Articles | Volume 12, issue 4
https://doi.org/10.5194/gmd-12-1601-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-1601-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| 
24 Apr 2019
Model evaluation paper |
| 24 Apr 2019
| 24 Apr 2019
Evaluating the E3SM land model version 0 (ELMv0) at a temperate forest site using flux and soil water measurements
Environmental Sciences Division and Climate Change Science
Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Environmental Sciences Division and Climate Change Science
Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of
Oklahoma, Norman, OK 73019, USA
Daniel M. Ricciuto
Environmental Sciences Division and Climate Change Science
Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Lianhong Gu
Environmental Sciences Division and Climate Change Science
Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Paul J. Hanson
Environmental Sciences Division and Climate Change Science
Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
Jeffrey D. Wood
School of Natural Resources, University of Missouri,
Columbia, MO 65211, USA
Melanie A. Mayes
Environmental Sciences Division and Climate Change Science
Institute, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA
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Jing Wang, Jianyang Xia, Xuhui Zhou, Kun Huang, Jian Zhou, Yuanyuan Huang, Lifen Jiang, Xia Xu, Junyi Liang, Ying-Ping Wang, Xiaoli Cheng, and Yiqi Luo
Biogeosciences, 16, 917–926, https://doi.org/10.5194/bg-16-917-2019, https://doi.org/10.5194/bg-16-917-2019, 2019
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Misha B. Krassovski, Glen E. Lyon, Jeffery S. Riggs, and Paul J. Hanson
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Biogeosciences, 15, 3421–3437, https://doi.org/10.5194/bg-15-3421-2018, https://doi.org/10.5194/bg-15-3421-2018, 2018
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Henrique F. Duarte, Brett M. Raczka, Daniel M. Ricciuto, John C. Lin, Charles D. Koven, Peter E. Thornton, David R. Bowling, Chun-Ta Lai, Kenneth J. Bible, and James R. Ehleringer
Biogeosciences, 14, 4315–4340, https://doi.org/10.5194/bg-14-4315-2017, https://doi.org/10.5194/bg-14-4315-2017, 2017
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Dan Lu, Daniel Ricciuto, Anthony Walker, Cosmin Safta, and William Munger
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Erik A. Hobbie, Janet Chen, Paul J. Hanson, Colleen M. Iversen, Karis J. McFarlane, Nathan R. Thorp, and Kirsten S. Hofmockel
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Paul J. Hanson, Jeffery S. Riggs, W. Robert Nettles, Jana R. Phillips, Misha B. Krassovski, Leslie A. Hook, Lianhong Gu, Andrew D. Richardson, Donald M. Aubrecht, Daniel M. Ricciuto, Jeffrey M. Warren, and Charlotte Barbier
Biogeosciences, 14, 861–883, https://doi.org/10.5194/bg-14-861-2017, https://doi.org/10.5194/bg-14-861-2017, 2017
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Yiqi Luo, Zheng Shi, Xingjie Lu, Jianyang Xia, Junyi Liang, Jiang Jiang, Ying Wang, Matthew J. Smith, Lifen Jiang, Anders Ahlström, Benito Chen, Oleksandra Hararuk, Alan Hastings, Forrest Hoffman, Belinda Medlyn, Shuli Niu, Martin Rasmussen, Katherine Todd-Brown, and Ying-Ping Wang
Biogeosciences, 14, 145–161, https://doi.org/10.5194/bg-14-145-2017, https://doi.org/10.5194/bg-14-145-2017, 2017
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Climate change is strongly regulated by land carbon cycle. However, we lack the ability to predict future land carbon sequestration. Here, we develop a novel framework for understanding what determines the direction and rate of future change in land carbon storage. The framework offers a suite of new approaches to revolutionize land carbon model evaluation and improvement.
Jinxin Zhang, Lianhong Gu, Jingbo Zhang, Rina Wu, Feng Wang, Guanghui Lin, Bo Wu, Qi Lu, and Ping Meng
Biogeosciences, 14, 131–144, https://doi.org/10.5194/bg-14-131-2017, https://doi.org/10.5194/bg-14-131-2017, 2017
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Plant nitrogen (N) isotope composition is an indicator of N cycling. How N isotopes are distributed within plants is not well understood. We found intra-plant variations in N isotopes were related to organ N and phosphorous (P) contents and predicted by the N–P interaction. We hypothesized that plant N volatilization, resorption and remobilization of N and P from senescing leaves, and mixing of the re-translocated foliar N and P, are responsible for the observed intra-plant N isotope variations.
Brett Raczka, Henrique F. Duarte, Charles D. Koven, Daniel Ricciuto, Peter E. Thornton, John C. Lin, and David R. Bowling
Biogeosciences, 13, 5183–5204, https://doi.org/10.5194/bg-13-5183-2016, https://doi.org/10.5194/bg-13-5183-2016, 2016
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We use carbon isotopes of CO2 to improve the performance of a land surface model, a component with earth system climate models. We found that isotope observations can provide important information related to the exchange of carbon and water from vegetation driven by environmental stress from low atmospheric moisture and nitrogen limitation. It follows that isotopes have a unique potential to improve model performance and provide insight into land surface model development.
Junyi Liang, Xuan Qi, Lara Souza, and Yiqi Luo
Biogeosciences, 13, 2689–2699, https://doi.org/10.5194/bg-13-2689-2016, https://doi.org/10.5194/bg-13-2689-2016, 2016
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J. Mao, D. M. Ricciuto, P. E. Thornton, J. M. Warren, A. W. King, X. Shi, C. M. Iversen, and R. J. Norby
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Gangsheng Wang, Henriette I. Jager, Latha M. Baskaran, Tyler F. Baker, and Craig C. Brandt
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2016-34, https://doi.org/10.5194/hess-2016-34, 2016
Manuscript not accepted for further review
J. Zhang, L. Gu, J. Zhang, R. Wu, F. Wang, G. Lin, B. Wu, Q. Lu, and P. Meng
Biogeosciences Discuss., https://doi.org/10.5194/bgd-12-18769-2015, https://doi.org/10.5194/bgd-12-18769-2015, 2015
Revised manuscript not accepted
X. Shi, P. E. Thornton, D. M. Ricciuto, P. J. Hanson, J. Mao, S. D. Sebestyen, N. A. Griffiths, and G. Bisht
Biogeosciences, 12, 6463–6477, https://doi.org/10.5194/bg-12-6463-2015, https://doi.org/10.5194/bg-12-6463-2015, 2015
G. Wohlfahrt, C. Amelynck, C. Ammann, A. Arneth, I. Bamberger, A. H. Goldstein, L. Gu, A. Guenther, A. Hansel, B. Heinesch, T. Holst, L. Hörtnagl, T. Karl, Q. Laffineur, A. Neftel, K. McKinney, J. W. Munger, S. G. Pallardy, G. W. Schade, R. Seco, and N. Schoon
Atmos. Chem. Phys., 15, 7413–7427, https://doi.org/10.5194/acp-15-7413-2015, https://doi.org/10.5194/acp-15-7413-2015, 2015
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Methanol is the second most abundant volatile organic compound in the troposphere and plays a significant role in atmospheric chemistry. While there is consensus about the dominant role of plants as the major source and the reaction with OH as the major sink, global methanol budgets diverge considerably in terms of source/sink estimates. Here we present micrometeorological methanol flux data from eight sites in order to provide a first cross-site synthesis of the terrestrial methanol exchange.
C. Safta, D. M. Ricciuto, K. Sargsyan, B. Debusschere, H. N. Najm, M. Williams, and P. E. Thornton
Geosci. Model Dev., 8, 1899–1918, https://doi.org/10.5194/gmd-8-1899-2015, https://doi.org/10.5194/gmd-8-1899-2015, 2015
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In this paper we propose a probabilistic framework for an uncertainty quantification study of a carbon cycle model and focus on the comparison between steady-state and transient
simulation setups. We study model parameters via global sensitivity analysis and employ a Bayesian approach to calibrate these parameters using NEE observations at the Harvard Forest site. The calibration results are then used to assess the predictive skill of the model via posterior predictive checks.
L. Gu, S. G. Pallardy, K. P. Hosman, and Y. Sun
Biogeosciences, 12, 2831–2845, https://doi.org/10.5194/bg-12-2831-2015, https://doi.org/10.5194/bg-12-2831-2015, 2015
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Co-occurring tree species with varying physiologies were continuously monitored for mortality with concurrent observations of key physiological and environmental variables for a decade in a central US forest. New predictors of drought-induced mortality were developed. Time-delayed mortality was shown to be nonlinearly related to drought intensity and species’ capacities in regulating their internal hydraulic status, with elevated risk associated with extreme isohydric and anisohydric behaviors.
