Articles | Volume 11, issue 5
https://doi.org/10.5194/gmd-11-1909-2018
© Author(s) 2018. 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-11-1909-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model description paper
| 
28 May 2018
Model description paper |
| 28 May 2018
| 28 May 2018
Modeling soil CO2 production and transport with dynamic source and diffusion terms: testing the steady-state assumption using DETECT v1.0
Edmund M. Ryan
CORRESPONDING AUTHOR
Lancaster Environment Centre, Lancaster University, Lancaster, UK
School of Life Sciences, Arizona State University, Tempe, Arizona, USA
Kiona Ogle
School of Life Sciences, Arizona State University, Tempe, Arizona, USA
School of Informatics, Computing, and Cyber Systems, Northern Arizona
University, Flagstaff, Arizona, USA
Center for Ecosystem Science and Society, Northern Arizona University,
Flagstaff, Arizona, USA
Department of Biological Sciences, Northern Arizona University,
Flagstaff, Arizona, USA
Heather Kropp
Department of Geography, Colgate University, Hamilton, New York, USA
Kimberly E. Samuels-Crow
School of Informatics, Computing, and Cyber Systems, Northern Arizona
University, Flagstaff, Arizona, USA
Yolima Carrillo
Hawkesbury Institute for the Environment, Western Sydney University,
NSW, Australia
Elise Pendall
Hawkesbury Institute for the Environment, Western Sydney University,
NSW, Australia
Related authors
Edmund Ryan, Oliver Wild, Apostolos Voulgarakis, and Lindsay Lee
Geosci. Model Dev., 11, 3131–3146, https://doi.org/10.5194/gmd-11-3131-2018, https://doi.org/10.5194/gmd-11-3131-2018, 2018
Short summary
Short summary
Global sensitivity analysis (GSA) identifies which parameters of a model most affect its output. We performed GSA using statistical emulators as surrogates of two slow-running atmospheric chemistry transport models. Due to the high dimension of the model outputs, we considered two alternative methods: one that reduced the output dimension and one that did not require an emulator. The alternative methods accurately performed the GSA but were significantly faster than the emulator-only method.
Emiko K. Stuart, Laura Castañeda-Gómez, Wolfram Buss, Jeff R. Powell, and Yolima Carrillo
Biogeosciences, 21, 1037–1059, https://doi.org/10.5194/bg-21-1037-2024, https://doi.org/10.5194/bg-21-1037-2024, 2024
Short summary
Short summary
We inoculated wheat plants with various types of fungi whose impacts on soil carbon are poorly understood. After several months of growth, we examined both their impacts on soil carbon and the underlying mechanisms using multiple methods. Overall the fungi benefitted the storage of carbon in soil, mainly by improving the stability of pre-existing carbon, but several pathways were involved. This study demonstrates their importance for soil carbon storage and, therefore, climate change mitigation.
Jacob A. Nelson, Sophia Walther, Fabian Gans, Basil Kraft, Ulrich Weber, Kimberly Novick, Nina Buchmann, Mirco Migliavacca, Georg Wohlfahrt, Ladislav Šigut, Andreas Ibrom, Dario Papale, Mathias Göckede, Gregory Duveiller, Alexander Knohl, Lukas Hörtnagl, Russell L. Scott, Weijie Zhang, Zayd Mahmoud Hamdi, Markus Reichstein, Sergio Aranda-Barranco, Jonas Ardö, Maarten Op de Beeck, Dave Billdesbach, David Bowling, Rosvel Bracho, Christian Brümmer, Gustau Camps-Valls, Shiping Chen, Jamie Rose Cleverly, Ankur Desai, Gang Dong, Tarek S. El-Madany, Eugenie Susanne Euskirchen, Iris Feigenwinter, Marta Galvagno, Giacomo Gerosa, Bert Gielen, Ignacio Goded, Sarah Goslee, Christopher Michael Gough, Bernard Heinesch, Kazuhito Ichii, Marcin Antoni Jackowicz-Korczynski, Anne Klosterhalfen, Sara Knox, Hideki Kobayashi, Kukka-Maaria Kohonen, Mika Korkiakoski, Ivan Mammarella, Gharun Mana, Riccardo Marzuoli, Roser Matamala, Stefan Metzger, Leonardo Montagnani, Giacomo Nicolini, Thomas O'Halloran, Jean-Marc Ourcival, Matthias Peichl, Elise Pendall, Borja Ruiz Reverter, Marilyn Roland, Simone Sabbatini, Torsten Sachs, Marius Schmidt, Christopher R. Schwalm, Ankit Shekhar, Richard Silberstein, Maria Lucia Silveira, Donatella Spano, Torbern Tagesson, Gianluca Tramontana, Carlo Trotta, Fabio Turco, Timo Vesala, Caroline Vincke, Domenico Vitale, Enrique R. Vivoni, Yi Wang, William Woodgate, Enrico A. Yepez, Junhui Zhang, Donatella Zona, and Martin Jung
EGUsphere, https://doi.org/10.5194/egusphere-2024-165, https://doi.org/10.5194/egusphere-2024-165, 2024
Short summary
Short summary
The movement of water, carbon, and energy from the earth surface to the atmosphere, or flux, is an important process to understand that impacts all of our lives. Here we outline a method to estimate global water and CO2 fluxes based on direct measurements from site around the world called FLUXCOM-X. We go on to demonstrate how these new estimates of net CO2 uptake/loss, gross CO2 uptake, total water evaporation, and transpiration from plants compare to previous and independent estimates.
