On The IPCC’s Undue Confidence In Coupled Ocean-Atmosphere Climate Models – A Summary Of Recent Posts

I’ve placed Bob’s Figure 21 at the top of this post, because it shows something quite interesting, note to caption in red, upper left. – Anthony

Guest post by Bob Tisdale

Figure 21

OVERVIEW

This post is a summary of the series of our recent posts that compared observed Surface Temperature data to the simulations of the coupled ocean-atmosphere climate models used by the IPCC in their 4thAssessment Report (AR4). The IPCC’s response to their Frequently Asked Question (FAQ) 8.1 serves as an introduction.

INTRODUCTION

The IPCC’s Frequently Asked Question 8.1 appears in Chapter 8 “Climate Models and their Evaluation and in their separate Frequently Asked Questionspublication. FAQ 8.1 and the opening paragraph of the IPCC’s answer read as follows (my boldface):

“How Reliable Are the Models Used to Make Projections of Future Climate Change?

“There is considerable confidence that climate models provide credible quantitative estimates of future climate change, particularly at continental scales and above. This confidence comes from the foundation of the models in accepted physical principles and from their ability to reproduce observed features of current climate and past climate changes. Confidence in model estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation). Over several decades of development, models have consistently provided a robust and unambiguous picture of significant climate warming in response to increasing greenhouse gases.”

Later in that discussion, the IPCC continues their remarkably confident claims about the climate models, and they introduce FAQ8.1, Figure 1, which should look familiar. It served as the backbone for many of the recent posts. It’s the same graph as cell a of Figure 9.5 (my boldface):

“A third source of confidence comes from the ability of models to reproduce features of past climates and climate changes. Models have been used to simulate ancient climates, such as the warm mid-Holocene of 6,000 years ago or the last glacial maximum of 21,000 years ago (see Chapter 6). They can reproduce many features (allowing for uncertainties in reconstructing past climates) such as the magnitude and broad-scale pattern of oceanic cooling during the last ice age. Models can also simulate many observed aspects of climate change over the instrumental record. One example is that the global temperature trend over the past century (shown in Figure 1) can be modeled with high skill when both human and natural factors that influence climate are included.”

Figure 1 (FAQ 8.1, Figure 1)

After reading the series of posts here at Climate Observationsthat discussed and illustrated how poorly the IPCC’s ocean-atmosphere climate models simulate global surface temperatures over the 20th Century, many of you might find it odd:

1. that the IPCC has repeatedly used the word “confidence” in the same sentence and paragraphs as climate models,

2. that the IPCC has stated that the climate models have shown “high skill” and “provide credible quantitative estimates”, and

3. that the IPCC has stated the models “have consistently provided a robust and unambiguous picture of significant climate warming in response to increasing greenhouse gases”, etc.

Credible, consistently, robust, and unambiguous are words that were well chosen by the IPCC, and they are contained in well-crafted sentences. They help to instill reader confidence in climate models—there’s that word confidence again. But the antonyms of those well-chosen words; not believable, inconsistently, weak, and uncertain; are definitely more appropriate.

Many of you may wonder if the authors who wrote that part of AR4 had actually compared the multi-model simulation data to the observed surface temperatures. Some of you may think the IPCC’s reply to FAQ8.1 is a total fabrication or that it misrepresents the actual capabilities of the climate models. If we try to look at the IPCC’s reply to FAQ8.1 in a positive light, it’s an embellishment that is intended to help market a supposition, and that supposition is that anthropogenic greenhouse gases have played something more than a miniscule role in the rise in surface temperatures over the 20thCentury, especially during the late warming period–since 1976. And, of course the IPCC authors had reason to do this: in order for the IPCC to market their projections of future catastrophic warming, they needed to extend and accelerate the modeled surface temperature trend from the recent warming period. A lower, more realistic rate of warming would never have done.

Let’s take a quick look at those posts again,

1. to determine if the IPCC is believable when they state their climate models have “high skill”,

2. to determine if the IPCC is realistic when they use the words “credible”, “consistently”, “robust”, and “unambiguous” to describe climate model simulations, and

3. to determine if anyone anywhere should have “confidence” in those models.

A QUICK NOTE ABOUT THE DATA PRESENTED IN THIS POST

All data presented in this post is either available online to the public or is easily reproducible. The majority of the data is available through the Royal Netherlands Meteorological Institute (KNMI) Climate Explorerwebsite. To replicate the data presented in the IPCC graphs like Figure 1 above, there is software available online to perform this function, or the X-Y coordinates of a graphics program such as MS Paint can be used. In short, anyone with internet access, spreadsheet software, and a little bit of time can confirm what is presented in this post.

THE 20TH CENTURY MODEL-DATA SURFACE TEMPERATURE COMPARISON POSTS

The post The IPCC Says… – The Video – Part 1 (A Discussion About Attribution) and the YouTube video presented in it included a replica of the IPCC’s comparison of climate model simulations and observed 20th Century Surface Temperature anomalies. The IPCC used the same graph in their Figure 9.5 cell a and their FAQ8.1, Figure 1, which is included in this post as Figure 1. The data in the replica was divided into four periods that the IPCC discusses in Chapter 3 Observations: Surface and Atmospheric Climate Change. Those periods are loosely defined by the IPCC as follows:

“Clearly, the changes are not linear and can also be characterized as level prior to about 1915, a warming to about 1945, leveling out or even a slight decrease until the 1970s, and a fairly linear upward trend since then (Figure 3.6 and FAQ 3.1).”

With respect to the model simulation data, the Model Mean represents the forced component of the model simulations when the models are forced by both natural and anthropogenic forcings.

NOTE: We confirmed that the replication of the data from Figure 9.5 cell a was realistic by comparing it to the ensemble member mean of the 12 climate modelsthat are available online. The trends of the early and late warming periods were used as reference in that comparison since those were the periods we were most concerned with in these posts.

Figure 2 shows that the IPCC’s models did a good job of simulating the rate at which instrument-based (observed) global surface temperature anomalies actually rose during the late warming period of the 20thCentury. And Figure 3 shows that the models could also simulate the observed trend in surface temperature anomalies during the mid-century “flat temperature” period.