J. Zhang, L. Gu, F. Bao, Y. Cao, Y. Hao, J. He, J. Li, Y. Li, Y. Ren, F. Wang, R. Wu, B. Yao, Y. Zhao, G. Lin, B. Wu, Q. Lu, and P. Meng
Biogeosciences, 12, 15–27, https://doi.org/10.5194/bg-12-15-2015, https://doi.org/10.5194/bg-12-15-2015, 2015
Y. Wei, S. Liu, D. N. Huntzinger, A. M. Michalak, N. Viovy, W. M. Post, C. R. Schwalm, K. Schaefer, A. R. Jacobson, C. Lu, H. Tian, D. M. Ricciuto, R. B. Cook, J. Mao, and X. Shi
Geosci. Model Dev., 7, 2875–2893, https://doi.org/10.5194/gmd-7-2875-2014, https://doi.org/10.5194/gmd-7-2875-2014, 2014
S. Jagadamma, M. A. Mayes, J. M. Steinweg, and S. M. Schaeffer
Biogeosciences, 11, 4665–4678, https://doi.org/10.5194/bg-11-4665-2014, https://doi.org/10.5194/bg-11-4665-2014, 2014
X. Yang, P. E. Thornton, D. M. Ricciuto, and W. M. Post
Biogeosciences, 11, 1667–1681, https://doi.org/10.5194/bg-11-1667-2014, https://doi.org/10.5194/bg-11-1667-2014, 2014
D. N. Huntzinger, C. Schwalm, A. M. Michalak, K. Schaefer, A. W. King, Y. Wei, A. Jacobson, S. Liu, R. B. Cook, W. M. Post, G. Berthier, D. Hayes, M. Huang, A. Ito, H. Lei, C. Lu, J. Mao, C. H. Peng, S. Peng, B. Poulter, D. Riccuito, X. Shi, H. Tian, W. Wang, N. Zeng, F. Zhao, and Q. Zhu
Geosci. Model Dev., 6, 2121–2133, https://doi.org/10.5194/gmd-6-2121-2013, https://doi.org/10.5194/gmd-6-2121-2013, 2013
P. C. Stoy, M. C. Dietze, A. D. Richardson, R. Vargas, A. G. Barr, R. S. Anderson, M. A. Arain, I. T. Baker, T. A. Black, J. M. Chen, R. B. Cook, C. M. Gough, R. F. Grant, D. Y. Hollinger, R. C. Izaurralde, C. J. Kucharik, P. Lafleur, B. E. Law, S. Liu, E. Lokupitiya, Y. Luo, J. W. Munger, C. Peng, B. Poulter, D. T. Price, D. M. Ricciuto, W. J. Riley, A. K. Sahoo, K. Schaefer, C. R. Schwalm, H. Tian, H. Verbeeck, and E. Weng
Biogeosciences, 10, 6893–6909, https://doi.org/10.5194/bg-10-6893-2013, https://doi.org/10.5194/bg-10-6893-2013, 2013
Related subject area
Biogeosciences
In silico calculation of soil pH by SCEPTER v1.0
Simple process-led algorithms for simulating habitats (SPLASH v.2.0): robust calculations of water and energy fluxes
A global behavioural model of human fire use and management: WHAM! v1.0
Terrestrial Ecosystem Model in R (TEMIR) version 1.0: simulating ecophysiological responses of vegetation to atmospheric chemical and meteorological changes
biospheremetrics v1.0.2: an R package to calculate two complementary terrestrial biosphere integrity indicators – human colonization of the biosphere (BioCol) and risk of ecosystem destabilization (EcoRisk)
Modeling boreal forest soil dynamics with the microbially explicit soil model MIMICS+ (v1.0)
Optimal enzyme allocation leads to the constrained enzyme hypothesis: the Soil Enzyme Steady Allocation Model (SESAM; v3.1)
Implementing a dynamic representation of fire and harvest including subgrid-scale heterogeneity in the tile-based land surface model CLASSIC v1.45
Inferring the tree regeneration niche from inventory data using a dynamic forest model
Optimising CH4 simulations from the LPJ-GUESS model v4.1 using an adaptive Markov chain Monte Carlo algorithm
The XSO framework (v0.1) and Phydra library (v0.1) for a flexible, reproducible, and integrated plankton community modeling environment in Python
AgriCarbon-EO v1.0.1: large-scale and high-resolution simulation of carbon fluxes by assimilation of Sentinel-2 and Landsat-8 reflectances using a Bayesian approach
SAMM version 1.0: a numerical model for microbial- mediated soil aggregate formation
Using Deep Learning to integrate paleoclimate and global biogeochemistry over Phanerozoic time
A model of the within-population variability of budburst in forest trees
Computationally efficient parameter estimation for high-dimensional ocean biogeochemical models
The community-centered freshwater biogeochemistry model unified RIVE v1.0: a unified version for water column
EAT v0.9.6: a 1D testbed for physical-biogeochemical data assimilation in natural waters
Observation-based sowing dates and cultivars significantly affect yield and irrigation for some crops in the Community Land Model (CLM5)
The statistical emulators of GGCMI phase 2: responses of year-to-year variation of crop yield to CO2, temperature, water, and nitrogen perturbations
A novel Eulerian model based on central moments to simulate age and reactivity continua interacting with mixing processes
Dynamic ecosystem assembly and escaping the “fire-trap” in the tropics: Insights from FATES_15.0.0
AdaScape 1.0: a coupled modelling tool to investigate the links between tectonics, climate, and biodiversity
An along-track Biogeochemical Argo modelling framework: a case study of model improvements for the Nordic seas
Peatland-VU-NUCOM (PVN 1.0): using dynamic plant functional types to model peatland vegetation, CH4, and CO2 emissions
Quantification of hydraulic trait control on plant hydrodynamics and risk of hydraulic failure within a demographic structured vegetation model in a tropical forest (FATES–HYDRO V1.0)
SedTrace 1.0: a Julia-based framework for generating and running reactive-transport models of marine sediment diagenesis specializing in trace elements and isotopes
A high-resolution marine mercury model MITgcm-ECCO2-Hg with online biogeochemistry
Improving nitrogen cycling in a land surface model (CLM5) to quantify soil N2O, NO, and NH3 emissions from enhanced rock weathering with croplands
Ocean biogeochemistry in the coupled ocean–sea ice–biogeochemistry model FESOM2.1–REcoM3
Forcing the Global Fire Emissions Database burned-area dataset into the Community Land Model version 5.0: impacts on carbon and water fluxes at high latitudes
Modeling boreal forest’s mineral soil and peat C stock dynamics with Yasso07 model coupled with updated moisture modifier
Modeling of non-structural carbohydrate dynamics by the spatially explicit individual-based dynamic global vegetation model SEIB-DGVM (SEIB-DGVM-NSC version 1.0)
MEDFATE 2.9.3: a trait-enabled model to simulate Mediterranean forest function and dynamics at regional scales
Modelling the role of livestock grazing in C and N cycling in grasslands with LPJmL5.0-grazing
Implementation of trait-based ozone plant sensitivity in the Yale Interactive terrestrial Biosphere model v1.0 to assess global vegetation damage
The Permafrost and Organic LayEr module for Forest Models (POLE-FM) 1.0
CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics
Validation of a new spatially explicit process-based model (HETEROFOR) to simulate structurally and compositionally complex forest stands in eastern North America
Global agricultural ammonia emissions simulated with the ORCHIDEE land surface model
ForamEcoGEnIE 2.0: incorporating symbiosis and spine traits into a trait-based global planktic foraminiferal model
FABM-NflexPD 2.0: testing an instantaneous acclimation approach for modeling the implications of phytoplankton eco-physiology for the carbon and nutrient cycles
Evaluating the vegetation–atmosphere coupling strength of ORCHIDEE land surface model (v7266)
Non-Redfieldian carbon model for the Baltic Sea (ERGOM version 1.2) – implementation and budget estimates
Implementation of a new crop phenology and irrigation scheme in the ISBA land surface model using SURFEX_v8.1
Simulating long-term responses of soil organic matter turnover to substrate stoichiometry by abstracting fast and small-scale microbial processes: the Soil Enzyme Steady Allocation Model (SESAM; v3.0)
Modeling demographic-driven vegetation dynamics and ecosystem biogeochemical cycling in NASA GISS's Earth system model (ModelE-BiomeE v.1.0)
Forest fluxes and mortality response to drought: model description (ORCHIDEE-CAN-NHA r7236) and evaluation at the Caxiuanã drought experiment
Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level
CANOPS-GRB v1.0: a new Earth system model for simulating the evolution of ocean–atmosphere chemistry over geologic timescales
Yoshiki Kanzaki, Isabella Chiaravalloti, Shuang Zhang, Noah J. Planavsky, and Christopher T. Reinhard
Geosci. Model Dev., 17, 4515–4532, https://doi.org/10.5194/gmd-17-4515-2024, https://doi.org/10.5194/gmd-17-4515-2024, 2024
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Soil pH is one of the most commonly measured agronomical and biogeochemical indices, mostly reflecting exchangeable acidity. Explicit simulation of both porewater and bulk soil pH is thus crucial to the accurate evaluation of alkalinity required to counteract soil acidification and the resulting capture of anthropogenic carbon dioxide through the enhanced weathering technique. This has been enabled by the updated reactive–transport SCEPTER code and newly developed framework to simulate soil pH.
David Sandoval, Iain Colin Prentice, and Rodolfo L. B. Nóbrega
Geosci. Model Dev., 17, 4229–4309, https://doi.org/10.5194/gmd-17-4229-2024, https://doi.org/10.5194/gmd-17-4229-2024, 2024
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Numerous estimates of water and energy balances depend on empirical equations requiring site-specific calibration, posing risks of "the right answers for the wrong reasons". We introduce novel first-principles formulations to calculate key quantities without requiring local calibration, matching predictions from complex land surface models.
