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about Gavin Schmidt

Gavin Schmidt is a climate modeler, working for NASA and with Columbia University.

Tributes to Geert Jan van Oldenborgh

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As many of you will know, Geert Jan van Oldenborgh died on Oct 12, 2021, and in the last week a number of very touching tributes have appeared. Notably, a lovely obituary in the NY Times by Henry Fountain, a segment on the BBC’s Inside Science from Roland Pease, a piece on Bloomberg News by Eric Roston and, of course, an appreciation from his colleagues at World Weather Attribution (including Friederike Otto, the co-recipient of the TIME 100 award to Geert earlier this year).

Geert’s work had been featured often at RealClimate (notably the rapid attribution work for the Pacific North West heat wave earlier this year), and we have made frequent reference to Climate Explorer, the tool he built to provide easier access to many sources of climate data. He also provided us with annual updates for the comparison between a 1981 climate projection to subsequent observations.

Comparison of Hansen et al (1981) projections to GISTEMP observations (to 2019) (credit Geert Jan van Oldenborgh).

He let us know earlier this year that this was likely the last update. Moge hij rusten in vrede.

A Nobel pursuit

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Klaus Hasselmann and Suki Manabe

Last week, the Nobel physics prize was (half) awarded to Suki Manabe and Klaus Hasselmann for their work on climate prediction and the detection and attribution of climate change. This came as quite a surprise to the climate community – though it was welcomed warmly. We’ve discussed the early climate model predictions a lot (including some from Manabe and his colleagues), and we’ve discussed detection and attribution of climate change as well, though with less explicit discussion of Hasselmann’s contribution. Needless to say these are big topics which have had many inputs from many scientists over the years.

But RC has a more attuned audience to these topics than most, and so it might be fun to dive into the details of their early work to see what has stood the test of time and what has not, and how that differs (if it does) from their colleagues and rivals at the time.

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The definitive CO2/CH4 comparison post

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There is a new push to reduce CH4 emissions as a possible quick ‘win-win’ for climate and air quality. To be clear this is an eminently sensible idea – as it has been for decades (remember the ‘Methane-to-markets’ initiative from the early 2000s?), but it inevitably brings forth a mish-mash of half-remembered, inappropriate or out-of-date comparisons between the impacts of carbon dioxide and methane. So this is an attempt to put all of that in context and provide a hopefully comprehensive guide to how, when, and why to properly compare the two greenhouse gases.

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AR6 of the best

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Half a dozen takeaways from a first read of the new IPCC AR6 report.

As climate scientists we tend to look at the IPCC reports a little differently than the general public might. Here are a few things that mark this report out from previous versions that relate to issues we’ve discussed here before:

  1. Extreme events are increasingly connected to climate (duh!)
  2. Sea level rise is a big deal
  3. Use, abuse and misuse of the CMIP6 ensemble
  4. The radiative forcing bar chart has gone full circle
  5. Droughts and floods are complicated
  6. Don’t mention the hiatus

There are other things that will get the headlines (the expected time before we get to 1.5ºC or 2ºC, the headline SLR numbers, the ‘unprecedented rate’ statement, constraints on climate sensitivity, carbon cycle feedbacks, the implications for the carbon budgets etc.), and other things worth noting – for instance, the much better and more direct graphics that they have clearly worked on a lot. As usual, most of the headlines will also focus on the Summary For Policy Makers (SPM) which was approved word by word by the governments over the last two weeks (full disclosure, I was advising the US delegation), but the full report will be worth dipping into over the next few months (there is a lot there to digest!).

1. Extremes: Back in 2012, the literature assessed by AR5 connecting changes in extremes to climate change was scant. As we wrote at the time, attribution of single events was difficult and experimental. But as was exemplified by the recent reaction to the PNW heatwave, things have moved on considerably. This has allowed the IPCC authors to produce regional assessments of past changes in heat extremes, intense precipitation and agricultural/ecological drought in drying regions (see below for a discussion on what that means), and produce assessed projections of a whole suite of what they call Climate-impact Drivers (CIDs) – which includes floods, marine heatwaves etc. People who (even a couple of weeks ago) were quoting the AR5 statements on extremes as if that was current are going to have to update their talking points (that is, of course, if they care about correctly reflecting the most up-to-date science…).

Figure SPM3.

