When is a trend meaningful? Insights to carbon cycle variability from an initial-condition large ensemble

Internal climate variability (ICV) creates a range of climate trajectories, which are superimposed upon the forced response. A single climate model realization may not represent forced change alone and may diverge from other realizations, as well as observations, due to ICV. We use an initial-condition large ensemble of simulations with the Community Earth System Model (CESM2) to show that ICV produces a range of outcomes in the terrestrial carbon cycle. Trends in gross primary production (GPP) from 1991 to 2020 differ among ensemble members due to the different climate trajectories resulting from ICV. We quantify how ICV imparts on GPP trends and apply our methodology to the observational record. Observed changes in GPP at two long-running eddy covariance flux towers are consistent with ICV, challenging the understanding of forced changes in the carbon cycle at these locations. A probabilistic framework that accounts for ICV is needed to interpret carbon cycle trends.

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Publication Details

Journal
npj Climate and Atmospheric Science
Published
2024-12-21
DOI
https://doi.org/10.1038/s41612-024-00878-w
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

When is a trend meaningful? Insights to carbon cycle variability from an initial-condition large ensemble

Flavio Lehner, Danica Lombardozzi, William R. Wieder, Clara Deser et al.
npj Climate and Atmospheric Science
Atmospheric and Environmental Gas Dynamics
article

When is a trend meaningful? Insights to carbon cycle variability from an initial-condition large ensemble

Flavio Lehner, Danica Lombardozzi, William R. Wieder, Clara Deser, Gordon B. Bonan
article en

Abstract

Internal climate variability (ICV) creates a range of climate trajectories, which are superimposed upon the forced response. A single climate model realization may not represent forced change alone and may diverge from other realizations, as well as observations, due to ICV. We use an initial-condition large ensemble of simulations with the Community Earth System Model (CESM2) to show that ICV produces a range of outcomes in the terrestrial carbon cycle. Trends in gross primary production (GPP) from 1991 to 2020 differ among ensemble members due to the different climate trajectories resulting from ICV. We quantify how ICV imparts on GPP trends and apply our methodology to the observational record. Observed changes in GPP at two long-running eddy covariance flux towers are consistent with ICV, challenging the understanding of forced changes in the carbon cycle at these locations. A probabilistic framework that accounts for ICV is needed to interpret carbon cycle trends.

npj Climate and Atmospheric ScienceVol. 7(1)
NSF National Center for Atmospheric Research (US), Institute of Arctic and Alpine Research (US), University of Colorado Boulder (US), Cornell University (US), NSF NCAR Climate and Global Dynamics Laboratory (US), Colorado State University (US)
National Science Foundation, U.S. Department of Energy, Office of Science
Openalex Percentile: Top 79%
Atmospheric and Environmental Gas Dynamics
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When is a trend meaningful? Insights to carbon cycle variability from an initial-condition large ensemble — Flavio Lehner, Danica Lombardozzi, et al. · npj Climate and Atmospheric Science (2024) | TGRS Research Map | TGRS