Oliver Perkins, Matthew Kasoar, Apostolos Voulgarakis, Cathy Smith, Jay Mistry, and James D. A. Millington
Geosci. Model Dev., 17, 3993–4016, https://doi.org/10.5194/gmd-17-3993-2024, https://doi.org/10.5194/gmd-17-3993-2024, 2024
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Wildfire is often presented in the media as a danger to human life. Yet globally, millions of people’s livelihoods depend on using fire as a tool. So, patterns of fire emerge from interactions between humans, land use, and climate. This complexity means scientists cannot yet reliably say how fire will be impacted by climate change. So, we developed a new model that represents globally how people use and manage fire. The model reveals the extent and diversity of how humans live with and use fire.
Amos P. K. Tai, David H. Y. Yung, and Timothy Lam
Geosci. Model Dev., 17, 3733–3764, https://doi.org/10.5194/gmd-17-3733-2024, https://doi.org/10.5194/gmd-17-3733-2024, 2024
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We have developed the Terrestrial Ecosystem Model in R (TEMIR), which simulates plant carbon and pollutant uptake and predicts their response to varying atmospheric conditions. This model is designed to couple with an atmospheric chemistry model so that questions related to plant–atmosphere interactions, such as the effects of climate change, rising CO2, and ozone pollution on forest carbon uptake, can be addressed. The model has been well validated with both ground and satellite observations.
Fabian Stenzel, Johanna Braun, Jannes Breier, Karlheinz Erb, Dieter Gerten, Jens Heinke, Sarah Matej, Sebastian Ostberg, Sibyll Schaphoff, and Wolfgang Lucht
Geosci. Model Dev., 17, 3235–3258, https://doi.org/10.5194/gmd-17-3235-2024, https://doi.org/10.5194/gmd-17-3235-2024, 2024
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We provide an R package to compute two biosphere integrity metrics that can be applied to simulations of vegetation growth from the dynamic global vegetation model LPJmL. The pressure metric BioCol indicates that we humans modify and extract > 20 % of the potential preindustrial natural biomass production. The ecosystems state metric EcoRisk shows a high risk of ecosystem destabilization in many regions as a result of climate change and land, water, and fertilizer use.
Elin Ristorp Aas, Heleen A. de Wit, and Terje K. Berntsen
Geosci. Model Dev., 17, 2929–2959, https://doi.org/10.5194/gmd-17-2929-2024, https://doi.org/10.5194/gmd-17-2929-2024, 2024
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By including microbial processes in soil models, we learn how the soil system interacts with its environment and responds to climate change. We present a soil process model, MIMICS+, which is able to reproduce carbon stocks found in boreal forest soils better than a conventional land model. With the model we also find that when adding nitrogen, the relationship between soil microbes changes notably. Coupling the model to a vegetation model will allow for further study of these mechanisms.
Thomas Wutzler, Christian Reimers, Bernhard Ahrens, and Marion Schrumpf
Geosci. Model Dev., 17, 2705–2725, https://doi.org/10.5194/gmd-17-2705-2024, https://doi.org/10.5194/gmd-17-2705-2024, 2024
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Soil microbes provide a strong link for elemental fluxes in the earth system. The SESAM model applies an optimality assumption to model those linkages and their adaptation. We found that a previous heuristic description was a special case of a newly developed more rigorous description. The finding of new behaviour at low microbial biomass led us to formulate the constrained enzyme hypothesis. We now can better describe how microbially mediated linkages of elemental fluxes adapt across decades.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
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Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Yannek Käber, Florian Hartig, and Harald Bugmann
Geosci. Model Dev., 17, 2727–2753, https://doi.org/10.5194/gmd-17-2727-2024, https://doi.org/10.5194/gmd-17-2727-2024, 2024
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Many forest models include detailed mechanisms of forest growth and mortality, but regeneration is often simplified. Testing and improving forest regeneration models is challenging. We address this issue by exploring how forest inventories from unmanaged European forests can be used to improve such models. We find that competition for light among trees is captured by the model, unknown model components can be informed by forest inventory data, and climatic effects are challenging to capture.
Jalisha T. Kallingal, Johan Lindström, Paul A. Miller, Janne Rinne, Maarit Raivonen, and Marko Scholze
Geosci. Model Dev., 17, 2299–2324, https://doi.org/10.5194/gmd-17-2299-2024, https://doi.org/10.5194/gmd-17-2299-2024, 2024
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By unlocking the mysteries of CH4 emissions from wetlands, our work improved the accuracy of the LPJ-GUESS vegetation model using Bayesian statistics. Via assimilation of long-term real data from a wetland, we significantly enhanced CH4 emission predictions. This advancement helps us better understand wetland contributions to atmospheric CH4, which are crucial for addressing climate change. Our method offers a promising tool for refining global climate models and guiding conservation efforts
Benjamin Post, Esteban Acevedo-Trejos, Andrew D. Barton, and Agostino Merico
Geosci. Model Dev., 17, 1175–1195, https://doi.org/10.5194/gmd-17-1175-2024, https://doi.org/10.5194/gmd-17-1175-2024, 2024
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Creating computational models of how phytoplankton grows in the ocean is a technical challenge. We developed a new tool set (Xarray-simlab-ODE) for building such models using the programming language Python. We demonstrate the tool set in a library of plankton models (Phydra). Our goal was to allow scientists to develop models quickly, while also allowing the model structures to be changed easily. This allows us to test many different structures of our models to find the most appropriate one.
Taeken Wijmer, Ahmad Al Bitar, Ludovic Arnaud, Remy Fieuzal, and Eric Ceschia
Geosci. Model Dev., 17, 997–1021, https://doi.org/10.5194/gmd-17-997-2024, https://doi.org/10.5194/gmd-17-997-2024, 2024
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Quantification of carbon fluxes of crops is an essential building block for the construction of a monitoring, reporting, and verification approach. We developed an end-to-end platform (AgriCarbon-EO) that assimilates, through a Bayesian approach, high-resolution (10 m) optical remote sensing data into radiative transfer and crop modelling at regional scale (100 x 100 km). Large-scale estimates of carbon flux are validated against in situ flux towers and yield maps and analysed at regional scale.
Moritz Laub, Sergey Blagodatsky, Marijn Van de Broek, Samuel Schlichenmaier, Benjapon Kunlanit, Johan Six, Patma Vityakon, and Georg Cadisch
Geosci. Model Dev., 17, 931–956, https://doi.org/10.5194/gmd-17-931-2024, https://doi.org/10.5194/gmd-17-931-2024, 2024
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To manage soil organic matter (SOM) sustainably, we need a better understanding of the role that soil microbes play in aggregate protection. Here, we propose the SAMM model, which connects soil aggregate formation to microbial growth. We tested it against data from a tropical long-term experiment and show that SAMM effectively represents the microbial growth, SOM, and aggregate dynamics and that it can be used to explore the importance of aggregate formation in SOM stabilization.
Dongyu Zheng, Andrew Merdith, Yves Goddéris, Yannick Donnadieu, Khushboo Gurung, and Benjamin J. W. Mills
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-230, https://doi.org/10.5194/gmd-2023-230, 2024
Revised manuscript accepted for GMD
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This study uses a deep learning method to enhance the time resolution of paleoclimate simulations to 1 million years. This improved resolution allows a climate-biogeochemical model for more accurate predictions of climate shifts. The method may be critical in developing new fully-continuous methods that are able to translate over a moving continental surface in deep time with high-resolution at a reasonable computational expense.
Jianhong Lin, Daniel Berveiller, Christophe François, Heikki Hänninen, Alexandre Morfin, Gaëlle Vincent, Rui Zhang, Cyrille Rathgeber, and Nicolas Delpierre
Geosci. Model Dev., 17, 865–879, https://doi.org/10.5194/gmd-17-865-2024, https://doi.org/10.5194/gmd-17-865-2024, 2024
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Currently, the high variability of budburst between individual trees is overlooked. The consequences of this neglect when projecting the dynamics and functioning of tree communities are unknown. Here we develop the first process-oriented model to describe the difference in budburst dates between individual trees in plant populations. Beyond budburst, the model framework provides a basis for studying the dynamics of phenological traits under climate change, from the individual to the community.
Skyler Kern, Mary E. McGuinn, Katherine M. Smith, Nadia Pinardi, Kyle E. Niemeyer, Nicole S. Lovenduski, and Peter E. Hamlington
Geosci. Model Dev., 17, 621–649, https://doi.org/10.5194/gmd-17-621-2024, https://doi.org/10.5194/gmd-17-621-2024, 2024
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Computational models are used to simulate the behavior of marine ecosystems. The models often have unknown parameters that need to be calibrated to accurately represent observational data. Here, we propose a novel approach to simultaneously determine a large set of parameters for a one-dimensional model of a marine ecosystem in the surface ocean at two contrasting sites. By utilizing global and local optimization techniques, we estimate many parameters in a computationally efficient manner.
