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Tropical tropospheric trends again

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Back in December 2007, we quite heavily criticised the paper of Douglass et al (in press at IJoC) which purported to show that models and data were inconsistent when it came to the trends in the tropical troposphere. There were two strands to our critique: i) that the statistical test they used was not appropriate and ii) that they did not acknowledge the true structural uncertainty in the observations. Most subsequent discussion has been related to the statistical issue, but the second point is perhaps more important.

Even when Douglass et al was written, those authors were aware that there were serious biases in the radiosonde data (they had been reported in Sherwood et al, 2005 and elsewhere), and that there were multiple attempts to objectively address the problems and to come up with more homogeneous analyses. We mentioned the RAOBCORE project at the time and noted the big difference using their version 1.4 vs 1.2 made to the comparison (a difference nowhere mentioned in Douglass et al’s original accepted paper which only reported on v1.2 despite them being aware of the issue). However, there are at least three new papers in press that independently tackle the issue, and their results go a long towards addressing the problems.
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How to cook a graph in three easy lessons

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These days, when global warming inactivists need to trot out somebody with some semblance of scientific credentials (from the dwindling supply who have made themselves available for such purposes), it seems that they increasingly turn to Roy Spencer, a Principal Research Scientist at the University of Alabama. Roy does have a handful of peer-reviewed publications, some of which have quite decent and interesting results in them. However, the thing you have to understand is that what he gets through peer-review is far less threatening to the mainstream picture of anthropogenic global warming than you’d think from the spin he puts on it in press releases, presentations and the blogosphere. His recent guest article on Pielke Sr’s site is a case in point, and provides the fodder for our discussion today.

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Climate Change and Tropical Cyclones (Yet Again)

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By Rasmus Benestad & Michael Mann
Hurricane Katerina
Just as Typhoon Nargis has reminded us of the destructive power of tropical cyclones (with its horrible death toll in Burma–around 100,000 according to the UN), a new paper by Knutson et al in the latest issue of the journal Nature Geosciences purports to project a reduction in Atlantic hurricane activity (principally the ‘frequency’ but also integrated measures of powerfulness).

The close timing of the Knutson et al and Typhoon Nargis is of course coincidental. But the study has been accorded the unprecedented privilege (that is, for a climate change article published during the past 7 years) of a NOAA press conference. What’s the difference this time? Well, for one thing, the title of the paper: “Simulated reduction in Atlantic hurricane frequency under twenty-first-century warming conditions” (emphasis added).

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What the IPCC models really say

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Translations: (Español) (Italian) (English)

Over the last couple of months there has been much blog-viating about what the models used in the IPCC 4th Assessment Report (AR4) do and do not predict about natural variability in the presence of a long-term greenhouse gas related trend. Unfortunately, much of the discussion has been based on graphics, energy-balance models and descriptions of what the forced component is, rather than the full ensemble from the coupled models. That has lead to some rather excitable but ill-informed buzz about very short time scale tendencies. We have already discussed how short term analysis of the data can be misleading, and we have previously commented on the use of the uncertainty in the ensemble mean being confused with the envelope of possible trajectories (here). The actual model outputs have been available for a long time, and it is somewhat surprising that no-one has looked specifically at it given the attention the subject has garnered. So in this post we will examine directly what the individual model simulations actually show.

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Global Cooling-Wanna Bet?

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Translations: (Español) (Deutsch) (Italian) (English)

By Stefan Rahmstorf, Michael Mann, Ray Bradley, William Connolley, David Archer, and Caspar Ammann

Global cooling appears to be the “flavour of the month”. First, a rather misguided media discussion erupted on whether global warming had stopped, based on the observed temperatures of the past 8 years or so (see our post). Now, an entirely new discussion is capturing the imagination, based on a group of scientists from Germany predicting a pause in global warming last week in the journal Nature (Keenlyside et al. 2008).

Specifically, they make two forecasts for global temperature, as discussed in the last paragraphs of their paper and shown in their Figure 4 (see below). The first forecast concerns the time interval 2000-2010, while the second concerns the interval 2005-2015 (*). For these two 10-year averages, the authors make the following prediction:

“… the initialised prediction indicates a slight cooling relative to 1994-2004 conditions”

Their graph shows this: temperatures in the two forecast intervals (green points shown at 2005 and 2010) are almost the same and are both lower than observed in 1994-2004 (the end of the red line in their graph).

Fig. 4 from <em/>Keenlyside et al ’08” align = “left” width=90%/><br /> <b>Figure 4 from <em>Keenlyside et al</em> ’08</b></p> <p>The authors also make regional predictions, but naturally it was this global prediction that captivated most newspaper stories around the world (e.g. <a href=New York Times, BBC News, Reuters, Bloomberg and so on), because of its seeming contradiction with global warming. The authors emphasise this aspect in their own media release, which was titled: Will Global Warming Take a Short Break?

That this cooling would just be a temporary blip and would change nothing about global warming goes without saying and has been amply discussed elsewhere (e.g. here). But another question has been rarely discussed: will this forecast turn out to be correct?

We think not – and we are prepared to bet serious money on this. We have double-checked with the authors: they say they really mean this as a serious forecast, not just as a methodological experiment. If the authors of the paper really believe that their forecast has a greater than 50% chance of being correct, then they should accept our offer of a bet; it should be easy money for them. If they do not accept our bet, then we must question how much faith they really have in their own forecast.

