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Unforced Variations: Feb 2020

Filed under: — group @ 5 February 2020

This month’s open thread. Focus on climate science. Be kind.

BAU wow wow

How should we discuss scenarios of future emissions? What is the range of scenarios we should explore? These are constant issues in climate modeling and policy discussions, and need to be reassessed every few years as knowledge improves.

I discussed some of this in a post on worst case scenarios a few months ago, but the issue has gained more prominence with a commentary by Zeke Hausfather and Glen Peters in Nature this week (which itself partially derives from ongoing twitter arguments which I won’t link to because there are only so many rabbit holes that you want to fall into).

My brief response to this is here though:

Mike Mann has a short discussion on this as well. But there are many different perspectives around – ranging from the merely posturing to the credible and constructive. The bigger questions are certainly worth discussing, but if the upshot of the current focus is that we just stop using the term ‘business-as-usual’ (as was suggested in the last IPCC report), then that is fine with me, but just not very substantive.


  1. Z. Hausfather, and G.P. Peters, "Emissions – the ‘business as usual’ story is misleading", Nature, vol. 577, pp. 618-620, 2020.

Update day 2020!

Following more than a decade of tradition (at least), I’ve now updated the model-observation comparison page to include observed data through to the end of 2019.

As we discussed a couple of weeks ago, 2019 was the second warmest year in the surface datasets (with the exception of HadCRUT4), and 1st, 2nd or 3rd in satellite datasets (depending on which one). Since this year was slightly above the linear trends up to 2018, it slightly increases the trends up to 2019. There is an increasing difference in trend among the surface datasets because of the polar region treatment. A slightly longer trend period additionally reduces the uncertainty in the linear trend in the climate models.

To summarize, the 1981 prediction from Hansen et al (1981) continues to underpredict the temperature trends due to an underestimate of the transient climate response. The projections in Hansen et al. (1988) bracket the actual changes, with the slight overestimate in scenario B due to the excessive anticipated growth rate of CFCs and CH4 which did not materialize. The CMIP3 simulations continue to be spot on (remarkably), with the trend in the multi-model ensemble mean effectively indistinguishable from the trends in the observations. Note that this doesn’t mean that CMIP3 ensemble means are perfect – far from it. For Arctic trends (incl. sea ice) they grossly underestimated the changes, and overestimated them in the tropics.

CMIP3 for the win!

The CMIP5 ensemble mean global surface temperature trends slightly overestimate the observed trend, mainly because of a short-term overestimate of solar and volcanic forcings that was built into the design of the simulations around 2009/2010 (see Schmidt et al (2014). This is also apparent in the MSU TMT trends, where the observed trends (which themselves have a large spread) are at the edge of the modeled histogram.

A number of people have remarked over time on the reduction of the spread in the model projections in CMIP5 compared to CMIP3 (by about 20%). This is due to a wider spread in forcings used in CMIP3 – models varied enormously on whether they included aerosol indirect effects, ozone depletion and what kind of land surface forcing they had. In CMIP5, most of these elements had been standardized. This reduced the spread, but at the cost of underestimating the uncertainty in the forcings. In CMIP6, there will be a more controlled exploration of the forcing uncertainty (but given the greater spread of the climate sensitivities, it might be a minor issue).

Over the years, the model-observations comparison page is regularly in the top ten of viewed pages on RealClimate, and so obviously fills a need. And so we’ll continue to keep it updated, and perhaps expand it over time. Please leave suggestions for changes in the comments below.


  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.
  2. J. Hansen, I. Fung, A. Lacis, D. Rind, S. Lebedeff, R. Ruedy, G. Russell, and P. Stone, "Global climate changes as forecast by Goddard Institute for Space Studies three-dimensional model", Journal of Geophysical Research, vol. 93, pp. 9341, 1988.
  3. G.A. Schmidt, D.T. Shindell, and K. Tsigaridis, "Reconciling warming trends", Nature Geoscience, vol. 7, pp. 158-160, 2014.

One more data point

Filed under: — gavin @ 15 January 2020

The climate summaries for 2019 are all now out. None of this will be a surprise to anyone who’s been paying attention, but the results are stark.

