This month’s open thread on climate science topics. It’s been a warm summer, dontcha know? Expect ERA5, the satellite data and then the surface data products to confirm this in the next week or so. Sea ice minimum in the Arctic will also occur soon, as will a record low maximum in the Antarctic. El Niño still building in the tropical Pacific. Interesting times…
For various reasons I’m motivated to provide an update on my current thinking regarding the slowdown and tipping point of the Atlantic Meridional Overturning Circulation (AMOC). I attended a two-day AMOC session at the IUGG Conference the week before last, there’s been interesting new papers, and in the light of that I have been changing my views somewhat. Here’s ten points, starting from the very basics, so you can easily jump to the aspects that interest you.
1. The AMOC is a big deal for climate. The Atlantic meridional overturning circulation (AMOC) is a large-scale overturning motion of the entire Atlantic, from the Southern Ocean to the high north. It moves around 15 million cubic meters of water per second (i.e. 15 Sverdrup). The AMOC water passes through the Gulf Stream along a part of its much longer journey, but contributes only the smaller part of its total flow of around 90 Sverdrup. The AMOC is driven by density differences and is a deep reaching vertical overturning of the Atlantic; the Gulf Stream is a near-surface current near the US Atlantic coast and mostly driven by winds. The AMOC however moves the bulk of the heat into the northern Atlantic so is highly relevant for climate, because the southward return flow is very cold and deep (heat transport is the flow multiplied by the temperature difference between northward and southward flow). The wind-driven part of the Gulf Stream contributes much less to the net northward heat transport, because that water returns to the south at the surface in the eastern Atlantic at a temperature not much colder than the northward flow, so it leaves little heat behind in the north. So for climate impact, the AMOC is the big deal, not the Gulf Stream.
2. The AMOC has repeatedly shown major instabilities in recent Earth history, for example during the Last Ice Age, prompting concerns about its stability under future global warming, see e.g. Broecker 1987 who warned about “unpleasant surprises in the greenhouse”. Major abrupt past climate changes are linked to AMOC instabilities, including Dansgaard-Oeschger-Events and Heinrich Events. For more on this see my Review Paper in Nature.
3. The AMOC has weakened over the past hundred years. We don’t have direct measurements over such a long time (only since 2004 from the RAPID project), but various indirect indications. We have used the time evolution of the ‘cold blob’ shown above, using SST observations since 1870, to reconstruct the AMOC in Caesar et al. 2018. In that article we also discuss a ‘fingerprint’ of an AMOC slowdown which also includes excessive warming along the North American coast, also seen in Figure 1. That this fingerprint is correlated with the AMOC in historic runs with CMIP6 models has recently been shown by Latif et al. 2022, see Figure 2.
Others have used changes in the Florida Current since 1909, or changes in South Atlantic salinity, to reconstruct past AMOC changes – for details check out my last AMOC article here at RealClimate.
4. The AMOC is now weaker than any time in the past millennium. Several groups of paleoclimatologists have used a variety of methods to reconstruct the AMOC over longer time spans. We compiled the AMOC reconstructions we could find in Caesar et al. 2021, see Figure 3. In case you’re wondering how the proxy data reconstructions compare with other methods for the recent variability since 1950, that is shown in Caesar et al. 2022 (my take: quite well).
5. The long-term weakening trend is anthropogenic. For one, it is basically what climate models predict as a response to global warming, though I’d argue they underestimate it (see point 8 below). A recent study by Qasmi 2023 has combined observations and models to isolate the role of different drivers and concludes for the ‘cold blob’ region: “Consistent with the observations, an anthropogenic cooling is diagnosed by the method over the last decades (1951–2021) compared to the preindustrial period.”
In addition there appear to be decadal oscillations particularly after the mid-20th Century. They may be natural variability, or an oscillatory response to modern warming, given there is a delayed negative feedback in the system (weak AMOC makes the ‘cold blob’ region cool down, that increases the water density there, which strengthens the AMOC). Increasing oscillation amplitude may also be an early warning sign of the AMOC losing stability, see point 10 below.
The very short term SST variability (seasonal, interannual) in the cold blob region is likely just dominated by the weather, i.e. surface heating and cooling, and not indicative of changes in ocean currents.
6. The AMOC has a tipping point, but it is highly uncertain where it is. This tipping point was first described by Stommel 1961 in a highly simple model which captures a fundamental feedback. The region in the northern Atlantic where the AMOC waters sink down is rather salty, because the AMOC brings salty water from the subtropics to this region. If it becomes less salty by an inflow of freshwater (rain or meltwater from melting ice), the water becomes less dense (less “heavy”), sinks down less, the AMOC slows down. Thus it brings less salt to the region, which slows the AMOC further. It is called the salt advection feedback. Beyond a critical threshold this becomes a self-amplifying “vicious circle” and the AMOC grinds to a halt. That threshold is the AMOC tipping point. Stommel wrote: “The system is inherently frought with possibilities for speculation about climatic change.”