The bet we propose is very simple and concerns the specific global prediction in their Nature article. If the average temperature 2000-2010 (their first forecast) really turns out to be lower or equal to the average temperature 1994-2004 (*), we will pay them € 2500. If it turns out to be warmer, they pay us € 2500. This bet will be decided by the end of 2010. We offer the same for their second forecast: If 2005-2015 (*) turns out to be colder or equal compared to 1994-2004 (*), we will pay them € 2500 – if it turns out to be warmer, they pay us the same. The basis for the temperature comparison will be the HadCRUT3 global mean surface temperature data set used by the authors in their paper.

To be fair, the bet needs an escape clause in case a big volcano erupts or a big meteorite hits the Earth and causes cooling below the 1994-2004 level. In this eventuality, the forecast of Keenlyside et al. could not be verified any more, and the bet is off.

The bet would also need a neutral arbiter – we propose, for example, the director of the Hadley Centre, home of the data used by Keenlyside et al., or a committee of neutral colleagues. This neutral arbiter would also decide whether a volcano or meteorite impact event is large enough as to make the bet obsolete.

We will discuss the scientific reasons for our assessment here another time – first we want to hear from Keenlyside et al. whether they accept our bet. Our friendly challenge is out – we hope they will accept it in good sportsmanship.

(*) We adopt here the definition of the 10-year intervals as in their paper, which is from 1 November of the first year to 31 October of the last year. I.e.: 2000-2010 means 1 November 2000 until 31 October 2010.

Update: We have now published part 2 of this bet with our scientific arguments.

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Update: Andy Revkin has weighed in at “dot earth”.

Update 5/11/08: so has Anna Barnett at Nature’s ‘climate feedback’ blog

Back to the future

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Translations: (Español) (English)

A few weeks ago I was at a meeting in Cambridge that discussed how (or whether) paleo-climate information can reduce the known uncertainties in future climate simulations.

The uncertainties in the impacts of rising greenhouse gases on multiple systems are significant: the potential impact on ENSO or the overturning circulation in the North Atlantic, probable feedbacks on atmospheric composition (CO2, CH4, N2O, aerosols), the predictability of decadal climate change, global climate sensitivity itself, and perhaps most importantly, what will happen to ice sheets and regional rainfall in a warming climate.

The reason why paleo-climate information may be key in these cases is because all of these climate components have changed in the past. If we can understand why and how those changes occurred then, that might inform our projections of changes in the future. Unfortunately, the simplest use of the record – just going back to a point that had similar conditions to what we expect for the future – doesn’t work very well because there are no good analogs for the perturbations we are making. The world has never before seen such a rapid rise in greenhouse gases with the present-day configuration of the continents and with large amounts of polar ice. So more sophisticated approaches must be developed and this meeting was devoted to examining them.

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Butterflies, tornadoes and climate modelling

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Ed Lorenz hiking Many of you will have seen the obituaries (MIT, NYT) for Ed Lorenz, who died a short time ago. Lorenz is most famous scientifically for discovering the exquisite sensitivity to initial conditions (i.e. chaos) in a simple model of fluid convection, which serves as an archetype for the weather prediction problem. He is most famous outside science for the ‘The Butterfly Effect’ described in his 1972 paper “Predictability: Does the Flap of a Butterfly’s Wings in Brazil Set Off a Tornado in Texas?”. Lorenz’s contributions to both atmospheric science and the mathematics of dynamical systems were wide ranging and seminal. He also directly touched the lives of many of us here at RealClimate, and both his wisdom, and quiet personal charm will be sorely missed.

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Moulins, Calving Fronts and Greenland Outlet Glacier Acceleration

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Translations: (Español) (English)

Guest Commentary by Mauri Pelto

The net loss in volume and hence sea level contribution of the Greenland Ice Sheet (GIS) has doubled in recent years from 90 to 220 cubic kilometers/year has been noted recently (Rignot and Kanagaratnam, 2007). The main cause of this increase is the acceleration of several large outlet glaciers. There has also been an alarming increase in the number of photographs of meltwater draining into a moulin somewhere on the GIS, often near Swiss Camp (35 km inland from the calving front). The story goes—warmer temperatures, more surface melting, more meltwater draining through moulins to glacier base, lubricating glacier bed, reducing friction, increasing velocity, and finally raising sea level. Examining this issue two years RealClimate suggested this was likely the correct story. A number of recent results suggest that we need to take another look at this story.

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Model-data-comparison, Lesson 2

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In January, we presented Lesson 1 in model-data comparison: if you are comparing noisy data to a model trend, make sure you have enough data for them to show a statistically significant trend. This was in response to a graph by Roger Pielke Jr. presented in the New York Times Tierney Lab Blog that compared observations to IPCC projections over an 8-year period. We showed that this period is too short for a meaningful trend comparison.

This week, the story has taken a curious new twist. In a letter published in Nature Geoscience, Pielke presents such a comparison for a longer period, 1990-2007 (see Figure). Lesson 1 learned – 17 years is sufficient. In fact, the very first figure of last year’s IPCC report presents almost the same comparison (see second Figure).
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