Figure 2

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

Figure 3

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

We also showed the models cannot simulate the observed trends in surface temperature anomalies during the early warming period (Figure 4) and during the early “flat temperature” period (Figure 5). In other words, the models do not come close to simulating the rates at which temperatures changed over those multidecadal periods.

Figure 4

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

Figure 5

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

Why is that important? During the early warming period, observed surface temperatures rose at a rate that was three times higher than the rate of the forced component of the models, as represented by the model mean. This suggests that the temperatures can rise over multidecadal periods at high rates without those rates being dictated by natural and anthropogenic forcings. But that’s not the message we hear from the IPCC.

Also understand that the rates at which global surface temperature anomalies rose during the early warming period and late warming period are comparable, as shown in Figure 6. The linear trend during the late warming period is only about 12% higher than the trend of the early warming period. But the rate at which the forced component of the models rose during the late warming period is far greater (more than 3 times greater) than during the early period. See Figure 7. The fact that the trend of the forced component of the models is so much higher in the late period, while trend of the observations is relatively unchanged, suggests any number of things. One is that the additional forcings had very little impact on the rate at which the instrument-based global surface temperature observations rose. And that also is not the message we hear from the IPCC.

Figure 6

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

Figure 7

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

In summary, instead of the models and data supporting the hypothesis of Anthropogenic Global Warming, they actually contradict it.

CONFIRMING AND CLARIFYING THOSE RESULTS

There were two initial follow-up posts:

Do Observations And Climate Models Confirm Or Contradict The Hypothesis of Anthropogenic Global Warming? – Part 1

And:

Part 2 – Do Observations and Climate Models Confirm Or Contradict The Hypothesis of Anthropogenic Global Warming?

In Part 1, we replaced the replicated model-mean data with the multi-model ensemble mean data from the CMIP3 climate models that the IPCC used in their Figure 9.5, cell a. CMIP3 is the climate model archive used by the IPCC for AR4. The results were similar to those shown earlier in Figures 2 through 5. These links will bring you to the graphs for the late warming period, the mid-20th Century “flat temperature” period, the early warming period, and the early “flat temperature” periodfrom that first follow-up post.

Comparisons were also presented using the recently updated Sea Surface Temperature data from the Hadley Centre. That new Sea Surface Temperature data was combined with the land surface temperature data and then compared to the models. The results were similar to Figure 2 during the late warming period, inasmuch as the model-mean trend was close to the trend of the observations. And the comparison results with the new Sea Surface Temperature data were similar to Figures 4 and 5 during early warming period and the early “flat temperature” period, inasmuch as the models failed in their attempt to simulate the trends during those periods.

But the new Sea Surface Temperature data when combined with the land surface data made a significant difference during the mid-20thCentury “flat temperature” period, as shown in Figure 8. The models now failed to simulate the observations during this period too.

Figure 8

That means, if the global land+sea surface temperature observational data uses the new and improved Sea Surface Temperature data, then the models can only simulate the observed rate of warming during the late 20th Century warming period—from 1976 to 2000. In other words, of the 20thCentury’s two warming periods and two “flat temperature” periods, the IPCC model mean (the forced component of the models) can only simulate the trends of one of those four periods. Only one of four. But that’s not the message presented by the IPCC.

In Part 2 of the initial follow-up posts, there were a few clarifications before three more model-data comparisons were presented. In one of the comparisons, the model data and observations were adjusted for the linear impacts of volcanic eruptions and El Niño-Southern Oscillation (ENSO) events. The adjustments minimize the variations in the two datasets caused by volcanic aerosols, and the adjustments minimize the year-to-year variations in the surface temperature observations cause by El Niño and La Niña events. (Those adjustments do not account for the multiyear and decadal aftereffects of significant El Niño/La Niña events. I’ll illustrate those later in this post.) The bottom line: the adjustments had little effect on the trend comparisons for the late warming period, the mid-20th Century “flat temperature” period, the early warming period, and the early “flat temperature” period. That is, the results were similar to those shown in Figures 2 through 5 above.

And the results were similar to those shown in Figures 2 through 5 if the observational dataset the IPCC used (the Hadley Centre’s HADCRUT) was replaced with the average of the three land+sea surface temperature products that are available from GISS, Hadley Centre, and NCDC. The following links show the graphs for the late warming period, the mid-20th Century “flat temperature” period, the early warming period, and the early “flat temperature” period,using the average of the three observation datasets.

Part 2 also included comparisons of modeled and observed Global Sea Surface Temperature anomalies. Always keep in mind that the global oceans cover about 70% of the surface of the Earth. With the Sea Surface Temperature data, the comparisons started in 1880. The reason for the earlier start year was to determine how well the model mean (the forced component of the models) simulated the significant decrease in Sea Surface Temperature that occurred from the 1860s to 1910. If you’re not aware, with some datasets, the Sea Surface Temperatures in the 1860s and 1870s were comparable to those of the mid-20thCentury “flat temperature” period, as shown in Figure 9. It would have been nice to extend the comparison back to the 1860s but some of the models and other Sea Surface Temperature datasets do not have data available before 1880.

Figure 9

For the Sea Surface Temperature comparisons, we used the average of 5 different instrument-based Sea Surface Temperature datasets for the observational data. As expected, the models agreed reasonably well with the observations in the mid-20th Century “flat temperature” period and the late warming period. Those agreements during the latter part of the 20th Century do not appear to be as good as the other comparisons, but they would probably pass statistical scrutiny. The models also failed to simulate the rate at which temperatures rose during the early warming period. And as shown in Figure 10, the models did not hindcast the significant drop in Sea Surface Temperature anomalies from 1880 to 1910. The model mean indicated that, with the natural and anthropogenic forcings, Sea Surface Temperatures should have risen slightly, but the observations showed they dropped considerably.

Figure 10

And the last comparison of Part 2 included the models versus the updated version of the Hadley Centre’s Sea Surface Temperature data, HADSST3. The update created a significant negative trend during mid-20thCentury “flat temperature” period of 1944 to 1975. This was caused in part from a correction for a discontinuity in the data around 1945. The bottom line: the models can no longer simulate the observed Sea Surface Temperatures as a result of the updates during that period, as shown in Figure 11.

Figure 11

In short, with the latest and greatest Sea Surface Temperature data, the multi-model mean (the forced component of the models) only simulates the observed rate of temperature change during the last 24 years of the 20thCentury.

