Global Warming. Fact or grossly exaggerated??

[basketcase]

Groggy, how can you say that when anthropogenic climate change hinges on global temperatures and natural variability of the global coupled climate models?? The TAR keeps showing multi-model results for future changes in climate, but since TAR is an unprecedented internationally coordinated climate change experiment thats been performed by over 23 models from around the world, how can you get a variable output of surface temperatures versus atmospheric temperatures??

Can you please answer that question for us??

I can give it a stab but the answer relies on science so you may not like it.

Models are different from each other mainly because of the 'environmental sensitivity' put into the model. This means that scientists project the impact of the increasing heat stored on earth differently. What this means is that different models predict the effects of climate change differently. For example we all know that excess heat will cause a diminishing of the arctic ice cap and the ice cap will create a feedback loop because of the changes in albedo comparing the ice to water. Where the models differ is that a small difference in the size of the ice cap will create diverging predictions.

The same issues apply to the effects of forest fires, changes to ocean and air currents, the amount of heat stored in the oceans, volcanic activity, and pretty much any other factor involved. Scientists creating the model set the sensitivity for each factor as their experience best sees them but as differences less than 1% in the actual sensitivity can cause a wide range of predictions.

Of course we are talking about science so environmental scientists are constantly comparing predicted values to actual and refining their models as they learn more. As MF said, science is based on evidence and as more evidence is gathered, the models are adjusted. If the models were as far off as MF states, they would have been thrown out and not refined.

 

[blackrock13]

Groggy, how can you say that when anthropogenic climate change hinges on global temperatures and natural variability of the global coupled climate models?? The TAR keeps showing multi-model results for future changes in climate, but since TAR is an unprecedented internationally coordinated climate change experiment thats been performed by over 23 models from around the world, how can you get a variable output of surface temperatures versus atmospheric temperatures??

Can you please answer that question for us??

How about we answer it this way? From http://www.ipcc.ch/publications_and_.../ch8s8-es.html

Climate models are based on well-established physical principles and have been demonstrated to reproduce observed features of recent climate (see Chapters 8 and 9) and past climate changes (see Chapter 6). There is considerable confidence that Atmosphere-Ocean General Circulation Models (AOGCMs) provide credible quantitative estimates of future climate change, particularly at continental and larger scales. Confidence in these estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation). This summary highlights areas of progress since the TAR:

Enhanced scrutiny of models and expanded diagnostic analysis of model behaviour have been increasingly facilitated by internationally coordinated efforts to collect and disseminate output from model experiments performed under common conditions. This has encouraged a more comprehensive and open evaluation of models. The expanded evaluation effort, encompassing a diversity of perspectives, makes it less likely that significant model errors are being overlooked.
Climate models are being subjected to more comprehensive tests, including, for example, evaluations of forecasts on time scales from days to a year. This more diverse set of tests increases confidence in the fidelity with which models represent processes that affect climate projections.
Substantial progress has been made in understanding the inter-model differences in equilibrium climate sensitivity. Cloud feedbacks have been confirmed as a primary source of these differences, with low clouds making the largest contribution. New observational and modelling evidence strongly supports a combined water vapour-lapse rate feedback of a strength comparable to that found in General Circulation Models (approximately 1 W m–2 °C–1, corresponding to around a 50% amplification of global mean warming). The magnitude of cryospheric feedbacks remains uncertain, contributing to the range of model climate responses at mid- to high latitudes.
There have been ongoing improvements to resolution, computational methods and parametrizations, and additional processes (e.g., interactive aerosols) have been included in more of the climate models.
Most AOGCMs no longer use flux adjustments, which were previously required to maintain a stable climate. At the same time, there have been improvements in the simulation of many aspects of present climate. The uncertainty associated with the use of flux adjustments has therefore decreased, although biases and long-term trends remain in AOGCM control simulations.
Progress in the simulation of important modes of climate variability has increased the overall confidence in the models’ representation of important climate processes. As a result of steady progress, some AOGCMs can now simulate important aspects of the El Niño-Southern Oscillation (ENSO). Simulation of the Madden-Julian Oscillation (MJO) remains unsatisfactory.
The ability of AOGCMs to simulate extreme events, especially hot and cold spells, has improved. The frequency and amount of precipitation falling in intense events are underestimated.
Simulation of extratropical cyclones has improved. Some models used for projections of tropical cyclone changes can simulate successfully the observed frequency and distribution of tropical cyclones.
Systematic biases have been found in most models’ simulation of the Southern Ocean. Since the Southern Ocean is important for ocean heat uptake, this results in some uncertainty in transient climate response.
The possibility that metrics based on observations might be used to constrain model projections of climate change has been explored for the first time, through the analysis of ensembles of model simulations. Nevertheless, a proven set of model metrics that might be used to narrow the range of plausible climate projections has yet to be developed.
To explore the potential importance of carbon cycle feedbacks in the climate system, explicit treatment of the carbon cycle has been introduced in a few climate AOGCMs and some Earth System Models of Intermediate Complexity (EMICs).
Earth System Models of Intermediate Complexity have been evaluated in greater depth than previously. Coordinated intercomparisons have demonstrated that these models are useful in addressing questions involving long time scales or requiring a large number of ensemble simulations or sensitivity experiments.
Developments in model formulation
Improvements in atmospheric models include reformulated dynamics and transport schemes, and increased horizontal and vertical resolution. Interactive aerosol modules have been incorporated into some models, and through these, the direct and the indirect effects of aerosols are now more widely included.