Johanna Pihlblad, Louise C. Andresen, Catriona A. Macdonald, David S. Ellsworth, and Yolima Carrillo
Biogeosciences, 20, 505–521, https://doi.org/10.5194/bg-20-505-2023, https://doi.org/10.5194/bg-20-505-2023, 2023
Short summary
Short summary
Elevated CO2 in the atmosphere increases forest biomass productivity when growth is not limited by soil nutrients. This study explores how mature trees stimulate soil availability of nitrogen and phosphorus with free-air carbon dioxide enrichment after 5 years of fumigation. We found that both nutrient availability and processes feeding available pools increased in the rhizosphere, and phosphorus increased at depth. This appears to not be by decomposition but by faster recycling of nutrients.
Jon Cranko Page, Martin G. De Kauwe, Gab Abramowitz, Jamie Cleverly, Nina Hinko-Najera, Mark J. Hovenden, Yao Liu, Andy J. Pitman, and Kiona Ogle
Biogeosciences, 19, 1913–1932, https://doi.org/10.5194/bg-19-1913-2022, https://doi.org/10.5194/bg-19-1913-2022, 2022
Short summary
Short summary
Although vegetation responds to climate at a wide range of timescales, models of the land carbon sink often ignore responses that do not occur instantly. In this study, we explore the timescales at which Australian ecosystems respond to climate. We identified that carbon and water fluxes can be modelled more accurately if we include environmental drivers from up to a year in the past. The importance of antecedent conditions is related to ecosystem aridity but is also influenced by other factors.
Martin G. De Kauwe, Belinda E. Medlyn, Andrew J. Pitman, John E. Drake, Anna Ukkola, Anne Griebel, Elise Pendall, Suzanne Prober, and Michael Roderick
Biogeosciences, 16, 903–916, https://doi.org/10.5194/bg-16-903-2019, https://doi.org/10.5194/bg-16-903-2019, 2019
Short summary
Short summary
Recent experimental evidence suggests that during heat extremes, trees may reduce photosynthesis to near zero but increase transpiration. Using eddy covariance data and examining the 3 days leading up to a temperature extreme, we found evidence of reduced photosynthesis and sustained or increased latent heat fluxes at Australian wooded flux sites. However, when focusing on heatwaves, we were unable to disentangle photosynthetic decoupling from the effect of increasing vapour pressure deficit.
Michael M. Loranty, Benjamin W. Abbott, Daan Blok, Thomas A. Douglas, Howard E. Epstein, Bruce C. Forbes, Benjamin M. Jones, Alexander L. Kholodov, Heather Kropp, Avni Malhotra, Steven D. Mamet, Isla H. Myers-Smith, Susan M. Natali, Jonathan A. O'Donnell, Gareth K. Phoenix, Adrian V. Rocha, Oliver Sonnentag, Ken D. Tape, and Donald A. Walker
Biogeosciences, 15, 5287–5313, https://doi.org/10.5194/bg-15-5287-2018, https://doi.org/10.5194/bg-15-5287-2018, 2018
Short summary
Short summary
Vegetation and soils strongly influence ground temperature in permafrost ecosystems across the Arctic and sub-Arctic. These effects will cause differences rates of permafrost thaw related to the distribution of tundra and boreal forests. As the distribution of forests and tundra change, the effects of climate change on permafrost will also change. We review the ecosystem processes that will influence permafrost thaw and outline how they will feed back to climate warming.
