Midwest US croplands determine model divergence in North American carbon fluxes

Wu Sun, Yuanyuan Fang, Xiangzhong Luo, Yoichi P. Shiga, Yao Zhang, Arlyn E. Andrews, Kirk W. Thoning, Joshua B. Fisher, Trevor F. Keenan, and Anna M. Michalak


Models of the land biosphere cannot agree on whether croplands or forests dominate summertime carbon uptake over North America. Such uncertainty limits the ability to predict climate impacts for management and policymaking. Here, we found that models that simulate strong summer carbon uptake in Midwestern croplands relative to forests are more consistent with atmospheric CO2 observations than models that do otherwise. We further showed that most models misrepresent cropland carbon uptake because they have the wrong crop types or simulate the annual life cycles of crops poorly. This study underscores the need to resolve crops in land models for accurate assessment of carbon flows between the atmosphere and the biosphere.

Figure: (a) A map of North American biomes with sites of the CO2 observational network, after Shiga et al. (2018). Enclosed within the dashed dark red contours are grid cells of which the total footprint sensitivity summed during 2007–2010 is among the top 80% over continental North America. (b) Percent coverage of observations (dark blue) sensitive to biomes during 2007–2010, compared with the area percentages of these biomes (light blue). Croplands (CRP), evergreen needleleaf forests (ENF), and deciduous broadleaf and mixed forests (DBMF) were the most extensively observed biomes. In contrast, savannahs (SAV) and tropical evergreen broadleaf forests (EBF) received little coverage in the observing system. Other biomes were underrepresented in terms of observational coverage.


Large uncertainties in North American terrestrial carbon fluxes hinder regional climate projections. Terrestrial biosphere models (TBMs), the essential tools for understanding continental-scale carbon cycle, diverge on whether temperate forests or croplands dominate carbon uptake in North America. Evidence from novel photosynthetic proxies, such as those based on chlorophyll fluorescence, has cast doubt on the “weak cropland, strong forest” carbon uptake patterns simulated by most TBMs. However, no systematic evaluation of TBMs has yet been attempted to pin down space-time patterns that are most consistent with regional CO2 observational constraints. Here, we leverage atmospheric CO2 observations and satellite-observed photosynthetic proxies to understand emergent space-time patterns in North American carbon fluxes from a large suite of TBMs and data-driven models. To do so, we evaluate how well the atmospheric signals resulting from carbon flux estimates reproduce the space-time variability in atmospheric CO2, as is observed by a network of continuous-monitoring towers over North America. Models with gross or net carbon fluxes that are consistent with the observed CO2variability share a salient feature of growing-season carbon uptake in Midwest US croplands. Conversely, the remaining models place most growing-season uptake in boreal or temperate forests. Differences in model explanatory power depend mainly on the simulated annual cycles of cropland uptake—especially, the timing of peak uptake—rather than the distribution of annual mean fluxes across biomes. Our results suggest that improved model representation of cropland phenology is crucial to robust, policy-relevant estimation of North American carbon exchange.

Sun, W., Y. Fang, X. Luo, Y. P. Shiga, Y. Zhang, A. E. Andrews, K. W. Thoning, J. B. Fisher, T. F. Keenan, & A. M. Michalak. (2021). Midwest US croplands determine model divergence in North American carbon fluxes. AGU Advances, 2(2). https://doi.org/10.1029/2020av000310