Articles | Volume 14, issue 6
https://doi.org/10.5194/gmd-14-3361-2021
https://doi.org/10.5194/gmd-14-3361-2021
Development and technical paper
 | 
04 Jun 2021
Development and technical paper |  | 04 Jun 2021

Addressing biases in Arctic–boreal carbon cycling in the Community Land Model Version 5

Leah Birch, Christopher R. Schwalm, Sue Natali, Danica Lombardozzi, Gretchen Keppel-Aleks, Jennifer Watts, Xin Lin, Donatella Zona, Walter Oechel, Torsten Sachs, Thomas Andrew Black, and Brendan M. Rogers

Related authors

Estimation of above- and below-ground ecosystem parameters for DVM-DOS-TEM v0.7.0 using MADS v1.7.3
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025,https://doi.org/10.5194/gmd-18-3857-2025, 2025
Short summary
Long-term meteorological and carbon, water and energy flux data from the Boreal Ecosystem Research and Monitoring Sites, Saskatchewan, Canada
Alan Barr, T. Andrew Black, Warren Helgason, Andrew Ireson, Bruce Johnson, J. Harry McCaughey, Zoran Nesic, Charmaine Hrynkiw, Amber Ross, and Newell Hedstrom
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-492,https://doi.org/10.5194/essd-2024-492, 2025
Preprint under review for ESSD
Short summary
Permafrost–wildfire interactions: active layer thickness estimates for paired burned and unburned sites in northern high latitudes
Anna C. Talucci, Michael M. Loranty, Jean E. Holloway, Brendan M. Rogers, Heather D. Alexander, Natalie Baillargeon, Jennifer L. Baltzer, Logan T. Berner, Amy Breen, Leya Brodt, Brian Buma, Jacqueline Dean, Clement J. F. Delcourt, Lucas R. Diaz, Catherine M. Dieleman, Thomas A. Douglas, Gerald V. Frost, Benjamin V. Gaglioti, Rebecca E. Hewitt, Teresa Hollingsworth, M. Torre Jorgenson, Mark J. Lara, Rachel A. Loehman, Michelle C. Mack, Kristen L. Manies, Christina Minions, Susan M. Natali, Jonathan A. O'Donnell, David Olefeldt, Alison K. Paulson, Adrian V. Rocha, Lisa B. Saperstein, Tatiana A. Shestakova, Seeta Sistla, Oleg Sizov, Andrey Soromotin, Merritt R. Turetsky, Sander Veraverbeke, and Michelle A. Walvoord
Earth Syst. Sci. Data, 17, 2887–2909, https://doi.org/10.5194/essd-17-2887-2025,https://doi.org/10.5194/essd-17-2887-2025, 2025
Short summary
WetCH4: a machine-learning-based upscaling of methane fluxes of northern wetlands during 2016–2022
Qing Ying, Benjamin Poulter, Jennifer D. Watts, Kyle A. Arndt, Anna-Maria Virkkala, Lori Bruhwiler, Youmi Oh, Brendan M. Rogers, Susan M. Natali, Hilary Sullivan, Amanda Armstrong, Eric J. Ward, Luke D. Schiferl, Clayton D. Elder, Olli Peltola, Annett Bartsch, Ankur R. Desai, Eugénie Euskirchen, Mathias Göckede, Bernhard Lehner, Mats B. Nilsson, Matthias Peichl, Oliver Sonnentag, Eeva-Stiina Tuittila, Torsten Sachs, Aram Kalhori, Masahito Ueyama, and Zhen Zhang
Earth Syst. Sci. Data, 17, 2507–2534, https://doi.org/10.5194/essd-17-2507-2025,https://doi.org/10.5194/essd-17-2507-2025, 2025
Short summary
Fusing Regional and Global Datasets to Develop a Composite Land Cover Product Across High Latitudes
Valeria Briones, Hélène Genet, Elchin E. Jafarov, Brendan M. Rogers, Jennifer D. Watts, Anna-Maria Virkkala, Annett Bartsch, Benjamin C. Maglio, Joshua Rady, and Susan M. Natali
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-226,https://doi.org/10.5194/essd-2025-226, 2025
Manuscript not accepted for further review
Short summary

