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about Gavin Schmidt

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

AGU Chapman Conference on Climate Science Communication

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A couple of weeks ago, there was a small conference on Climate Science communication run by the AGU. Both Mike and I attended, but it was very notable that it wasn’t just scientists attending – there were also entertainers, psychologists, film-makers and historians. There were a lot of quite diverse perspectives and many discussions about the what’s, why’s and how’s of climate science communication.

There were a couple of notable features: the conference had a lively twitter hashtag (#climatechapman), and almost the entire proceedings were webcast live (schedule). The video from this has now been posted on YouTube in more bite-sized chunks.

While our own presentations (Mike here and Gavin here) are available, it is worth watching the presentations from people you might not have heard of, as well as a few from more established people. We’ll embed a few here, but please point out some of the other ones of interest in the comments.
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2012 Updates to model-observation comparisons

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Time for the 2012 updates!

As has become a habit (2009, 2010, 2011), here is a brief overview and update of some of the most discussed model/observation comparisons, updated to include 2012. I include comparisons of surface temperatures, sea ice and ocean heat content to the CMIP3 and Hansen et al (1988) simulations.
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What to study?

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I recently got an email from newly graduated Math(s) major (mildly edited):

I am someone with a deep-seated desire to help the planet remain as habitable as possible in the face of the trials humanity is putting it through. I’d like to devote my career to this cause, but am young and haven’t chosen a definitive career path yet. My bachelors is in pure math and I am considering graduate study in either applied math or statistics. I’m curious what you would recommend to someone in my position. Between getting, say, a PhD in statistics vs. one in applied math, what positions me best for a career in the climate science community? What are its acute needs, where are the job opportunities, and how competitive is it?

My response was as follows (also slightly edited):

As you may know I too started out as a mathematician, and then moved to more climate related applications only in my post-doc(s).

I can’t possibly give you ‘the’ answer to your question – but I do suggest working from the top down. What do you see specifically as something where someone like you could have maximum impact? Then acquire the skills needed to make that happen. If that seems too hard to do now, spend time on the developing your basic toolkits – Bayesian approaches to statistics, forward modeling, some high level coding languages (R, python, matlab etc.), while reading widely about applications.

One of the things I appreciated most in finding my niche was being exposed to a very large number of topics – which while bewildering at the start, in the end allowed me to see the gaps where I could be most useful. At all times though, I pursued approaches and topics that were somewhat aesthetically pleasing to me, which is to say, I didn’t just take up problems just for the sake of it.

I’ve found that I get more satisifaction from focusing on making some progress related to big problems, rather than finding complete solutions to minor issues, but this probably differs from person to person.

But what do other people think? How should people prepare to work on important problems? Are there any general rules? What advice did people give you when you were starting out? Was it useful, or not? Any advice – from existing researchers, graduate students or interested public – will be welcome.

On sensitivity: Part I

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Climate sensitivity is a perennial topic here, so the multiple new papers and discussions around the issue, each with different perspectives, are worth discussing. Since this can be a complicated topic, I’ll focus in this post on the credible work being published. There’ll be a second part from Karen Shell, and in a follow-on post I’ll comment on some of the recent games being played in and around the Wall Street Journal op-ed pages.

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Improving the Tropical Cyclone Climate Record

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Guest Commentary by Christopher Hennon (UNC Asheville)

Get involved in a new citizen science project at CycloneCenter.org.

The poor quality of the tropical cyclone (TC) data record provides severe constraints on the ability of climate scientists to: a) determine to what degree TCs have responded to shifts in climate, b) evaluate theories on how TCs will respond to climate change in the future. The root cause for the poor data is the severity of the TC conditions (e.g. high wind, rough seas) and the remoteness of these storms – the vast majority of which form and remain well away from most observing networks. Thus, most TCs are not observed directly and those that are (with buoys, aircraft reconnaissance, ships) are often not sampled sufficiently (see the IBTrACS, (Knapp et al., 2010)).

This leaves tropical cyclone forecasters, who are ultimately responsible for recording TC tracks and intensities (i.e. maximum wind speeds), with a challenging problem. Fortunately, there is a tool called the Dvorak Technique which allows forecasters to make a reasonable determination of the TC intensity by simply analyzing a single infrared or visible satellite image, which is almost always available Velden et al., 2006). The technique calls for the analyst to determine the center location of the system, the cloud pattern type, the degree of organization of the pattern, and the intensity trend. A maximum surface wind speed is determined after the application of a number of rules and constraints.