For example, IPCC finds that Northern Europe, Western Central Europe and Eastern Europe all show an observed increase in heavy precipitation events, such as the one causing the recent massive flooding in Germany and Belgium. Western Central Europe is one of the few regions where both an increase in extreme precipitation and in drought have already been documented. The IPCC notes that it’s the most rare and severe extremes which are expected to show the biggest percentage increase in frequency (see this past RealClimate post).

2. Sea Level Rise: The previous IPCC reports, notably AR4 and AR5 (to a lesser extent), have had a hard time dealing with SLR. This has been due to multiple issues, including a historical lack of comprehensive literature to assess, very uncertain observations of ice sheets, and difficultlies in blending different lines of evidence. In this report they’ve tried much harder to put the data together more coherently, there is more evidence, and they haven’t shied away from being explicit about the low-likelihood/high-impact possibilities (mostly associated with a collapse of WAIS). Literally, the sea level projection runs off the page… (Stefan will have a more detailed assessment later).

Figure SPM 8. Projections of (a) temperature (constrained), (b) Arctic sea ice area (raw CMIP6), (c) ocean pH (constrained), and sea level (d)to 2100, and (e) to 2300 (constrained).

3. Use, Abuse and Misuse of the CMIP6 ensemble: I’ll discuss this in more detail in another post, but I want to commend the IPCC authors for dealing with the increased spread in the CMIP6 ensemble climate sensitivity in two very sensible ways. Firstly, the use constrained projections for all the temperature (and sea level) time series out to 2100 allows them to downweight (effectively to zero) the high (and low) ECS models that are outside of the assessed range (note this would not have made much (if any) difference in CMIP5). Secondly, they choose to focus on the patterns of change, not for certain time-periods, but for specific “Global Warming Levels” (GWLs). That is to say, what the expected pattern of rainfall (for instance) might be when the global mean temperature reaches 1.5ºC, or 2ºC or 4ºC etc. This allows them to include all the models (including good models with improved climatologies that happen to have high ECS like the NCAR CESM2 or the HadGEM3 models). Additionally, the GWL impacts plots neatly divorce the limited scenarios that were used in CMIP6 from the ability to assess impacts. Thus if policy-makers or others want to explore the impacts of other scenarios that might reach specific warming levels earlier or later than any one of the SSPs, they can do so easily, without having to rerun the models.

AR6 Figure SPM 5 showing the patterns of temperature, rainfall and soil moisture for specified global warming levels.

4. The radiative forcing bar chart has gone full circle: Almost every IPCC report has a version of the radiative bar chart showing the contributions over the historical period of all the different forcings (greenhouse gases, aerosols, solar, etc.). Every iteration has changed in trivial and sometimes substantive ways (I wrote a history of this a few years back), for instance, it’s oscillated from a vertical or horizontal presentation for no apparent reason, and the individual components have followed the scientific views of what was important. In this SPM it appears in Fig. SPM 2c and has gone back to being vertical. They have stuck with the contributions by emission (as opposed to concentration – something we pushed for last time), but the novelty here is that they are plotting the estimated temperature impact from each of the contributions (using the radiative forcing, the assessed climate sensitivity and an simple impulse-response model). Oddly enough this is most reminiscent of the very first bar chart that appeared in Hansen et al. (1981) which can be seen here.

Fig SPM2b. The radiative forcing bar chart now converted to temperature.

5. Droughts and floods are complicated: The picture on droughts and floods is more complicated than most people think. First, there is a great deal of regional variation, second the historical metrics we use to assess drought (such as the Palmer Drought Severity Index) don’t perform very well in a changing climate, and third the attribution of meteorological or agricultural or ecological drought varies as well. Analyses that average over too wide an area, or that look at the wrong metrics, will come to erroneous conclusions. The IPCC authors went to a lot of trouble to disentangle this and the assessment in Fig. SPM3 of evidence for observed drought changes focuses specifically on agricultural and ecological drought (based on soil moisture), as opposed to hydrological drought (runoff) or meteorological drought (based on rainfall). This is because we don’t see strong attribution in total rainfall amounts, but we do in evaporative demand (which depends on temperature). Thus when we have a longterm precipitation anomaly (such as in the American South West (WNA in the hexagon plot above)), we can’t (yet) attribute the rainfall change, but we can attribute the soil moisture change. Floods are also complicated because they too don’t solely depend on a single factor (such as intense precipitation) – but instead are a function of prior state of soil moisture, water management practices and other hyper-local effects. Work here will continue to advance, but the picture is clear only in a few regions so far.