Shuaitao Wang, Vincent Thieu, Gilles Billen, Josette Garnier, Marie Silvestre, Audrey Marescaux, Xingcheng Yan, and Nicolas Flipo
Geosci. Model Dev., 17, 449–476, https://doi.org/10.5194/gmd-17-449-2024, https://doi.org/10.5194/gmd-17-449-2024, 2024
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This paper presents unified RIVE v1.0, a unified version of the freshwater biogeochemistry model RIVE. It harmonizes different RIVE implementations, providing the referenced formalisms for microorganism activities to describe full biogeochemical cycles in the water column (e.g., carbon, nutrients, oxygen). Implemented as open-source projects in Python 3 (pyRIVE 1.0) and ANSI C (C-RIVE 0.32), unified RIVE v1.0 promotes and enhances collaboration among research teams and public services.
Jorn Bruggeman, Karsten Bolding, Lars Nerger, Anna Teruzzi, Simone Spada, Jozef Skákala, and Stefano Ciavatta
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-238, https://doi.org/10.5194/gmd-2023-238, 2023
Revised manuscript accepted for GMD
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To understand and predict the ocean’s capacity for carbon sequestration, its ability to supply food, and its response to climate change, we need the best possible estimate of its physical and biogeochemical properties. This is obtained through “data assimilation”, which blends numerical models and observations. Here, we present EAT, a flexible and efficient testbed that allows any scientist to explore and further develop the state-of-the-art in data assimilation.
Sam S. Rabin, William J. Sacks, Danica L. Lombardozzi, Lili Xia, and Alan Robock
Geosci. Model Dev., 16, 7253–7273, https://doi.org/10.5194/gmd-16-7253-2023, https://doi.org/10.5194/gmd-16-7253-2023, 2023
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Climate models can help us simulate how the agricultural system will be affected by and respond to environmental change, but to be trustworthy they must realistically reproduce historical patterns. When farmers plant their crops and what varieties they choose will be important aspects of future adaptation. Here, we improve the crop component of a global model to better simulate observed growing seasons and examine the impacts on simulated crop yields and irrigation demand.
Weihang Liu, Tao Ye, Christoph Müller, Jonas Jägermeyr, James A. Franke, Haynes Stephens, and Shuo Chen
Geosci. Model Dev., 16, 7203–7221, https://doi.org/10.5194/gmd-16-7203-2023, https://doi.org/10.5194/gmd-16-7203-2023, 2023
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We develop a machine-learning-based crop model emulator with the inputs and outputs of multiple global gridded crop model ensemble simulations to capture the year-to-year variation of crop yield under future climate change. The emulator can reproduce the year-to-year variation of simulated yield given by the crop models under CO2, temperature, water, and nitrogen perturbations. Developing this emulator can provide a tool to project future climate change impact in a simple way.
Jurjen Rooze, Heewon Jung, and Hagen Radtke
Geosci. Model Dev., 16, 7107–7121, https://doi.org/10.5194/gmd-16-7107-2023, https://doi.org/10.5194/gmd-16-7107-2023, 2023
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Chemical particles in nature have properties such as age or reactivity. Distributions can describe the properties of chemical concentrations. In nature, they are affected by mixing processes, such as chemical diffusion, burrowing animals, and bottom trawling. We derive equations for simulating the effect of mixing on central moments that describe the distributions. We then demonstrate applications in which these equations are used to model continua in disturbed natural environments.
Jacquelyn K. Shuman, Rosie A. Fisher, Charles D. Koven, Ryan G. Knox, Lara M. Kueppers, and Chonggang Xu
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-191, https://doi.org/10.5194/gmd-2023-191, 2023
Revised manuscript accepted for GMD
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We adapt a fire-behavior and effects module for use in a size-structured vegetation demographic model to test how climate, fire regime and fire-tolerance plant traits interact to determine the distribution of tropical forests and grasslands. Our model captures the connection between fire disturbance and plant fire-tolerance strategies in determining plant distribution and provides a useful tool for understanding the vulnerability of these areas under changing conditions across the tropics.
Esteban Acevedo-Trejos, Jean Braun, Katherine Kravitz, N. Alexia Raharinirina, and Benoît Bovy
Geosci. Model Dev., 16, 6921–6941, https://doi.org/10.5194/gmd-16-6921-2023, https://doi.org/10.5194/gmd-16-6921-2023, 2023
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The interplay of tectonics and climate influences the evolution of life and the patterns of biodiversity we observe on earth's surface. Here we present an adaptive speciation component coupled with a landscape evolution model that captures the essential earth-surface, ecological, and evolutionary processes that lead to the diversification of taxa. We can illustrate with our tool how life and landforms co-evolve to produce distinct biodiversity patterns on geological timescales.
Veli Çağlar Yumruktepe, Erik Askov Mousing, Jerry Tjiputra, and Annette Samuelsen
Geosci. Model Dev., 16, 6875–6897, https://doi.org/10.5194/gmd-16-6875-2023, https://doi.org/10.5194/gmd-16-6875-2023, 2023
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We present an along BGC-Argo track 1D modelling framework. The model physics is constrained by the BGC-Argo temperature and salinity profiles to reduce the uncertainties related to mixed layer dynamics, allowing the evaluation of the biogeochemical formulation and parameterization. We objectively analyse the model with BGC-Argo and satellite data and improve the model biogeochemical dynamics. We present the framework, example cases and routines for model improvement and implementations.
Tanya J. R. Lippmann, Ype van der Velde, Monique M. P. D. Heijmans, Han Dolman, Dimmie M. D. Hendriks, and Ko van Huissteden
Geosci. Model Dev., 16, 6773–6804, https://doi.org/10.5194/gmd-16-6773-2023, https://doi.org/10.5194/gmd-16-6773-2023, 2023
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Vegetation is a critical component of carbon storage in peatlands but an often-overlooked concept in many peatland models. We developed a new model capable of simulating the response of vegetation to changing environments and management regimes. We evaluated the model against observed chamber data collected at two peatland sites. We found that daily air temperature, water level, harvest frequency and height, and vegetation composition drive methane and carbon dioxide emissions.
Chonggang Xu, Bradley Christoffersen, Zachary Robbins, Ryan Knox, Rosie A. Fisher, Rutuja Chitra-Tarak, Martijn Slot, Kurt Solander, Lara Kueppers, Charles Koven, and Nate McDowell
Geosci. Model Dev., 16, 6267–6283, https://doi.org/10.5194/gmd-16-6267-2023, https://doi.org/10.5194/gmd-16-6267-2023, 2023
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We introduce a plant hydrodynamic model for the U.S. Department of Energy (DOE)-sponsored model, the Functionally Assembled Terrestrial Ecosystem Simulator (FATES). To better understand this new model system and its functionality in tropical forest ecosystems, we conducted a global parameter sensitivity analysis at Barro Colorado Island, Panama. We identified the key parameters that affect the simulated plant hydrodynamics to guide both modeling and field campaign studies.
Jianghui Du
Geosci. Model Dev., 16, 5865–5894, https://doi.org/10.5194/gmd-16-5865-2023, https://doi.org/10.5194/gmd-16-5865-2023, 2023
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Trace elements and isotopes (TEIs) are important tools to study the changes in the ocean environment both today and in the past. However, the behaviors of TEIs in marine sediments are poorly known, limiting our ability to use them in oceanography. Here we present a modeling framework that can be used to generate and run models of the sedimentary cycling of TEIs assisted with advanced numerical tools in the Julia language, lowering the coding barrier for the general user to study marine TEIs.
Siyu Zhu, Peipei Wu, Siyi Zhang, Oliver Jahn, Shu Li, and Yanxu Zhang
Geosci. Model Dev., 16, 5915–5929, https://doi.org/10.5194/gmd-16-5915-2023, https://doi.org/10.5194/gmd-16-5915-2023, 2023
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In this study, we estimate the global biogeochemical cycling of Hg in a state-of-the-art physical-ecosystem ocean model (high-resolution-MITgcm/Hg), providing a more accurate portrayal of surface Hg concentrations in estuarine and coastal areas, strong western boundary flow and upwelling areas, and concentration diffusion as vortex shapes. The high-resolution model can help us better predict the transport and fate of Hg in the ocean and its impact on the global Hg cycle.
Maria Val Martin, Elena Blanc-Betes, Ka Ming Fung, Euripides P. Kantzas, Ilsa B. Kantola, Isabella Chiaravalloti, Lyla L. Taylor, Louisa K. Emmons, William R. Wieder, Noah J. Planavsky, Michael D. Masters, Evan H. DeLucia, Amos P. K. Tai, and David J. Beerling
Geosci. Model Dev., 16, 5783–5801, https://doi.org/10.5194/gmd-16-5783-2023, https://doi.org/10.5194/gmd-16-5783-2023, 2023
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Enhanced rock weathering (ERW) is a CO2 removal strategy that involves applying crushed rocks (e.g., basalt) to agricultural soils. However, unintended processes within the N cycle due to soil pH changes may affect the climate benefits of C sequestration. ERW could drive changes in soil emissions of non-CO2 GHGs (N2O) and trace gases (NO and NH3) that may affect air quality. We present a new improved N cycling scheme for the land model (CLM5) to evaluate ERW effects on soil gas N emissions.
