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| Excellent Graphic Demonstrating Climate Change Timeline | |
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| Tweet Topic Started: Dec 18 2016, 02:39 AM (853 Views) | |
| ImaHeadaU | Dec 18 2016, 06:40 AM Post #21 |
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Fire & Ice Senior Diplomat
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Berton, Until you provide some names or a link, we have only your word that this graph is based on "empirical data." What is more we don't know how much of the globe is represented or whether the data is accurate. There have been many misleading reports based on bad satellite generated data. Since these satellites rarely pass over the same spots at the same distance twice, the temperature records have been problematic. |
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| Berton | Dec 18 2016, 06:56 AM Post #22 |
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Thunder Fan
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Here is 38 years of empirical data clearly showing a relationship between the satellite temperature and the rate of change of atmospheric CO2 concentration at the Mauna Loa Observatory. Figure 1. Mauna Loa Observatory Figure 1 shows the monthly lower tropospheric satellite temperature for the Tropics-Land component in blue and the annual change in CO2 concentration in red. The obvious correlation between the two raises the possibility that there may be some common causal factor whereby the temperature drives the rate of change of CO2 concentration. It is not possible for the rate of change of CO2 to cause the temperature level as a time rate of change does not define a base. For example a rate of 2 ppm per annum could be from 0 to 2 ppm in 12 months, 456 to 458 ppm in 12 months or any other pair of numbers that differ by 2. Note that the satellite temperature data is supplied as a residual after removal of the estimated seasonal variation. This makes it comparable to the annual rate of change of CO2 concentration as taking the annual rate eliminates the seasonal variation. Calculation of the Ordinary Linear Regression between the two time series gave a correlation coefficient of 0.65 from the 448 monthly data pairs. Detrending of the time series in order to determine the statistical significance gave a correlation coefficient of 0.56 with 446 degrees of freedom. However the Durbin-Watson test of the time series gave a value of 1.08 indicating positive autocorrelation which means that Ordinary Linear Regression is inapplicable. The autocorrelation was estimated to be 0.53. When applied to the transformed time series, that is, applying a First Order Autoregressive Model, it resulted in a correlation coefficient of 0.25 with 445 degrees of freedom and a t statistic of 5.38, implying an infinitesimal probability that the coefficient is equal to zero from a two-sided t-test. Applying a First Order Autoregressive Model to the Tropics-Ocean component of the satellite temperature compared to the annual change in CO2 concentration gave a correlation coefficient of 0.14 with 445 degrees of freedom and a t statistic of 3.06, implying a probability of 0.2% that the coefficient is equal to zero from a two-sided t-test. It follows that this synthesis of empirical data conclusively reveals that CO2 has not caused temperature change over the past 38 years but that the rate of change in CO2 concentration may have been influenced to a statistically significant degree by the temperature level. Note that it is not possible for a rise in CO2 concentration to cause the temperature to increase and for the temperature level to control the rate of change of CO2 concentration as this would mean that there was a positive feedback loop causing both CO2 concentration and temperature to rise continuously and the oceans would have evaporated long ago. Support for this thesis is seen in a statistical analysis of the monthly CO2 concentration with respect to the lower tropospheric temperature for Macquarie Island in the Southern Ocean at Latitude 54̊ 29ʹ South, Longitude 158̊ 58ʹ East. Applying a First Order Autoregressive Model to the various components of the temperature, Global, Southern Hemisphere, Tropics, and Southern Extension and their Land and Ocean components gave correlation coefficients ranging from a minimum of 0.01 for 284 degrees of freedom, t statistic 0.15, probability of zero correlation 88% for the Southern Hemisphere zone, 90̊S to 0̊, to a maximum of 0.55, 284 deg. of free., t statistic 10.97, infinitesimal probability of zero correlation for the Tropics temperature zone, 20̊S to 20̊N. This explains the well known fact that CO2 change lags temperature change over a large time range. Ice core data has revealed that the cycle of ice ages and interglacial warm periods shows CO2 change lagging temperature change by several centuries to more than a millennium while modern CO2 and temperature data shows lags of 9 to 12 months, Humlum et el., 2013 [1]. Cross correlation of annual changes in each of CO2 concentration at Mauna Loa and satellite lower tropospheric Tropics – Land temperature showed that CO2 change lagged temperature change by 5 months. As temperature controls the rate of change of CO2 concentration, local maxima in the CO2 rate must correspond to temperature maxima which, mathematically, must occur after the maxima in the rate of change of temperature. Likewise the CO2 concentration maxima must post-date the maxima in the CO2 rate and thus post-date the corresponding temperature maxima. Put simply, CO2 does not cause global warming. Still don't understand? That is the question, do you even understand what you are trying to discuss? Do you understand the mathematics used? |
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| Jim Miller | Dec 18 2016, 07:03 AM Post #23 |
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Fire & Ice Senior Diplomat
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I don't think he gets it, Berton. |
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| Neutral | Dec 18 2016, 07:12 AM Post #24 |
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Fire & Ice Senior Diplomat
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I don't know why you even bother. |
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| Stoned | Dec 18 2016, 07:12 AM Post #25 |
Fire & Ice Senior Diplomat
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(Yawn) According to Dr. Michael Mann (Penn State), the satellite temperature record has actually been subject to more adjustments than the surface record. Mann also states that the global satellite temperature record has been shown to have a bias of showing too little warming. Studies have shown that satellite data was not properly interpreted. Atmospheric friction slows satellites down, causing them to lose altitude (1 km loss of height per year). In order to derive atmospheric temperature, scientists need to know the altitude of the satellite. Without the correct altitude, the temperature results can become distorted. Satellite drift can also cause problems. Temperatures that were earlier analyzed at 2pm where a few years later being analyzed at 6pm, which made it look like there was cooling, when in fact there was no cooling. UAH corrections were made, but still underestimated the warming, according to Dr. Kevin Trenberth (NCAR) According to Dr. Andrew Dessler of Texas A&M, satellites actually measure radiance and not temperature. In order to determine temperature from the radiance the UAH/RSS team's use a "retrieval algorithm", which is essentially a model, according to Dessler. Unfortunately, that model has repeatedly been shown to be in error. One reason why satellite measured anomalies are significantly lower than the surface measured temperatures is the fact that the satellite temperatures are measured against the 1981-2010 mean, whereas the NASA surface database is measured against the lower 1951-1980 mean and the NOAA database is measured against the 20th century average. |
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| ImaHeadaU | Dec 18 2016, 08:44 AM Post #26 |
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Fire & Ice Senior Diplomat
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Do you understand that you haven't provided an author or link to the material you are posting? How are we expected to believe the data is accurate? |
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| Neutral | Dec 18 2016, 08:48 AM Post #27 |
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Fire & Ice Senior Diplomat
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| Jim Miller | Dec 18 2016, 09:33 AM Post #28 |
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Fire & Ice Senior Diplomat
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Why care? |
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| ImaHeadaU | Dec 18 2016, 09:43 AM Post #29 |
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Fire & Ice Senior Diplomat
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What does Mr. Trump have to do with the topic of this thread? |
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| Neutral | Dec 18 2016, 09:47 AM Post #30 |
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Fire & Ice Senior Diplomat
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LOL That is Jim's signature Ima. DUH |
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