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Post by steve on Apr 13, 2013 20:14:16 GMT
magellan, You are making my point magellan. The document referred to the seasonal forecast. Both the decadal and seasonal forecasts are somewhat experimental. That said, the seasonal forecast does have some skill. The idea that the Met Office would allow the seasonal forecasters to fiddle with the model to fix the seasonal forecast, when the fiddling could impact on the Met Office's bread-and-butter short term forecasts, is inane. To say Met O doesn't fiddle with their models is completely laughable. What you're saying is their forecasts will continue to be wrong forever. Why do they continually need larger computers if they don't change anything? Stop being an apologist for Met O. I didn't say they don't fiddle with the model. The model, though, is fiddled primarily to fix the weather forecast, because the weather forecast is where the Met Office earns its money. The climate model is derived from the weather model.
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Post by sigurdur on Apr 14, 2013 19:03:53 GMT
Was thinking about climate models as the weather models are missing the speed of the storm around here. A slight change in one parameter changes the whole outlook.
Climate models are much the same, but on longer time scales. We can observe the failure of a weather model in a few hours, it may take 10's of years to observe the failure of a climate model.
That is the bad thing about actual changes in climate. To verify takes decades....
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Post by sigurdur on Apr 16, 2013 19:50:29 GMT
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Post by trbixler on Apr 18, 2013 1:13:29 GMT
Gets deep quickly but finishes on a high note kiss the models goodby use your thermometer. Instruments trump models every time. "On the scales of warming worry magnitudes– Part 2" "Please note that I am not using any of ‘Mike’s tricks’ in Graph 2 where Y-axis range is identical to the Y-axis range in Graph1. Since Graph 2 is created by averaging data in Graph 1 it has to be displayed using the same temperature ranges to demonstrate what happens when 730-dimensional space is reduced to a single number by ‘averaging-to-death’ approach. BTW, I am not sure whether anyone has realised that not only a paper that analyse thermometer data has not been written by AGW community, but also not a single paper has been written that validates conversion of Graph 1 to Graph 2 – NOT A SINGLE PAPER! I have quite good idea, actually I am certain why that is the case but will let reader make his/her mind about that most unusual approach to inventing new proxy-thermometer without bothering to explain to wider scientific community validity of the whole process. The main reason for displaying the two graphs above is to help me explain the main objective of my paper, which is to test whether the Hockey stick scenario of global warming, which was detected in theoretical space of annual averages, can be found in the physical reality of the Earth atmosphere, i.e. thermometer data. The whole concept of AGW hypothesis is based on idea that the calculated numbers are real and thermometer data are not, while the opposite is true. Graph 1 is reality and Graph 2 is a failed attempt to use averages in order to represent reality." link Daunting Math from WUWT
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Post by trbixler on Apr 18, 2013 13:20:45 GMT
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Post by cuttydyer on May 17, 2013 14:08:15 GMT
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Post by cuttydyer on Jun 7, 2013 11:57:56 GMT
Dr Roy Spencer (former Senior Scientist for Climate Studies at NASA’s Marshall Space Flight Center) plots 73 Climate Models vs. Measurements, Running 5-Year Means. Link
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Post by icefisher on Jun 9, 2013 6:52:56 GMT
Dr Roy Spencer (former Senior Scientist for Climate Studies at NASA’s Marshall Space Flight Center) plots 73 Climate Models vs. Measurements, Running 5-Year Means. LinkLooks to me they tried at least 72 times and missed all 72 times. Seems likely they all have the same error. The Gore Effect!
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Post by steve on Jun 9, 2013 20:23:30 GMT
I think you have to be a little wary of these model-data comparisons from Spencer and Christy.
True the most of the model projections are diverging from the observations. Whether this is due to natural variability, unknown changes in forcings or due to model error is not clear to modelers - though clearly sceptics will assume it is the latter.
So diversion in other metrics is not surprising. That said, the Christy graphs are pretty skewed and don't mention the fact that there is an awful lot of difference and uncertainty within the satellite and radiosonde data.