  • 2019 was the second warmest year (in analyses from GISTEMP, NOAA NCEI, ERA5, JRA55, Berkeley Earth and Cowtan & Way, RSS TLT), it was third warmest in the standard HadCRUT4 product and in the UAH TLT. It was the warmest year in the AIRS Ts product.
  • For ocean heat content, it was the warmest year, though in terms of just the sea surface temperature (HadSST3), it was the third warmest.
  • The top 5 years in all surface temperature series, are the last five years. [Update: this isn’t true for the MSU TLT data which have 2010 (RSS) and 1998 (UAH) still in the mix].
  • The decade was the first with temperatures more than 1ºC above the late 19th C in almost all products.

This year there are two new additions to the discussion, notably the ERA5 Reanalyses product (1979-2019) which is independent of the surface weather stations, and the AIRS Ts product (2003-2019) which again, is totally independent of the surface data. Remarkably, they line up almost exactly. [Update: the ERA5 system assimilates the SYNOP reports from weather stations, which is not independent of the source data for the surface temperature products. However, the interpolation is based on the model physics and many other sources of observed data.]

The two MSU lowermost troposphere products are distinct from the surface record (showing notably more warming in the 1998, 2010 El Niño years – though it wasn’t as clear in 2016), but with similar trends. The biggest outlier is (as usual) the UAH record, indicating that the structural uncertainty in the MSU TLT trends remains significant.

One of the most interesting comparisons this year has been the coherence of the AIRS results which come from an IR sensor on board EOS Aqua and which has been producing surface temperature estimates from 2003 onwards. The rate and patterns of warming of this and GISTEMP for the overlap period are remarkably close, and where they differ, suggest potential issues in the weather station network.

The trends over that period in the global mean are very close (0.24ºC/dec vs. 0.25ºC/dec), with AIRS showing slightly more warming in the Arctic. Interestingly, AIRS 2019 slightly beats 2016 in their ranking.

I will be updating the model/observation comparisons over the next few days.

Unforced variations: Jan 2020

Filed under: — group @ 1 January 2020

The new open thread on climate science for a new year, and a new decade – perhaps the Soaring Twenties? What precisely will be soaring is yet to be decided though.

Two things will almost certainly go up – CO2 emissions and temperatures:

But maybe also ambition, determination, and changes that will lead to reduced emissions in future? Fingers crossed.

AGU 2019

Filed under: — gavin @ 8 December 2019

Another year, another AGU. Back in San Francisco for the first time in 3 years, and with a massive assortment of talks, events and workshops. For those not able to go, there is an increasing, though not yet exhaustive, availability of streaming and online content.

Notably, the AGU GO service is streaming 15 sessions live on Wednesday, Thursday and Friday, with the ability to ask questions and interact with other registrants, both in San Francisco and online.

Additionally, there are many posters available electronically at the ‘eLightning’ sessions covering the full range of AGU topics.

The hashtag to follow on Twitter is #AGU19.

Forced Responses: Dec 2019

Filed under: — group @ 6 December 2019

Open thread for climate solution discussion. Climate science discussions should remain on the Unforced Variations thread.

How good have climate models been at truly predicting the future?

A new paper from Hausfather and colleagues (incl. me) has just been published with the most comprehensive assessment of climate model projections since the 1970s. Bottom line? Once you correct for small errors in the projected forcings, they did remarkably well.

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Unforced variations: Dec 2019

Filed under: — group @ 1 December 2019

This month’s open thread. December already?

10 years on

Filed under: — gavin @ 17 November 2019

I woke up on Tuesday, 17 Nov 2009 completely unaware of what was about to unfold. I tried to log in to RealClimate, but for some reason my login did not work. Neither did the admin login. I logged in to the back-end via ssh, only to be inexplicably logged out again. I did it again. No dice. I then called the hosting company and told them to take us offline until I could see what was going on. When I did get control back from the hacker (and hacker it was), there was a large uploaded file on our server, and a draft post ready to go announcing the theft of the CRU emails. And so it began.

From “One year later”, 2010.

Many people are weighing in on the 10 year anniversary of ‘Climategate’ – the Observer, a documentary on BBC4 (where I was interviewed), Mike at Newsweek – but I’ve struggled to think of something actually interesting to say.

It’s hard because even in ten years almost everything and yet nothing has changed. The social media landscape has changed beyond recognition but yet the fever swamps of dueling blogs and comment threads has just been replaced by troll farms and noise-generating disinformation machines on Facebook and Twitter. The nominally serious ‘issues’ touched on by the email theft – how robust are estimates of global temperature over the instrumental period, what does the proxy record show etc. – have all been settled in favor of the mainstream by scientists plodding along in normal science mode, incrementally improving the analyses, and yet they are still the most repeated denier talking points.

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