Significant developments have occurred in the representation of terrestrial processes. Individual components continue to be improved via systematic evaluation against observations and against more comprehensive models. The terrestrial processes that might significantly affect large-scale climate over the next few decades are included in current climate models. Some processes important on longer time scales are not yet included.

Development of the oceanic component of AOGCMs has continued. Resolution has increased and models have generally abandoned the ‘rigid lid’ treatment of the ocean surface. New physical parametrizations and numerics include true freshwater fluxes, improved river and estuary mixing schemes and the use of positive definite advection schemes. Adiabatic isopycnal mixing schemes are now widely used. Some of these improvements have led to a reduction in the uncertainty associated with the use of less sophisticated parametrizations (e.g., virtual salt flux).

Progress in developing AOGCM cryospheric components is clearest for sea ice. Almost all state-of-the-art AOGCMs now include more elaborate sea ice dynamics and some now include several sea ice thickness categories and relatively advanced thermodynamics. Parametrizations of terrestrial snow processes in AOGCMs vary considerably in formulation. Systematic evaluation of snow suggests that sub-grid scale heterogeneity is important for simulating observations of seasonal snow cover. Few AOGCMs include ice sheet dynamics; in all of the AOGCMs evaluated in this chapter and used in Chapter 10 for projecting climate change in the 21st century, the land ice cover is prescribed.

There is currently no consensus on the optimal way to divide computer resources among: finer numerical grids, which allow for better simulations; greater numbers of ensemble members, which allow for better statistical estimates of uncertainty; and inclusion of a more complete set of processes (e.g., carbon feedbacks, atmospheric chemistry interactions).

Developments in model climate simulation
The large-scale patterns of seasonal variation in several important atmospheric fields are now better simulated by AOGCMs than they were at the time of the TAR. Notably, errors in simulating the monthly mean, global distribution of precipitation, sea level pressure and surface air temperature have all decreased. In some models, simulation of marine low-level clouds, which are important for correctly simulating sea surface temperature and cloud feedback in a changing climate, has also improved. Nevertheless, important deficiencies remain in the simulation of clouds and tropical precipitation (with their important regional and global impacts).

Some common model biases in the Southern Ocean have been identified, resulting in some uncertainty in oceanic heat uptake and transient climate response. Simulations of the thermocline, which was too thick, and the Atlantic overturning and heat transport, which were both too weak, have been substantially improved in many models.

Despite notable progress in improving sea ice formulations, AOGCMs have typically achieved only modest progress in simulations of observed sea ice since the TAR. The relatively slow progress can partially be exp**********d by the fact that improving sea ice simulation requires improvements in both the atmosphere and ocean components in addition to the sea ice component itself.

Since the TAR, developments in AOGCM formulation have improved the representation of large-scale variability over a wide range of time scales. The models capture the dominant extratropical patterns of variability including the Northern and Southern Annular Modes, the Pacific Decadal Oscillation, the Pacific-North American and Cold Ocean-Warm Land Patterns. AOGCMs simulate Atlantic multi-decadal variability, although the relative roles of high- and low-latitude processes appear to differ between models. In the tropics, there has been an overall improvement in the AOGCM simulation of the spatial pattern and frequency of ENSO, but problems remain in simulating its seasonal phase locking and the asymmetry between El Niño and La Niña episodes. Variability with some characteristics of the MJO is simulated by most AOGCMs, but the events are typically too infrequent and too weak.