Edmund Ryan, Oliver Wild, Apostolos Voulgarakis, and Lindsay Lee
Geosci. Model Dev., 11, 3131–3146, https://doi.org/10.5194/gmd-11-3131-2018, https://doi.org/10.5194/gmd-11-3131-2018, 2018
Short summary
Short summary
Global sensitivity analysis (GSA) identifies which parameters of a model most affect its output. We performed GSA using statistical emulators as surrogates of two slow-running atmospheric chemistry transport models. Due to the high dimension of the model outputs, we considered two alternative methods: one that reduced the output dimension and one that did not require an emulator. The alternative methods accurately performed the GSA but were significantly faster than the emulator-only method.
Alexandre A. Renchon, Anne Griebel, Daniel Metzen, Christopher A. Williams, Belinda Medlyn, Remko A. Duursma, Craig V. M. Barton, Chelsea Maier, Matthias M. Boer, Peter Isaac, David Tissue, Victor Resco de Dios, and Elise Pendall
Biogeosciences, 15, 3703–3716, https://doi.org/10.5194/bg-15-3703-2018, https://doi.org/10.5194/bg-15-3703-2018, 2018
Short summary
Short summary
We report the seasonality of net ecosystem–atmosphere CO2 exchange (NEE) in a temperate evergreen broadleaved forest in Sydney, Australia. We investigated how carbon exchange varied with climatic drivers and canopy dynamics (leaf area index, litter fall). We found that our site acted as a net source of carbon in summer and a net sink in winter. Ecosystem respiration (ER) drove NEE seasonality, as the seasonal amplitude of ER was greater than gross primary productivity.
Eva van Gorsel, Sebastian Wolf, James Cleverly, Peter Isaac, Vanessa Haverd, Cäcilia Ewenz, Stefan Arndt, Jason Beringer, Víctor Resco de Dios, Bradley J. Evans, Anne Griebel, Lindsay B. Hutley, Trevor Keenan, Natascha Kljun, Craig Macfarlane, Wayne S. Meyer, Ian McHugh, Elise Pendall, Suzanne M. Prober, and Richard Silberstein
Biogeosciences, 13, 5947–5964, https://doi.org/10.5194/bg-13-5947-2016, https://doi.org/10.5194/bg-13-5947-2016, 2016
Short summary
Short summary
Temperature extremes are expected to become more prevalent in the future and understanding ecosystem response is crucial. We synthesised measurements and model results to investigate the effect of a summer heat wave on carbon and water exchange across three biogeographic regions in southern Australia. Forests proved relatively resilient to short-term heat extremes but the response of woodlands indicates that the carbon sinks of large areas of Australia may not be sustainable in a future climate.
Jason Beringer, Lindsay B. Hutley, Ian McHugh, Stefan K. Arndt, David Campbell, Helen A. Cleugh, James Cleverly, Víctor Resco de Dios, Derek Eamus, Bradley Evans, Cacilia Ewenz, Peter Grace, Anne Griebel, Vanessa Haverd, Nina Hinko-Najera, Alfredo Huete, Peter Isaac, Kasturi Kanniah, Ray Leuning, Michael J. Liddell, Craig Macfarlane, Wayne Meyer, Caitlin Moore, Elise Pendall, Alison Phillips, Rebecca L. Phillips, Suzanne M. Prober, Natalia Restrepo-Coupe, Susanna Rutledge, Ivan Schroder, Richard Silberstein, Patricia Southall, Mei Sun Yee, Nigel J. Tapper, Eva van Gorsel, Camilla Vote, Jeff Walker, and Tim Wardlaw
Biogeosciences, 13, 5895–5916, https://doi.org/10.5194/bg-13-5895-2016, https://doi.org/10.5194/bg-13-5895-2016, 2016
Short summary
Short summary
OzFlux is the regional Australian and New Zealand flux tower network that aims to provide a continental-scale national facility to monitor and assess trends, and improve predictions, of Australia’s terrestrial biosphere and climate. We describe the evolution, design, and status as well as an overview of data processing. We suggest that a synergistic approach is required to address all of the spatial, ecological, human, and cultural challenges of managing Australian ecosystems.