Özgür Gürses, Laurent Oziel, Onur Karakuş, Dmitry Sidorenko, Christoph Völker, Ying Ye, Moritz Zeising, Martin Butzin, and Judith Hauck
Geosci. Model Dev., 16, 4883–4936, https://doi.org/10.5194/gmd-16-4883-2023, https://doi.org/10.5194/gmd-16-4883-2023, 2023
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This paper assesses the biogeochemical model REcoM3 coupled to the ocean–sea ice model FESOM2.1. The model can be used to simulate the carbon uptake or release of the ocean on timescales of several hundred years. A detailed analysis of the nutrients, ocean productivity, and ecosystem is followed by the carbon cycle. The main conclusion is that the model performs well when simulating the observed mean biogeochemical state and variability and is comparable to other ocean–biogeochemical models.
Hocheol Seo and Yeonjoo Kim
Geosci. Model Dev., 16, 4699–4713, https://doi.org/10.5194/gmd-16-4699-2023, https://doi.org/10.5194/gmd-16-4699-2023, 2023
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Wildfire is a crucial factor in carbon and water fluxes on the Earth system. About 2.1 Pg of carbon is released into the atmosphere by wildfires annually. Because the fire processes are still limitedly represented in land surface models, we forced the daily GFED4 burned area into the land surface model over Alaska and Siberia. The results with the GFED4 burned area significantly improved the simulated carbon emissions and net ecosystem exchange compared to the default simulation.
Boris Ťupek, Aleksi Lehtonen, Alla Yurova, Rose Abramoff, Stefano Manzoni, Bertrand Guenet, Elisa Bruni, Samuli Launiainen, Mikko Peltoniemi, Shoji Hashimoto, Xianglin Tian, Juha Heikkinen, Kari Minkkinen, and Raisa Mäkipää
EGUsphere, https://doi.org/10.5194/egusphere-2023-1523, https://doi.org/10.5194/egusphere-2023-1523, 2023
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Improving representation of peatlands in Earth system models (ESMs) (e.g., in Yasso soil C model coupled with JSBACH model) is rare. We updated Yasso07 moisture dependency for applications on both the mineral soils and peatlands of boreal forest. Our moisture function improved the simulated peatland C stocks and CO2 dynamics. However, due to nature of the measurements used for Bayesian MCMC data assimilation, it contrasts with functions in other ESMs (see graphical abstract).
Hideki Ninomiya, Tomomichi Kato, Lea Végh, and Lan Wu
Geosci. Model Dev., 16, 4155–4170, https://doi.org/10.5194/gmd-16-4155-2023, https://doi.org/10.5194/gmd-16-4155-2023, 2023
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Non-structural carbohydrates (NSCs) play a crucial role in plants to counteract the effects of climate change. We added a new NSC module into the SEIB-DGVM, an individual-based ecosystem model. The simulated NSC levels and their seasonal patterns show a strong agreement with observed NSC data at both point and global scales. The model can be used to simulate the biotic effects resulting from insufficient NSCs, which are otherwise difficult to measure in terrestrial ecosystems globally.
Miquel De Cáceres, Roberto Molowny-Horas, Antoine Cabon, Jordi Martínez-Vilalta, Maurizio Mencuccini, Raúl García-Valdés, Daniel Nadal-Sala, Santiago Sabaté, Nicolas Martin-StPaul, Xavier Morin, Francesco D'Adamo, Enric Batllori, and Aitor Améztegui
Geosci. Model Dev., 16, 3165–3201, https://doi.org/10.5194/gmd-16-3165-2023, https://doi.org/10.5194/gmd-16-3165-2023, 2023
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Regional-level applications of dynamic vegetation models are challenging because they need to accommodate the variation in plant functional diversity. This can be done by estimating parameters from available plant trait databases while adopting alternative solutions for missing data. Here we present the design, parameterization and evaluation of MEDFATE (version 2.9.3), a novel model of forest dynamics for its application over a region in the western Mediterranean Basin.
Jens Heinke, Susanne Rolinski, and Christoph Müller
Geosci. Model Dev., 16, 2455–2475, https://doi.org/10.5194/gmd-16-2455-2023, https://doi.org/10.5194/gmd-16-2455-2023, 2023
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We develop a livestock module for the global vegetation model LPJmL5.0 to simulate the impact of grazing dairy cattle on carbon and nitrogen cycles in grasslands. A novelty of the approach is that it accounts for the effect of feed quality on feed uptake and feed utilization by animals. The portioning of dietary nitrogen into milk, feces, and urine shows very good agreement with estimates obtained from animal trials.
Yimian Ma, Xu Yue, Stephen Sitch, Nadine Unger, Johan Uddling, Lina M. Mercado, Cheng Gong, Zhaozhong Feng, Huiyi Yang, Hao Zhou, Chenguang Tian, Yang Cao, Yadong Lei, Alexander W. Cheesman, Yansen Xu, and Maria Carolina Duran Rojas
Geosci. Model Dev., 16, 2261–2276, https://doi.org/10.5194/gmd-16-2261-2023, https://doi.org/10.5194/gmd-16-2261-2023, 2023
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Plants have been found to respond differently to O3, but the variations in the sensitivities have rarely been explained nor fully implemented in large-scale assessment. This study proposes a new O3 damage scheme with leaf mass per area to unify varied sensitivities for all plant species. Our assessment reveals an O3-induced reduction of 4.8 % in global GPP, with the highest reduction of >10 % for cropland, suggesting an emerging risk of crop yield loss under the threat of O3 pollution.
Winslow D. Hansen, Adrianna Foster, Benjamin Gaglioti, Rupert Seidl, and Werner Rammer
Geosci. Model Dev., 16, 2011–2036, https://doi.org/10.5194/gmd-16-2011-2023, https://doi.org/10.5194/gmd-16-2011-2023, 2023
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Permafrost and the thick soil-surface organic layers that insulate permafrost are important controls of boreal forest dynamics and carbon cycling. However, both are rarely included in process-based vegetation models used to simulate future ecosystem trajectories. To address this challenge, we developed a computationally efficient permafrost and soil organic layer module that operates at fine spatial (1 ha) and temporal (daily) resolutions.
Heewon Jung, Hyun-Seob Song, and Christof Meile
Geosci. Model Dev., 16, 1683–1696, https://doi.org/10.5194/gmd-16-1683-2023, https://doi.org/10.5194/gmd-16-1683-2023, 2023
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Microbial activity responsible for many chemical transformations depends on environmental conditions. These can vary locally, e.g., between poorly connected pores in porous media. We present a modeling framework that resolves such small spatial scales explicitly, accounts for feedback between transport and biogeochemical conditions, and can integrate state-of-the-art representations of microbes in a computationally efficient way, making it broadly applicable in science and engineering use cases.
Arthur Guignabert, Quentin Ponette, Frédéric André, Christian Messier, Philippe Nolet, and Mathieu Jonard
Geosci. Model Dev., 16, 1661–1682, https://doi.org/10.5194/gmd-16-1661-2023, https://doi.org/10.5194/gmd-16-1661-2023, 2023
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Spatially explicit and process-based models are useful to test innovative forestry practices under changing and uncertain conditions. However, their larger use is often limited by the restricted range of species and stand structures they can reliably account for. We therefore calibrated and evaluated such a model, HETEROFOR, for 23 species across southern Québec. Our results showed that the model is robust and can predict accurately both individual tree growth and stand dynamics in this region.
Maureen Beaudor, Nicolas Vuichard, Juliette Lathière, Nikolaos Evangeliou, Martin Van Damme, Lieven Clarisse, and Didier Hauglustaine
Geosci. Model Dev., 16, 1053–1081, https://doi.org/10.5194/gmd-16-1053-2023, https://doi.org/10.5194/gmd-16-1053-2023, 2023
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Ammonia mainly comes from the agricultural sector, and its volatilization relies on environmental variables. Our approach aims at benefiting from an Earth system model framework to estimate it. By doing so, we represent a consistent spatial distribution of the emissions' response to environmental changes.
We greatly improved the seasonal cycle of emissions compared with previous work. In addition, our model includes natural soil emissions (that are rarely represented in modeling approaches).
Rui Ying, Fanny M. Monteiro, Jamie D. Wilson, and Daniela N. Schmidt
Geosci. Model Dev., 16, 813–832, https://doi.org/10.5194/gmd-16-813-2023, https://doi.org/10.5194/gmd-16-813-2023, 2023
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Planktic foraminifera are marine-calcifying zooplankton; their shells are widely used to measure past temperature and productivity. We developed ForamEcoGEnIE 2.0 to simulate the four subgroups of this organism. We found that the relative abundance distribution agrees with marine sediment core-top data and that carbon export and biomass are close to sediment trap and plankton net observations respectively. This model provides the opportunity to study foraminiferal ecology in any geological era.
Onur Kerimoglu, Markus Pahlow, Prima Anugerahanti, and Sherwood Lan Smith
Geosci. Model Dev., 16, 95–108, https://doi.org/10.5194/gmd-16-95-2023, https://doi.org/10.5194/gmd-16-95-2023, 2023
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In classical models that track the changes in the elemental composition of phytoplankton, additional state variables are required for each element resolved. In this study, we show how the behavior of such an explicit model can be approximated using an
instantaneous acclimationapproach, in which the elemental composition of the phytoplankton is assumed to adjust to an optimal value instantaneously. Through rigorous tests, we evaluate the consistency of this scheme.