6. Don’t mention the hiatus: Readers will probably remember the prominence of the ‘hiatus’ in the discussions around the AR5 report (written in 2013) (see here, here, or here). Due in part to (IMO) an over-reliance on a single temperature record (HadCRUT4), and (it turns out) non-climatic biases in the ocean temperature records, the trends from 1998-2012 got a specific call out in the AR5 SPM:

In addition to robust multi-decadal warming, global mean surface temperature exhibits substantial decadal and interannual variability (see Figure SPM.1). Due to natural variability, trends based on short records are very sensitive to the beginning and end dates and do not in general reflect long-term climate trends. As one example, the rate of warming over the past 15 years (1998–2012; 0.05 [–0.05 to 0.15] °C per decade), which begins with a strong El Niño, is smaller than the rate calculated since 1951 (1951–2012; 0.12 [0.08 to 0.14] °C per decade)5. {2.4}

Section B.1, SPM AR5

The observed reduction in surface warming trend over the period 1998 to 2012 as compared to the period 1951 to 2012, is due in roughly equal measure to a reduced trend in radiative forcing and a cooling contribution from natural internal variability, which includes a possible redistribution of heat within the ocean (medium confidence). The reduced trend in radiative forcing is primarily due to volcanic eruptions and the timing of the downward phase of the 11-year solar cycle. However, there is low confidence in quantifying the role of changes in radiative forcing in causing the reduced warming trend. There is medium confidence that natural internal decadal variability causes to a substantial degree the difference between observations and the simulations; the latter are not expected to reproduce the timing of natural internal variability. There may also be a contribution from forcing inadequacies and, in some models, an overestimate of the response to increasing greenhouse gas and other anthropogenic forcing (dominated by the effects of aerosols). {9.4, Box 9.2, 10.3, Box 10.2, 11.3}

Section D.1, SPM, AR5

Now however, the updates to the historical warming, the use of four datasets instead of one, and of course, the series of record breaking years subsequently (2014, 2015, 2016/2020), the issue of variability in decadal trends is no longer so salient. The shifts in the quoted trends (1998-2012 is now 0.12ºC/decade, 1951-2012 is 0.13ºC, HadCRUT5) underlines the trivialness of the issue. To be fair, there is one mention of the hiatus in the AR6 Technical Summary:

The observed slower global surface temperature increase (relative to preceding and following periods) in the 1998–2012 period, sometimes referred to as ‘the hiatus’, was temporary (very high confidence). The increase in global surface temperature during the 1998–2012 period is also greater in the data sets used in the AR6 assessment than in those available at the time of AR5. Using these updated observational data sets and a like- for-like consistent comparison of simulated and observed global surface temperature, all observed estimates of the 1998–2012 trend lie within the very likely range of CMIP6 trends. Since 2012, global surface temperature has warmed strongly, with the past five years (2016–2020) being the hottest five-year period between 1850 and 2020 (high confidence). {2.3.1, 3.3.1, 3.5.1, Cross-Chapter Box 3.1}

AR6 Cross-Section Box TS.1

Let this episode stand as a clear reminder for assessment reports not to get ahead of the science…

And so to bed…

Finally, let me finish up with a couple of personal observations. This was the first IPCC report where I was involved in the SPM approval process, and while that was frustrating at times, the vast majority of delegates were obviously focussed on getting the best summary consistent with the science that they could. Obviously, some countries had specific sensitivities, but seeing the negotiations on how those issues could be finessed while sticking to language that the authors approved of was impressive. In particular, the chairing of the meeting by Valerie Masson-Delmotte was a masterclass in effective meeting strategies. The virtual nature of the proceedings means that this was undoubtedly the SPM approval session with the lowest carbon footprint which might serve as a model for future efforts. However, the ‘all time zone’ nature of the proceedings and the very interrupted nature of my resulting sleep patterns has left a mark on pretty much everyone involved. Forgive me if I sleep in for the rest of this week…

References

  1. J. Hansen, D. Johnson, A. Lacis, S. Lebedeff, P. Lee, D. Rind, and G. Russell, "Climate Impact of Increasing Atmospheric Carbon Dioxide", Science, vol. 213, pp. 957-966, 1981. http://dx.doi.org/10.1126/science.213.4511.957

Why is future sea level rise still so uncertain?