That this tipping point exists has been confirmed in numerous models since Stommel’s 1961 paper, including sophisticated 3-dimensional ocean circulation models as well as fully fledged coupled climate models. We published an early model comparison about this in 2005. The big uncertainty, however, is in how far the present climate is from this tipping point. Models greatly differ in this regard, the location appears to be sensitively dependent on the finer details of the density distribution of the Atlantic waters. I have compared the situation to sailing with a ship into uncharted waters, where you know there are dangerous rocks hidden below the surface that could seriously damage your ship, but you don’t know where they are.
7. Standard climate models have suggested the risk is relatively small during this century. Take the IPCC reports: For example, the Special Report on the Ocean and Cryosphere concluded:
The AMOC is projected to weaken in the 21st century under all RCPs (very likely), although a collapse is very unlikely (medium confidence). Based on CMIP5 projections, by 2300, an AMOC collapse is about
as likely as not for high emissions scenarios and very unlikely for lower ones (medium confidence).
It has long been my opinion that “very unlikely”, meaning less than 10% in the calibrated IPCC uncertainty jargon, is not at all reassuring for a risk we really should rule out with 99.9 % probability, given the devastating consequences should a collapse occur.
8. But: Standard climate models probably underestimate the risk. There are two reasons for that. They largely ignore Greenland ice loss and the resulting freshwater input to the northern Atlantic which contributes to weakening the AMOC. And their AMOC is likely too stable. There is a diagnostic for AMOC stability, namely the overturning freshwater transport, which I introduced in a paper in 1996 based on Stommel’s 1961 model. Basically, if the AMOC exports freshwater out of the Atlantic, then an AMOC weakening would lead to a fresher (less salty) Atlantic, which would weaken the AMOC further. Data suggest that the real AMOC exports freshwater, in most models it imports freshwater. This is still the case and was also discussed at the IUGG conference.
Here a quote from Liu et al. 2014, which nicely sums up the problem and gives some references:
Using oceanic freshwater transport associated with the overturning circulation as an indicator of the AMOC bistability (Rahmstorf 1996), analyses of present-day observations also indicate a bistable AMOC (Weijer et al. 1999; Huisman et al. 2010; Hawkins et al. 2011a,b; Bryden et al. 2011; Garzoli et al. 2012). These observational studies suggest a potentially bistable AMOC in the real world. In contrast, sensitivity experiments in CGCMs tend to show a monostable AMOC (Stouffer et al. 2006), indicating a model bias toward a monostable AMOC. This monostable bias of the AMOC in CGCMs, as first pointed out by Weber et al. (2007) and later confirmed by Drijfhout et al. (2011), could be related to a bias in the northward freshwater transport in the South Atlantic by the meridional overturning circulation.
9. Standard climate models get the observed ‘cold blob’, but only later. Here is some graphs from the current IPCC report, AR6.
10. There are possible Early Warning Signals (EWS). New methods from nonlinear dynamics search for those warning signals when approaching tipping points in observational data, from cosmology to quantum systems. They use the critical slowing down, increasing variance or increasing autocorrelation in the variability of the system. There is the paper by my PIK colleague Niklas Boers (2021), which used 8 different data series (Figure 6) and concluded there is “strong evidence that the AMOC is indeed approaching a critical, bifurcation-induced transition.”
Another study, this time using 312 paleoclimatic proxy data series going back a millennium, is Michel et al. 2022. They argue to have found a “robust estimate, as it is based on sufficiently long observations, that the Atlantic Multidecadal Variability may now be approaching a tipping point after which the Atlantic current system might undergo a critical transition.”
And today (update!) a third comparable study by Danish colleagues has been published, Ditlevsen & Ditlevsen 2023, which expects the tipping point already around 2050, with a 95% uncertainty range for the years 2025-2095. Individual studies always have weaknesses and limitations, but when several studies with different data and methods point to a tipping point that is already quite close, I think this risk should be taken very seriously.
Timing of the critical AMOC transition is still highly uncertain, but increasingly the evidence points to the risk being far greater than 10 % during this century – even rather worrying for the next few decades. The conservative IPCC estimate, based on climate models which are too stable and don’t get the full freshwater forcing, is in my view outdated now. I side with the recent Climate Tipping Points report by the OECD, which advised:
Yet, the current scientific evidence unequivocally supports unprecedented, urgent and ambitious climate action to tackle the risks of climate system tipping points.