Atmosphere-Ocean General Circulation Models are able to simulate extreme warm temperatures, cold air outbreaks and frost days reasonably well. Models used in this report for projecting tropical cyclone changes are able to simulate present-day frequency and distribution of cyclones, but intensity is less well simulated. Simulation of extreme precipitation is dependent on resolution, parametrization and the thresholds chosen. In general, models tend to produce too many days with weak precipitation (<10 mm day–1) and too little precipitation overall in intense events (>10 mm day–1).

Earth system Models of Intermediate Complexity have been developed to investigate issues in past and future climate change that cannot be addressed by comprehensive AOGCMs because of their large computational cost. Owing to the reduced resolution of EMICs and their simplified representation of some physical processes, these models only allow inferences about very large scales. Since the TAR, EMICs have been evaluated via several coordinated model intercomparisons which have revealed that, at large scales, EMIC results compare well with observational data and AOGCM results. This lends support to the view that EMICS can be used to gain understanding of processes and interactions within the climate system that evolve on time scales beyond those generally accessible to current AOGCMs. The uncertainties in long-term climate change projections can also be explored more comprehensively by using large ensembles of EMIC runs.

Developments in analysis methods
Since the TAR, an unprecedented effort has been initiated to make available new model results for scrutiny by scientists outside the modelling centres. Eighteen modelling groups performed a set of coordinated, standard experiments, and the resulting model output, analysed by hundreds of researchers worldwide, forms the basis for much of the current IPCC assessment of model results. The benefits of coordinated model intercomparison include increased communication among modelling groups, more rapid identification and correction of errors, the creation of standardised benchmark calculations and a more complete and systematic record of modelling progress.

A few climate models have been tested for (and shown) capability in initial value predictions, on time scales from weather forecasting (a few days) to seasonal forecasting (annual). The capability demonstrated by models under these conditions increases confidence that they simulate some of the key processes and teleconnections in the climate system. ............

 

[blackrock13]

........... Developments in evaluation of climate feedbacksWater vapour feedback is the most important feedback enhancing climate sensitivity. Although the strength of this feedback varies somewhat among models, its overall impact on the spread of model climate sensitivities is reduced by lapse rate feedback, which tends to be anti-correlated. Several new studies indicate that modelled lower- and upper-tropospheric humidity respond to seasonal and interannual variability, volcanically induced cooling and climate trends in a way that is consistent with observations. Recent observational and modelling evidence thus provides strong additional support for the combined water vapour-lapse rate feedback being around the strength found in AOGCMs.

Recent studies reaffirm that the spread of climate sensitivity estimates among models arises primarily from inter-model differences in cloud feedbacks. The shortwave impact of changes in boundary-layer clouds, and to a lesser extent mid-level clouds, constitutes the largest contributor to inter-model differences in global cloud feedbacks. The relatively poor simulation of these clouds in the present climate is a reason for some concern. The response to global warming of deep convective clouds is also a substantial source of uncertainty in projections since current models predict different responses of these clouds. Observationally based evaluation of cloud feedbacks indicates that climate models exhibit different strengths and weaknesses, and it is not yet possible to determine which estimates of the climate change cloud feedbacks are the most reliable.

Despite advances since the TAR, substantial uncertainty remains in the magnitude of cryospheric feedbacks within AOGCMs. This contributes to a spread of modelled climate response, particularly at high latitudes. At the global scale, the surface albedo feedback is positive in all the models, and varies between models much less than cloud feedbacks. Understanding and evaluating sea ice feedbacks is complicated by the strong coupling to polar cloud processes and ocean heat and freshwater transport. Scarcity of observations in polar regions also hampers evaluation. New techniques that evaluate surface albedo feedbacks have recently been developed. Model performance in reproducing the observed seasonal cycle of land snow cover may provide an indirect evaluation of the simulated snow-albedo feedback under climate change.

Systematic model comparisons have helped establish the key processes responsible for differences among models in the response of the ocean to climate change. The importance of feedbacks from surface flux changes to the meridional overturning circulation has been established in many models. At present, these feedbacks are not tightly constrained by available observations.

The analysis of processes contributing to climate feedbacks in models and recent studies based on large ensembles of models suggest that in the future it may be possible to use observations to narrow the current spread in model projections of climate change.

