging a try to see how it feels. And all of it as a purely voluntary and unpaid activity!

If you blog independently or are thinking about it, it’s worth going over the advantages of a group blog (see here for a discussion): It can remain active even if for a short period individuals are too busy; it comes with an existing critical mass of commenters and readers that you don’t have to build; You don’t need to be an expert on everything that comes up; and there is support if things go wrong. RealClimate has always had an internal peer review system for substantive posts and this is fun to participate in even if you don’t have time to write full posts yourself. It is also a big help if you are looking for input on tone, level and writing style.

Additionally, we are specifically looking for someone with blogging experience to act as a general editor. This would involve keeping the WordPress software up-to-date, dealing with guest posts, comment moderation etc. This is not hard, but does take a little time, though the existing group will provide backup initially.

Note that we are specifically focused on climate science (including impacts), so blogging about more general topics (scientific publishing in general, scientist’s clothes, academic inside baseball, politics, religion etc.) is best done somewhere else. Additionally, if you only want to write about your ideas for saving the world, there are probably better venues for that too. But if you are interested in joining the effort or at least talking about it, let us know. A few of us will be at #AGU14, so catch us there if you like. We’ll hopefully have a transition period over the next few months where people can try this out for size, put up a few posts, get advice, and see if they are interested in keeping this going. Hopefully, we’ll have a new critical mass of contributors by then.

In the meantime, we are always soliciting guest posts, so send along ideas even if you don’t want to commit to anything more involved!

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Ten Years of RealClimate Wed, 10 Dec 2014 20:08:10 +0000

rc10In the spring of 2004, when we (individually) first started talking to people about starting a blog on climate science, almost everyone thought it was a great idea, but very few thought it was something they should get involved in. Today, scientists communicating on social media is far more commonplace. On the occasion of our 10 year anniversary today it is worth reflecting on the impact of those changes, what we’ve learned and where we go next.

Why we started and why we continue

The introductory post Welcome to RealClimate set out our aspiration:

RealClimate is a commentary site on climate science by working climate scientists for the interested public and journalists. We aim to provide a quick response to developing stories and provide the context sometimes missing in mainstream commentary.

Looking back, we think we’ve done well on both these goals. We have provided the most, and the most accessible, context on topics like climate sensitivity, GCMs, attribution, paleo-climate than any other site, with an exception only for the IPCC reports themselves and other assessments, while engaging in depth with commenters from the interested public, journalists and other scientists. We haven’t led the response to every developing story on climate science (an impossible task), but we did where it mattered. Our rebuttals of shop-worn contrarian rhetoric built off experiences on USENET and at Tim Lambert’s Deltoid, and have now been enhanced further at places like

When we started, there were a number of motivations: the desire to have a site where scientists communicated directly with the interested public on issues arising from the “The Day After Tomorrow” say, or provided rebuttals to misinformation as the “The Panda’s Thumb” did for evolution science, or just to write down background we gave to journalists so that we didn’t have to repeat ourselves. But the impetus to keep this going has been a continued desire to elevate the level of conversation on climate so that people could get a sense of what the real issues in the science were, as opposed to arguing about irrelevancies.


To our surprise though, one of key audiences has always been the wider scientific community and other climate scientists themselves. In retrospect this should have been expected. “Climate science” as a topic has grown a little like the Borg – assimilating fields that were loosely connected (oceanography, meteorology, atmospheric chemistry, geology etc.) which over time have become far more connected. This has meant that many people who started out as different kinds of “-ologists” now find themselves being asked questions, teaching and writing about climate. It’s understandable that ecologists might not have learned much about stratospheric chemistry in their training, or that synoptic meteorologists wouldn’t know much about paleo-climate, or that field scientists don’t know much about GCMs. RealClimate has played a big role in bringing these diverse groups “up to speed” on the shared concepts of climate science.

Of course, there are still plenty of know-nothing op-eds from people who’d really prefer the science not to exist, and many loud and misinformed commenters elsewhere on the web; but, in contrast, there have been countless people who have thanked us for providing more background on the issues and for engaging their questions. To be sure, there were times when it all seemed like nothing had changed.

RealClimate has had a noticeable effect on our scientific careers. We would argue that it has made us better communicators (our early posts are much less polished then ones now) and it certainly increased our public profiles in both positive (e.g. the inaugural AGU Climate Communication Prize) and negative ways (FOIA lawsuits to access RealClimate emails). It has even driven our research in cases where we found that there wasn’t much literature on questions that came up here.