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Three new papers in the last couple of weeks have each made separate claims about whether sea level rise from the loss of ice in West Antarctica is more or less than you might have thought last month and with more or less certainty. Each of these papers make good points, but anyone looking for coherent picture to emerge from all this work will be disappointed. To understand why, you need to know why sea level rise is such a hard problem in the first place, and appreciate how far we’ve come, but also how far we need to go.

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Nenana Ice Classic 2021

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And…. it’s that time again. The clock stopped on the Nenana ice classic this afternoon (April 30, 12:50pm AT). This is pretty much on trend and unsurprising given the relatively slightly cool winter in Alaska. The jackpot on offer this year was $233,591 but will likely be shared among several winners. This year’s ‘break up’ is a little odd, since the ice moved sufficiently to trigger the clock, but not enough to actually topple the tripod (which is still visible as this is being written (9pm ET) – Update 10:30pm ET: gone now though!). But, the rules are the rules…

Nenana Ice Classic break-up dates since 1917.

The trends in the break up date is about 8 days earlier per century (±4), estimated over the whole record, but substantially faster over the last 50 years (16 ± 12 days/century, 95% CI).

Other phenological records show similar trends, notably the longest cherry blossom record from Kyoto which dates back to 9th Century, and which had a record earliest peak bloom this year and a clear trend over the last few decades:

Kyoto Cherry Blossom trends (graph from Statista)

Feel free to link to your favorite such record in the comments…

Laschamps-ing at the bit

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A placeholder to provide some space to discuss the paper last week (Cooper et al, 2021) on the putative climate consequences of the Laschamps Geomagnetic Excursion, some 42,000 yrs ago.

There was some rather breathless reporting on this paper, but there were also a lot of sceptical voices – not of the main new result (a beautiful new 14C dataset from a remarkable kauri tree log found in New Zealand), but of the more speculative implications – both climatically and anthropologically.

On twitter there were some good threads covering multiple aspects of the paper (and the lead author):

https://twitter.com/tinyicybubbles/status/1362743531438227457?s=20

But let me make a couple of different points. We have occasionally discussed the Laschamps event here as a counter-example to the notion that changes in galactic cosmic rays have a major impact on climate. A reversal or near-reversal of the geomagnetic field would be expected to greatly increase the GCR getting to the lower atmosphere – in far greater amounts than over a solar cycle, or grand solar minimum (like the Maunder Minimum). So if people want to postulate a big role for GCR there, they needed to explain why there wasn’t a much bigger signal at 42kya too. These authors are thus not the only people to have looked for significant climate impacts at this time. They are perhaps the first to claim to have found them…

To be clear, the modeling that was done in this paper was good (if extreme) and suggested that the geomagnetic event combined with a severe grand solar minimum (much bigger than the Maunder minimum) would cause significant depletion of the ozone layer and some shifts in the annular modes. But the ozone depletion is less than we’ve seen due to anthropogenic ozone depletion since the 1980s, and the surface climate changes don’t seem very significant at all – especially compared to the massive variability exhibited in the ice cores throughout the last ice age (particularly in Marine Isotope Stage 3 – the Dansgaard-Oeschgar events). At best these are nuanced and subtle climate effects, and certainly not anything apocalyptic (despite Stephen Fry’s dulcet tones).

Finally, it should be called the Laschamps event (with a final, and etymologically correct, ‘s’) after the village in the Auvergne where it was first identified. There is unfortunately 50 years of legacy references to the “Laschamp” excursion, but hopefully it isn’t too late to fix!

References

  1. A. Cooper, C.S.M. Turney, J. Palmer, A. Hogg, M. McGlone, J. Wilmshurst, A.M. Lorrey, T.J. Heaton, J.M. Russell, K. McCracken, J.G. Anet, E. Rozanov, M. Friedel, I. Suter, T. Peter, R. Muscheler, F. Adolphi, A. Dosseto, J.T. Faith, P. Fenwick, C.J. Fogwill, K. Hughen, M. Lipson, J. Liu, N. Nowaczyk, E. Rainsley, C. Bronk Ramsey, P. Sebastianelli, Y. Souilmi, J. Stevenson, Z. Thomas, R. Tobler, and R. Zech, "A global environmental crisis 42,000 years ago", Science, vol. 371, pp. 811-818, 2021. http://dx.doi.org/10.1126/science.abb8677

Don’t climate bet against the house

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Decades ago (it seems) when perhaps it was still possible to have good faith disagreements about the attribution of current climate trends, James Annan wrote a post here summarizing the thinking and practice of Climate Betting. That led to spate of wagers on continued global warming (a summary of his bets through 2005 and attempts to set up others is here).

