Overestimated global warming over the past 20 years

[longknife]

John C. Fyfe, Nathan P. Gillett and Francis W. Zwiers

From NATURE CLIMATE CHANGE,| VOL 3 | SEPTEMBER 2013 | @ http://www.see.ed.ac.uk/~shs/Climate change/Climate model results/over estimate.pdf

Recent observed global warming is significantly less than that simulated by climate models. Thisdifference might be explained by some combination of errors in external forcing, model response andinternal climate variability.

Oh really? And this comes from a leading source of environmental commentary!

 

[Old Rocks]

Overestimated warming, vastly underestimated effects. The Arctic Ice Cap is where it was supposed to between 2050 and 2080. The increase in extreme weather events was not expected to happen until midcentury. But when we get another moderate El Nino, I fully expect the underestimate of the warming will disappear.

 

[Old Rocks]

5.2.2 Ocean Heat Content - AR4 WGI Chapter 5: Observations: Oceanic Climate Change and Sea Level

Figure 5.1 shows two time series of ocean heat content for the 0 to 700 m layer of the World Ocean, updated from Ishi et al. (2006) and Levitus et al. (2005a) for 1955 to 2005, and a time series for 0 to 750 m for 1993 to 2005 updated from Willis et al. (2004). Approximately 7.9 million temperature profiles were used in constructing the two longer time series. The three heat content analyses cover different periods but where they overlap in time there is good agreement. The time series shows an overall trend of increasing heat content in the World Ocean with interannual and inter-decadal variations superimposed on this trend. The root mean square difference between the three data sets is 1.5 × 1022 J. These year-to-year differences, which are due to differences in quality control and data used, are small and now approaching the accuracies required to close the Earth’s radiation budget (e.g., Carton et al., 2005). On longer time scales, the two longest time series (using independent criteria for selection, quality control, interpolation and analysis of similar data sets) show good agreement about long-term trends and also on decadal time scales.

 

[IanC]

Overestimated warming, vastly underestimated effects. The Arctic Ice Cap is where it was supposed to between 2050 and 2080. The increase in extreme weather events was not expected to happen until midcentury. But when we get another moderate El Nino, I fully expect the underestimate of the warming will disappear.

Let me get this straight....the predictions for Arctic ice extent were wrong by large amounts due to misunderstood or neglected natural factors and yet you are claiming success?

'broadly consistent' is very broad indeed. Climate models presently lack the skill to make meaningful projections. Even the ones that appear to be 'broadly consistent' are only by chance not skill.

 

[Abraham3]

I believe he is saying that current ocean heat content is GREATER than the AR4 predictions.

 

[Old Rocks]

Overestimated warming, vastly underestimated effects. The Arctic Ice Cap is where it was supposed to between 2050 and 2080. The increase in extreme weather events was not expected to happen until midcentury. But when we get another moderate El Nino, I fully expect the underestimate of the warming will disappear.

Let me get this straight....the predictions for Arctic ice extent were wrong by large amounts due to misunderstood or neglected natural factors and yet you are claiming success?

'broadly consistent' is very broad indeed. Climate models presently lack the skill to make meaningful projections. Even the ones that appear to be 'broadly consistent' are only by chance not skill.

No, I am not claiming success. What I am claiming is that the predictions were far too conservative. And that the predictions of the denialists of that day are laughable when viewed from our present perspective. Just as their denial today will look enormously stupid a decade from now. Up until 2000, the denialists were flat out denying that there was any warming going on at all. Then they changed their tune to, "Well yes, it is warming, but it is natural causes". Yet they cannot name any of the 'natural causes'.

 

[daveman]

Overestimated warming, vastly underestimated effects. The Arctic Ice Cap is where it was supposed to between 2050 and 2080. The increase in extreme weather events was not expected to happen until midcentury. But when we get another moderate El Nino, I fully expect the underestimate of the warming will disappear.

Let me get this straight....the predictions for Arctic ice extent were wrong by large amounts due to misunderstood or neglected natural factors and yet you are claiming success?

It's the Wimp Lo strategy:

 

[daveman]

As I've shown in another thread, the models are absolute crap. They can't even predict past temperatures, when we have the record to compare results to.

And we should trust the models to predict future climate...why, exactly?