LAND SURFACE TEMPERATURE COMPARISONS

CMIP3 Models Versus 20th Century Land Surface Temperature Anomalies is the most recent follow-up post. As its title states, it compares observed changes in global Land Surface Temperature anomalies to the climate models from the CMIP3 archive, which is the source of the IPCC’s data for AR4. Not unexpectedly, the rate at which land surface temperatures rose during the late warming period was simulated well by the models. Also not unexpectedly, the models also failed to hindcast the trends during the early “flat temperature” period and the early warming period of the 20th Century. But the models also failed to simulate the rate at which land surface temperatures cooled during the mid-20th Century “flat temperature” period that lasted from 1938 to 1976 with land surface temperature data. So for another dataset, the models have illustrated that they are only capable of simulating surface temperatures during the last quarter of the 20thCentury.

IF NOT GREENHOUSE GASES, WHAT CAUSED THE RISE IN SURFACE TEMPERATURE OVER THE PAST 30 YEARS?

And that brings us to another follow-up post, IPCC Models Versus Sea Surface Temperature Observations During The Recent Warming Period.

To illustrate the cause of the rise in Surface Temperatures over the past 30 years, we shifted to a different dataset. For that discussion, we used satellite-based Sea Surface Temperature data (NOAA’s Optimum Interpolated Sea Surface Temperature data Version 2, which is also known as OI.v2) because it has the best coverage of the global oceans. Other Sea Surface Temperature datasets rely only on in situ observations from buoys and ships and do not have complete coverage over that time period. A few infill the missing data using statistical methods but observations are, of course, preferred.

Figure 12 compares Global Sea Surface Temperature anomalies to those hindcast (20C3M) and projected (SRES A1B) by the Multi-Model Mean of the CMIP3 Climate Models. Again CMIP3 is the climate model archive used by the IPCC for AR4. (Note that this graph was not presented in the linked post. I’ve provided it here as a reference.) The rate at which observed global Sea Surface Temperature anomalies rose over the past 30 years is only about 60% of the rate simulated by the models. The models aren’t looking very good over this time period, especially with those base years for anomalies, and for Figure 16, we used the same base years (1980-1999) that the IPCC used for its projections.

Figure 12

For the following discussions and in the linked post, the Sea Surface Temperature data and the model mean of the Sea Surface Temperature simulations both have the base years of 1982 to 2011. This was done to better align the observations and model simulation data over that time period. Additionally, both datasets have been adjusted for the impacts of volcanic eruptions. The adjustments affect the appearance of the data during the years when the aerosols emitted by the explosive volcanic eruptions of El Chichon and Mount Pinatubo caused global Sea Surface Temperatures to drop. It took a few years after those eruptions in 1982 and 1991 for surface temperatures to rebound. The linear trends of the data that has not been corrected for the volcanic eruptions have slightly different linear trends. We discussed the method used to adjust the data for volcanic aerosols in the post linked above, and it won’t be repeated here.

To illustrate why Sea Surface Temperatures have risen over the past 30 years, we’ll divide the global oceans into two subsets. These include the East Pacific Ocean from pole to pole (90S-90N, 180-80W), and the Rest Of The World from pole to pole (90S-90N, 80W-180). The areas are shown in Figure 13.

Figure 13

The East Pacific Ocean model-observation comparison is shown in Figure 14. The first thing that stands out is the difference in the year-to-year variability. The observed variations in Sea Surface Temperature anomalies due to the El Niño and La Niña events are much greater than those of the Multi-Model Mean. The large upward spikes are caused by El Niño events, and the lesser, but still major, downward spikes are caused by La Niña events. Keep in mind when viewing the model-observations comparisons in this post that the model mean is the average of all of the ensemble members, and since the variations in the individual ensemble members are basically random, they will smooth out with the averaging. The average, therefore, represents the forced component (from natural and anthropogenic forcings) of the models. And it’s the forced component of the model data we’re interested in illustrating and comparing with the observations in this post, not the big wiggles associated with ENSO.

Figure 14

The difference in the linear trends between the Multi-Model Mean and the observations is extremely important. That has been the focus of this series of posts. The linear trend of the model simulations is 0.114 deg C per decade for the East Pacific Ocean. This means, based on the linear trend of the Multi-Model Mean, that anthropogenic forcings should have raised the East Pacific Sea Surface Temperature anomalies, from pole to pole, by more than 0.34 deg C over the past 30 years. But the observed Sea Surface Temperature anomalies have actually declined slightly. The East Pacific Ocean dataset represents about 33% of the surface area of the global oceans, and the Sea Surface Temperature anomalies there have not risen in response to the forcings of anthropogenic greenhouse gases. The IPCC has overlooked that basic fact.

The Sea Surface Temperature anomalies and Model simulation data for the Rest-Of-The-World (Atlantic, Indian, and West Pacific Oceans) from pole to pole are shown in Figure 15. The linear trends show that the models have overestimated the warming by about 23%.

Figure 15

But that might give the wrong impression, leading some to believe that anthropogenic greenhouse gases were somehow responsible for the rise in the Rest-Of-The-World Sea Surface Temperatures. But that’s not what the instrument-based Sea Surface Temperature data shows. The observed Sea Surface Temperature anomalies only rose in response to significant El Niño-La Nina events, and during the 9- and 11-year periods between those ENSO events, the observed Sea Surface Temperatures for the Rest of the World are remarkably flat. This is illustrated first in Figure 16, using the period average Sea Surface Temperature anomalies between the significant El Niño events, and second, in Figure 17, by showing the linear trends of the instrument-based observations data between the 1986/87/88 and 1997/98 El Niño events and between the 1997/98 and 2009/10 El Niño events.

Figure 16

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

Figure 17

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

As you will note, the significant El Niño events of 1982/83, 1986/87/88, 1997/98, and 2009/10 have been isolated for the Rest-Of-The-World data. To accomplish this, the NOAA Oceanic Nino Index (ONI) was used to determine the official months of those El Niño events. There is a 6-month lag between NINO3.4 SST anomalies and the response of the Rest-Of-The-World SST anomalies during the evolution phase of the 1997/98 El Niño. So the ONI data was lagged by six months, and the Rest-Of-The-World SST data that corresponded to the 1982/83, 1986/87/88, 1998/98, and 2009/10 El Niño events was excluded from the trend analyses. All other months of data remain.

