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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

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Search for 2008/2009

Comments matching the search 2008/2009:

  • Modeled and Observed Ocean Heat Content - Is There a Discrepancy?

    Alex C at 08:53 AM on 1 June, 2012

    Bob Tisdale:

    I've been looking through the interwebs to see if I could find anything on the GISS Model ER simulations past 2003 to see whether or not the straight-line extrapolation is an accurate estimation of what the models actually said would happen. I came across a post at Troy's, you commented there so I think you might be familiar:

    http://troyca.wordpress.com/2011/10/06/giss-er-and-ocean-heat-content/

    I think that, in the absence of a more formal showing of the model output (and since I don't see any reason to suspect Troy has done anything wrong in his plotting), this should serve as a useful tool for all of us to see how the models predicted the past decade. The straight-line extrapolation that you use (and RealClimate and others) appears to be a pretty accurate estimation of the model output over the last decade, so I don't see any reason to stand by the opinion that you're misrepresenting the model output.

    However, the model output starting after 2004 does not appear to actually be based on known data, but the A1B scenario specifications. To compare the model output to the observations makes the assumption that our climate system has seen comparable forcing to A1B, which isn't obvious is the case since again we had an increased aerosol effect, a prolonged solar minimum through 2008/2009, for instance. I can't see how the model's A1B output is any better than the linear extrapolation, because it is just as physically unrepresentative of the past decade.

    Feedback on this of course appreciated, from anyone that might have anything else to add on to this as well.
  • Lean and Rind Estimate Human and Natural Global Warming

    KR at 01:37 AM on 12 January, 2012

    skept.fr - "...this point of TSI-UV-EUV correlation, albeit probably marginal or null in terrestrial temperature trend, is still in debate among solar scientists." (emphasis added)

    That, the emphasized portion, is a critical point - the largest part of solar variance seems correlated with TSI (or sunspots - Foster and Rahmstorf 2011 found no significant difference when substituting sunspot number for a TSI index). And once the major contributors to temperature change are identified we gain a better understanding of climate - some ability to predict future temperature evolution.

    The results in Lean and Rind 2008/2009, Foster and Rahmstorf 2011, and others - these all indicate that we have a pretty good grip on the major influences behind climate change. Other influences are certainly there, with varying degrees of uncertainty - but they appear quite small.

    While small changes around the edges are interesting, and quite worthy of research effort, we really do know what the elephant in the room is - anthropogenic greenhouse gases.
  • Pre-1940 Warming Causes and Logic

    HumanityRules at 12:31 PM on 23 March, 2011

    40 IanC

    There is this review which explains the background to different estimates of multi-centennial TSI variation (starting on page 11 if you don't want to read all 53 pages). It specifically states why the early Hoyt and Schatten estimates may simply be wrong based on false assumptions. It can't help with why the more recent estimates (1-2 W/M2 for MM to present) are different to the new Schrijver work, the review doesn't include the Schrijver work. The Schrijver explanation for the difference between the recent estimates and their work is described on page 4 of the PDF and is summarized in Fig3. I have to admit it get's too technical for me but the gist would seem to be thus. It would seem that TSI variation is affected by things that were visible (sunspots) and not visible (faculae??) to early observers. Modern scientist have to extrapolate back these non-visible features by modelling them. Without access to the conditions in 2008/2009 to constrain some of the parameters the use of SSN to estimate magnetic flux has introduced biases which are compounded the further one goes back in time. I think Schrijvers point is that the quiet conditions of 2008/2009 constrain some of the modelling parameters better and lead to lower estimates of TSI variation. But as I say this is all too technical for me so I could be wrong, I also have no way of judging the merit of the argument

    It seems highly disturbing that in your view the TSI variation can undergo maybe a ten-fold revision downward without having implications about our understanding of what drives climate. If that's the case it seems hardly worth deriving estimates in the first place, again this looks like far too much wiggle factor for this to be meaningful science. Maybe you can explain why ten-fold drops in TSI variation don't really matter?

    I know the line on this website is that if solar forcing is lowered then that just pushes up climate sensitivity. I see how that works with respect to the simple equation that describes the relationship between temperature change and forcing, but that's all. It's certainly not the only conclusion one could draw from that observation and can only be made by assuming a high degree of certainty about the science. The knock on effects of high climate sensitivity for other aspects of the science just seem to be ignored as well.
  • Arctic Sea Ice: Why Do Skeptics Think in Only Two Dimensions?

    HumanityRules at 12:00 PM on 24 August, 2010

    To be fair it's not just skeptics that favour extent and area it's the scientists themselves. Every online website from polar groups seems to have it's own measure of extent. In fact PIOMAS ice volume graph you show is a fairly unique online metric from my trawling.