 

[Abraham3]

As I've shown in another thread, the models are absolute crap. They can't even predict past temperatures, when we have the record to compare results to.

And we should trust the models to predict future climate...why, exactly?

It's how it's done. Besides, what else have we got? The Farmer's Almanac?

ps: you didn't show shit.

 

[daveman]

As I've shown in another thread, the models are absolute crap. They can't even predict past temperatures, when we have the record to compare results to.

And we should trust the models to predict future climate...why, exactly?

It's how it's done. Besides, what else have we got? The Farmer's Almanac?

It's how it's done? We should hang the economies of the entire Western world on computer models that can't predict the past because that's how it's done?

Not in reality, it's not.

ps: you didn't show shit.

Two unsourced graphs. Less than compelling, really.

Meanwhile, I did exactly show what I said. But it really wasn't me; it was:

Clim. Past, 9, 1089-1110, 2013
www.clim-past.net/9/1089/2013/
doi:10.5194/cp-9-1089-2013

Climate of the last millennium: ensemble consistency of simulations and reconstructions

O. Bothe1,2,*, J. H. Jungclaus1, D. Zanchettin1, and E. Zorita3,4

1Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany
2University of Hamburg, KlimaCampus Hamburg, Hamburg, Germany
3Institute for Coastal Research, Helmholtz Centre Geesthacht, Geesthacht, Germany
4Bert Bolin Centre for Climate Research, University of Stockholm, Stockholm, Sweden
*now at: Leibniz Institute for Atmospheric Physics at the University of Rostock, Kühlungsborn, Germany​

You can claim these scientists are all funded by Big Oil. I don't mind you looking like an idiot.

 

[S.J.]

Best to ignore the climate cultists. They've been predicting doom since the word "smog" was first invented.

http://wattsupwiththat.com/2011/04/22/failed-mirth-earth-day-predictions/

 

[bripat9643]

Overestimated warming, vastly underestimated effects. The Arctic Ice Cap is where it was supposed to between 2050 and 2080. The increase in extreme weather events was not expected to happen until midcentury. But when we get another moderate El Nino, I fully expect the underestimate of the warming will disappear.

Let me get this straight....the predictions for Arctic ice extent were wrong by large amounts due to misunderstood or neglected natural factors and yet you are claiming success?

'broadly consistent' is very broad indeed. Climate models presently lack the skill to make meaningful projections. Even the ones that appear to be 'broadly consistent' are only by chance not skill.

No, I am not claiming success. What I am claiming is that the predictions were far too conservative. And that the predictions of the denialists of that day are laughable when viewed from our present perspective. Just as their denial today will look enormously stupid a decade from now. Up until 2000, the denialists were flat out denying that there was any warming going on at all. Then they changed their tune to, "Well yes, it is warming, but it is natural causes". Yet they cannot name any of the 'natural causes'.

So far, after 20 years of hysterical screaming about global warming, it's the warmist cult members who look enormously stupid. Why would anyone believe that they are going to suddenly look better in the next 20 years?

 

[bripat9643]

Overestimated warming, vastly underestimated effects. The Arctic Ice Cap is where it was supposed to between 2050 and 2080. The increase in extreme weather events was not expected to happen until midcentury. But when we get another moderate El Nino, I fully expect the underestimate of the warming will disappear.

According to whom? Only six years ago, the BBC reported that the Arctic would be ice-free in summer by 2013, citing a scientist in the US who claimed this was a ‘conservative’ forecast. What "increase in extreme weather events?" There isn't a shred of evidence for that.

 

[Abraham3]

Overestimated warming, vastly underestimated effects. The Arctic Ice Cap is where it was supposed to between 2050 and 2080. The increase in extreme weather events was not expected to happen until midcentury. But when we get another moderate El Nino, I fully expect the underestimate of the warming will disappear.

According to whom? Only six years ago, the BBC reported that the Arctic would be ice-free in summer by 2013, citing a scientist in the US who claimed this was a ‘conservative’ forecast. What "increase in extreme weather events?" There isn't a shred of evidence for that.

BBC.... quoting "a scientist".

Let's get real. No one - not even your side of this argument, saw the hiatus coming. And you have no explanation for it, do you? Thought not.

And, of course, we're still waiting on some kind of answer from you on how one makes climate projections without resorting to models. I suppose we could have a look at the models YOUR fellows have created. Now where might those be Dave?