Note: The El Niño event of 1982/83 was counteracted by the volcanic eruption of El Chichon, so its apparent role in the long-term warming is minimal.

And what do the climate models show should have taken place during the periods between those ENSO events for the Rest-Of-The-World Sea Surface Temperatures?

For the period between the 1986/87/88 and the 1997/98 El Niño events, Figure 18, the model simulations show a positive linear trend of 0.044 deg C per decade, while the observed linear trend is negative, at -0.01 deg C per decade. The difference of 0.054 deg C per decade is substantial.

Figure 18

The difference in the linear trends is even more significant between the El Niño events of 1997/98 and 2009/10, as shown in Figure 19. The linear trend of the Rest-Of-The-World observations is basically flat, while trend of the models is relatively high at 0.16 deg C per decade.

Figure 19

Keep in mind that the model mean, according to the IPCC, represents the anthropogenically forced component of the climate models during the period of 1981 to 2011. Unfortunately for the models and the IPCC, there is no evidence of anthropogenic forcing in the East Pacific Sea Surface Temperature data (90S-90N, 180-80W), Figure 20, or in the Sea Surface Temperature data for the Rest Of The World (90S-90N-80W-180), Figure 21.

Figure 20

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

Figure 21

HHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHHH

ADDITIONAL NOTES ABOUT THE SEA SURFACE TEMPERATURE COMPARSIONS

There have been and will be criticisms about the discussion above, because it shows that the El Niño-Southern Oscillation (ENSO) was responsible for most if not all of the rise in Global Sea Surface Temperatures over the past 30 years. Even though the data clearly shows what has been discussed, to counter the obvious contribution of ENSO, proponents of Anthropogenic Global Warming have and will continue to present the tired old argument that ENSO is a cycle and as such it cannot contribute to the long-term trend. Only those who do not understand the process of ENSO would try to use that or similar arguments. For who are not familiar with the El Niño-Southern Oscillation, refer the post An Introduction To ENSO, AMO, and PDO – Part 1.

With that basic understanding of ENSO, refer to following two posts. The first discusses, illustrates, and animates many of the variables that create the upward shifts in the Rest-Of-The-World data:

ENSO Indices Do Not Represent The Process Of ENSO Or Its Impact On Global Temperature

The second makes a clarification:

Supplement To “ENSO Indices Do Not Represent The Process Of ENSO Or Its Impact On Global Temperature”

The post IPCC Models Versus Sea Surface Temperature Observations During The Recent Warming Period also divided the Rest-Of-The-World subset into two more subsets to isolate the North Atlantic from the South Atlantic, Indian, and West Pacific Oceans, because the Sea Surface Temperatures of the North Atlantic have an additional mode of variability called the Atlantic Multidecadal Oscillation. For more information on the Atlantic Multidecadal Oscillation refer to the post An Introduction To ENSO, AMO, and PDO — Part 2.

Two more model-observation comparison posts: Refer also to the comparisons of Sea Surface Temperature and model mean datasets (see here and here). As shown, the Multi-Model Mean of the CMIP3 coupled ocean-atmosphere climate models do not simulate the Sea Surface Temperature anomalies in any ocean basin with any skill. It does not matter if the data is presented on times-series basis or on a zonal mean (latitude-based) basis. The model simulations show no basis in reality.

CLOSING COMMENTS

The IPCC attempted to and failed to confirm the hypothesis of Anthropogenic Global Warming with climate models, and without the climate models, the IPCC has no means to verify that hypothesis. That obvious failure aside, the IPCC along with its contributors and disciples have done a masterful job at marketing the concept of Carbon Dioxide-driven anthropogenic global warming to the general public and to politicians. It really was a great job. The IPCC claims:

“Models can also simulate many observed aspects of climate change over the instrumental record. One example is that the global temperature trend over the past century (shown in Figure 1) can be modeled with high skill when both human and natural factors that influence climate are included.”

But the data actually shows the models are not able to reproduce the rates at which global surface temperatures rose or fell during first three multidecadal periods of the 20thCentury with any consistency. In other words, the model-data comparisons repeatedly show that the observed rates at which surface temperatures can vary over multidecadal time periods can be significantly different than the rates simulated by the climate models. The models and observations actually contradict the hypothesis of greenhouse gas-driven anthropogenic global warming.

In response to the IPCC’s FAQ8.1 “How Reliable Are the Models Used to Make Projections of Future Climate Change?, a more accurate answer would be:

There should be little confidence in climate models. The model simulations fail in their attempts to provide credible quantitative estimates of future climate change, on regional, or continental, or global scales. The models have shown little to no ability to reproduce observed features of current climate and past climate changes. Confidence in model estimates is greatly overstated by the IPCC for the most common of climate variables (e.g., surface temperature) used to present the supposition of manmade global warming. After several decades of development, models have continued to show no skill at establishing that climate warming is a response to increasing greenhouse gases. No skill whatsoever.

The only skill shown by the IPCC is their unlimited capacity to market a concept that has been shown to have little basis in reality.

ABOUT: Bob Tisdale – Climate Observations

SOURCES

Refer to the linked posts for the sources of the data presented in this summary post.

Advertisements

  Subscribe  
newest oldest most voted
Notify of
David A. Evans

Problem is, you’re playing their game!
Global temperatures mean FA! If a humid cell cools, an arid cell must warm more.
It’s BS!
DaveE.

Theo Goodwin

Brilliant work, Mr. Tisdale! Hats off to you once again.

Theo Goodwin

Brilliant work, Mr. Tisdale! Hats off to you once again.

David A. Evans

In the same vein as my last post…
Try pre-heating an oven to 200°C then opening it to put in a stew.
Notice the air coming out is comfortably warm.
After cooking, note the humid air is noticeably warmer!
Humidity and energy at work.
DaveE.

crosspatch

That the temperatures correspond during one 30 year period when the slope of the temperature rise roughly correlated to the slope of CO2 rise means they have their CO2 sensitivity too high in the models and they just happened across a period of time when the two slopes were in agreement.
Growth in NASCAR attendance could have probably been substituted for CO2 with the same result.
The IPCC will say that this is proof that the heat is hiding (in the Hadley Heat Hidey Hole just off the coast of Cabo San Lucas, Mexico) until El Nino frightens it and it escapes into the rest of the oceans. Or something.

