03 Aug 2023
 | 03 Aug 2023
Status: this preprint is currently under review for the journal BG.

Multiscale assessment of North American terrestrial carbon balance

Kelsey T. Foster, Wu Sun, Yoichi P. Shiga, Jiafu Mao, and Anna M. Michalak

Abstract. Comparisons of carbon uptake estimates from bottom-up terrestrial biosphere models (TBMs) to top-down atmospheric inversions help assess how well we understand carbon dioxide (CO2) exchange between the atmosphere and terrestrial biosphere. Previous comparisons have shown varying levels of agreement between bottom-up and top-down approaches, but they have almost exclusively focused on large, aggregated scales, providing limited insights into reasons for the mismatches. Here we explore how consistency, defined as the spread in net ecosystem exchange (NEE) estimates within an ensemble of TBMs or inversions, varies with spatial scale. We also evaluate how well consistency informs accuracy in overall NEE estimates by filtering models based on their agreement with the variability, magnitude, and seasonality in observed atmospheric CO2 drawdowns or enhancements. We find that TBMs produce more consistent estimates of NEE for most regions and at most scales compared to inversions. Filtering models using atmospheric CO2 metrics causes ensemble spread to decrease substantially for TBMs, but not for inversions. This suggests that ensemble spread is likely not a reliable measure of the uncertainty associated with the North American carbon balance. Promisingly, applying atmospheric CO2 metrics leads to a set of models with converging flux estimates across TBMs and inversions. Overall, we show that multiscale assessment of the agreement between bottom-up and top-down NEE estimates, aided by regional-scale observational constraints, illuminates a promising path towards identifying fine-scale sources of uncertainty and improving both ensemble consistency and accuracy. These findings help refine our understanding of biospheric carbon balance, particularly at scales relevant for informing regional carbon-climate feedbacks.

Kelsey T. Foster et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2023-111 by Guillermo Murray-Tortarolo', Guillermo Murray-Tortarolo, 07 Sep 2023
  • RC2: 'Comment on bg-2023-111', Anonymous Referee #2, 15 Sep 2023

Kelsey T. Foster et al.

Kelsey T. Foster et al.


Total article views: 287 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
195 79 13 287 22 4 5
  • HTML: 195
  • PDF: 79
  • XML: 13
  • Total: 287
  • Supplement: 22
  • BibTeX: 4
  • EndNote: 5
Views and downloads (calculated since 03 Aug 2023)
Cumulative views and downloads (calculated since 03 Aug 2023)

Viewed (geographical distribution)

Total article views: 284 (including HTML, PDF, and XML) Thereof 284 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 24 Sep 2023
Short summary
Assessing agreement between bottom-up and top-down methods across spatial scales can provide insights into the relationship between ensemble spread (difference across models) and model accuracy (difference between model estimates and reality). We find that ensemble spread is unlikely to be a good indicator of actual uncertainty in the North American carbon balance. However, models that are consistent with atmospheric constraints show stronger agreement between top-down and bottom-up estimates.