 

[groggy]

For the record, Curry's position is that we don't know what affect man-made carbon dioxide might be having -- if any -- on the climate. In any event, the bet was whether or not she backs the IPCC's reports. Her position is very clear:

http://opinion.financialpost.com/2013/09/30/ipcc-climate-global-warming/

As for the definition of "legit," it was clearly described in the bet:

If you didn't agree with that definition of "legit", you shouldn't have accepted the bet.

But you did accept it.

The terms were clear and have been met, in full. You lost.

So you really think creationists are 'legit' scientists?

 

[Moviefan-2]

So you really think creationists are 'legit' scientists?

Nice try. In the bet, the definition of "legit" -- which you accepted -- was that the climatologists are employed and conduct research at recognized universities.

All three meet the definition that you and I agreed to.

I won. You lost.

 

[AK-47]

How about we answer it this way? From http://www.ipcc.ch/publications_and_.../ch8s8-es.html

Climate models are based on well-established physical principles and have been demonstrated to reproduce observed features of recent climate (see Chapters 8 and 9) and past climate changes (see Chapter 6). There is considerable confidence that Atmosphere-Ocean General Circulation Models (AOGCMs) provide credible quantitative estimates of future climate change, particularly at continental and larger scales. Confidence in these estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation). This summary highlights areas of progress since the TAR:

Enhanced scrutiny of models and expanded diagnostic analysis of model behaviour have been increasingly facilitated by internationally coordinated efforts to collect and disseminate output from model experiments performed under common conditions. This has encouraged a more comprehensive and open evaluation of models. The expanded evaluation effort, encompassing a diversity of perspectives, makes it less likely that significant model errors are being overlooked.
Climate models are being subjected to more comprehensive tests, including, for example, evaluations of forecasts on time scales from days to a year. This more diverse set of tests increases confidence in the fidelity with which models represent processes that affect climate projections.
Substantial progress has been made in understanding the inter-model differences in equilibrium climate sensitivity. Cloud feedbacks have been confirmed as a primary source of these differences, with low clouds making the largest contribution. New observational and modelling evidence strongly supports a combined water vapour-lapse rate feedback of a strength comparable to that found in General Circulation Models (approximately 1 W m–2 °C–1, corresponding to around a 50% amplification of global mean warming). The magnitude of cryospheric feedbacks remains uncertain, contributing to the range of model climate responses at mid- to high latitudes.
There have been ongoing improvements to resolution, computational methods and parametrizations, and additional processes (e.g., interactive aerosols) have been included in more of the climate models.
Most AOGCMs no longer use flux adjustments, which were previously required to maintain a stable climate. At the same time, there have been improvements in the simulation of many aspects of present climate. The uncertainty associated with the use of flux adjustments has therefore decreased, although biases and long-term trends remain in AOGCM control simulations.
Progress in the simulation of important modes of climate variability has increased the overall confidence in the models’ representation of important climate processes. As a result of steady progress, some AOGCMs can now simulate important aspects of the El Niño-Southern Oscillation (ENSO). Simulation of the Madden-Julian Oscillation (MJO) remains unsatisfactory.
The ability of AOGCMs to simulate extreme events, especially hot and cold spells, has improved. The frequency and amount of precipitation falling in intense events are underestimated.
Simulation of extratropical cyclones has improved. Some models used for projections of tropical cyclone changes can simulate successfully the observed frequency and distribution of tropical cyclones.
Systematic biases have been found in most models’ simulation of the Southern Ocean. Since the Southern Ocean is important for ocean heat uptake, this results in some uncertainty in transient climate response.
The possibility that metrics based on observations might be used to constrain model projections of climate change has been explored for the first time, through the analysis of ensembles of model simulations. Nevertheless, a proven set of model metrics that might be used to narrow the range of plausible climate projections has yet to be developed.
To explore the potential importance of carbon cycle feedbacks in the climate system, explicit treatment of the carbon cycle has been introduced in a few climate AOGCMs and some Earth System Models of Intermediate Complexity (EMICs).
Earth System Models of Intermediate Complexity have been evaluated in greater depth than previously. Coordinated intercomparisons have demonstrated that these models are useful in addressing questions involving long time scales or requiring a large number of ensemble simulations or sensitivity experiments.
Developments in model formulation
Improvements in atmospheric models include reformulated dynamics and transport schemes, and increased horizontal and vertical resolution. Interactive aerosol modules have been incorporated into some models, and through these, the direct and the indirect effects of aerosols are now more widely included.