The IPCC well should use the word Confidence, as often as possible, since a Confidence game, is what their reason for existence is all about.

pat

27 Dec: DNA India: Arvind Kumar: The great global climate con
India must eschew the global climate deal that was recently proposed in Durban as it will infringe on the economic freedom of Indians. The proposal seeks to raise money for a global climate fund by setting up an international license-raj for industries and imposing shipping and carbon taxes. The taxes and fees will result in the transfer of wealth from India and China to the West as the two countries will contribute the most to global economic activity in coming years.
The shipping tax will increase the cost of various goods while the carbon tax will reduce India’s competitiveness by retarding the growth of its industries.
While India potentially faces these hardships, supporters of the fund have prepared themselves to reap a windfall. The licences, known as carbon credits, will be traded on financial exchanges resulting in billions of dollars in transaction fees and profits for the European Climate Exchange and financial firms like Goldman Sachs…
The proposed climate fund will be similar to other international funds that award contracts and grants to corporations and non-profit groups based in the US and Europe. Many members of the Intergovernmental Panel on Climate Change will receive huge grants. It is little wonder, then, that despite claims of helping poor countries, it is the politicians in the West who are eager to set up the fund.
The rationale behind the fund too is unconvincing. Proponents of the fund claim that global warming is underway and warn of a catastrophic flood of biblical proportions if they are not given money. Supporters of the claim have been likened to members of a doomsday cult. In the 1970s, they predicted the onset of an ice age due to smoke from stoves in India blocking out sunlight. At that time, India was forced to purchase so-called ‘clean stoves’ from the World Bank for millions of dollars. In recent times, Al Gore, the messiah of global warming believers, has accused India’s poor of heating up the earth by using kerosene stoves to cook food. Ironically, Al Gore’s private jet plane burns up thousands of gallons of aviation grade kerosene on each flight.
Data related to the global warming claims too have not been without controversy and some scientists have invited ethics investigations due to scientific misconduct…
In recent years, NASA has also quietly lowered its baseline long term global average temperature from 15 to 14 degrees Celsius, allowing it to claim higher temperature deviations. Despite the change, collating NASA’s press releases over several years shows a decline in global temperature. NASA now puts out numbers from a computer software model instead of actual temperatures.
Indians who oppose corruption should also fight it at the global level. The desperation of the proponents of the climate fund to clinch the deal is seen from their wooing of Indian politicians at conferences organised at Copenhagen, Cancun and Durban. It is important for India to reject the climate deal and ensure that its interests are not sold by politicians for personal gains.
http://www.dnaindia.com/analysis/column_the-great-global-climate-con_1630432

pat

28 Dec: Times of India: India against binding pact on emission cuts: Jayanthi
India will not accept any binding targets under a new post 2020 climate regime until the principle of differentiation based on equity is defined, Union environment and forests minister Jayanthi Natarajan told the Rajya Sabha on Tuesday…
http://timesofindia.indiatimes.com/home/environment/developmental-issues/India-against-binding-pact-on-emission-cuts-Jayanthi/articleshow/11273991.cms
——————————————————————————–

pat

28 Dec: AFP: India ‘won’t sign binding emissions pact’: minister
India said Tuesday it would reject any global pact legally binding it to cut greenhouse gas emissions as such a move could stifle economic growth needed to eradicate poverty…
“There is no question of signing a legally binding agreement at this point of our development. We need to make sure that our development does not suffer,” Natarajan told the upper house of parliament.
“Our emissions are bound to grow as we have to ensure our social and economic development and fulfil the imperative of poverty eradication,” the minister added.
Some 42 percent of Indians, or 455 million people, live on less than $1.25 a day, according to the World Bank…
http://www.google.com/hostednews/afp/article/ALeqM5hbQEJL8fZ4bFFLfI-rTlPq9m4hqA?docId=CNG.f7ab34b17766df497253151fb35e8bcd.591
——————————————————————————–

Thanks, Anthony.

DonB in VA

My 6 year old grandson asked “grandpa when they take the Earth’s temperature where do they put the thermometer?”

Phil R

pat says:
December 27, 2011 at 4:29 pm
27 Dec: DNA India: Arvind Kumar: The great global climate con
Supporters of the claim have been likened to members of a doomsday cult. In the 1970s, they predicted the onset of an ice age due to smoke from stoves in India blocking out sunlight. At that time, India was forced to purchase so-called ‘clean stoves’ from the World Bank for millions of dollars.
Finally, the truth. Global warming isn’t caused by CO2. It’s caused by an overabundance of clean stoves.

Ken in Beaverton, OR

DonB in VA says:
December 27, 2011 at 4:54 pm
My 6 year old grandson asked “grandpa when they take the Earth’s temperature where do they put the thermometer?”
I think they put it in Michael Mann’s butt.

KR

Bob Tisdale
I would like to note that:
(1) You are attempting to fit trends to 8-12 year periods, when a statistical analysis of the data variance indicates that a minimum of 17 years is needed to establish a linear trend with any confidence (Santer et al. 2011).
(2) You are then using these very short periods to attempt to fit a multiple-step set of changes, much more complex than a linear fit, and hence requiring even more data to establish confidence.
Your conclusions of a multiple-step set of changes is simply not supportable with the small set of data you have used.
And (3) In your discussion of IPCC models versus the temperature record, you properly should include both the mean and the range of the climate models. Otherwise you are once again comparing an average of multiple models against a single observation record – apples versus oranges, as the average of 58 runs will have a much lower variance than a single set of observations. Looking at the temperature record against the range of the models shows that >95% of the observations are within the model range. That’s not bad at all.

Mary Turner

So, El Nino creates heat? That is moronic.

RobW

It will be interesting watching exactly how this “worlds biggest scientific fraud” unravels and how the politico ( except for the UN, they need the money) distance themselves from the scam.

crosspatch

@DonB in VA
Apparently here:

It’s been burning for over 35 years so far in Darvaz, Uzbekistan.

Pamela Gray

Apparently they have been looking for the “hidey hole”? It must fit there. And thanks for the new word. Second time today I spit coffee on my phone screen.