Yuan Zhang, Devaraju Narayanappa, Philippe Ciais, Wei Li, Daniel Goll, Nicolas Vuichard, Martin G. De Kauwe, Laurent Li, and Fabienne Maignan
Geosci. Model Dev., 15, 9111–9125, https://doi.org/10.5194/gmd-15-9111-2022, https://doi.org/10.5194/gmd-15-9111-2022, 2022
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There are a few studies to examine if current models correctly represented the complex processes of transpiration. Here, we use a coefficient Ω, which indicates if transpiration is mainly controlled by vegetation processes or by turbulence, to evaluate the ORCHIDEE model. We found a good performance of ORCHIDEE, but due to compensation of biases in different processes, we also identified how different factors control Ω and where the model is wrong. Our method is generic to evaluate other models.
Thomas Neumann, Hagen Radtke, Bronwyn Cahill, Martin Schmidt, and Gregor Rehder
Geosci. Model Dev., 15, 8473–8540, https://doi.org/10.5194/gmd-15-8473-2022, https://doi.org/10.5194/gmd-15-8473-2022, 2022
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Marine ecosystem models are usually constrained by the elements nitrogen and phosphorus and consider carbon in organic matter in a fixed ratio. Recent observations show a substantial deviation from the simulated carbon cycle variables. In this study, we present a marine ecosystem model for the Baltic Sea which allows for a flexible uptake ratio for carbon, nitrogen, and phosphorus. With this extension, the model reflects much more reasonable variables of the marine carbon cycle.
Arsène Druel, Simon Munier, Anthony Mucia, Clément Albergel, and Jean-Christophe Calvet
Geosci. Model Dev., 15, 8453–8471, https://doi.org/10.5194/gmd-15-8453-2022, https://doi.org/10.5194/gmd-15-8453-2022, 2022
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Crop phenology and irrigation is implemented into a land surface model able to work at a global scale. A case study is presented over Nebraska (USA). Simulations with and without the new scheme are compared to different satellite-based observations. The model is able to produce a realistic yearly irrigation water amount. The irrigation scheme improves the simulated leaf area index, gross primary productivity, evapotransipiration, and land surface temperature.
Thomas Wutzler, Lin Yu, Marion Schrumpf, and Sönke Zaehle
Geosci. Model Dev., 15, 8377–8393, https://doi.org/10.5194/gmd-15-8377-2022, https://doi.org/10.5194/gmd-15-8377-2022, 2022
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Soil microbes process soil organic matter and affect carbon storage and plant nutrition at the ecosystem scale. We hypothesized that decadal dynamics is constrained by the ratios of elements in litter inputs, microbes, and matter and that microbial community optimizes growth. This allowed the SESAM model to descibe decadal-term carbon sequestration in soils and other biogeochemical processes explicitly accounting for microbial processes but without its problematic fine-scale parameterization.
Ensheng Weng, Igor Aleinov, Ram Singh, Michael J. Puma, Sonali S. McDermid, Nancy Y. Kiang, Maxwell Kelley, Kevin Wilcox, Ray Dybzinski, Caroline E. Farrior, Stephen W. Pacala, and Benjamin I. Cook
Geosci. Model Dev., 15, 8153–8180, https://doi.org/10.5194/gmd-15-8153-2022, https://doi.org/10.5194/gmd-15-8153-2022, 2022
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We develop a demographic vegetation model to improve the representation of terrestrial vegetation dynamics and ecosystem biogeochemical cycles in the Goddard Institute for Space Studies ModelE. The individual-based competition for light and soil resources makes the modeling of eco-evolutionary optimality possible. This model will enable ModelE to simulate long-term biogeophysical and biogeochemical feedbacks between the climate system and land ecosystems at decadal to centurial temporal scales.
Yitong Yao, Emilie Joetzjer, Philippe Ciais, Nicolas Viovy, Fabio Cresto Aleina, Jerome Chave, Lawren Sack, Megan Bartlett, Patrick Meir, Rosie Fisher, and Sebastiaan Luyssaert
Geosci. Model Dev., 15, 7809–7833, https://doi.org/10.5194/gmd-15-7809-2022, https://doi.org/10.5194/gmd-15-7809-2022, 2022
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To facilitate more mechanistic modeling of drought effects on forest dynamics, our study implements a hydraulic module to simulate the vertical water flow, change in water storage and percentage loss of stem conductance (PLC). With the relationship between PLC and tree mortality, our model can successfully reproduce the large biomass drop observed under throughfall exclusion. Our hydraulic module provides promising avenues benefiting the prediction for mortality under future drought events.
Arthur Nicolaus Fendrich, Philippe Ciais, Emanuele Lugato, Marco Carozzi, Bertrand Guenet, Pasquale Borrelli, Victoria Naipal, Matthew McGrath, Philippe Martin, and Panos Panagos
Geosci. Model Dev., 15, 7835–7857, https://doi.org/10.5194/gmd-15-7835-2022, https://doi.org/10.5194/gmd-15-7835-2022, 2022
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Currently, spatially explicit models for soil carbon stock can simulate the impacts of several changes. However, they do not incorporate the erosion, lateral transport, and deposition (ETD) of soil material. The present work developed ETD formulation, illustrated model calibration and validation for Europe, and presented the results for a depositional site. We expect that our work advances ETD models' description and facilitates their reproduction and incorporation in land surface models.
Kazumi Ozaki, Devon B. Cole, Christopher T. Reinhard, and Eiichi Tajika
Geosci. Model Dev., 15, 7593–7639, https://doi.org/10.5194/gmd-15-7593-2022, https://doi.org/10.5194/gmd-15-7593-2022, 2022
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A new biogeochemical model (CANOPS-GRB v1.0) for assessing the redox stability and dynamics of the ocean–atmosphere system on geologic timescales has been developed. In this paper, we present a full description of the model and its performance. CANOPS-GRB is a useful tool for understanding the factors regulating atmospheric O2 level and has the potential to greatly refine our current understanding of Earth's oxygenation history.
Cited articles
Brooks, R. H. and Corey, A. T.: Hydraulic properties of porous media,
Hydrology Papers, No. 3, Colorado State university, Fort Collins, Colorado,
1964.
Brussaard, L., de Ruiter, P. C., and Brown, G. G.: Soil biodiversity for
agricultural sustainability, Agr. Ecosyst. Environ., 121, 233–244, 2007.
Chapin III, F. S., Matson, P. A., and Vitousek, P.: Principles of
terrestrial ecosystem ecology, Springer, New York, USA, 2011.
Childs, E.: The use of soil moisture characteristics in soil studies, Soil
Sci., 50, 239–252, 1940.
Clapp, R. B. and Hornberger, G. M.: Empirical Equations for Some Soil
Hydraulic-Properties, Water Resour. Res., 14, 601–604, 1978.
Coleman, D. C.: From peds to paradoxes: Linkages between soil biota and
their influences on ecological processes, Soil Biol. Biochem., 40, 271–289,
2008.
Cosby, B. J., Hornberger, G. M., Clapp, R. B., and Ginn, T. R.: A
Statistical Exploration of the Relationships of Soil-Moisture Characteristics
to the Physical-Properties of Soils, Water Resour. Res., 20, 682–690, 1984.
Craine, J. M., Wedin, D. A., and Chapin, F. S.: Predominance of
ecophysiological controls on soil CO2 flux in a Minnesota
grassland, Plant Soil, 207, 77–86, 1999.
De Kauwe, M. G., Medlyn, B. E., Zaehle, S., Walker, A. P., Dietze, M. C.,
Hickler, T., Jain, A. K., Luo, Y. Q., Parton, W. J., Prentice, I. C., Smith,
B., Thornton, P. E., Wang, S. S., Wang, Y. P., Warlind, D., Weng, E. S.,
Crous, K. Y., Ellsworth, D. S., Hanson, P. J., Seok Kim, H., Warren, J. M.,
Oren, R., and Norby, R. J.: Forest water use and water use efficiency at
elevated CO2: a model-data intercomparison at two contrasting
temperate forest FACE sites, Glob. Change Biol., 19, 1759–1779, 2013.
Duarte, H. F., Raczka, B. M., Ricciuto, D. M., Lin, J. C., Koven, C. D.,
Thornton, P. E., Bowling, D. R., Lai, C.-T., Bible, K. J., and Ehleringer, J.
R.: Evaluating the Community Land Model (CLM4.5) at a coniferous forest site
in northwestern United States using flux and carbon-isotope measurements,
Biogeosciences, 14, 4315–4340, https://doi.org/10.5194/bg-14-4315-2017,
2017.
Edwards, N. T. and Riggs, J. S.: Automated monitoring of soil respiration:
A moving chamber design, Soil Sci. Soc. Am. J., 67, 1266–1271, 2003.
E3SM Project: Energy Exascale Earth System Model (E3SM), available at: https://github.com/E3SM-Project/E3SM, last access: 7 March 2017.
Franzluebbers, A. J.: Microbial activity in response to water-filled pore
space of variably eroded southern Piedmont soils, Appl. Soil Ecol., 11,
91–101, 1999.
Fredlund, D. G. and Xing, A. Q.: Equations for the Soil-Water
Characteristic Curve, Can. Geotech. J., 31, 521–532, 1994.