Related subject area
Climate and Earth system modeling
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Evaluation of CMIP6 model simulations of PM2.5 and its components over China
Assessment of a tiling energy budget approach in a land surface model, ORCHIDEE-MICT (r8205)
Multivariate adjustment of drizzle bias using machine learning in European climate projections
Development and evaluation of the interactive Model for Air Pollution and Land Ecosystems (iMAPLE) version 1.0
A perspective on the next generation of Earth system model scenarios: towards representative emission pathways (REPs)
Parallel SnowModel (v1.0): a parallel implementation of a distributed snow-evolution modeling system (SnowModel)
LB-SCAM: a learning-based method for efficient large-scale sensitivity analysis and tuning of the Single Column Atmosphere Model (SCAM)
Quantifying the impact of SST feedback frequency on Madden–Julian oscillation simulations
Systematic and objective evaluation of Earth system models: PCMDI Metrics Package (PMP) version 3
A revised model of global silicate weathering considering the influence of vegetation cover on erosion rate
A radiative–convective model computing precipitation with the maximum entropy production hypothesis
Leveraging regional mesh refinement to simulate future climate projections for California using the Simplified Convection-Permitting E3SM Atmosphere Model Version 0
Machine learning parameterization of the multi-scale Kain–Fritsch (MSKF) convection scheme and stable simulation coupled in the Weather Research and Forecasting (WRF) model using WRF–ML v1.0
Impacts of spatial heterogeneity of anthropogenic aerosol emissions in a regionally refined global aerosol–climate model
cfr (v2024.1.26): a Python package for climate field reconstruction
NEWTS1.0: Numerical model of coastal Erosion by Waves and Transgressive Scarps
Evaluation of isoprene emissions from the coupled model SURFEX–MEGANv2.1
A comprehensive Earth system model (AWI-ESM2.1) with interactive icebergs: effects on surface and deep-ocean characteristics
The regional climate–chemistry–ecology coupling model RegCM-Chem (v4.6)–YIBs (v1.0): development and application
An overview of cloud–radiation denial experiments for the Energy Exascale Earth System Model version 1
The computational and energy cost of simulation and storage for climate science: lessons from CMIP6
Subgrid-scale variability of cloud ice in the ICON-AES 1.3.00
INFERNO-peat v1.0.0: a representation of northern high-latitude peat fires in the JULES-INFERNO global fire model
The 4DEnVar-based weakly coupled land data assimilation system for E3SM version 2
Continental-scale bias-corrected climate and hydrological projections for Australia
G6-1.5K-SAI: a new Geoengineering Model Intercomparison Project (GeoMIP) experiment integrating recent advances in solar radiation modification studies
Modeling the effects of tropospheric ozone on the growth and yield of global staple crops with DSSAT v4.8.0
A one-dimensional urban flow model with an eddy-diffusivity mass-flux (EDMF) scheme and refined turbulent transport (MLUCM v3.0)
DCMIP2016: the tropical cyclone test case
Interactions between atmospheric composition and climate change – progress in understanding and future opportunities from AerChemMIP, PDRMIP, and RFMIP
Applying double-cropping and interactive irrigation in the North China Plain using WRF4.5
CD-type discretization for sea ice dynamics in FESOM version 2
Dynamic MJO forecasts using an ensemble subseasonal-to-seasonal forecast system of IAP-CAS model
CSDMS Data Components: data–model integration tools for Earth surface processes modeling
A generic algorithm to automatically classify urban fabric according to the local climate zone system: implementation in GeoClimate 0.0.1 and application to French cities
Modelling water isotopologues (1H2H16O, 1H217O) in the coupled numerical climate model iLOVECLIM (version 1.1.5)
Localized injections of interactive volcanic aerosols and their climate impacts in a simple general circulation model
CICERO Simple Climate Model (CICERO-SCM v1.1.1) – an improved simple climate model with a parameter calibration tool
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
Towards variance-conserving reconstructions of climate indices with Gaussian process regression in an embedding space
A diatom extension to the cGEnIE Earth system model – EcoGEnIE 1.1
Carbon isotopes in the marine biogeochemistry model FESOM2.1-REcoM3
Flux coupling approach on an exchange grid for the IOW Earth System Model (version 1.04.00) of the Baltic Sea region
Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model
New model ensemble reveals how forcing uncertainty and model structure alter climate simulated across CMIP generations of the Community Earth System Model
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024, https://doi.org/10.5194/gmd-17-5191-2024, 2024
Short summary
Short summary
Modeling global freshwater solid and nutrient loads, in both magnitude and form, is imperative for understanding emerging eutrophication problems. Such efforts, however, have been challenged by the difficulty of balancing details of freshwater biogeochemical processes with limited knowledge, input, and validation datasets. Here we develop a global freshwater model that resolves intertwined algae, solid, and nutrient dynamics and provide performance assessment against measurement-based estimates.
