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Within measurement error, all of these records paint a similar picture of temperature change and global warming. However, climate models predict carbon dioxide based greenhouse warming should result in lower atmosphere warming roughly 1.3 times higher than the surface warming. This prediction is consistent with the RSS vs. surface comparison ...
Doing this, through December 2019, the UAH linear temperature trend 1979-2019 shows a warming of +0.13 °C/decade. [7] [8] For comparison, a different group, Remote Sensing Systems (RSS), also analyzes the MSU data. From their data: the RSS linear temperature trend shows a warming of +0.208 °C/decade. [9] [10]
In an early attempt to show that climate had changed, Hubert Lamb's 1965 paper generalised from temperature records of central England together with historical, botanical, and archeological evidence to produce a qualitative estimate of temperatures in the North Atlantic region. Subsequent quantitative reconstructions used statistical techniques ...
Higher than normal temperatures are shown in red and lower then normal temperatures are shown in blue. The final frame represents the global temperatures 5-year averaged from 2014 through 2018. Scale in degree Celsius." "These calculations produce the global average temperature deviations from the baseline period of 1951 to 1980."
The following day (10 May), Jason Samenow wrote in The Washington Post that the spiral graph was "the most compelling global warming visualization ever made", [27] and, likewise, former Climate Central senior science writer Andrew Freedman wrote in Mashable that it was "the most compelling climate change visualization we’ve ever seen". [28]
The longer history of the proxy is then used to reconstruct temperature from earlier periods. Proxy records must be averaged in some fashion if a global or hemispheric record is desired. The "Composite Plus Scaling" (CPS) method is widely used for large-scale multiproxy reconstructions of hemispheric or global average temperatures.
The initial concept of visualizing historical temperature data has been extended to involve animation, [10] to visualize sea level rise [11] and predictive climate data, [12] and to visually juxtapose temperature trends with other data such as atmospheric CO 2 concentration, [13] global glacier retreat, [14] precipitation, [4] progression of ...
For example, changes in SST monitored via satellite have been used to document the progression of the El Niño-Southern Oscillation since the 1970s. [12] Over land the retrieval of temperature from radiances is harder, because of inhomogeneities in the surface. [13] Studies have been conducted on the urban heat island effect via satellite ...