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CO_2 seasonal variation and global change: Test global warming from another point of view

Research in Cold and Arid Regions 2017年第1期9卷 46-53页

作者： XiuMing Liu JiaSheng Chen School of Geographical Sciences Fujian Normal University Department of Environment and Geography Macquarie University

CO2 and temperature records at mauna loa, Hawaii, and other observation stations show that the correlation between CO2 and temperature is not significant. These stations are located away from big cities, and in various latitudes and hemi-spheres. But the correlation is significant in global mean data. Over the last five decades, CO2 has grown at an accelerating rate with no corresponding rise in temperature in the stations. This discrepancy indicates that CO2 probably is not the driving force of temperature change globally but only locally （mainly in big cities）. We suggest that the Earth＇s atmospheric concentration of CO2 is too low to drive global temperature change. Our empirical perception of the global warming record is due to the urban heat island effect： temperature rises in areas with rising population density and rising industrial activity. This effect mainly occurs in the areas with high population and intense human activities, and is not representative of global warming. Regions far from cities, such as the mauna loa highland, show no evident warming trend. The global monthly mean temperature calculated by record data, widely used by academic researchers, shows R2=0.765, a high degree of correlation with CO2 . However, the R2 shows much less significance （mean R2=0.024） if calculated by each record for 188 selected stations over the world. This test suggests that the inflated high correlation between CO2 and temperature （mean R2=0.765-0.024=0.741） used in reports from the Intergovernmental Panel on Climate Change （IPCC） was very likely produced during data correction and processing. This untrue global monthly mean temperature has created a picture： human emission drives global warming.

关键词： CO2 mauna loa Hawaii seasonal variations greenhouse effect global warming

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