Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

Journal metrics

  • IF value: 5.240 IF 5.240
  • IF 5-year value: 5.768 IF 5-year
    5.768
  • CiteScore value: 8.9 CiteScore
    8.9
  • SNIP value: 1.713 SNIP 1.713
  • IPP value: 5.53 IPP 5.53
  • SJR value: 3.18 SJR 3.18
  • Scimago H <br class='hide-on-tablet hide-on-mobile'>index value: 71 Scimago H
    index 71
  • h5-index value: 51 h5-index 51
GMD | Articles | Volume 12, issue 11
Geosci. Model Dev., 12, 4781–4802, 2019
https://doi.org/10.5194/gmd-12-4781-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 12, 4781–4802, 2019
https://doi.org/10.5194/gmd-12-4781-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Model description paper 20 Nov 2019

Model description paper | 20 Nov 2019

A new model of the coupled carbon, nitrogen, and phosphorus cycles in the terrestrial biosphere (QUINCY v1.0; revision 1996)

Tea Thum et al.

Related authors

Evaluating two soil carbon models within a global land surface model using surface and spaceborne observations of atmospheric CO2 mole fractions
Tea Thum, Julia E. S. M. Nabel, Aki Tsuruta, Tuula Aalto, Edward J. Dlugokencky, Jari Liski, Ingrid T. Luijkx, Tiina Markkanen, Julia Pongratz, Yukio Yoshida, and Sönke Zaehle
Biogeosciences Discuss., https://doi.org/10.5194/bg-2020-7,https://doi.org/10.5194/bg-2020-7, 2020
Revised manuscript under review for BG
Short summary
Parameter calibration and stomatal conductance formulation comparison for boreal forests with adaptive population importance sampler in the land surface model JSBACH
Jarmo Mäkelä, Jürgen Knauer, Mika Aurela, Andrew Black, Martin Heimann, Hideki Kobayashi, Annalea Lohila, Ivan Mammarella, Hank Margolis, Tiina Markkanen, Jouni Susiluoto, Tea Thum, Toni Viskari, Sönke Zaehle, and Tuula Aalto
Geosci. Model Dev., 12, 4075–4098, https://doi.org/10.5194/gmd-12-4075-2019,https://doi.org/10.5194/gmd-12-4075-2019, 2019
Short summary
Response of water use efficiency to summer drought in a boreal Scots pine forest in Finland
Yao Gao, Tiina Markkanen, Mika Aurela, Ivan Mammarella, Tea Thum, Aki Tsuruta, Huiyi Yang, and Tuula Aalto
Biogeosciences, 14, 4409–4422, https://doi.org/10.5194/bg-14-4409-2017,https://doi.org/10.5194/bg-14-4409-2017, 2017
Short summary
Modelling sun-induced fluorescence and photosynthesis with a land surface model at local and regional scales in northern Europe
Tea Thum, Sönke Zaehle, Philipp Köhler, Tuula Aalto, Mika Aurela, Luis Guanter, Pasi Kolari, Tuomas Laurila, Annalea Lohila, Federico Magnani, Christiaan Van Der Tol, and Tiina Markkanen
Biogeosciences, 14, 1969–1987, https://doi.org/10.5194/bg-14-1969-2017,https://doi.org/10.5194/bg-14-1969-2017, 2017
Short summary
Assessing various drought indicators in representing summer drought in boreal forests in Finland
Y. Gao, T. Markkanen, T. Thum, M. Aurela, A. Lohila, I. Mammarella, M. Kämäräinen, S. Hagemann, and T. Aalto
Hydrol. Earth Syst. Sci., 20, 175–191, https://doi.org/10.5194/hess-20-175-2016,https://doi.org/10.5194/hess-20-175-2016, 2016