 

[Old Rocks]

What scientific organization has the initial BBC? Come on, dumb fuck, that is not a source that has credibility as far as predictions on climate or ice. Now here is where you should go for that kind of prediction;

PIOMAS August 2013 - Arctic Sea Ice

 

[Abraham3]

From Dave's link:
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Abstract. Are simulations and reconstructions of past climate and its variability consistent with each other? We assess the consistency of simulations and reconstructions for the climate of the last millennium under the paradigm of a statistically indistinguishable ensemble. In this type of analysis, the null hypothesis is that reconstructions and simulations are statistically indistinguishable and, therefore, are exchangeable with each other. Ensemble consistency is assessed for Northern Hemisphere mean temperature, Central European mean temperature and for global temperature fields. Reconstructions available for these regions serve as verification data for a set of simulations of the climate of the last millennium performed at the Max Planck Institute for Meteorology.

Consistency is generally limited to some sub-domains and some sub-periods. Only the ensemble simulated and reconstructed annual Central European mean temperatures for the second half of the last millennium demonstrates unambiguous consistency. Furthermore, we cannot exclude consistency of an ensemble of reconstructions of Northern Hemisphere temperature with the simulation ensemble mean.

If we treat simulations and reconstructions as equitable hypotheses about past climate variability, the found general lack of their consistency weakens our confidence in inferences about past climate evolutions on the considered spatial and temporal scales. That is, our available estimates of past climate evolutions are on an equal footing but, as shown here, inconsistent with each other.

Citation: Bothe, O., Jungclaus, J. H., Zanchettin, D., and Zorita, E.: Climate of the last millennium: ensemble consistency of simulations and reconstructions, Clim. Past, 9, 1089-1110, doi:10.5194/cp-9-1089-2013, 2013.
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Yo, Dave,

How about you show us where your article says that the models ("of past climate") overestimate warming?

 

[Abraham3]

At several points in this thread the comment was made that the models checked here could not accurately simulate the climate even where the climate was known. That comment does not jibe with the article. There is NO direct observational knowledge of the climate in the areas being simulated. The only inputs are proxy data from various biological, geological and chemical indications. These model runs were NOT judged for accuracy, but for statistical consistency.

I suggest, Dave, that you did not read this article before citing it as evidence.

 

[Abraham3]

Here is the conclusion of Dave's article:

Concluding remarks

Rank histograms, χ 2 goodness-of-fit test decomposition and residual quantile-quantile plots help to assess the probabilistic and climatological consistency of ensemble projections against a verification data set (e.g. Annan and Hargreaves, 2010; Marzban et al., 2011). If no reliable observable target can be identified, as is the case in periods and regions without Concluding remarks Rank histograms, χ 2 goodness-of-fit test decomposition and residual quantile-quantile plots help to assess the probabilistic and climatological consistency of ensemble projections against a verification data set (e.g. Annan and Hargreaves, 2010; Marzban et al., 2011). If no reliable observable target can be identified, as is the case in periods and regions without instrumental observations, such statistical analyses reduce the subjectivity in comparing simulation ensembles and statistical approximations from paleo-sensor data (Braconnot et al., 2012) under uncertainty and go beyond “wiggle matching”. The approach permits a succinct visualization of the consistency between an ensemble of estimates and an uncertain verification target. Ideally, it also reduces the dependence on the reference climatology which is present in many visual and mathematical methods that aim to qualify the correspondence between simulations and (approximated) observations.

We considered the COSMOS-Mill ensemble (Jungclaus et al., 2010) and various reconstructions within the described approach. We found the simulation ensemble to be consistent, within sampling variability, with the Central European temperature reconstruction by Dobrovolny et al. ´ (2010). The ensemble possibly lacks consistency with respect to the mean of the ensemble of Northern Hemisphere mean temperature reconstructions by Frank et al. (2010) due to probabilistic over-dispersion and various climatological deviations. The ensemble generally samples from a significantly wider distribution than the reconstruction ensemble mean. The distribution of the reconstruction ensemble in turn is possibly consistent relative to the simulation ensemble mean.