If you like to know more about this topic, you can either watch my short talk from the Exeter Tipping Points conference last autumn (where also Peter Ditlevsen first presented the study which was just published), or the longer video of my EPA Climate Lecture in Dublin Mansion House last April.
You can tell how worried the climate deniers are by how many fields of science they have to trash to try and have people not see what’s happening.
it will not have escaped most people’s notice that global temperatures are heading into uncharted territory. The proximate cause of this week’s headlines is the Climate Reanalyzer website at the U. Maine which provides a nice front end to the NOAA NCEP CFS forecast system and reanalysis and shows absolute daily temperatures in early July clearly exceeding the highest pre-existing temperatures from August 2016. It’s an arresting graphic, and follows in from the record high ocean surface temperatures that were being reported a month ago.
This is however a relatively new resource and was not online the last time that we set absolute temperature records (in summer 2016). So this has both salience and novelty – a potent combination!
The ultimate cause of these patterns is of course the ongoing global warming, driven almost entirely by human activities.
What are we looking at?
As we’ve explained before, all global temperature products are based on some kind of model – statistical, physical etc. There is no direct measurement of the global temperature – not from satellites, stations, or from the one random person who happens to be in most average place on Earth (where might that even be?). But that doesn’t mean the products aren’t useful!
In this particular instance we are looking at the output of a weather forecast model (NCEP CFS) that ingests multiple sources of in situ and satellite data every 3 hours which is then averaged over a day and over the surface of the planet. These calculations are precise reflections of what is in the model, but for multiple reasons this might not be a perfect reflection of what the real world is doing.
We looked at the coherence of different products, including the reanalyses, before and found that while they are highly correlated in terms of annual anomalies, they differ in their absolute magnitude (graphic from 2017).
Differences will depend on resolution – higher resolution models have better (and higher topography) and then will have slightly cooler temperatures (all else being equal – which it isn’t!), tuning, model structure etc. and can’t really be discriminated using the pure (sparse) observations.
Coherence at the monthly scale is also quite good (though a little noisier), and I haven’t (yet) seen a good comparison of the coherence of the different products at the daily scale (note that the standard products (like GISTEMP, HadCRUT5 and NOAAv5) don’t produce a daily product). One might anticipate that there is a similarity, but perhaps not a one-to-one correspondence on exactly which days were the warmest.
What are we seeing?
For the global temperature, it’s well established that the maximum is during the Northern Hemisphere summer. This sometimes comes as a surprise to people (why doesn’t the opposing seasonality in the Southern Hemisphere cancel this out?), but it relates to the fact that there is a lot more land in the Northern Hemisphere. Since the seasonal cycle over land is much larger than over the ocean (smaller heat capacity, and less evaporation), that means that the seasonal variations in the north outweigh the variations in the south.
Thus the months of July and August are generally the warmest in the year, and consequently we expect the warmest days during those months – and this is reflected in the CFS output (and in the ERA5 output also). The monthly variations are also reflected in the GISTEMP product which allows you to see the shifts from 1880 onward (about a 1ºC warming in each month since the late 19th C):
The station-based products are a little delayed with respect to the reanalyses, but they generally reflect the same patterns – thus one should expect the June temperatures in NOAA, GISTEMP and HadCRUT5 to be the warmest June on record. Given too, that these temperatures are being driven by persistent warming in the oceans, increasingly juiced by the growing El Niño event in the tropical Pacific, records in July and August are also likely. This is of course increasing the odds for 2023 to be a record year (I would estimate about 50% at this point).
But the WSJ Opinion page says that there’s no such thing as the global temperature!
Well, they would say that wouldn’t they. [Narrator: there is, in fact, a perfectly well defined global mean of any two-dimensional field defined on the sphere, including temperature].
More generously, one might think that their argument (such as it is), is that the global mean isn’t directly relevant for anyone. That is, no-one lives in the global mean, all impacts are local and driven by weather variations. But we’ve known for decades that the global mean change is a really good predictor (not perfect, but pretty good) of local impacts on heat waves, intense rainfall, drought intensity etc.
But let’s be honest, it’s basically pure distraction and attempts to complicate something that is pretty basic:
The climate is warming, records are being broken, and we are increasingly seeing the impacts.
I know why the WSJ doesn’t want you to realise this, but it’s not hard to see past their obfuscation.
The world is full of climate dashboards (and dashboards of dashboards), and so you might imagine that all datasets and comparisons are instantly available in whatever graphical form you like. Unfortunately, we often want graphics to emphasize a particular point or comparison, and generic graphs from the producers of the data often don’t have the same goal in mind. Dashboards that allow for more flexibility (like WoodForTrees) are useful, but aren’t as visually appealing as they could be. Thus, I find myself creating bespoke graphics of climate and climate model data all the time.