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024, https://doi.org/10.5194/gmd-17-5087-2024, 2024
Short summary
Short summary
Explosive volcanic eruptions lead to long-lived, microscopic particles in the upper atmosphere which act to cool the Earth's surface by reflecting the Sun's light back to space. We include and test this process in a global climate model, E3SM. E3SM is tested against satellite and balloon observations of the 1991 eruption of Mt. Pinatubo, showing that with these particles in the model we reasonably recreate Pinatubo and its global effects. We also explore how particle size leads to these effects.
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024, https://doi.org/10.5194/gmd-17-4923-2024, 2024
Short summary
Short summary
Our research shows the importance of modeling new particle formation (NPF) and growth of particles in the atmosphere on a global scale, as they influence the outcomes of clouds and our climate. With the global model EC-Earth3 we show that using a new method for NPF modeling, which includes new detailed processes with NH3 and H2SO4, significantly impacts the number of particles in the air and clouds and changes the radiation balance of the same magnitude as anthropogenic greenhouse emissions.
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024, https://doi.org/10.5194/gmd-17-4871-2024, 2024
Short summary
Short summary
The impact of biochar (BC) on soil organic carbon (SOC) dynamics is not represented in most land carbon models used for assessing land-based climate change mitigation. Our study develops a BC model that incorporates our current understanding of BC effects on SOC based on a soil carbon model (MIMICS). The BC model can reproduce the SOC changes after adding BC, providing a useful tool to couple dynamic land models to evaluate the effectiveness of BC application for CO2 removal from the atmosphere.
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024, https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary
Short summary
Hector is an easy-to-use, global climate–carbon cycle model. With its quick run time, Hector can provide climate information from a run in a fraction of a second. Hector models on a global and annual basis. Here, we present an updated version of the model, Hector V3. In this paper, we document Hector’s new features. Hector V3 is capable of reproducing historical observations, and its future temperature projections are consistent with those of more complex models.
Fangxuan Ren, Jintai Lin, Chenghao Xu, Jamiu A. Adeniran, Jingxu Wang, Randall V. Martin, Aaron van Donkelaar, Melanie S. Hammer, Larry W. Horowitz, Steven T. Turnock, Naga Oshima, Jie Zhang, Susanne Bauer, Kostas Tsigaridis, Øyvind Seland, Pierre Nabat, David Neubauer, Gary Strand, Twan van Noije, Philippe Le Sager, and Toshihiko Takemura
Geosci. Model Dev., 17, 4821–4836, https://doi.org/10.5194/gmd-17-4821-2024, https://doi.org/10.5194/gmd-17-4821-2024, 2024
Short summary
Short summary
We evaluate the performance of 14 CMIP6 ESMs in simulating total PM2.5 and its 5 components over China during 2000–2014. PM2.5 and its components are underestimated in almost all models, except that black carbon (BC) and sulfate are overestimated in two models, respectively. The underestimation is the largest for organic carbon (OC) and the smallest for BC. Models reproduce the observed spatial pattern for OC, sulfate, nitrate and ammonium well, yet the agreement is poorer for BC.
Yi Xi, Chunjing Qiu, Yuan Zhang, Dan Zhu, Shushi Peng, Gustaf Hugelius, Jinfeng Chang, Elodie Salmon, and Philippe Ciais
Geosci. Model Dev., 17, 4727–4754, https://doi.org/10.5194/gmd-17-4727-2024, https://doi.org/10.5194/gmd-17-4727-2024, 2024
Short summary
Short summary
The ORCHIDEE-MICT model can simulate the carbon cycle and hydrology at a sub-grid scale but energy budgets only at a grid scale. This paper assessed the implementation of a multi-tiling energy budget approach in ORCHIDEE-MICT and found warmer surface and soil temperatures, higher soil moisture, and more soil organic carbon across the Northern Hemisphere compared with the original version.
Georgia Lazoglou, Theo Economou, Christina Anagnostopoulou, George Zittis, Anna Tzyrkalli, Pantelis Georgiades, and Jos Lelieveld
Geosci. Model Dev., 17, 4689–4703, https://doi.org/10.5194/gmd-17-4689-2024, https://doi.org/10.5194/gmd-17-4689-2024, 2024
Short summary
Short summary
This study focuses on the important issue of the drizzle bias effect in regional climate models, described by an over-prediction of the number of rainy days while underestimating associated precipitation amounts. For this purpose, two distinct methodologies are applied and rigorously evaluated. These results are encouraging for using the multivariate machine learning method random forest to increase the accuracy of climate models concerning the projection of the number of wet days.