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Post by sigurdur on Jun 10, 2013 3:54:36 GMT
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Post by sigurdur on Jun 10, 2013 3:57:17 GMT
I think you have to be a little wary of these model-data comparisons from Spencer and Christy. True the most of the model projections are diverging from the observations. Whether this is due to natural variability, unknown changes in forcings or due to model error is not clear to modelers - though clearly sceptics will assume it is the latter. So diversion in other metrics is not surprising. That said, the Christy graphs are pretty skewed and don't mention the fact that there is an awful lot of difference and uncertainty within the satellite and radiosonde data. Steve: The error bars and the differences between the data sets are small enough that they do not overcome the 2 sigma model deviation. I posted a paper above that shows how the models do such a poor job on a few critical areas. There is no corruption involved here, just a total, as of yet, lack of understanding that can be incorporated into the models to help them perform better.
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Post by icefisher on Jun 10, 2013 8:42:42 GMT
I think you have to be a little wary of these model-data comparisons from Spencer and Christy. True the most of the model projections are diverging from the observations. Whether this is due to natural variability, unknown changes in forcings or due to model error is not clear to modelers - though clearly sceptics will assume it is the latter. So diversion in other metrics is not surprising. That said, the Christy graphs are pretty skewed and don't mention the fact that there is an awful lot of difference and uncertainty within the satellite and radiosonde data. You appear to incorrectly assume that the models missing natural variability, or being ignorant of forces that can change climate are mutually exclusive from the models being wrong. The reason why does not matter the models are in error! There has never been a kicker in professional football who has missed 72 consecutive field goals. Thats probably due to the fact kickers get fired long before approaching such a level of futility. . . .not because there are no bad kickers.
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Post by steve on Jun 10, 2013 12:52:50 GMT
I think you have to be a little wary of these model-data comparisons from Spencer and Christy. True the most of the model projections are diverging from the observations. Whether this is due to natural variability, unknown changes in forcings or due to model error is not clear to modelers - though clearly sceptics will assume it is the latter. So diversion in other metrics is not surprising. That said, the Christy graphs are pretty skewed and don't mention the fact that there is an awful lot of difference and uncertainty within the satellite and radiosonde data. You appear to incorrectly assume that the models missing natural variability, or being ignorant of forces that can change climate are mutually exclusive from the models being wrong. The reason why does not matter the models are in error! There has never been a kicker in professional football who has missed 72 consecutive field goals. Thats probably due to the fact kickers get fired long before approaching such a level of futility. . . .not because there are no bad kickers. I should correct the appearance and say that all three aspects are probably at work. So adding to those aspects if one also ignores or hides errors in the observations, and is selective about start-points, then one can make quite a compelling image. Imagine if a climate scientist had averaged two different datasets and hidden the fact that they differed by claiming that the average was the ground-truth that proved the sceptics' belief was wrong? Sceptics (and other climate scientists) would be up in arms.
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Post by duwayne on Jun 10, 2013 14:34:26 GMT
You appear to incorrectly assume that the models missing natural variability, or being ignorant of forces that can change climate are mutually exclusive from the models being wrong. The reason why does not matter the models are in error! There has never been a kicker in professional football who has missed 72 consecutive field goals. Thats probably due to the fact kickers get fired long before approaching such a level of futility. . . .not because there are no bad kickers. I should correct the appearance and say that all three aspects are probably at work. So adding to those aspects if one also ignores or hides errors in the observations, and is selective about start-points, then one can make quite a compelling image. Imagine if a climate scientist had averaged two different datasets and hidden the fact that they differed by claiming that the average was the ground-truth that proved the sceptics' belief was wrong? Sceptics (and other climate scientists) would be up in arms. I'd also be interested in seeing the individual datasets. I'd like to know if he is hiding something. I can't imagine the warmists ever combining the model predictions into an ensemble and building their case based using such questionable practices.
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Post by cuttydyer on Jun 10, 2013 15:05:49 GMT
Prof. Murry Salby’s Presentation In Hamburg: Climate “Model World” Diverges Starkly From “Real World”. "Prof. Murry Salby, climate scientist at Macquarie University of Sydney, made a presentation in Hamburg on April 18th as part of a European tour. Prof. Salby is author of the textbook Physics of the Atmosphere and Climate (Cambridge University Press) and Fundamentals of Atmospheric Physics (Academic Press) and is renowned worldwide as an astrophysicist." Model world (left) vs real world (right). video presentation of Murry Salby in Hamburg in April: The points of Salby’s presentation lead to the following implications: - In the Real World global temperature is not controlled exclusively by CO2, as it is in the Model World. - In significant part, however, CO2 is controlled by Global Temperature, as it is in the Proxy Record. Report from notrickszone : notrickszone.com/2013/06/10/murry-salbys-presentation-in-hamburg/
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