With increasing public attention on changing climate, it is useful to have a "real-time" estimate of a single integrating metric that expresses the combined atmospheric levels of the long-lived greenhouse gases contributing to that change. Such a metric can help convey to the public how fast these levels are increasing, how close we are to the stabilization levels relevant to policy discussions, and the progress, or lack thereof, in slowing the rate of increase. Three key issues that arise in making such a calculation are: (1) long-lived greenhouse gases include multiple gases with varying lifetimes and radiative properties, (2) there are inevitable lags between the time measurements are taken to when they can be checked and assembled to produce an estimate of global average levels (usually expressed as mole fractions), and (3) these mole fractions are subject to seasonal and other cyclical variations that need to be removed if we want to clearly reveal the underlying long term trends. In this project we address these issues by development of a model that fits a suitable integrating metric that is calculated using global network measurements for greenhouse gases. We evaluate the accuracy with which this model can simulate the actual metric, and also provide "real-time" estimates of the de-seasonalized metric using its values in the recent past.

The calculations produced in the MIT Joint Program are made possible by support from Sustainable Insight Capital Management (SICM) and are available as a real-time carbon counter.  

Technical details of the carbon counter calculations are provided in Joint Program Report 174: A semi-empirical representation of the temporal variation of total greenhouse gas levels expressed as equivalent levels of carbon dioxide (J. Huang, R. Wang, R. Prinn and D. Cunnold, June 2009).