Hurricane Gay (1992)The Dvorak Technique has been used for many years at all global tropical cyclone forecast centers and has been shown in many cases to yield a good estimate of maximum TC wind speed, when applied properly (Knaff et al., 2010). However, there is a level of analyst subjectivity inherent in the procedure; the cloud patterns are not always clear, it is sometimes difficult to accurately determine the storm center and the rules and constraints have been interpreted and applied differently across agencies. This introduces heterogeneity in the global TC record since the Dvorak Technique is usually the only available tool for assessing the maximum wind speed.

There has been recent work to eliminate the human element in the Dvorak Technique by automating the procedure. The Advanced Dvorak Technique (ADT) uses objective storm center and cloud pattern schemes to remove the subjectivity (Olander and Velden, 2007). All other classification rules and constraints are then applied and combined with additional statistical information to produce automated intensity estimates. Although the ADT skill is comparable to experienced human Dvorak analysts, large errors can occur if the scene type is not identified properly.

A new crowd sourcing project, called Cyclone Center, embraces the human element by enabling the public to perform a simplified version of the Dvorak Technique to analyze historical global tropical cyclone (TC) intensities (Hennon, 2012). Cyclone Center’s primary goal is to resolve discrepancies in the recent global TC record arising principally from inconsistent development of tropical cyclone intensity data. The Cyclone Center technique standardizes the classification procedure by condensing the Dvorak Technique to a few simple questions that can be answered by global, nonprofessional users.

One of the main advantages of this approach is the inclusion of thousands of users, instead of the 1-3 who would normally classify a TC image. This allows the computation of measures of uncertainty in addition to a mean intensity. Nearly 300,000 images, encompassing all global TCs that formed from 1978-2009, will be classified 30 times each – a feat that would take a dedicated team of twenty Dvorak-trained experts about 12 years to complete. Citizen scientists have already performed over 100,000 classifications since the project launch in September. Once the project is complete, a new dataset of global TC tracks and intensities will be made available to the community to contribute to our efforts to provide the best possible TC data record.

Interested readers are encouraged to learn more about and participate in the project at the cyclonecenter.org website (there are some FAQ on the project blog). The CycloneCenter project is a collaboration between the Citizen Science Alliance, NOAA National Climatic Data Center (NCDC), University of North Carolina at Asheville, and the Cooperative Institute for Climate and Satellites (CICS) – North Carolina.

References

  1. K.R. Knapp, M.C. Kruk, D.H. Levinson, H.J. Diamond, and C.J. Neumann, "The International Best Track Archive for Climate Stewardship (IBTrACS)", Bulletin of the American Meteorological Society, vol. 91, pp. 363-376, 2010. http://dx.doi.org/10.1175/2009BAMS2755.1
  2. C. Velden, B. Harper, F. Wells, J.L. Beven, R. Zehr, T. Olander, M. Mayfield, C.â. Guard, M. Lander, R. Edson, L. Avila, A. Burton, M. Turk, A. Kikuchi, A. Christian, P. Caroff, and P. McCrone, "The Dvorak Tropical Cyclone Intensity Estimation Technique: A Satellite-Based Method that Has Endured for over 30 Years", Bulletin of the American Meteorological Society, vol. 87, pp. 1195-1210, 2006. http://dx.doi.org/10.1175/BAMS-87-9-1195
  3. J.A. Knaff, D.P. Brown, J. Courtney, G.M. Gallina, and J.L. Beven, "An Evaluation of Dvorak Technique–Based Tropical Cyclone Intensity Estimates", Weather and Forecasting, vol. 25, pp. 1362-1379, 2010. http://dx.doi.org/10.1175/2010WAF2222375.1
  4. T.L. Olander, and C.S. Velden, "The Advanced Dvorak Technique: Continued Development of an Objective Scheme to Estimate Tropical Cyclone Intensity Using Geostationary Infrared Satellite Imagery", Weather and Forecasting, vol. 22, pp. 287-298, 2007. http://dx.doi.org/10.1175/WAF975.1
  5. C.C. Hennon, "Citizen scientists analyzing tropical cyclone intensities", Eos, Transactions American Geophysical Union, vol. 93, pp. 385-387, 2012. http://dx.doi.org/10.1029/2012EO400002

IPCC draft (redux)

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Amid the manufactured spin and excitement of the unofficial release of the IPCC WG1 Second Order Draft, it is worth remembering that this happened last time too:

IPCC draft: No comment

May 4, 2006

As everyone has now realised, the second-order draft of the new IPCC report has become very widely available and many of the contributors to this site, commenters and readers will have seen copies. Part of the strength of the IPCC process are the multiple stages of review – the report is already significantly improved (in clarity and scientific basis) from the first round of reviews, and one can anticipate further improvements from the ongoing round as well. Thus no statements from this draft report can be considered ‘official’. While most of the contents of the report will come as no surprise to frequent visitors here, we have decided that we are not going to discuss the report until it is finalised and released (sometime in February 2007). At that time, we’ll go chapter by chapter hopefully pulling out the interesting bits, but until then, we feel it’s more appropriate to respect the ‘Do not cite or quote’ injunctions that can be found on every page. We trust that our commenters will likewise respect the process. Patience, people, patience!

