The proper way of looking for causal relationships between time series data (e.g. between atmospheric CO2 and temperature) is discussed. While statistical analysis alone is unlikely to provide “proof” of causation, use of the ‘master equation’ is shown to avoid common pitfalls. Correlation analysis of natural and anthropogenic forcings with year-on-year changes in Mauna Loa CO2 suggest a role for increasing global temperature at least partially explaining observed changes in CO2, but purely statistical analysis cannot tie down the magnitude. One statistically-based model using anthropogenic and natural forcings suggests ~15% of the rise in CO2 being due to natural factors, with an excellent match between model and observations for the COVID-19 related downturn in global economic activity in 2020.
The record of atmospheric CO2 concentration at Mauna Loa, Hawaii since 1959 is the longest continuous record we have of actual (not inferred) atmospheric CO2 concentrations. I’ve visited the…
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