There were earlier bets, the most well known perhaps was the one for $100 between Hugh Ellsaesser and Jim Hansen in 1989 on whether there would be a new temperature record within three years. There was (1990), and Ellsaesser paid up in January 1991 (Kerr, 1991). But these more recent bets were more extensive.

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References

  1. R.A. Kerr, "Global Temperature Hits Record Again", Science, vol. 251, pp. 274-274, 1991. http://dx.doi.org/10.1126/science.251.4991.274

Update day 2021

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As is now traditional, every year around this time we update the model-observation comparison page with an additional annual observational point, and upgrade any observational products to their latest versions.

A couple of notable issues this year. HadCRUT has now been updated to version 5 which includes polar infilling, making the Cowtan and Way dataset (which was designed to address that issue in HadCRUT4) a little superfluous. Going forward it is unlikely to be maintained so, in a couple of figures, I have replaced it with the new HadCRUT5. The GISTEMP version is now v4.

For the comparison with the Hansen et al. (1988), we only had the projected output up to 2019 (taken from fig 3a in the original paper). However, it turns out that fuller results were archived at NCAR, and now they have been added to our data file (and yes, I realise this is ironic). This extends Scenario B to 2030 and Scenario A to 2060.

Nothing substantive has changed with respect to the satellite data products, so the only change is the addition of 2020 in the figures and trends.

So what do we see? The early Hansen models have done very well considering the uncertainty in total forcings (as we’ve discussed (Hausfather et al., 2019)). The CMIP3 models estimates of SAT forecast from ~2000 continue to be astoundingly on point. This must be due (in part) to luck since the spread in forcings and sensitivity in the GCMs is somewhat ad hoc (given that the CMIP simulations are ensembles of opportunity), but is nonetheless impressive.

CMIP3 (circa 2004) model hindcast and forecast estimates of SAT.

The forcings spread in CMIP5 was more constrained, but had some small systematic biases as we’ve discussed Schmidt et al., 2014. The systematic issue associated with the forcings and more general issue of the target diagnostic (whether we use SAT or a blended SST/SAT product from the models), give rise to small effects (roughly 0.1ºC and 0.05ºC respectively) but are independent and additive.

The discrepancies between the CMIP5 ensemble and the lower atmospheric MSU/AMSU products are still noticeable, but remember that we still do not have a ‘forcings-adjusted’ estimate of the CMIP5 simulations for TMT, though work with the CMIP6 models and forcings to address this is ongoing. Nonetheless, the observed TMT trends are very much on the low side of what the models projected, even while stratospheric and surface trends are much closer to the ensemble mean. There is still more to be done here. Stay tuned!

The results from CMIP6 (which are still being rolled out) are too recent to be usefully added to this assessment of forecasts right now, though some compilations have now appeared:

CMIP6 model SAT (observed forcings to 2014, SSP2-45 scenario subsequently) (Zeke Hausfather)

The issues in CMIP6 related to the excessive spread in climate sensitivity will need to be looked at in more detail moving forward. In my opinion ‘official’ projections will need to weight the models to screen out those ECS values outside of the constrained range. We’ll see if other’s agree when the IPCC report is released later this year.

Please let us know in the comments if you have suggestions for improvements to these figures/analyses, or suggestions for additions.

References

  1. Z. Hausfather, H.F. Drake, T. Abbott, and G.A. Schmidt, "Evaluating the Performance of Past Climate Model Projections", Geophysical Research Letters, vol. 47, 2020. http://dx.doi.org/10.1029/2019GL085378
  2. G.A. Schmidt, D.T. Shindell, and K. Tsigaridis, "Reconciling warming trends", Nature Geoscience, vol. 7, pp. 158-160, 2014. http://dx.doi.org/10.1038/ngeo2105