The only change is that AR5 will be released in September 2013.

Responses to volcanoes in tree rings and models

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Houston, we have a problem.

Admittedly, not a huge problem and not one that most people, or even most climatologists, are particularly fascinated by, but one which threads together many topics (climate models, tree rings, paleo-climate) which have been highlighted here in the past. The problem is that we have good evidence in the ice core records for very large tropical eruptions over the last 1000 years – in particular the eruptions in 1258/1259, 1452 and 1809 to 1815 – but for which many paleo-reconstructions barely show a blip in temperature. Models, in attempting to simulate this period, show varied but generally larger (and sometimes much larger) responses. The differences are significant enough to have prompted a few people to try and look into why this mismatch is occurring.

Whenever there is a mismatch between model and observation, there are, roughly speaking, at least three (non-exclusive) possibilities: the model is wrong, the observational data are wrong or the comparison is not like-with-like. There have been many examples of resolved mismatches in each category so all possibilities need to be looked at.

As described in a previous post earlier this year, Mann et al., 2012 (pdf), postulated that for extreme volcanoes, the cooling would be sufficient to saturate the growth response, and that some trees might `skip´ a ring for that year leading to a slight slippage in tree-ring dating, a potential smearing of the composite chronologies, and a further underestimate of the cooling in tree-ring based large-scale reconstructions.

This hypothesis has now been challenged by a group of authors in a comment (Anchukaitis et al.) (pdf, SI, code), who focus on the appropriateness of the tree ring growth model and the spatial pattern the volcanic climate responses. The Mann et al. response (pdf, SI) presents some further modeling and 19th century observational data in support of the original hypothesis.

Of course, there are still two other possibilities to consider. First, the models may have an excessive response. This could be due to either models responding excessively to the correct forcing, or could be related to an excessive forcing itself. There are indeed some important uncertainties in estimating the history of volcanic forcing – which involves inferring a stratospheric aerosol load (and effective radius of the particles and their distribution) from a network of sulphate peaks in ice cores in Greenland and Antarctica. For example, the forcing for the big eruption around 1453 differs by a factor of 2 in the inferred forcing (-12 W/m2 and -5.4 W/m2) in the two estimates proposed for the recent model-intercomparison (Schmidt et al., 2012). Note too that the details of how aerosols are implemented in any specific model can also make a difference to the forcing, and there are many (as yet untested) assumptions built into the forcing reconstructions.

It is also conceivable that climate models overreact to volcanic forcing – however, excellent matches to the Pinatubo response in temperature, radiative anomalies, water vapour and dynamic responses, where we know the volcanic aerosol load well, make that tricky to support (Hansen et al, 2007) (pdf, SI). (As an aside, the suggestion in this paper that the response to Krakatoa (1883) was underpredicted by the historical SST fields was partially vindicated by the results from HadSST3 which showed substantially more cooling).

The third possibility is that some tree-ring reconstructions can’t be easily compared to simple temperature averages from the models. As both the original paper and the comment suggests, there are important effects from memory from previous years in ring widths and, potentially, increases in diffuse light post-eruption promoting growth spurts. This needs to be assessed using more sophisticated forward models for tree ring growth applied to the models’ output – a feature in both the Mann et al, and Anchukaitis et al. approaches. More work is likely needed on this, and using the wider variety of model experiments coming out of CMIP5/PMIP3.

There is clearly potential for these competing hypotheses to get sorted out. Information from newly-digitised old instrumental records in the early 19th Century such as shipping records for the East India Company (Brohan et al, 2012), doesn’t support the largest modelled responses to Tambora (1815), but does suggest a response larger and more defined than that seen in some reconstructions. However, other 19th Century temperature compilations such Berkeley Earth show larger responses to Tambora – though there are spatial sampling issues there as well. There is also the potential for non-tree ring based reconstructions to provide independent confirmation of the magnitude of the response.

So while neither of the latest comments and responses provide a definitive answer to the principal problem, there is certainly lots of scope for extended and (hopefully) productive discussions.