Lessons learned

Over the last ten years we have (in our opinion) got better at running a blog, and indeed, at writing for them. To start with, we didn’t envisage there would be quite as much interaction as we ended up with and this brought up a host of issues for how to handle it. Firstly, we have always (and unapologetically) moderated the comment threads. In our opinion this remains essential for curating an interesting and substantive conversation. It took us a while to realise that a continuously available ‘Open Thread’ (the first one was in Jan 2011) was a really good way to keep other threads on topic which was a perennial problem. At that same time, we started a “Bore Hole” thread to dump the more tedious of the troll comments – this too was something we should have done from the start to increase transparency.

One thing we did from the beginning was set up a system of internal peer review among the group for all the substantive posts. While on rare occasions there was disagreement on what to say (and more commonly, how to say it), overall this has been a huge boost to getting the science right, improving the writing and setting the tone. Another excellent idea (and it might even have been a novelty) is to respond to questions and comments “inline”. This has been very helpful in building conversations and effectively interacting with readers without a sprawling mess of threaded comments, and remains a highlight of the comment threads. Our responses are often pointed, though hopefully sometimes amusing, as well as being informative, though on occasion we let frustration get the better of us.

Standing the test of time

Looking back over the hundreds of posts, the breadth of science covered by the contributors (including the guest posts) has been huge. Some of the content was very specific to ephemeral issues that now seems a little quaint, but a lot of the content stands out clearly as worth referencing still. The relevance of critiques of particular idiocies from Fred Singer or an obscure article, while valid, has faded, while general posts on attribution, paleoclimate, climate sensitivity and the surface temperature records remain interesting even years later.

Overall, we think we have much to be proud of and that the sometimes enormous amount of time spent on the site was (almost all) worthwhile. We are however very interested in what you, the readers, think about this. If you have always lurked and never commented, please let us know why. If you think we’re wasting our time, again, let us know (politely please!). If you have learned anything interesting here, from either the posts or the comments, please tell us what.

In three follow-up posts we give some of the numbers on what RealClimate has done, a big shout out to the people who’ve contributed and later this week we’ll discuss what happens next.

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Ten years of RealClimate: Thanks Wed, 10 Dec 2014 20:07:49 +0000

rc10 As well as the current core team – David Archer, Eric Steig, Gavin Schmidt, Mike Mann, Rasmus Benestad, Ray Bradley, Ray Pierrehumbert, Stefan Rahmstorf – this blog has had input from many others over the years:

The 90+ guest contributors and previous team members who bring a necessary diversity of experience and expertise to the blog: Abby Swann, Alan Robock, Anders Levermann, Andrew Monaghan, Andy Baker, Andy Dessler, Axel Schweiger, Barry Bickmore, Bart Strengers, Bart Verheggen, Beate Liepert, Ben Santer, Brian Helmuth, Brian Soden, Brigitte Knopf, Caspar Ammann, Cecilia Bitz, Chris Colose, Christopher Hennon, Corrine LeQuere, Darrell Kaufman, David Briske, David Karoly, David Ritson, David Vaughan, Dim Coumou, Dirk Notz, Dorothy Koch, Drew Shindell, Ed Hawkins, Eugenie Scott, Figen Mekik, Francisco Doblas-Reyes, Frank Zeman, Geert Jan van Oldenborgh, Georg Feulner, Georg Hoffmann, George Tselioudis, Jacob Harold, Jared Rennie, Jason West, Jeffrey Pierce, Jim Bouldin, Jim Prall, John Fasullo, Joy Shumake-Guillemot, Juliane Fry, Karen Shell, Keith Briffa, Kelly Levin, Kevin Brown, Kevin Trenberth, Kim Cobb, Kyle Swanson, Loretta Mickley, Marco Tedesco, Mark Boslough, Martin Manning, Martin Vermeer, Matt King, Matthew England, Mauri Pelto, Michael Bentley, Michael Oppenheimer, Michael Tobis, Michelle L’Heureux, Natassa Romanou, Paul Higgins, Peter Minnett, Phil Jones, Pippa Whitehouse, PubPeer, Raimund Muscheler, Rein Haarsma, Richard Millar, Robert Rohde, Ron Lindsay, Ron Miller, Russell Seitz, Sarah Feakins, Scott Mandia, Scott Saleska, Simon Lewis, Spencer Weart, Stephen Schneider, Steve Ghan, Steve Sherwood, Sybren Drijfhout, Tad Pfeffer, Tamino, Terry Gerlach, Thibault de Garidel, Thomas Crowley, Tim Osborn, Tom Melvin, Urs Neu, Vicky Slonosky, William Anderegg, William Connolley and Zeke Hausfather;