Related subject area

Biogeosciences
Emulating grid-based forest carbon dynamics using machine learning: an LPJ-GUESS v4.1.1 application
Carolina Natel, David Martín Belda, Peter Anthoni, Neele Haß, Sam Rabin, and Almut Arneth
Geosci. Model Dev., 18, 4317–4333, https://doi.org/10.5194/gmd-18-4317-2025,https://doi.org/10.5194/gmd-18-4317-2025, 2025
Short summary
ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model
Ye Liu, Huilin Huang, Sing-Chun Wang, Tao Zhang, Donghui Xu, and Yang Chen
Geosci. Model Dev., 18, 4103–4117, https://doi.org/10.5194/gmd-18-4103-2025,https://doi.org/10.5194/gmd-18-4103-2025, 2025
Short summary
Development and assessment of the physical–biogeochemical ocean regional model in the Northwest Pacific: NPRT v1.0 (ROMS v3.9–TOPAZ v2.0)
Daehyuk Kim, Hyun-Chae Jung, Jae-Hong Moon, and Na-Hyeon Lee
Geosci. Model Dev., 18, 3941–3964, https://doi.org/10.5194/gmd-18-3941-2025,https://doi.org/10.5194/gmd-18-3941-2025, 2025
Short summary
Estimation of above- and below-ground ecosystem parameters for DVM-DOS-TEM v0.7.0 using MADS v1.7.3
Elchin E. Jafarov, Hélène Genet, Velimir V. Vesselinov, Valeria Briones, Aiza Kabeer, Andrew L. Mullen, Benjamin Maglio, Tobey Carman, Ruth Rutter, Joy Clein, Chu-Chun Chang, Dogukan Teber, Trevor Smith, Joshua M. Rady, Christina Schädel, Jennifer D. Watts, Brendan M. Rogers, and Susan M. Natali
Geosci. Model Dev., 18, 3857–3875, https://doi.org/10.5194/gmd-18-3857-2025,https://doi.org/10.5194/gmd-18-3857-2025, 2025
Short summary
Alquimia v1.0: a generic interface to biogeochemical codes – a tool for interoperable development, prototyping and benchmarking for multiphysics simulators
Sergi Molins, Benjamin J. Andre, Jeffrey N. Johnson, Glenn E. Hammond, Benjamin N. Sulman, Konstantin Lipnikov, Marcus S. Day, James J. Beisman, Daniil Svyatsky, Hang Deng, Peter C. Lichtner, Carl I. Steefel, and J. David Moulton
Geosci. Model Dev., 18, 3241–3263, https://doi.org/10.5194/gmd-18-3241-2025,https://doi.org/10.5194/gmd-18-3241-2025, 2025
Short summary

Cited articles

Alexander, H. D. and Mack, M. C.: A canopy shift in interior Alaskan boreal forests: consequences for above-and belowground carbon and nitrogen pools during post-fire succession, Ecosystems, 19, 98–114, 2016. a
Ali, A. A., Xu, C., Rogers, A., Fisher, R. A., Wullschleger, S. D., Massoud, E. C., Vrugt, J. A., Muss, J. D., McDowell, N. G., Fisher, J. B., Reich, P. B., and Wilson, C. J.: A global scale mechanistic model of photosynthetic capacity (LUNA V1.0), Geosci. Model Dev., 9, 587–606, https://doi.org/10.5194/gmd-9-587-2016, 2016. a, b
Amiro, B.: FLUXNET2015 CA-SF1 Saskatchewan-Western Boreal, forest burned in 1977, Tech. rep., FluxNet, University of Manitoba, 2016. a
Archer, S. and Tieszen, L.: Effects of simulated grazing on foliage and root production and biomass allocation in an arctic tundra sedge (Eriophorum vaginatum), Oecologia, 58, 92–102, 1983. a
Arora, V. K. and Boer, G. J.: A parameterization of leaf phenology for the terrestrial ecosystem component of climate models, Glob. Change Biol., 11, 39–59, 2005. a, b, c, d
Download
Short summary
The high-latitude landscape or Arctic–boreal zone has been warming rapidly, impacting the carbon balance both regionally and globally. Given the possible global effects of climate change, it is important to have accurate climate model simulations. We assess the simulation of the Arctic–boreal carbon cycle in the Community Land Model (CLM 5.0). We find biases in both the timing and magnitude photosynthesis. We then use observational data to improve the simulation of the carbon cycle.
Share