The browser you are using is not supported by this website. All versions of Internet Explorer are no longer supported, either by us or Microsoft (read more here: https://www.microsoft.com/en-us/microsoft-365/windows/end-of-ie-support).

Please use a modern browser to fully experience our website, such as the newest versions of Edge, Chrome, Firefox or Safari etc.

Michal Heliasz. Photo.

Michal Heliasz

Research engineer

Michal Heliasz. Photo.

An algorithm to detect non-background signals in greenhouse gas time series from European tall tower and mountain stations

Author

  • Alex Resovsky
  • Michel Ramonet
  • Leonard Rivier
  • Jerome Tarniewicz
  • Philippe Ciais
  • Martin Steinbacher
  • Ivan Mammarella
  • Meelis Mölder
  • Michal Heliasz
  • Dagmar Kubistin
  • Matthias Lindauer
  • Jennifer Müller-Williams
  • Sebastien Conil
  • Richard Engelen

Summary, in English

We present a statistical framework to identify regional signals in station-based CO2 time series with minimal local influence. A curve-fitting function is first applied to the detrended time series to derive a harmonic describing the annual CO2 cycle. We then combine a polynomial fit to the data with a short-term residual filter to estimate the smoothed cycle and define a seasonally adjusted noise component, equal to 2 standard deviations of the smoothed cycle about the annual cycle. Spikes in the smoothed daily data which surpass this ±2σ threshold are classified as anomalies. Examining patterns of anomalous behavior across multiple sites allows us to quantify the impacts of synoptic-scale atmospheric transport events and better understand the regional carbon cycling implications of extreme seasonal occurrences such as droughts.

Department/s

  • Dept of Physical Geography and Ecosystem Science

Publishing year

2021-09-17

Language

English

Pages

6119-6135

Publication/Series

Atmospheric Measurement Techniques

Volume

14

Issue

9

Document type

Journal article

Publisher

Copernicus GmbH

Topic

  • Climate Research

Status

Published

ISBN/ISSN/Other

  • ISSN: 1867-1381