The thousands of commenters that have enlivened the conversation and explored many issues in more depth than is possible in the main posts;

The translators of hundreds of posts into Polish, French, Czech, German, Italian, Spanish, Turkish, Mandarin etc;

Miloslav Nic for his “Guide to RC” which provides a comprehensive set of indexes to the content here;

Ryan and the internet service providers at Peer, and now Webfaction, that have helped deal with the many technical challenges and to Environmental Media Services and later, the Science Communication Network, for covering some of those costs;

A sincere thanks to all.

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Ten years of Realclimate: By the numbers Wed, 10 Dec 2014 20:06:46 +0000

rc10Start date: 10 December 2004

Number of posts: 914

Number of comments: ~172,000

Number of comments with inline responses: 14,277

Minimum number of total unique page visits, and unique views, respectively: 19 Million, 35 Million

Number of guest posts: 100+

Number of mentions in newspaper sources indexed by LexisNexis: 225

Minimum number of contributors and guest authors: 105

Minimum number of times RealClimate was hacked: 2

Busiest month: December 2009

Busiest day of the week: Monday

Number of times the IPCC and the NIPCC are mentioned, respectively: 357, 5

Minimum number of Science papers arising from a blog post here: 1

Minimum number of RealClimate mentions in Web Of Science references: 14

Minimum number of RealClimate mentions in theses indexed by ProQuest: 33

Posts highest ranked by Google by year:

2004 CO2 in ice cores
2005 Water vapour: feedback or forcing?
2006 Al Gore’s Movie
2007 Swindled!
2008 FAQ on climate models
2009 The CRU Hack
2010 Feedback on cloud feedback
2011 Misdiagnosis of surface temperature feedback
2012 Extremely Hot
2013 The new IPCC climate report
2014 Climate response estimates from Lewis and Curry

All numbers are estimates from latest available data, but no warranty is implied or provided so all use of these numbers is at your own risk.

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The most popular deceptive climate graph Mon, 08 Dec 2014 10:38:20 +0000

The “World Climate Widget” from Tony Watts’ blog is probably the most popular deceptive image among climate “skeptics”.  We’ll take it under the microscope and show what it would look like when done properly.

So called “climate skeptics” deploy an arsenal of misleading graphics, with which the human influence on the climate can be down played (here are two other  examples deconstructed at Realclimate).  The image below is especially widespread.  It is displayed on many “climate skeptic” websites and is regularly updated.


The “World Climate Widget” of US “climate skeptic” Anthony Watts with our explanations added.  The original can be found on Watts’ blog

What would a more honest display of temperature, CO2 and sunspots look like?

  1.  It is better to plot the surface air temperature.  That is what is relevant for us humans: we do not live up in the troposphere, nor do natural ecosystems, nor do we grow our food up there. By the way, the satellite-based tropospheric temperatures shown by Watts show almost the same climatic warming trend as those measured by weather stations near ground level (in both cases 0.16 C per decade over the last 30 years).  However, variability in the tropospheric data is considerably larger, especially because of higher sensitivity to El Niño (as happened in 1998) and the solar cycle (we showed that in Foster and Rahmstorf ERL 2011 – when corrected for those factors the surface and troposphere data agree closely).  Because of increased noise, the trend is less obvious to the eye, especially if one shows monthly values which adds yet more noise.  Let us thus use the GISTEMP global annual temperature record from NASA’s Goddard Institute for Space Science (all surface data sets agree to better than 0.1 °C, see comparison graph).
  1.  One needs to scale the CO2 data correctly for an honest comparison with temperature, so that it can actually be used to evaluate climate scientists’ predictions of the CO2 effect.  You can calculate this with a complicated climate model, but one can also use a back-of-envelope estimate.  A CO2 increase from 280 to 400 ppm (equivalent to 2 Watts/meter2 radiative forcing) produces about 1 °C of global warming (at the time when 400 ppm is reached – some further warming will follow with delay). Thus, an increase of 100 ppm CO2 on the right hand side of the graph corresponds to a temperature increase of 0.8°C on the left hand side. That matches the IPCC’s estimate of the “transient climate response (TCR)” of ~2°C at the time of CO2 doubling (see Technical Summary of the IPCC WG1 report, p. 84). The TCR is smaller than the equilibrium climate sensitivity (about 3°C for doubled CO2) because it takes time to warm the oceans. The full equilibrium warming is thus only reached after a time delay. We are going to use the annual values from the famous CO2 measurements which began in 1958 on Mauna Loa in Hawaii.
  1.  And last but not least one should show honest sunspot data (annual time series), not just a snapshot of the number of spots on the sun today (which is completely uninformative for climate purposes – it’s apparently been added to the widget simply to insinuate an important role of the sun). Here also there is a question of the proper scaling (which is actually not that important because solar activity is cyclical and shows no significant trend over the period of the graph).  We will chose the scaling from the correlation analysis of Lean and Rind (2008) from which one can find a measurable effect on global temperature with an amplitude of 0.05°C.