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., Bloh, W. V., Brovkin, V.,
Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C.,
Joos, F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D.,
Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K.-G., Schnur,
R., Strassmann, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.:
Climate–Carbon Cycle Feedback Analysis: Results from the C4MIP Model
Intercomparison, J. Climate, 19, 3337–3353, https://doi.org/10.1175/jcli3800.1, 2006.
Ghezzehei, T. A., Sulman, B., Arnold, C. L., Bogie, N. A., and Berhe, A. A.:
On the role of soil water retention characteristic on aerobic microbial
respiration, Biogeosciences, 16, 1187–1209,
https://doi.org/10.5194/bg-16-1187-2019, 2019.
Grandy, A. S., Wieder, W. R., Wickings, K., and Kyker-Snowman, E.: Beyond
microbes: Are fauna the next frontier in soil biogeochemical models?, Soil
Biol. Biochem., 102, 40–44, 2016.
Gu, L., Hanson, P. J., Mac Post, W., and Liu, Q.: A novel approach for
identifying the true temperature sensitivity from soil respiration
measurements, Global Biogeochem. Cy., 22, GB4009, https://doi.org/10.1029/2007GB003164,
2008.
Gu, L. H., Pallardy, S. G., Yang, B., Hosman, K. P., Mao, J. F., Ricciuto,
D., Shi, X. Y., and Sun, Y.: Testing a land model in ecosystem functional
space via a comparison of observed and modeled ecosystem flux responses to
precipitation regimes and associated stresses in a Central US forest, J.
Geophys. Res.-Biogeo., 121, 1884–1902, 2016.
Hanson, P. J., O'Neill, E. G., Chambers, M. L. S., Riggs, J. S., Joslin, J.
D., and Wolfe, M. H.: Soil respiration and litter decomposition, in: North
American temperate deciduous forest responses to changing precipitation
regimes, Springer, 163–189, 2003.
Högberg, P., Nordgren, A., Buchmann, N., Taylor, A. F. S., Ekblad, A.,
Hogberg, M. N., Nyberg, G., Ottosson-Lofvenius, M., and Read, D. J.:
Large-scale forest girdling shows that current photosynthesis drives soil
respiration, Nature, 411, 789–792, 2001.
Holtan, H. N., England, C. B., Lawless, G. P., and Schumaker, G. A.:
Moisture-tension data for selected soils on experimental watersheds, Report ARS 41-144, ARS, US Department of Agriculture, Washington DC,
USA,
1968.
IPCC: Climate Change 2013: The Physical Science Basis. Contribution of
Working Group I to the Fifth Assessment Report of the Intergovernmental Panel
on Climate Change, Cambridge University Press, Cambridge, United Kingdom and
New York, NY, USA, 2013.
Jackson, R. B., Canadell, J., Ehleringer, J. R., Mooney, H. A., Sala, O. E.,
and Schulze, E. D.: A global analysis of root distributions for terrestrial
biomes, Oecologia, 108, 389–411, 1996.
Jones, C., Robertson, E., Arora, V., Friedlingstein, P., Shevliakova, E.,
Bopp, L., Brovkin, V., Hajima, T., Kato, E., Kawamiya, M., Liddicoat, S.,
Lindsay, K., Reick, C. H., Roelandt, C., Segschneider, J., and Tjiputra, J.:
Twenty-First-Century Compatible CO2 Emissions and Airborne Fraction
Simulated by CMIP5 Earth System Models under Four Representative
Concentration Pathways, J. Climate, 26, 4398–4413,
https://doi.org/10.1175/jcli-d-12-00554.1, 2013.
Kelting, D. L., Burger, J. A., and Edwards, G. S.: Estimating root
respiration, microbial respiration in the rhizosphere, and root-free soil
respiration in forest soils, Soil Biol. Biochem., 30, 961–968, 1998.
Kuzyakov, Y.: Separating microbial respiration of exudates from root
respiration in non-sterile soils: a comparison of four methods, Soil Biol.
Biochem., 34, 1621–1631, 2002.
Lasslop, G., Reichstein, M., Papale, D., Richardson, A. D., Arneth, A.,
Barr, A., Stoy, P., and Wohlfahrt, G.: Separation of net ecosystem exchange
into assimilation and respiration using a light response curve approach:
critical issues and global evaluation, Glob. Change Biol., 16, 187–208,
https://doi.org/10.1111/j.1365-2486.2009.02041.x, 2010.
Lawrence, D. M. and Slater, A. G.: Incorporating organic soil into a global
climate model, Clim. Dynam., 30, 145–160, 2008.
Lennon, J. T. and Jones, S. E.: Microbial seed banks: the ecological and
evolutionary implications of dormancy, Nat. Rev. Microbiol., 9, 119–130,
2011.
Linn, D. M. and Doran, J. W.: Effect of Water-Filled Pore-Space on
Carbon-Dioxide and Nitrous-Oxide Production in Tilled and Nontilled Soils,
Soil Sci. Soc. Am. J., 48, 1267–1272, 1984.
Lu, D., Ricciuto, D., Stoyanov, M., and Gu, L.: Calibration of the E3SM Land
Model Using Surrogate Based Global Optimization, J. Adv. Model. Earth Sy., 10,
1337–1356,
https://doi.org/10.1002/2017MS001134, 2018.
Luo, Y. and Zhou, X.: Soil respiration and the environment, Academic press,
2006.
Mao, J., Ricciuto, D. M., Thornton, P. E., Warren, J. M., King, A. W., Shi,
X., Iversen, C. M., and Norby, R. J.: Evaluating the Community Land Model in
a pine stand with shading manipulations and 13CO2 labeling,
Biogeosciences, 13, 641–657, https://doi.org/10.5194/bg-13-641-2016, 2016.
Monard, C., Mchergui, C., Nunan, N., Martin-Laurent, F., and Vieuble-Gonod,
L.: Impact of soil matric potential on the fine-scale spatial distribution
and activity of specific microbial degrader communities, Fems Microbiol.
Ecol., 81, 673–683, 2012.
Montané, F., Fox, A. M., Arellano, A. F., MacBean, N., Alexander, M. R.,
Dye, A., Bishop, D. A., Trouet, V., Babst, F., Hessl, A. E., Pederson, N.,
Blanken, P. D., Bohrer, G., Gough, C. M., Litvak, M. E., Novick, K. A.,
Phillips, R. P., Wood, J. D., and Moore, D. J. P.: Evaluating the effect of
alternative carbon allocation schemes in a land surface model (CLM4.5) on
carbon fluxes, pools, and turnover in temperate forests, Geosci. Model Dev.,
10, 3499–3517, https://doi.org/10.5194/gmd-10-3499-2017, 2017.
Moyano, F. E., Manzoni, S., and Chenu, C.: Responses of soil heterotrophic
respiration to moisture availability: An exploration of processes and models,
Soil Biol. Biochem., 59, 72–85, 2013.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M.,
Koven, C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S.,
Thornton, P. E., Bozbiyik, A., R., F., Heald, C. L., Kluzek, E., Lamarque, J.
F., Lawrence, P. J., Leung, L. R., Lipscomb, W., Muszala, S. P., Ricciuto, D.
M., Sacks, W. J., Sun, Y., Tang, J., and Yang, Z. L.: Technical Description
of Version 4.5 of the Community Land Model (CLM), NCAR Technical Note
NCAR/TN-503+ STR, Boulder, Colorado, 2013.
Powell, T. L., Galbraith, D. R., Christoffersen, B. O., Harper, A.,
Imbuzeiro, H. M. A., Rowland, L., Almeida, S., Brando, P. M., da Costa, A. C.
L., Costa, M. H., Levine, N. M., Malhi, Y., Saleska, S. R., Sotta, E.,
Williams, M., Meir, P., and Moorcroft, P. R.: Confronting model predictions
of carbon fluxes with measurements of Amazon forests subjected to
experimental drought, New Phytol., 200, 350–364, 2013.
Randerson, J. T., Hoffman, F. M., Thornton, P. E., Mahowald, N. M., Lindsay,
K., Lee, Y. H., Nevison, C. D., Doney, S. C., Bonan, G., Stockli, R., Covey,
C., Running, S. W., and Fung, I. Y.: Systematic assessment of terrestrial
biogeochemistry in coupled climate-carbon models, Glob. Change Biol., 15,
2462–2484, 2009.
Rawls, W., Yates, P., and Asmussen, L.: Calibration of selected infiltration
equations for the Georgia Coastal Plain, Report ARS-S-113 July 1976, 110 pp.,
2 fig, 8 tab, 25 ref, 1 append., 1976.
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M.,
Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A.,
Grünwald, T., Havránková, K., Ilvesniemi, H., Janous, D., Knohl, A.,
Laurila, T., Lohila, A., Loustau, D., Matteucci, G., Meyers, T., Miglietta,
F., Ourcival, J. M., Pumpanen, J., Rambal, S., Rotenberg, E., Sanz, M.,
Tenhunen, J., Seufert, G. n., Vaccari, F., Vesala, T., Yakir, D., and
Valentini, R.: On the separation of net ecosystem exchange into assimilation
and ecosystem respiration: Review and improved algorithm, Glob. Change Biol.,
11, 1424–1439, https://doi.org/10.1111/j.1365-2486.2005.001002.x, 2005.