Significant developments have occurred in the representation of terrestrial processes. Individual components continue to be improved via systematic evaluation against observations and against more comprehensive models. The terrestrial processes that might significantly affect large-scale climate over the next few decades are included in current climate models. Some processes important on longer time scales are not yet included.

Development of the oceanic component of AOGCMs has continued. Resolution has increased and models have generally abandoned the ‘rigid lid’ treatment of the ocean surface. New physical parametrizations and numerics include true freshwater fluxes, improved river and estuary mixing schemes and the use of positive definite advection schemes. Adiabatic isopycnal mixing schemes are now widely used. Some of these improvements have led to a reduction in the uncertainty associated with the use of less sophisticated parametrizations (e.g., virtual salt flux).

Progress in developing AOGCM cryospheric components is clearest for sea ice. Almost all state-of-the-art AOGCMs now include more elaborate sea ice dynamics and some now include several sea ice thickness categories and relatively advanced thermodynamics. Parametrizations of terrestrial snow processes in AOGCMs vary considerably in formulation. Systematic evaluation of snow suggests that sub-grid scale heterogeneity is important for simulating observations of seasonal snow cover. Few AOGCMs include ice sheet dynamics; in all of the AOGCMs evaluated in this chapter and used in Chapter 10 for projecting climate change in the 21st century, the land ice cover is prescribed.

There is currently no consensus on the optimal way to divide computer resources among: finer numerical grids, which allow for better simulations; greater numbers of ensemble members, which allow for better statistical estimates of uncertainty; and inclusion of a more complete set of processes (e.g., carbon feedbacks, atmospheric chemistry interactions).

Developments in model climate simulation
The large-scale patterns of seasonal variation in several important atmospheric fields are now better simulated by AOGCMs than they were at the time of the TAR. Notably, errors in simulating the monthly mean, global distribution of precipitation, sea level pressure and surface air temperature have all decreased. In some models, simulation of marine low-level clouds, which are important for correctly simulating sea surface temperature and cloud feedback in a changing climate, has also improved. Nevertheless, important deficiencies remain in the simulation of clouds and tropical precipitation (with their important regional and global impacts).

Some common model biases in the Southern Ocean have been identified, resulting in some uncertainty in oceanic heat uptake and transient climate response. Simulations of the thermocline, which was too thick, and the Atlantic overturning and heat transport, which were both too weak, have been substantially improved in many models.

Despite notable progress in improving sea ice formulations, AOGCMs have typically achieved only modest progress in simulations of observed sea ice since the TAR. The relatively slow progress can partially be exp**********d by the fact that improving sea ice simulation requires improvements in both the atmosphere and ocean components in addition to the sea ice component itself.

Since the TAR, developments in AOGCM formulation have improved the representation of large-scale variability over a wide range of time scales. The models capture the dominant extratropical patterns of variability including the Northern and Southern Annular Modes, the Pacific Decadal Oscillation, the Pacific-North American and Cold Ocean-Warm Land Patterns. AOGCMs simulate Atlantic multi-decadal variability, although the relative roles of high- and low-latitude processes appear to differ between models. In the tropics, there has been an overall improvement in the AOGCM simulation of the spatial pattern and frequency of ENSO, but problems remain in simulating its seasonal phase locking and the asymmetry between El Niño and La Niña episodes. Variability with some characteristics of the MJO is simulated by most AOGCMs, but the events are typically too infrequent and too weak.

Atmosphere-Ocean General Circulation Models are able to simulate extreme warm temperatures, cold air outbreaks and frost days reasonably well. Models used in this report for projecting tropical cyclone changes are able to simulate present-day frequency and distribution of cyclones, but intensity is less well simulated. Simulation of extreme precipitation is dependent on resolution, parametrization and the thresholds chosen. In general, models tend to produce too many days with weak precipitation (<10 mm day–1) and too little precipitation overall in intense events (>10 mm day–1).

Earth system Models of Intermediate Complexity have been developed to investigate issues in past and future climate change that cannot be addressed by comprehensive AOGCMs because of their large computational cost. Owing to the reduced resolution of EMICs and their simplified representation of some physical processes, these models only allow inferences about very large scales. Since the TAR, EMICs have been evaluated via several coordinated model intercomparisons which have revealed that, at large scales, EMIC results compare well with observational data and AOGCM results. This lends support to the view that EMICS can be used to gain understanding of processes and interactions within the climate system that evolve on time scales beyond those generally accessible to current AOGCMs. The uncertainties in long-term climate change projections can also be explored more comprehensively by using large ensembles of EMIC runs.