Related subject area

Biogeosciences
Simulating stable carbon isotopes in the ocean component of the FAMOUS general circulation model with MOSES1 (XOAVI)
Jennifer E. Dentith, Ruza F. Ivanovic, Lauren J. Gregoire, Julia C. Tindall, and Laura F. Robinson
Geosci. Model Dev., 13, 3529–3552, https://doi.org/10.5194/gmd-13-3529-2020,https://doi.org/10.5194/gmd-13-3529-2020, 2020
Short summary
Quantitative assessment of fire and vegetation properties in simulations with fire-enabled vegetation models from the Fire Model Intercomparison Project
Stijn Hantson, Douglas I. Kelley, Almut Arneth, Sandy P. Harrison, Sally Archibald, Dominique Bachelet, Matthew Forrest, Thomas Hickler, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Lars Nieradzik, Sam S. Rabin, I. Colin Prentice, Tim Sheehan, Stephen Sitch, Lina Teckentrup, Apostolos Voulgarakis, and Chao Yue
Geosci. Model Dev., 13, 3299–3318, https://doi.org/10.5194/gmd-13-3299-2020,https://doi.org/10.5194/gmd-13-3299-2020, 2020
Short summary
Marine biogeochemical cycling and oceanic CO2 uptake simulated by the NUIST Earth System Model version 3 (NESM v3)
Yifei Dai, Long Cao, and Bin Wang
Geosci. Model Dev., 13, 3119–3144, https://doi.org/10.5194/gmd-13-3119-2020,https://doi.org/10.5194/gmd-13-3119-2020, 2020
Short summary
CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 1: Model framework and site-level performance
Joe R. Melton, Vivek K. Arora, Eduard Wisernig-Cojoc, Christian Seiler, Matthew Fortier, Ed Chan, and Lina Teckentrup
Geosci. Model Dev., 13, 2825–2850, https://doi.org/10.5194/gmd-13-2825-2020,https://doi.org/10.5194/gmd-13-2825-2020, 2020
Short summary
HR3DHG version 1: modeling the spatiotemporal dynamics of mercury in the Augusta Bay (southern Italy)
Giovanni Denaro, Daniela Salvagio Manta, Alessandro Borri, Maria Bonsignore, Davide Valenti, Enza Quinci, Andrea Cucco, Bernardo Spagnolo, Mario Sprovieri, and Andrea De Gaetano
Geosci. Model Dev., 13, 2073–2093, https://doi.org/10.5194/gmd-13-2073-2020,https://doi.org/10.5194/gmd-13-2073-2020, 2020
Short summary

Cited articles

Ahrens, B., Braakhekke, M. C., Guggenberger, G., Schrumpf, M., and Reichstein, M.: Contribution of sorption, DOC transport and microbial interactions to the 14C age of a soil organic carbon profile: Insights from a calibrated process model, Soil Biol. Biochem., 88, 390–402, 2015. a
Ammann, C., Flechard, C., Leifeld, J., Neftel, A., and Fuhrer, J.: The carbon budget of newly established temperate grassland depends on management intensity, Agr. Ecosyst. Environ., 121, 5–20, https://doi.org/10.1016/j.agee.2006.12.002, 2007. a
Araújo, A. C., Nobre, A. D., Kruijt, B., Elbers, J. A., Dallarosa, R., Stefani, P., von Randow, C., Manzi, A. O., Culf, A. D., Gash, J. H. C., Valentini, R., and Kabat, P.: Comparative measurements of carbon dioxide fluxes from two nearby towers in a central Amazonian rainforest: The Manaus LBA site, J. Geophys. Res.-Atmos., 107, LBA 58–1–LBA 58–20, https://doi.org/10.1029/2001JD000676, 2002. a
Archibald, S., Nickless, A., Govender, N., Scholes, R. J., and Lehsten, V.: Climate and the inter-annual variability of fire in southern Africa: a meta-analysis using long-term field data and satellite-derived burnt area data, Global Ecol. Biogeogr., 19, 794–809, https://doi.org/10.1111/j.1466-8238.2010.00568.x, 2010. a
Atkin, O. K., Meir, P., and Turnbull, M. H.: Improving representation of leaf respiration in large-scale predictive climate–vegetation models, New Phytol., 202, 743–748, https://doi.org/10.1111/nph.12686, 2014. a, b
Publications Copernicus
Download
Short summary
To predict the response of the vegetation to climate change, we need global models that describe the relevant processes taking place in the vegetation. Recently, we have obtained more in-depth understanding of vegetation processes and the role of nutrients in the biogeochemical cycles. We have developed a new global vegetation model that includes carbon, water, nitrogen, and phosphorus cycles. We show that the model is successful in evaluation against a wide range of observations.
To predict the response of the vegetation to climate change, we need global models that describe...
Citation