Thanks Mr Tisdale for your most thorough and professional analysis. It is an indispensable resource to many 10s of thousands of us. It is careful, understated and shows high quality workmanship.
I would like to remind WUWT readers of other corroborative resources: the website distinguished, highly acclaimed Professor, Dimitris Koutsoyiannis, and the book, The Climate Caper (2009) by Emeritus Professor Garth Paltridge, (http://www.connorcourt.com/catalog1/index.php?main_page=product_info&cPath=29&products_id=113) a pioneer of non-equilibrium thermodynamics, one who as distinguished chief scientist in Australia’s CSIRO was deeply involved in the IPCC and antecedents in the early years.
Richard KM

Pamela Gray

By the way Bob, best post of yours since… like the last one. Brain candy. Loved it.

Paul Penrose

The models are software, so until they have been validated and verified they can’t be relied on for anything. The reason the IPCC does not seem to know this is because none of them are Software Engineers. From what I can tell they are amateurs in that arena. This for me is the bottom line in regards to the models.

eyesonu

Thank you Bob. You have obviously put a lot of effort into this.
I especially like your conclusion as reads in part:
In response to the IPCC’s FAQ8.1 “How Reliable Are the Models Used to Make Projections of Future Climate Change?, a more accurate answer would be:
There should be little confidence in climate models.

Mary Turner says: “So, El Nino creates heat? That is moronic.”
Obviously, Mary Turner, you believe ENSO is an index and not a process. In other words, you haven’t a clue what ENSO represents. I anticipated comments like yours, which was why I provided a link to a post that introduces readers to the process of ENSO… http://bobtisdale.wordpress.com/2010/08/08/an-introduction-to-enso-amo-and-pdo-%e2%80%93-part-1/
…and the reason I provided a link to a post that illustrates, describes and animates the processes that cause those upward shifts in Sea Surface Temperatures, so that people like you could actually watch it happen:
http://bobtisdale.wordpress.com/2011/07/26/enso-indices-do-not-represent-the-process-of-enso-or-its-impact-on-global-temperature/
And when you’re done with that one, you can add the additional influence of the Atlantic Multidecadal Oscillation on the North Atlantic:
http://bobtisdale.wordpress.com/2011/08/07/supplement-to-enso-indices-do-not-represent-the-process-of-enso-or-its-impact-on-global-temperature/
Have a nice day.

Alan Statham

“Basically, The Entire Rise In The Rest-Of World Sea Surface Temperature Anomalies Occurred During The Three El Nino Events”, you say, adopting a strange capitalisation convention and an ignorance of the proper spelling of El Niño. This amateurish exercise in drawing lines through graphs tells us nothing of physical significance. Either all El Niños cause this effect, or it’s a mere artefact of the way you are looking at the data. From the fact that Earth’s temperature historically has not gone up every time there is an El Niño event, we can easily deduce which option is correct.

King of Cool

crosspatch says:
December 27, 2011 at 5:25 pm

Ref The Door to Hell (in Turkmenistan?)
Obviously Red Adair went to Heaven:
“I’ve done made a deal with the devil. He said he’s going to give me an air-conditioned place when I go down there, if I go there, so I won’t put all the fires out.”
Looks like a very big job for Son of Red.

Alan Statham,
Since you can’t credibly refute the article, you criticize the capitalization?
Very weak.

andy

Some of your trend lines are drawn over fairly short periods. If you go even shorter they change again, wildly in some cases. Does the process you have applied seem a bit arbitrary ?

jorgekafkazar

Mary Turner says: “So, El Nino creates heat? That is moronic.”
And your statement is ignorance, Mary.

crosspatch

I think what this points out re: the models is the question:
Please explain why the rise from 1975 to 2005 is anthropogenic and the rise from 1910 to 1940 isn’t and why the later rise isn’t simply the continuation of the earlier rise with a 30 year hiatus. And both rises could be considered a continuation of the late 19th century rise that also had a hiatus that ended in about 1910.

andy

In other words, you may be getting lost in the trees and missing the overall forest ? Just a thought, I’m still a skeptic, but only just. The IPCC graph seems reasonable at the forest level.

From a precision and accuracy point of view I am inclined to dismiss it all, your work and IPCC’s. I have seen very little evidence that some unitary value, thought to repentant anything as vast as on ocean or continent let alone the planet, represents much other then some highly unreliable models. In arriving at these anomalies, one makes a host of assumptions which we know to be both incomplete and not necessarily fully understood, in the context of a dynamic system. Combine that with the rather short time sequences available these trends, all of them, are simply educated guesses. We humans do this all the time we call it gambling.
My sage advice, trust them all but cut the card and anytime you see the word adjusted run away the dice are loaded.

jorgekafkazar

KR says: (1) You are attempting to fit trends to 8-12 year periods, when a statistical analysis of the data variance indicates that a minimum of 17 years is needed to establish a linear trend with any confidence (Santer et al. 2011).
Climatologists are making this up as they go along, and Santer’s new 17-year meme is just more of the same. Nothing sacred about it. The “required minimum period” jumps around to suit Warmistas latest failure to prove anything.
(2) You are then using these very short periods to attempt to fit a multiple-step set of changes, much more complex than a linear fit, and hence requiring even more data to establish confidence.
Each fit matches both the physics of ENSO and the data.
Your conclusions of a multiple-step set of changes is [sic] simply not supportable with the small set of data you have used.
If so, then neither are the IPCC’s.
…Looking at the temperature record against the range of the models shows that >95% of the observations are within the model range. That’s not bad at all.
No, not bad. Atrocious. The models are so imprecise that they demonstrate only that the IPCC might hit a mouse with a shotgun from ten feet away. The latest data diverge significantly from the IPCC models. Any divergence falsifies the models. No causation has been proven. You lose.

Alan Statham

Smokey: I refuted it, yes. Read again. I also criticised the capitalisation, yes.

AusieDan

KR
I suggest that you look at the East Pacific SST anomolies chart which show no trend over 30 years.
Then look again at the Rest of the World SST chart.
If you cannot see three flat periods jerked up by El Ninos, then you don’t have much experience in charting. I suggest that you go away and gets some by trading Stocks & Commodities, then come back and think some more.
As to using the range from 58 different computer model runs.
Well really!
You could fit an ocean liner within the bounds of many different computer runs based on different assumptions.
Anybody with any knowledge of charting knows that the IPCC models have been trained on the rising wave from 1976 to 2000 (or so).
It was not designed to model reality but to project a short trend into the future to produce a desided effect.
Yes in reality even 30 years is far, far too short a time to beging to determine long term trends.
Finally as the climate is chaotic, all attempts to project future values are doomed to failure.
Forecasting the temperature, let alone the entire climate in the year 2100 is just for laughs.
Bob has just pointed out that the IPCC cannot even model the past with any accuracy.
That is because very little is as yet known about the climate and the IPCC is handicapped by working on from the basis of an ideology rather than from observations.