Some of these are maintained on the Climate model-observations comparison page but many of the graphs that I make (often to make a point on twitter) aren’t saved there and often their provenance is a bit obscure. Given that twitter will not last forever (though it might be around for slightly longer than a head of lettuce), it’s probably useful to have a spot to upload these graphics to, along with some explanation, to serve as a reference.
I have therefore created a couple of ‘pages’ (in wordpress speak) with fixed URLs where I will be curating relevant graphics I make (and findable at the bottom of the page under “DATA AND GRAPHICS”). The first is focused on the surface temperature records. I often update relevant graphics associated with this in early January (when we get another dot on the graphs), but there are associated graphs that I’ve made that don’t make it into those updates, so this is a place for them too. This includes the impacts of ENSO, comparisons across different platforms, or the impact of homogenization.
The second page is bit more eclectic. These are graphs that are relevant to some trope or talking point that often pops up, and my graphs are an attempt to provide context (usually), or to debunk it entirely. This is where you’ll find maps of where the climate is warming faster than the global average, time-series of river ice break-up dates, and an example of sensible scaling of CO2 changes and temperature.
To start with, I’m just going to upload some graphs I’ve made recently (with any updates that are needed), and I’ll add content as I make something new. If there are any other ideas (that aren’t too involved!), I’ll be happy to look at adding those too. Let me know if this is useful.
The detection and the attribution of climate change are based on fundamentally different frameworks and shouldn’t be conflated.
We read about and use the phrase ‘detection and attribution’ of climate change so often that it seems like it’s just one word ‘detectionandattribution’ and that might lead some to think that it is just one concept. But it’s not.[Read more…] about Watching the detections
With the signing of the Inflation Reduction Act (IRA) on Tuesday Aug 16, the most significant climate legislation in US federal history (so far) became law.
Despite the odd name (and greatly overused TLA), the IRA contains a huge number of elements, totalling roughly $350 billion of investment, in climate solutions over the next ten years. This is an historic effort though it falls short of the broader ‘Green New Deal‘ goals that were proposed in 2019, and doesn’t include all of the elements that were in the proposed 2021 reconcilliation package (the American Jobs Plan in “Build Back Better“) that ultimately floundered.[Read more…] about Climate impacts of the #IRA
One of our most-read old posts is the step-by-step explanation for why increasing CO2 is a significant problem (The CO2 problem in 6 easy steps). However, that was written in 2007 – 15 years ago! While the basic steps and concepts have not changed, there’s 15 years of more data, updates in some of the details and concepts, and (it turns out) better graphics to accompany the text. And so, here is a mildly updated and referenced version that should be a little more useful.[Read more…] about The CO2 problem in six easy steps (2022 Update)
Some of the authors of a recent commentary on k-scale modeling respond to RealClimate.[Read more…] about Overselling k-scale? Hmm
As in previous years, the spring break-up of river ice on the Tanana River at Nenana and the Yukon River at Dawson City in Canada (new! h/t Ed Wiebe), is a great opportunity to highlight phenology that indicates that the planet is in fact reacting to the ongoing global warming. As we’ve done in previous years, the Nenana dates can be plotted and show a clear trend towards earlier break-ups (by about 8 days/century over the whole record, or 13 days/century since 1975).
2022 was on trend, and in 2014, I noted that May 3rd was the most likely date given the trends until then.
Dawson City in the Yukon is about 250 miles east of Nenana which is close enough for the seasonal anomalies in climate to be quite highly correlated. So one might expect that the break-up dates would be similarly correlated… and indeed they are:
The ice at Dawson breaks up on average 3.8 days later than the ice at Nenana (5.1 days this year), but the correlation between the two series is an impressive 0.82. There have been 15 times the ice went out within 24 hours of each other and in 1963 they broke up less than 3 minutes apart! The trends are likewise very similar 7.7±3.8 days/century for Nenana, compared to 6.5±3.1 days/century since 1917. This pretty much puts paid to the occasional claim of the urban heat island in Fairbanks affecting the water and causing the trend.
[Update: I misunderstood the Yukon river break up website, and erroneously stated that the break-up was on May 2nd. It was not. I’ll update this again when it has. Apologies.]
[Update II: The Yukon river ice broke up on May 7, and I’ve updated the graph and text.]
A couple of weeks ago the EU announced that they were funding a project called DestinE (Destination Earth) to build ‘digital twins’ of the Earth System to support policy making and rapid reaction to weather and climate events.
While the term ‘digitial twin’ has a long history in the engineering world, it’s only recently been applied to Earth System Modeling, and is intended (I surmise, as does Bryan Lawrence) to denote something more than the modeling of either weather or climate that we’ve been doing for years. But what exactly? And is it an achievable goal or just a rebranding effort of things that are happening anyway?[Read more…] about Digital Twinge