Estimating the short-time rate of change in the trend of the Keeling curve

• What exactly is the short-time rate of change (growth rate) in the trend of CO2 data such as the Keeling curve? The answer to this question will obviously depend very much on the duration in time over which the trend has been defined, as well as the smoothing technique that has been used. As an estimate of the short-time rate of change we propose to employ a very simple and robust definition of the trend based on a centered 1-year sliding data window for averaging and a corresponding centered 1-year difference (2-year data window) to estimate its rate of change. In this paper, we show that this simple strategy applied to weekly data of the Keeling curve (1974–2020) gives an estimated rate of change which is perfectly consistent with a more sophisticated regression analysis technique based on Taylor and Fourier series expansions. From a statistical analysis of the regression model and by using the Cramér–Rao lower bound, it is demonstrated that the relative error in the estimated rate of change is less than 5 %%. As an illustration, the estimates are finally compared to some other publicly available data regarding anthropogenic CO2 emissions and natural phenomena such as the El Niño.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Signalbehandling (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Signal Processing (hsv//eng)

Nyckelord

Waves, Signals and Systems

Vågor, signaler och system

Publikations- och innehållstyp

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