Rex

>> In short, with the latest and greatest Sea Surface Temperature data, the
>> multi-model mean (the forced component of the models) only simulates the
>> observed rate of temperature change during the last 24 years of the 20thCentury.
I assume you mean … :
> In short, with the latest and greatest Sea Surface Temperature data, the
> multi-model mean (the forced component of the models) simulates the observed
> rate of temperature change only during the last 24 years of the 20thCentury.
Never mind. If I was to comment on every misplaced ‘only’ in WUWT posts
I would be a constant visitor, and a perpetual irritant.
From one who has only been in the market research business for 40 years.

Arno Arrak

First thing I have to tell you Bob is that the jagged appearance of the temperature curve is real. The same peaks and valleys are present in all temperature curves. They contain information and must not be treated as noise in any averaging process.The peaks are all El Nino peaks, the valleys are La Ninas, and together they form the ENSO oscillation. ENSO has been with us since the Isthmus of Panama rose from the sea and is guaranteed to be part of our climate future. The basic oscillation is of ocean water along the equator in the Pacific that starts out as a wave train but is randomly influenced by oceanic conditions. This accounts for the observed departure from regularity and because of this it is impossible to model. The locations of the El Nino peaks are important when it comes to determining the so-called “volcanic cooling.” Whether this “cooling” by a volcano can be observed or not depends upon the timing of the eruption with reference to the phase of ENSO. If a volcano erupts just when a La Nina phase of ENSO is beginning that La Nina is appropriated to the volcano as its expected volcanic cooling. But in actual fact the hot aerosols from the eruption go straight up into the stratosphere and warm it, followed by cooling a couple of years later. As an example, Pinatubo eruption was followed by the 1992 La Nina which was quickly pronounced to be caused by its volcanic cooling power. But if the eruption takes place when a La Nina has bottomed out and an El Nino is beginning to form the eruption is not followed by any trace of cooling. This is what happened to El Chichon. Had you bothered to read my book you would know this by now. It is apparent that you did not. Self et al. who originally assigned the 1992 El Nino to Pinatubo cooling knew about lack of El Chichon cooling but simply ignored it. It was enough for them that both Pinatubo and Gunung Agung were followed by cooling. If you look at figure 1 you see that both Pinatubo and Gunung Agung are followed by a La Nina while El Chichon sits there at the low point of a La Nina and is followed by an El Nino. Best pontificated that in the period 1991 to 1993 Pinatubo cooling effect was stronger than the opposite, warming effects of the El Nino event or anthropogenic greenhouse gases. This, of course, is wrong. In so doing he shows ignorance of the fact that there was no El Nino event scheduled for that slot because Pinatubo erupted at the El Nino peak and from that point on the La Nina formation took over. You can trace these relationships to every known volcano for which cooling or otherwise is reported. But these model-makers have their own huge theory that allows them calculate volcanic cooling out of nothing for all of the 58 global temperature simulations they show in figure 1. Their average curve has cooling after every eruption including El Chichon. Plus, now they even have volcano-adjusted sea surface temperatures that that are purely imaginary. As to their various linear trends, these are worthless. There really are linear trends but you don’t find them by casting around at random. There are actually two linear trends in the satellite era, one in the eighties and nineties, and one beginning with the new year. Check them out in my figure 15. And while you have the book out check out figures 8 to 10 also for volcanic cooling.

KR says: “You are attempting to fit trends to 8-12 year periods, when a statistical analysis of the data variance indicates that a minimum of 17 years is needed to establish a linear trend with any confidence (Santer et al. 2011).”
Santer et al included the 1982/83, the 1986/87/88 and 1997/98 El Nino events in their evaluation . They are excluded in mine, if you haven’t noticed.
You continued, “Your conclusions of a multiple-step set of changes is simply not supportable with the small set of data you have used.”
Satellite-era SST data is only available since November 1981. That’s 30 years. And if you can’t see the “multiple-step set of changes” in the data presented in this post, maybe you need to refer to the posts that are linked that include detailed discussions so that you can understand what causes them.

John F. Hultquist

KR says:
December 27, 2011 at 5:20 pm

. . . cites Santer
I’ll see your Santer and raise you a Rutherford:
Ernest Rutherford is quoted as saying “If your result needs a statistician then you should design a better experiment.”
————————————————————–
Mary Turner says:
December 27, 2011 at 5:21 pm

I’ll try to make this simple.
Water in a certain part of the ocean gets warm (hot, temperature goes up).
Something happens:
Causing warmth in the water to move into the air. (The water cools, the air warms.)
You can look this up:
{Heat (noun): The energy transferred from a high-temperature system to a lower-temperature system is called heat. Heat is never regarded as being stored within a system. Like work, it exists only as energy in transit from one system to another or between a system and its surroundings.}
So while the wording of your question rises a doubt as to what you intended by it – Yes, it seems El Nino does put energy in transit, thus, creating heat.

Alan Statham says: “Either all El Niños cause this effect, or it’s a mere artefact of the way you are looking at the data. From the fact that Earth’s temperature historically has not gone up every time there is an El Niño event, we can easily deduce which option is correct.”
Obviously, you did not read the posts linked under the heading of ADDITIONAL NOTES ABOUT THE SEA SURFACE TEMPERATURE COMPARSIONS.

andy says: “Some of your trend lines are drawn over fairly short periods. If you go even shorter they change again, wildly in some cases. Does the process you have applied seem a bit arbitrary ?”
Not at all. The bases for the periods are explained in the post.