Reichstein, M., Moffat, A. M., Wutzler, T., and Sickel, K.: REddyProc: Data
processing and plotting utilities of (half-)hourly eddy-covariance
measurements, R package version 1.0.0/r18, available at:
https://R-Forge.R-project.org/projects/reddyproc/, last access: 5 June
2017.
Reyes, W. M., Epstein, H. E., Li, X., McGlynn, B. L., Riveros-Iregui, D. A.,
and Emanuel, R. E.: Complex terrain influences ecosystem carbon responses to
temperature and precipitation, Global Biogeochem. Cy., 31, 1306–1317,
https://doi.org/10.1002/2017GB005658, 2017.
Richardson, A. D., Anderson, R. S., Arain, M. A., Barr, A. G., Bohrer, G.,
Chen, G. S., Chen, J. M., Ciais, P., Davis, K. J., Desai, A. R., Dietze, M.
C., Dragoni, D., Garrity, S. R., Gough, C. M., Grant, R., Hollinger, D. Y.,
Margolis, H. A., McCaughey, H., Migliavacca, M., Monson, R. K., Munger, J.
W., Poulter, B., Raczka, B. M., Ricciuto, D. M., Sahoo, A. K., Schaefer, K.,
Tian, H. Q., Vargas, R., Verbeeck, H., Xiao, J. F., and Xue, Y. K.:
Terrestrial biosphere models need better representation of vegetation
phenology: results from the North American Carbon Program Site Synthesis,
Glob. Change Biol., 18, 566–584, 2012.
Sierra, C. A., Malghani, S., and Loescher, H. W.: Interactions among
temperature, moisture, and oxygen concentrations in controlling decomposition
rates in a boreal forest soil, Biogeosciences, 14, 703–710,
https://doi.org/10.5194/bg-14-703-2017, 2017.
Stolpovsky, K., Martinez-Lavanchy, P., Heipieper, H. J., Van Cappellen, P.,
and Thullner, M.: Incorporating dormancy in dynamic microbial community
models, Ecol. Model., 222, 3092–3102, 2011.
Sun, L. J., Ataka, M., Kominami, Y., and Yoshimura, K.: Relationship between
fine-root exudation and respiration of two Quercus species in a Japanese
temperate forest, Tree Physiol. 37, 1011–1020, 2017.
Tian, H. Q., Lu, C. Q., Yang, J., Banger, K., Huntzinger, D. N., Schwalm, C.
R., Michalak, A. M., Cook, R., Ciais, P., Hayes, D., Huang, M. Y., Ito, A.,
Jain, A. K., Lei, H. M., Mao, J. F., Pan, S. F., Post, W. M., Peng, S. S.,
Poulter, B., Ren, W., Ricciuto, D., Schaefer, K., Shi, X. Y., Tao, B., Wang,
W. L., Wei, Y. X., Yang, Q. C., Zhang, B. W., and Zeng, N.: Global patterns
and controls of soil organic carbon dynamics as simulated by multiple
terrestrial biosphere models: Current status and future directions, Global
Biogeochem. Cy., 29, 775–792, 2015.
Todd-Brown, K. E. O., Randerson, J. T., Post, W. M., Hoffman, F. M.,
Tarnocai, C., Schuur, E. A. G., and Allison, S. D.: Causes of variation in
soil carbon simulations from CMIP5 Earth system models and comparison with
observations, Biogeosciences, 10, 1717–1736,
https://doi.org/10.5194/bg-10-1717-2013, 2013.
Todd-Brown, K. E. O., Randerson, J. T., Hopkins, F., Arora, V., Hajima, T.,
Jones, C., Shevliakova, E., Tjiputra, J., Volodin, E., Wu, T., Zhang, Q., and
Allison, S. D.: Changes in soil organic carbon storage predicted by Earth
system models during the 21st century, Biogeosciences, 11, 2341–2356,
https://doi.org/10.5194/bg-11-2341-2014, 2014.
Tuller, M. and Or, D.: Retention of water in soil and the soil water
characteristic curve, Encyclopedia of Soils in the Environment, 4, 278–289,
2004.
van Genuchten, M. T.: A Closed-Form Equation for Predicting the Hydraulic
Conductivity of Unsaturated Soils, Soil Sci. Soc. Am. J., 44, 892–898, 1980.
Verburg, P. S. J., Arnone, J. A., Obrist, D., Schorran, D. E., Evans, R. D.,
Leroux-Swarthout, D., Johnson, D. W., Luo, Y. Q., and Coleman, J. S.: Net
ecosystem carbon exchange in two experimental grassland ecosystems, Glob.
Change Biol., 10, 498–508, 2004.
Verhoef, H. A. and Brussaard, L.: Decomposition and Nitrogen Mineralization
in Natural and Agroecosystems – the Contribution of Soil Animals,
Biogeochemistry, 11, 175–211, 1990.
Walker, A. P., Hanson, P. J., De Kauwe, M. G., Medlyn, B. E., Zaehle, S.,
Asao, S., Dietze, M., Hickler, T., Huntingford, C., Iversen, C. M., Jain, A.,
Lomas, M., Luo, Y. Q., McCarthy, H., Parton, W. J., Prentice, I. C.,
Thornton, P. E., Wang, S. S., Wang, Y. P., Warlind, D., Weng, E. S., Warren,
J. M., Woodward, F. I., Oren, R., and Norby, R. J.: Comprehensive ecosystem
model-data synthesis using multiple data sets at two temperate forest
free-air CO2 enrichment experiments: Model performance at ambient
CO2 concentration, J. Geophys. Res.-Biogeo., 119, 937–964, 2014.
Wan, S. Q. and Luo, Y. Q.: Substrate regulation of soil respiration in a
tallgrass prairie: Results of a clipping and shading experiment, Global
Biogeochem. Cy., 17, 1054, https://doi.org/10.1029/2002GB001971, 2003.
Wang, G., Mayes, M. A., Gu, L., and Schadt, C. W.: Representation of dormant
and active microbial dynamics for ecosystem modeling, PloS one, 9, e89252,
https://doi.org/10.1371/journal.pone.0089252,
2014.
Wang, G., Jagadamma, S., Mayes, M. A., Schadt, C. W., Steinweg, J. M., Gu,
L., and Post, W. M.: Microbial dormancy improves development and experimental
validation of ecosystem model, ISME J., 9, 226–237, 2015.
Wenk, E. S., Callaham, M. A., O'Brien, J. J., and Hanson, P. J.: Soil
Macroinvertebrate Communities across a Productivity Gradient in Deciduous
Forests of Eastern North America, Northeast. Nat., 23, 25–44, 2016.
Wood, J., Knapp, B. O., Muzika, R.-M., Stambaugh, M. C., and Gu, L.: The
importance of drought-pathogen interactions in driving oak mortality events
in the Ozark Border Region, Environ. Res. Lett., 13, 015004,
https://doi.org/10.1088/1748-9326/aa94fa, 2017.
Xia, J., McGuire, A. D., Lawrence, D., Burke, E., Chen, G., Chen, X.,
Delire, C., Koven, C., MacDougall, A., Peng, S., Rinke, A., Saito, K., Zhang,
W., Alkama, R., Bohn, T. J., Ciais, P., Decharme, B., Gouttevin, I., Hajima,
T., Hayes, D. J., Huang, K., Ji, D., Krinner, G., Lettenmaier, D. P., Miller,
P. A., Moore, J. C., Smith, B., Sueyoshi, T., Shi, Z., Yan, L., Liang, J.,
Jiang, L., Zhang, Q., and Luo, Y.: Terrestrial ecosystem model performance in
simulating productivity and its vulnerability to climate change in the
northern permafrost region, J. Geophys. Res.-Biogeo., 122, 430–446,
https://doi.org/10.1002/2016JG003384, 2017.
Yan, Z. F., Bond-Lamberty, B., Todd-Brown, K. E., Bailey, V. L., Li, S. L.,
Liu, C. Q., and Liu, C. X.: A moisture function of soil heterotrophic
respiration that incorporates microscale processes, Nat. Commun., 9, 2562, https://doi.org/10.1038/s41467-018-04971-6,
2018.
Young, F. J., Radatz, C. A., and Marshall, C. A.: Soil survey of Boone
County, Missouri, U.S., Department of Agriculture, Natural Resources Conservation Service, Washington DC, USA,
2001.
Zaehle, S., Medlyn, B. E., De Kauwe, M. G., Walker, A. P., Dietze, M. C.,
Hickler, T., Luo, Y. Q., Wang, Y. P., El-Masri, B., Thornton, P., Jain, A.,
Wang, S. S., Warlind, D., Weng, E. S., Parton, W., Iversen, C. M.,
Gallet-Budynek, A., McCarthy, H., Finzi, A. C., Hanson, P. J., Prentice, I.
C., Oren, R., and Norby, R. J.: Evaluation of 11 terrestrial carbon-nitrogen
cycle models against observations from two temperate Free-Air CO2
Enrichment studies, New Phytol., 202, 803–822, 2014.
Short summary
Soil respiration, the second largest carbon fluxes between the atmosphere and land, is not well represented in global land models. In this study, using long-term observations at a temperate forest, we identified a solution for using better soil water potential simulations to improve predictions of soil respiration in the E3SM land model. In addition, parameter calibration further improved model performance.
Soil respiration, the second largest carbon fluxes between the atmosphere and land, is not well...