When done this way the graph looks like this:


One of the readers of our German sister blog KlimaLounge, Bernd Herd, has programmed a widget for this graph so it can be added to any website at a size you like, automatically updated annually.

The trends in the CO2 and temperature anomaly curves agree very well with each other.  This is surprising at first because CO2 is of course not the only factor that influences global temperature. There are two reasons for this agreement:

(1)  Of the other anthropogenic factors, some have a warming effect (other greenhouse gases such as methane) while others have a cooling effect (air pollution). These roughly balance in global average. The IPCC AR4 report found a radiative forcing of 1.7 W/m2 from the CO2 increase alone, while the total from all anthropogenic factors amounted to 1.6 W/m2.

(2)  Natural factors (volcanoes, solar cycle) influencing the trend are very small in comparison to anthropogenic CO2 (as e.g. standard correlation analyses show, see for example Lean and Rind 2008Foster and Rahmstorf 2011). The IPCC AR5 found their contribution to global temperature change since 1951 to be in the range of −0.1°C to 0.1°C.

It requires quite some skill to produce a misleading graph like Watts’ global climate widget, which hides the actual connections between global temperature, CO2 and the sunspot cycle. Watts’ widget is quite a useful indicator though: whenever you see it on a website, you know they are trying to fool rather than inform you there.


A quick ‘n dirty guide to falsifying AGW

Dot Earth: Warming Trend and Variations on a Greenhouse-Heated Planet

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Recent global warming trends: significant or paused or what? Thu, 04 Dec 2014 21:09:13 +0000

As the World Meteorological Organisation WMO has just announced that “The year 2014 is on track to be the warmest, or one of the warmest years on record”, it is timely to have a look at recent global temperature changes.

I’m going to use Kevin Cowtan’s nice interactive temperature plotting and trend calculation tool to provide some illustrations. I will be using the HadCRUT4 hybrid data, which have the most sophisticated method to fill data gaps in the Arctic with the help of satellites, but the same basic points can be illustrated with other data just as well.

Let’s start by looking at the full record, which starts in 1979 since the satellites come online there (and it’s not long after global warming really took off).

trend1Fig. 1. Global temperature 1979 to present – monthly values (crosses), 12-months running mean (red line) and linear trend line with uncertainty (blue)

You clearly see a linear warming trend of 0.175 °C per decade, with confidence intervals of ±0.047 °C per decade. That’s global warming – a measured fact.

But you might have heard claims like “there’s been no warming since 1998”, so let us have a look at temperatures starting in 1998 (the year sticking out most above the trend line in the previous graph).

trend2Fig. 2. Global temperature 1998 to present.

You see a warming trend (blue line) of 0.116 °C per decade, so the claim that there has been no warming is wrong. But is the warming significant? The confidence intervals on the trend (± 0.137) suggest not – they seem to suggest that the temperature trend might have been as much as +0.25 °C, or zero, or even slightly negative. So are we not sure whether there even was a warming trend?

That conclusion would be wrong – it would simply be a misunderstanding of the meaning of the confidence intervals. They are not confidence intervals on whether a warming has taken place – it certainly has. These confidence intervals have nothing to do with measurement uncertainties, which are far smaller.

Rather, these confidence intervals refer to the confidence with which you can reject the null hypothesis that the observed warming trend is just due to random variability (where all the variance beyond the linear trend is treated as random variability). So the confidence intervals (and claims of statistical significance) do not tell us whether a real warming has taken place, rather they tell us whether the warming that has taken place is outside of what might have happened by chance.