The problem is more subtle than described by Mr. Tisdale. As he points out, the IPCC raises the question of the reliability of “the models used to make projections of future climate change.” This question raises the additional question of the semantics of “reliable” and “reliability.”
The IPCC’s methodology is drawn from the field of ensemble forecasting, wherein “reliable” is defined without ambiguity. That the forecasts of a model are “reliable” implies that the predicted probabilities of observed events match the associated relative frequencies in a specified statistical sample. Contrary to what one might think, the “reliability” is a binary variable that takes on the values “reliable” and “unreliable.”
Whether or not the IPCC’s models are “reliable” is necessarily indeterminate because:
* while these models make projections, they do not make predictions (aka forecasts) and
* a statistical sample is not referenced by the IPCC’s argument.
Nonetheless, a number of folks believe it to be determined that the IPCC’s models are reliable; among them is the IPCC itself. These folks confuse the idea that is referenced by the word “projection” with the idea that is referenced by the word “prediction” (aka, “forecast”). Folks who are confused in this manner understand that a comparison of a model projection (such as the ensemble mean) to a global temperature time series (such as the HADCRUT3) suffices for the purpose of establishing the reliability of models but this understanding is inconsistent with the semantics of “reliability” in the field of ensemble forecasting.
A number of folks believe it to be determined that the IPCC’s models are unreliable; among these folks is Mr. Tisdale. However, like the folks who believe it to be determined that the IPCC’s models are reliable, the latter folks confuse the concept that is referenced by “projection” with the concept that is referenced by “prediction.” In reality, we can’t determine the reliability of the IPCC models but if we confuse the idea that is referenced by the word “projection” with the idea that is referenced by the word “prediction” it can seem as though we can do so.

KR

AusieDan“I suggest that you look at the East Pacific SST anomolies chart which show no trend over 30 years.”
I would suggest that you look at the global changes, both SST and LST (land surface temperature) anomalies: http://en.wikipedia.org/wiki/Surface_temperature_record#Spatial_variability, and in particular in relation to your remark http://en.wikipedia.org/wiki/File:NOAA_Ocean.svg. It certainly does not show a series of step changes.
As many people have noted, if you pick small enough areas, or short enough time frames (as Bob Tisdale has done here), you can pick out any trend you like – except that it’s a small bit of the noise, not the trend.

jorgekafkazar“Climatologists are making this up as they go along, and Santer’s new 17-year meme is just more of the same. Nothing sacred about it. The “required minimum period” jumps around to suit Warmistas latest failure to prove anything.”
Really? What is your statistical basis for stating this? Short term noise jumps all over the place – but given sufficient time an underlying trend can be identified with some certainty (a 95% chance that the null hypothesis does not hold, as generally accepted in all fields of science). Can you show where Santer et al 2011 made their math errors in demonstrating that 17 years is a minimum requirement?
Because otherwise – that sounds like a great waving of arms…

In regards to ‘step-functions’ – identifying a linear trend requires enough data to provide a slope and offset: identifying 2 variables. A three-level step-function, on the other hand, requires five different slopes: 10 variables. And hence requires a great deal more data to identify with any certainty. A 4 year, a 9 year, and a 12 year set of flat trends? I think you could (cherry)pick multiple 4, 9, and 12 year periods from the data and get any slope you wanted.

andy says: “In other words, you may be getting lost in the trees and missing the overall forest ? Just a thought, I’m still a skeptic, but only just. The IPCC graph seems reasonable at the forest level.”
The visual noise of the ensemble member data (the yellow curves) in the IPCC graph hide the fact that the forced component of the models (the model mean) fails to capture the rise in surface temperature during the early warming period. Here’s a copy of that IPCC graph with the noise reduced:
http://i41.tinypic.com/n5n04y.jpg
And here it is again with the warming and flat temperature periods isolated:
http://i39.tinypic.com/11wasmt.jpg
Regards

Jon

The basis for all the models is the UN’s climate convention, UNFCCC. That climate convention was politically established during the Rio conference in 1992.
The models are used by IPCC because they are conform to the politically established UNFCCC. They are not conform to the reality, unless you do UNFCCC conform “measurements” of reality.

Theo Goodwin

Bob Tisdale says:
December 27, 2011 at 6:45 pm
“Mary Turner says: “So, El Nino creates heat? That is moronic.”
Obviously, Mary Turner, you believe ENSO is an index and not a process. In other words, you haven’t a clue what ENSO represents. I anticipated comments like yours, which was why I provided a link to a post that introduces readers to the process of ENSO…”
One of the great divides between Warmists and their critics is the belief in natural processes. Warmists believe that ENSO is an index and not a natural process. Of course, they have to treat it as an index because their science consists entirely of data points and statistics. If they admitted that ENSO is a natural process then they would admit that they need some well-confirmed physical hypotheses to describe it. But such views go against the Warmist religion. They believe that the only natural process worthy of climate science is the radiation balance between Earth and Sun.
One of Mr. Tisdale’s great contributions to this debate is his description of ENSO. Read it here: http://bobtisdale.wordpress.com/2010/08/08/an-introduction-to-enso-amo-and-pdo-%e2%80%93-part-1/

sceptical

Based on the posts by Mr. Tisdale, it seems the IPCC’s ocean-atmosphere climate models have simulated global surface temperatures over the 20th Century very well. Thank you for the posts.

JPeden

KR says:
December 27, 2011 at 5:20 pm
Looking at the temperature record against the range of the models shows that >95% of the observations are within the model range. That’s not bad at all.
Yes, the Models have gotten about as close to Saying Nothing At All as they can get, by making CO2 = AGW “consistent with” everything that has happened as well as with everything that will happen. Therefore, they’ve informed us that “What has happened has happened, and what will happen will happen!” But if they’d said nothing at all, that would have been even better!

ferdberple

David A. Evans says:
December 27, 2011 at 4:24 pm
Try pre-heating an oven to 200°C then opening it to put in a stew.
Agreed. Global average temperatures without humidity are meaningless. There is can be more energy in cool moist air than warm dry air, so temperature on its own is meaningless. If temperatures are rising while humidity is falling, the the earth could actually be cooling.

David L

The government should require that the IPCC add a discaimer to the bottom of their document, in small print “Past performance is no guarantee of future results. ” as they do with any stock market analysis.

Richard111

JPeden says:
December 27, 2011 at 10:37 pm
Indeed. Would be interesting if they would start a model run in say 1970 with 1970 climate conditions for input and check how well the output for 2000 agrees with 2000 climate conditions.
A test like this could be used to assign a confidence factor to each model. Of course they would have to release the model code for independant verification. Unlikely I suppose. (someone will find something wrong with it) /sarc