Developments in analysis methods
Since the TAR, an unprecedented effort has been initiated to make available new model results for scrutiny by scientists outside the modelling centres. Eighteen modelling groups performed a set of coordinated, standard experiments, and the resulting model output, analysed by hundreds of researchers worldwide, forms the basis for much of the current IPCC assessment of model results. The benefits of coordinated model intercomparison include increased communication among modelling groups, more rapid identification and correction of errors, the creation of standardised benchmark calculations and a more complete and systematic record of modelling progress.

A few climate models have been tested for (and shown) capability in initial value predictions, on time scales from weather forecasting (a few days) to seasonal forecasting (annual). The capability demonstrated by models under these conditions increases confidence that they simulate some of the key processes and teleconnections in the climate system. ............

Groggy says you're mostly right

 

[Moviefan-2]

Groggy says you're mostly right

LMAO!! :thumb:

 

[blackrock13]

LMAO!! :thumb:

Except AK is mostly wrong. Considering how badly you understand the basics of the scientific method and what role a theory plays in research, as clearly shown is recent posts, it's hard to believe you have any understanding of what that summary says.

 

[AK-47]

LMAO!! :thumb:

Funny thing is if I had not called groggy out on my bullshit, he and blackidiot wouldve fallen for all the giant obfusctaed bullshit I just wrote. A second time, yes they would have!!!!

:eyebrows:

 

[groggy]

Nice try. In the bet, the definition of "legit" -- which you accepted -- was that the climatologists are employed and conduct research at recognized universities.

All three meet the definition that you and I agreed to.

I won. You lost.

Employment at a university does not make a scientist legit. Respected and peer assessed papers do. Creationists are about as legit as the flat earth society.

 

[AK-47]

how badly you understand the basics of the scientific method and what role a theory plays in research

LoL

..................

 

[Moviefan-2]

...it's hard to believe you have any understanding of what that summary says.

No, it isn't. It's easy to believe, since I didn't read it.

AK-47's point goes back to Groggy's endorsement of the gibberish. Groggy would say your post was "mostly right," even though he has no idea what it means.

 

[Moviefan-2]

Employment at a university does not make a scientist legit.

It makes a climatologist "legit" according to the terms of the bet that were set by me and that you accepted (see posts 513 and 514).

This isn't skepticalscience.com. You don't get to go back and rewrite (or "adjust") the terms of the bet after you have already lost.

The terms were clear and you accepted them. You lost.

 

[blackrock13]

No, it isn't. It's easy to believe, since I didn't read it.

AK-47's point goes back to Groggy's endorsement of the gibberish. Groggy would say your post was "mostly right," even though he has no idea what it means.

That was quite event.

 

[AK-47]

AK-47's point goes back to Groggy's endorsement of the gibberish. Groggy would say your post was "mostly right," even though he has no idea what it means

The fact he said it was "mostly right", when it was complete horseshit, was the funniest part.

I think groggy is still recovering from that one, because he hasnt come up with a single decent comeback yet

 

[blackrock13]

No, it isn't. It's easy to believe, since I didn't read it.

AK-47's point goes back to Groggy's endorsement of the gibberish. Groggy would say your post was "mostly right," even though he has no idea what it means.

Still looking where GROGGY said I was mostly right. Perhaps you can point it out.Somehow i doubt it though.

 

[AK-47]

Blackrock really needs to get laid :biggrin1:

 

[Moviefan-2]

Still looking where GROGGY said I was mostly right. Perhaps you can point it out.Somehow i doubt it though.

This has been a long thread, so perhaps you missed the joke.

Earlier in the thread, Groggy had posted some blather from the IPCC website that he didn't understand, and then dared AK-47 and I to try to explain it. After some back and forth, AK-47 posted some cut-and-paste information, interspersed with nonsense, and said it was his explanation.

It was, by AK-47's own admission, complete gibberish.

However, Groggy -- not realizing it was gibberish (AK-47 had shared the details with me privately) -- said that AK-47 had "got most of it."

 

[AK-47]

^^^^ yeah, it was "mostly right." .............. LOL.

Still waiting for groggy to bullshit his way out of that one

 

[Moviefan-2]

^^^^ yeah, it was "mostly right." .............. LOL.

Still waiting for groggy to bullshit his way out of that one

He's busy trying to weasel out of the bet that he has already lost.