Articles | Volume 16, issue 14
https://doi.org/10.5194/gmd-16-4113-2023
https://doi.org/10.5194/gmd-16-4113-2023
Development and technical paper
 | 
20 Jul 2023
Development and technical paper |  | 20 Jul 2023

Modelling the terrestrial nitrogen and phosphorus cycle in the UVic ESCM

Makcim L. De Sisto, Andrew H. MacDougall, Nadine Mengis, and Sophia Antoniello

Related authors

Effect of terrestrial nutrient limitation on the estimation of the remaining carbon budget
Makcim L. De Sisto and Andrew H. MacDougall
Biogeosciences, 21, 4853–4873, https://doi.org/10.5194/bg-21-4853-2024,https://doi.org/10.5194/bg-21-4853-2024, 2024
Short summary

Related subject area

Climate and Earth system modeling
Development and evaluation of a new 4DEnVar-based weakly coupled ocean data assimilation system in E3SMv2
Pengfei Shi, L. Ruby Leung, and Bin Wang
Geosci. Model Dev., 18, 2443–2460, https://doi.org/10.5194/gmd-18-2443-2025,https://doi.org/10.5194/gmd-18-2443-2025, 2025
Short summary
TemDeep: a self-supervised framework for temporal downscaling of atmospheric fields at arbitrary time resolutions
Liwen Wang, Qian Li, Qi Lv, Xuan Peng, and Wei You
Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025,https://doi.org/10.5194/gmd-18-2427-2025, 2025
Short summary
The ensemble consistency test: from CESM to MPAS and beyond
Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025,https://doi.org/10.5194/gmd-18-2349-2025, 2025
Short summary
Presentation, calibration and testing of the DCESS II Earth system model of intermediate complexity (version 1.0)
Esteban Fernández Villanueva and Gary Shaffer
Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025,https://doi.org/10.5194/gmd-18-2161-2025, 2025
Short summary
Synthesizing global carbon–nitrogen coupling effects – the MAGICC coupled carbon–nitrogen cycle model v1.0
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
Geosci. Model Dev., 18, 2193–2230, https://doi.org/10.5194/gmd-18-2193-2025,https://doi.org/10.5194/gmd-18-2193-2025, 2025
Short summary

Cited articles

Archer, D.: A data-driven model of the global calcite lysocline, Global Biogeochem. Cy., 10, 511–526, https://doi.org/10.1029/96GB01521, 1996. a
Arora, V. K., Katavouta, A., Williams, R. G., Jones, C. D., Brovkin, V., Friedlingstein, P., Schwinger, J., Bopp, L., Boucher, O., Cadule, P., Chamberlain, M. A., Christian, J. R., Delire, C., Fisher, R. A., Hajima, T., Ilyina, T., Joetzjer, E., Kawamiya, M., Koven, C. D., Krasting, J. P., Law, R. M., Lawrence, D. M., Lenton, A., Lindsay, K., Pongratz, J., Raddatz, T., Séférian, R., Tachiiri, K., Tjiputra, J. F., Wiltshire, A., Wu, T., and Ziehn, T.: Carbon–concentration and carbon–climate feedbacks in CMIP6 models and their comparison to CMIP5 models, Biogeosciences, 17, 4173–4222, https://doi.org/10.5194/bg-17-4173-2020, 2020. a
Avis, C. A.: Simulating the Present-Day and Future Distribution of Permafrost in the UVic Earth System Climate Model, PhD thesis, University of Victoria, http://hdl.handle.net/1828/4030, 2012. a, b, c, d
Bitz, C. M., Holland, M. M., Weaver, A. J., and Eby, M.: Simulating the ice-thickness distribution in a coupled, J. Geophys. Res., 106, 2441–2463, https://doi.org/10.1029/1999JC000113, 2001. a
Bonan, G. B. and Levis, S.: Quantifying carbon-nitrogen feedbacks in the Community Land Model (CLM4), Geophys. Res. Lett., 37, 2261–2282, 2010. a
Download
Short summary
In this study, we developed a nitrogen and phosphorus cycle in an intermediate-complexity Earth system climate model. We found that the implementation of nutrient limitation in simulations has reduced the capacity of land to take up atmospheric carbon and has decreased the vegetation biomass, hence, improving the fidelity of the response of land to simulated atmospheric CO2 rise.
Share