References

  1. M.E. Mann, J.D. Fuentes, and S. Rutherford, "Underestimation of volcanic cooling in tree-ring-based reconstructions of hemispheric temperatures", Nature Geoscience, vol. 5, pp. 202-205, 2012. http://dx.doi.org/10.1038/ngeo1394
  2. K.J. Anchukaitis, P. Breitenmoser, K.R. Briffa, A. Buchwal, U. Büntgen, E.R. Cook, R.D. D'Arrigo, J. Esper, M.N. Evans, D. Frank, H. Grudd, B.E. Gunnarson, M.K. Hughes, A.V. Kirdyanov, C. Körner, P.J. Krusic, B. Luckman, T.M. Melvin, M.W. Salzer, A.V. Shashkin, C. Timmreck, E.A. Vaganov, and R.J.S. Wilson, "Tree rings and volcanic cooling", Nature Geoscience, vol. 5, pp. 836-837, 2012. http://dx.doi.org/10.1038/ngeo1645
  3. M.E. Mann, J.D. Fuentes, and S. Rutherford, "Reply to 'Tree rings and volcanic cooling'", Nature Geoscience, vol. 5, pp. 837-838, 2012. http://dx.doi.org/10.1038/ngeo1646
  4. G.A. Schmidt, J.H. Jungclaus, C.M. Ammann, E. Bard, P. Braconnot, T.J. Crowley, G. Delaygue, F. Joos, N.A. Krivova, R. Muscheler, B.L. Otto-Bliesner, J. Pongratz, D.T. Shindell, S.K. Solanki, F. Steinhilber, and L.E.A. Vieira, "Climate forcing reconstructions for use in PMIP simulations of the Last Millennium (v1.1)", Geoscientific Model Development, vol. 5, pp. 185-191, 2012. http://dx.doi.org/10.5194/gmd-5-185-2012
  5. J. Hansen, M. Sato, R. Ruedy, P. Kharecha, A. Lacis, R. Miller, L. Nazarenko, K. Lo, G.A. Schmidt, G. Russell, I. Aleinov, S. Bauer, E. Baum, B. Cairns, V. Canuto, M. Chandler, Y. Cheng, A. Cohen, A. Del Genio, G. Faluvegi, E. Fleming, A. Friend, T. Hall, C. Jackman, J. Jonas, M. Kelley, N.Y. Kiang, D. Koch, G. Labow, J. Lerner, S. Menon, T. Novakov, V. Oinas, J. Perlwitz, J. Perlwitz, D. Rind, A. Romanou, R. Schmunk, D. Shindell, P. Stone, S. Sun, D. Streets, N. Tausnev, D. Thresher, N. Unger, M. Yao, and S. Zhang, "Climate simulations for 1880–2003 with GISS modelE", Climate Dynamics, vol. 29, pp. 661-696, 2007. http://dx.doi.org/10.1007/s00382-007-0255-8
  6. P. Brohan, R. Allan, E. Freeman, D. Wheeler, C. Wilkinson, and F. Williamson, "Constraining the temperature history of the past millennium using early instrumental observations", Climate of the Past, vol. 8, pp. 1551-1563, 2012. http://dx.doi.org/10.5194/cp-8-1551-2012

Trying to shoot the messenger

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Does this sound familiar? A quantitative prediction is inconvenient for some heavily invested folks. Legitimate questions about methodology morph quickly into accusations that the researchers have put their thumb on the scale and that they are simply making their awkward predictions to feather their own nest. Others loudly proclaim that the methodology could never work and imply that anyone who knows anything knows that -it’s simply common sense! Audit sites spring up to re-process the raw data and produce predictions more to the liking of their audience. People who have actually championed the methods being used, and so really should know better, indulge in some obvious wish-casting (i.e. forecasting what you would like to be true, despite the absence of any evidence to support it).

Contrarian attacks on climate science, right?
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Short term trends: Another proxy fight

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One might assume that people would be happy that the latest version of the Hadley Centre and CRU combined temperature index is now being updated on a monthly basis. The improvements over the previous version in terms of coverage and error estimates is substantial. One might think that these advances – albeit incremental – would at least get mentioned in a story that used the new data set. Of course, one would not be taking into account the monumental capacity for some journalists and the outlets they work for to make up stories whenever it suits them. But all of the kerfuffle over the Mail story and the endless discussions over short and long term temperature trends hides what people are actually arguing about – what is likely to happen in the future, rather than what has happened in the past.

The fundamental point I will try and make here is that, given a noisy temperature record, many different statements can be true at the same time, but very few of them are informative about future trends. Thus vehemence of arguments about the past trends is in large part an unacknowledged proxy argument about the future.

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