Xu Yue, Hao Zhou, Chenguang Tian, Yimian Ma, Yihan Hu, Cheng Gong, Hui Zheng, and Hong Liao
Geosci. Model Dev., 17, 4621–4642, https://doi.org/10.5194/gmd-17-4621-2024, https://doi.org/10.5194/gmd-17-4621-2024, 2024
Short summary
Short summary
We develop the interactive Model for Air Pollution and Land Ecosystems (iMAPLE). The model considers the full coupling between carbon and water cycles, dynamic fire emissions, wetland methane emissions, biogenic volatile organic compound emissions, and trait-based ozone vegetation damage. Evaluations show that iMAPLE is a useful tool for the study of the interactions among climate, chemistry, and ecosystems.
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
Short summary
Short summary
The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Ross Mower, Ethan D. Gutmann, Glen E. Liston, Jessica Lundquist, and Soren Rasmussen
Geosci. Model Dev., 17, 4135–4154, https://doi.org/10.5194/gmd-17-4135-2024, https://doi.org/10.5194/gmd-17-4135-2024, 2024
Short summary
Short summary
Higher-resolution model simulations are better at capturing winter snowpack changes across space and time. However, increasing resolution also increases the computational requirements. This work provides an overview of changes made to a distributed snow-evolution modeling system (SnowModel) to allow it to leverage high-performance computing resources. Continental simulations that were previously estimated to take 120 d can now be performed in 5 h.
Jiaxu Guo, Juepeng Zheng, Yidan Xu, Haohuan Fu, Wei Xue, Lanning Wang, Lin Gan, Ping Gao, Wubing Wan, Xianwei Wu, Zhitao Zhang, Liang Hu, Gaochao Xu, and Xilong Che
Geosci. Model Dev., 17, 3975–3992, https://doi.org/10.5194/gmd-17-3975-2024, https://doi.org/10.5194/gmd-17-3975-2024, 2024
Short summary
Short summary
To enhance the efficiency of experiments using SCAM, we train a learning-based surrogate model to facilitate large-scale sensitivity analysis and tuning of combinations of multiple parameters. Employing a hybrid method, we investigate the joint sensitivity of multi-parameter combinations across typical cases, identifying the most sensitive three-parameter combination out of 11. Subsequently, we conduct a tuning process aimed at reducing output errors in these cases.
Yung-Yao Lan, Huang-Hsiung Hsu, and Wan-Ling Tseng
Geosci. Model Dev., 17, 3897–3918, https://doi.org/10.5194/gmd-17-3897-2024, https://doi.org/10.5194/gmd-17-3897-2024, 2024
Short summary
Short summary
This study uses the CAM5–SIT coupled model to investigate the effects of SST feedback frequency on the MJO simulations with intervals at 30 min, 1, 3, 6, 12, 18, 24, and 30 d. The simulations become increasingly unrealistic as the frequency of the SST feedback decreases. Our results suggest that more spontaneous air--sea interaction (e.g., ocean response within 3 d in this study) with high vertical resolution in the ocean model is key to the realistic simulation of the MJO.
Jiwoo Lee, Peter J. Gleckler, Min-Seop Ahn, Ana Ordonez, Paul A. Ullrich, Kenneth R. Sperber, Karl E. Taylor, Yann Y. Planton, Eric Guilyardi, Paul Durack, Celine Bonfils, Mark D. Zelinka, Li-Wei Chao, Bo Dong, Charles Doutriaux, Chengzhu Zhang, Tom Vo, Jason Boutte, Michael F. Wehner, Angeline G. Pendergrass, Daehyun Kim, Zeyu Xue, Andrew T. Wittenberg, and John Krasting
Geosci. Model Dev., 17, 3919–3948, https://doi.org/10.5194/gmd-17-3919-2024, https://doi.org/10.5194/gmd-17-3919-2024, 2024
Short summary
Short summary
We introduce an open-source software, the PCMDI Metrics Package (PMP), developed for a comprehensive comparison of Earth system models (ESMs) with real-world observations. Using diverse metrics evaluating climatology, variability, and extremes simulated in thousands of simulations from the Coupled Model Intercomparison Project (CMIP), PMP aids in benchmarking model improvements across generations. PMP also enables efficient tracking of performance evolutions during ESM developments.
Haoyue Zuo, Yonggang Liu, Gaojun Li, Zhifang Xu, Liang Zhao, Zhengtang Guo, and Yongyun Hu
Geosci. Model Dev., 17, 3949–3974, https://doi.org/10.5194/gmd-17-3949-2024, https://doi.org/10.5194/gmd-17-3949-2024, 2024
Short summary
Short summary
Compared to the silicate weathering fluxes measured at large river basins, the current models tend to systematically overestimate the fluxes over the tropical region, which leads to an overestimation of the global total weathering flux. The most possible cause of such bias is found to be the overestimation of tropical surface erosion, which indicates that the tropical vegetation likely slows down physical erosion significantly. We propose a way of taking this effect into account in models.