Furthermore, the simulation ensemble is found to be statistically distinguishable from the global field temperature reconstruction by Mann et al. (2009). Although the data is probabilistically consistent for multi-centennial sub-periods and certain regions according to the applied full test, analyses of single probabilistic deviations and climatological differences emphasise a general lack of consistency. We found the largest, but still limited, consistency over areas of Eurasia and North America for both full and sub-periods. For some periods, we also cannot reject consistency for most tropical and northern hemispheric ocean regions. The profound lack of climatological and probabilistic consistency between the simulation ensemble and reconstructions stresses the importance of improving simulations and reconstructions to investigate past climates in order to achieve a more resilient estimate of the true past climate state and evolution.

If our estimates are not consistent with each other for certain periods and areas, it is unclear how we should compare their accuracy. Thus if these reconstructions and this simulation ensemble are employed in dynamical comparisons and in studies on climate processes, we have to account for the climatological and probabilistic discrepancies between both data sets, which have been described in the present work.(see Jolliffe and Primo, 2008). The distributional degrees of freedom equal n − 1 for the full test and n is the number of classes in the rank histogram. The decomposition of the χ2 test statistic implies that we have only 1 degree of freedom for the single deviation test (Jolliffe and Primo, 2008; Annan and Hargreaves, 2010).

We reject consistency for certain right p values of thetest. Where appropriate, we also interpret the test statistics in terms of a reversed null hypothesis to test that there is a deviation from uniformity. This refers to the general goodnessof-fit χ2 statistic or to a specific deviation for the decomposed statistic. It is reasonable to consider significance at a conservative one-sided 90 % level due to the large uncertainties associated with the data. Thus critical chi-square values become 2.706 for the single deviation test. For the full goodness-of-fit test, we consider ensembles of eleven, nine, five and three members (see Sect. 2.2). Critical values are respectively 17.275, 14.684, 9.236 and 6.251.

Meaningful results for the tests require accounting for dependencies in the data (Jolliffe and Primo, 2008; Annan and Hargreaves, 2010). All analyses account for effective sample size (see discussions by and references of Bretherton et al., 1999). A larger effective sample size essentially leads to a higher chance of rejecting the hypothesis of uniformity. Furthermore, the results are sensitive to the made assumptions, particularly those with respect to the included uncertainty estimates (see Sect. 2.3).

Some further notes are in place. If ensemble and verification data are smoothed (as for the global data by Mann et al., 2009), either the sample size or the expected number of rank counts may be small compared with the theoretical requirements (but see e.g. Bradley et al., 1979, and
references therein). Temporal correlations further affect the structure of the rank histograms (Marzban et al., 2011; Wilks, 2011), and sampling variability can result in erroneous conclusions from the rank counts. That is, a flat rank histogram is only a necessary condition for consistency (see discussions by e.g. Hamill, 2001; Marzban et al., 2011). To account for this, we display, for area-averaged time series, quantile statistics of block-bootstrapped rank histograms (Marzban et al., 2011; Efron and Tibshirani, 1994). We apply a block length of 50 yr, calculate 2000 bootstrap replicates and display 0.5, 50 and 99.5 percentiles. This additionally allows for a secondary test of uniformity. The results are sensitive to the chosen block length, and 50 yr are possibly too short according to the auto-correlation functions for some reconstructions. However, 50 yr appear to be a reasonable compromise if we consider that the optimal length may also be shorter for some records.
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Maybe I missed it, Dave, but I just cannot locate where, in this study, they said that the model they used (the Max Planck Earth Model System,"based on the atmosphere model ECHAM5, the ocean model MPI-OM, a land-surface module including vegetation (JSBACH), a module for ocean biogeochemistry (HAMOCC) and an interactive carbon cycle" - that is to say a SINGLE model run in ensemble fashionand compared for consistency with proxy-based reconstructions) WAS OVERESTIMATING TEMPERATURE.

This entire thread is based on a false statement.

 

[skookerasbil]

"The models".......another climate crusader hoax!!


The models are wrong | Behind The Black



They get people to buy this shit because it says "computer" when talking about models. But heres the problem.......they are always wrong. The climate nuts do a fair job of duping the clueless and otherwise uninformed who aren't going to check the facts!!

 

[skookerasbil]

"Computer models"


You know, some of the climate crusaders know this is total BS and are just in here to perpetuate the hoax but I do think there are a handful of mental cases who really do believe the ruse on the computer model shit!!