Even if there was no slowdown whatsoever, a recent warming trend may not be statistically significant. Look at this example:


Fig 3. Global temperature 1999 to 2010.

Over this interval 1999-2010 the warming trend is actually larger than the long-term trend of 0.175 °C per decade. Yet it is not statistically significant. But this has nothing to do with the trend being small, it simply is to do with the confidence interval being large, which is entirely due to the shortness of the time period considered. Over a short interval, random variability can create large temporary trends. (If today is 5 °C warmer than yesterday, than this is clearly, unequivocably warmer! But it is not “statistically significant” in the sense that it couldn’t just be natural variability – i.e. weather.)

The lesson of course is to use a sufficiently long time interval, as in Fig. 1, if you want to find out something about the signal of climate change rather than about short-term “noise”. All climatologists know this and the IPCC has said so very clearly. “Climate skeptics”, on the other hand, love to pull short bits out of noisy data to claim that they somehow speak against global warming – see my 2009 Guardian article Climate sceptics confuse the public by focusing on short-term fluctuations on Björn Lomborg’s misleading claims about sea level.

But the question the media love to debate is not: can we find a warming trend since 1998 which is outside what might be explained by natural variability? The question being debated is: is the warming since 1998 significantly less than the long-term warming trend? Significant again in the sense that the difference might not just be due to chance, to random variability? And the answer is clear: the 0.116 since 1998 is not significantly different from those 0.175 °C per decade since 1979 in this sense. Just look at the confidence intervals. This difference is well within the range expected from the short-term variability found in that time series. (Of course climatologists are also interested in understanding the physical mechanisms behind this short-term variability in global temperature, and a number of studies, including one by Grant Foster and myself, has shown that it is mostly related to El Niño / Southern Oscillation.) There simply has been no statistically significant slowdown, let alone a “pause”.

There is another more elegant way to show this, and it is called change point analysis (Fig. 4). This analysis was performed for Realclimate by Niamh Cahill of the School of Mathematical Sciences, University College Dublin.

Fig. 4. Global temperature (annual values, GISTEMP data 1880-2014) together with piecewise linear trend lines from an objective change point analysis. (Note that the value for 2014 will change slightly as it is based on Jan-Oct data only.) Graph by Niamh Cahill.

It is the proper statistical technique for subdividing a time series into sections with different linear trends. Rather than hand-picking some intervals to look at, like I did above, this algorithm objectively looks for times in the data where the trend changes in a significant way. It will scan through the data and try out every combination of years to check whether you can improve the fit with the data by putting change points there. The optimal solution found for the global temperature data is 3 change points, approximately in the years 1912, 1940 and 1970. There is no way you can get the model to produce 4 change points, even if you ask it to – the solution does not converge then, says Cahill. There simply is no further significant change in global warming trend, not in 1998 nor anywhere else.

In summary: that the warming since 1998 “is not significant” is completely irrelevant. This warming is real (in all global surface temperature data sets), and it is factually wrong to claim there has been no warming since 1998. There has been further warming despite the extreme cherry pick of 1998.

What is relevant, in contrast, is that the warming since 1998 is not significantly less than the long-term warming. So while there has been a slowdown, this slowdown is not significant in the sense that it is not outside of what you expect from time to time due to year-to-year natural variability, which is always present in this time series.

Given the warm temperature of 2014, we already see the meme emerge in the media that “the warming pause is over”. That is doubly wrong – there never was a significant pause to start with, and of course a single year couldn’t tell us whether there has been a change in trend.

Just look at Figure 1 or Figure 4 – since the 1970s we simply are in an ongoing global warming trend which is superimposed by short-term natural variability.

Weblink: Statistician Tamino shows that in none of the global temperature data sets (neither for the surface nor the satellite MSU data) has there recently been as statistically significant slowdown in warming trend. In other words: the variation seen in short-term trends is all within what one expects due to short-term natural variability. Discussing short-term trends is simply discussing the short-term “noise” in the climate system, and teaches us nothing about the “signal” of global warming.

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Unforced variations: Dec 2014 Wed, 03 Dec 2014 13:30:21 +0000

This month’s open thread. Think history, Lima, and upcoming additions of a single data point to timeseries based on arbitrary calendrical boundaries.

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