Articles | Volume 12, issue 5
https://doi.org/10.5194/amt-12-2611-2019
https://doi.org/10.5194/amt-12-2611-2019
Research article
 | 
07 May 2019
Research article |  | 07 May 2019

A segmentation algorithm for characterizing rise and fall segments in seasonal cycles: an application to XCO2 to estimate benchmarks and assess model bias

Leonardo Calle, Benjamin Poulter, and Prabir K. Patra

Viewed

Total article views: 2,374 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,587 713 74 2,374 346 86 70
  • HTML: 1,587
  • PDF: 713
  • XML: 74
  • Total: 2,374
  • Supplement: 346
  • BibTeX: 86
  • EndNote: 70
Views and downloads (calculated since 05 Nov 2018)
Cumulative views and downloads (calculated since 05 Nov 2018)

Viewed (geographical distribution)

Total article views: 2,374 (including HTML, PDF, and XML) Thereof 2,219 with geography defined and 155 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 29 Jun 2024
Download
Short summary
Satellite observations of atmospheric carbon dioxide offer extraordinary insights into terrestrial ecosystem activity on Earth. The algorithm we present provides researchers with a great deal more information from these satellite data than has been available in the past. We hope the application of this algorithm and analyses tools provides insight into atmospheric dynamics of carbon dioxide and helps inform the development of global ecosystem models in the future.