Quentin Pikeroen, Didier Paillard, and Karine Watrin
Geosci. Model Dev., 17, 3801–3814, https://doi.org/10.5194/gmd-17-3801-2024, https://doi.org/10.5194/gmd-17-3801-2024, 2024
Short summary
Short summary
All accurate climate models use equations with poorly defined parameters, where knobs for the parameters are turned to fit the observations. This process is called tuning. In this article, we use another paradigm. We use a thermodynamic hypothesis, the maximum entropy production, to compute temperatures, energy fluxes, and precipitation, where tuning is impossible. For now, the 1D vertical model is used for a tropical atmosphere. The correct order of magnitude of precipitation is computed.
Jishi Zhang, Peter Bogenschutz, Qi Tang, Philip Cameron-smith, and Chengzhu Zhang
Geosci. Model Dev., 17, 3687–3731, https://doi.org/10.5194/gmd-17-3687-2024, https://doi.org/10.5194/gmd-17-3687-2024, 2024
Short summary
Short summary
We developed a regionally refined climate model that allows resolved convection and performed a 20-year projection to the end of the century. The model has a resolution of 3.25 km in California, which allows us to predict climate with unprecedented accuracy, and a resolution of 100 km for the rest of the globe to achieve efficient, self-consistent simulations. The model produces superior results in reproducing climate patterns over California that typical modern climate models cannot resolve.
Xiaohui Zhong, Xing Yu, and Hao Li
Geosci. Model Dev., 17, 3667–3685, https://doi.org/10.5194/gmd-17-3667-2024, https://doi.org/10.5194/gmd-17-3667-2024, 2024
Short summary
Short summary
In order to forecast localized warm-sector rainfall in the south China region, numerical weather prediction models are being run with finer grid spacing. The conventional convection parameterization (CP) performs poorly in the gray zone, necessitating the development of a scale-aware scheme. We propose a machine learning (ML) model to replace the scale-aware CP scheme. Evaluation against the original CP scheme has shown that the ML-based CP scheme can provide accurate and reliable predictions.
Taufiq Hassan, Kai Zhang, Jianfeng Li, Balwinder Singh, Shixuan Zhang, Hailong Wang, and Po-Lun Ma
Geosci. Model Dev., 17, 3507–3532, https://doi.org/10.5194/gmd-17-3507-2024, https://doi.org/10.5194/gmd-17-3507-2024, 2024
Short summary
Short summary
Anthropogenic aerosol emissions are an essential part of global aerosol models. Significant errors can exist from the loss of emission heterogeneity. We introduced an emission treatment that significantly improved aerosol emission heterogeneity in high-resolution model simulations, with improvements in simulated aerosol surface concentrations. The emission treatment will provide a more accurate representation of aerosol emissions and their effects on climate.
Feng Zhu, Julien Emile-Geay, Gregory J. Hakim, Dominique Guillot, Deborah Khider, Robert Tardif, and Walter A. Perkins
Geosci. Model Dev., 17, 3409–3431, https://doi.org/10.5194/gmd-17-3409-2024, https://doi.org/10.5194/gmd-17-3409-2024, 2024
Short summary
Short summary
Climate field reconstruction encompasses methods that estimate the evolution of climate in space and time based on natural archives. It is useful to investigate climate variations and validate climate models, but its implementation and use can be difficult for non-experts. This paper introduces a user-friendly Python package called cfr to make these methods more accessible, thanks to the computational and visualization tools that facilitate efficient and reproducible research on past climates.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev., 17, 3433–3445, https://doi.org/10.5194/gmd-17-3433-2024, https://doi.org/10.5194/gmd-17-3433-2024, 2024
Short summary
Short summary
Models of rocky coastal erosion help us understand the controls on coastal morphology and evolution. In this paper, we present a simplified model of coastline erosion driven by either uniform erosion where coastline erosion is constant or wave-driven erosion where coastline erosion is a function of the wave power. This model can be used to evaluate how coastline changes reflect climate, sea-level history, material properties, and the relative influence of different erosional processes.