    While PIOMAS seemed accurate before 2007 there does seem to have been a deviation between their modelled results and reality since. In 2008 and 2009 this model underestimated the minimum extent and looks like it will again underestimate extent. Surely a model is always under scrutiny going forward, this is the best test for how well it is modelling the real world, at what point do we say that a model is no longer accurate. It seems that continually referring back to 3 years when it matched well with a short satellite data set can't be enough to keep it afloat.

    There are still issues with ice thickness measurements specifically the lack of good spatial and temporal coverage which leaves uncertainty in any estimate of volume or trends. Looking back to the 1990's here's two papers covering that period which came to very different conclusions (Windsor and Rothrock). More recently I just read this paper

    Thickness sensitivities in the CICE sea ice model
    Elizabeth C. Hunke
    Ocean Modelling Volume 34, Issues 3-4, 2010, Pages 137-149

    which suggests that the probable number of factors which affect ice thickness out-numbers the data sets by which those factors can be constrained suggesting we still don't have the data by which we can directly or through models accurately estimate thickness and more importantly trends.

    It seems there are good reasons why some are cautious about ice thickness. Why not highlight the uncertainty associated with this particular metric? It seems like an important aspect of the work.


    (Just for correction the Giles 2008 and Kwok 2009 only seem to cover 2008 data not 2008/2009 as you seem to suggest in your article. You've also managed to leave out the word modelled with regard to the PIOMAS graph.)
  • What causes the tropospheric hot spot?

    Peter Hogarth at 08:12 AM on 29 June, 2010

    One of the issues at the heart of the matter is the trend differences between UAH and RSS satellite temperature estimates for the tropical lower and mid troposphere, both based on the MSU (microwave soundings) raw data from various satellites.



    Santer 2008
    uses data from 1979 to 2000, Bengtsson 2009 uses a similar methodology with (Ocean only) satellite data updated to 2008, and I have updated the satellite trend values to current, with the latest UAH LT5.3 data. All trend value are degrees C per decade.

    Santers analysis of the satellite trends and surface temperature and Radiosonde trends to 2000 pointed to a much reduced discrepancy between observations and model outputs than found previously (see figure below). He also suggests where models may be lacking.

    Bengtsson 2009 follows on from this but uses the later lower trend values. Based on these and a modeling/statistical approach, the probability of the satellite temperature trends being due to natural causes is given as 27% for the UAH measurements and 2.5% for the RSS measurements. Maybe reasonable odds, but not “robust” yet except perhaps in the case of the RSS trend.

    Bengtsson also argues that the UAH values are closer to observed SST, but conversely Santer 2008 suggests the RSS values are closer to other global temperature series, and other interpretations of the MSU raw data. This relatively small RSS/UAH difference weighs heavily.

    Bengtsson concludes “Observed and re-analyzed lapse rate trends are all positive and for the period 1979-2008 well outside the range of natural variability”, but in terms of temperature trends, “The present 30-years of tropospheric temperature observations are still insufficient to identify robust trends as the internal variability of realistic climate models is larger than the observed trends”

    Has the situation changed since 2008/2009?

    A little. The UAH/RSS divergence has reduced with the latest revisions and data, the RSS trend values are slightly lower but the revised UAH tropical trend values have increased (I should mention UAH global trends did not change with the update) so that they are higher than in Santers original analysis. As the trends have continued (ie troposheric temperatures have continued to rise) we would expect that the updated 2010 data will push further towards (rather than away from) any statistically robust result.

    The following image is from Santer 2008 and summarises the story of the models and measurements as at 2008 quite nicely.



    If you view the JoNova post linked in the article you will see a related but older chart from Santer 2005, which supports the idea of significant divergence despite Jo citing the later 2008 paper in which Santer argues otherwise. Likewise her second figure should be updated in line with more recent work, as science has moved on.

    I also have serious concerns about the one later reference which Jo uses (Paltridge 2009) to support a view that tropospheric relative humidity is falling. This is at odds with the conclusions of the bulk of recent papers I have read, and Paltridge himself states “It is accepted that radiosonde-derived humidity data must be treated with great caution” the data is single source (NCEP) re-analysis.

    As well as Sherwood 2010a listed earlier, and evidence from Sherwood 2010b, he has also completed a recent review of independent work examining tropospheric water vapour using multiple data sets from several types of sensor Sherwood 2010c which adds a more thoroughly referenced and wide perspective on Tropospheric water vapour:

    “Thus, all primary data sets support the conclusion that water vapor mixing ratios in the troposphere are increasing at roughly the rate expected from the Clausius-Clapeyron equation. Although a few analyses have found otherwise, these relied on secondary data sets that are less suitable for quantifying trends”.
  • Has solar cycle 24 begun?

    Mizimi at 00:01 AM on 17 August, 2008

    16th August...still no sunspots..(www.spaceweather.com)
    Looking forward with interest to see what 2008/2009 GMT is.


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