A semi-empirical representation of the temporal variation of total greenhouse gas levels expressed as equivalent levels of carbon dioxide
Name
MITJPSPGC_Rpt174.pdf
Size
615.29 KB
Format
Adobe PDF
Checksum (MD5)
dc004768669c4197bff7f23fb50fd4e5
Author(s)
Cunnold, Derek
Prinn, Ronald G.
Huang, Jin
Wang, Ray
Date Issued
June 2009
Publisher
MIT Joint Program on the Science and Policy of Global Change
Citation
Report no. 174
Series/Report no.
;Report no. 174
Abstract
In order to examine the underlying longer-term trends in greenhouse gases, that are driven for example by anthropogenic emissions or climate change, it is useful to remove the recurring effects of natural cycles and oscillations on the sources and/or sinks of those gases that have strong biological (e.g., CO2, CH4, N2O) and/or photochemical (e.g. CH4) influences on their global atmospheric cycles. We use global observations to calculate monthly estimates of greenhouse gas levels expressed as CO2 equivalents, and then fit these estimates to a semi-empirical model that includes the natural seasonal, QBO, and ENSO variations, as well as a second order polynomial expressing longer-term variations. We find that this model provides a reasonably accurate fit to the observation-based monthly data. We also show that this semiempirical model has some predictive capability; that is it can be used to provide a reasonably reliable estimate of CO2 equivalents at the current time using validated observations that lag real time by a few to several months.
Description
Abstract and PDF report are also available on the MIT Joint Program on the Science and Policy of Global Change website (http://globalchange.mit.edu/).