Safae Oumami, Joaquim Arteta, Vincent Guidard, Pierre Tulet, and Paul David Hamer
Geosci. Model Dev., 17, 3385–3408, https://doi.org/10.5194/gmd-17-3385-2024, https://doi.org/10.5194/gmd-17-3385-2024, 2024
Short summary
Short summary
In this paper, we coupled the SURFEX and MEGAN models. The aim of this coupling is to improve the estimation of biogenic fluxes by using the SURFEX canopy environment model. The coupled model results were validated and several sensitivity tests were performed. The coupled-model total annual isoprene flux is 442 Tg; this value is within the range of other isoprene estimates reported. The ultimate aim of this coupling is to predict the impact of climate change on biogenic emissions.
Lars Ackermann, Thomas Rackow, Kai Himstedt, Paul Gierz, Gregor Knorr, and Gerrit Lohmann
Geosci. Model Dev., 17, 3279–3301, https://doi.org/10.5194/gmd-17-3279-2024, https://doi.org/10.5194/gmd-17-3279-2024, 2024
Short summary
Short summary
We present long-term simulations with interactive icebergs in the Southern Ocean. By melting, icebergs reduce the temperature and salinity of the surrounding ocean. In our simulations, we find that this cooling effect of iceberg melting is not limited to the surface ocean but also reaches the deep ocean and propagates northward into all ocean basins. Additionally, the formation of deep-water masses in the Southern Ocean is enhanced.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Beiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
Geosci. Model Dev., 17, 3259–3277, https://doi.org/10.5194/gmd-17-3259-2024, https://doi.org/10.5194/gmd-17-3259-2024, 2024
Short summary
Short summary
For the first time, we coupled a regional climate chemistry model, RegCM-Chem, with a dynamic vegetation model, YIBs, to create a regional climate–chemistry–ecology model, RegCM-Chem–YIBs. We applied it to simulate climatic, chemical, and ecological parameters in East Asia and fully validated it on a variety of observational data. Results show that RegCM-Chem–YIBs model is a valuable tool for studying the terrestrial carbon cycle, atmospheric chemistry, and climate change on a regional scale.
Bryce E. Harrop, Jian Lu, L. Ruby Leung, William K. M. Lau, Kyu-Myong Kim, Brian Medeiros, Brian J. Soden, Gabriel A. Vecchi, Bosong Zhang, and Balwinder Singh
Geosci. Model Dev., 17, 3111–3135, https://doi.org/10.5194/gmd-17-3111-2024, https://doi.org/10.5194/gmd-17-3111-2024, 2024
Short summary
Short summary
Seven new experimental setups designed to interfere with cloud radiative heating have been added to the Energy Exascale Earth System Model (E3SM). These experiments include both those that test the mean impact of cloud radiative heating and those examining its covariance with circulations. This paper documents the code changes and steps needed to run these experiments. Results corroborate prior findings for how cloud radiative heating impacts circulations and rainfall patterns.
Mario C. Acosta, Sergi Palomas, Stella V. Paronuzzi Ticco, Gladys Utrera, Joachim Biercamp, Pierre-Antoine Bretonniere, Reinhard Budich, Miguel Castrillo, Arnaud Caubel, Francisco Doblas-Reyes, Italo Epicoco, Uwe Fladrich, Sylvie Joussaume, Alok Kumar Gupta, Bryan Lawrence, Philippe Le Sager, Grenville Lister, Marie-Pierre Moine, Jean-Christophe Rioual, Sophie Valcke, Niki Zadeh, and Venkatramani Balaji
Geosci. Model Dev., 17, 3081–3098, https://doi.org/10.5194/gmd-17-3081-2024, https://doi.org/10.5194/gmd-17-3081-2024, 2024
Short summary
Short summary
We present a collection of performance metrics gathered during the Coupled Model Intercomparison Project Phase 6 (CMIP6), a worldwide initiative to study climate change. We analyse the metrics that resulted from collaboration efforts among many partners and models and describe our findings to demonstrate the utility of our study for the scientific community. The research contributes to understanding climate modelling performance on the current high-performance computing (HPC) architectures.
Sabine Doktorowski, Jan Kretzschmar, Johannes Quaas, Marc Salzmann, and Odran Sourdeval
Geosci. Model Dev., 17, 3099–3110, https://doi.org/10.5194/gmd-17-3099-2024, https://doi.org/10.5194/gmd-17-3099-2024, 2024
Short summary
Short summary
Especially over the midlatitudes, precipitation is mainly formed via the ice phase. In this study we focus on the initial snow formation process in the ICON-AES, the aggregation process. We use a stochastical approach for the aggregation parameterization and investigate the influence in the ICON-AES. Therefore, a distribution function of cloud ice is created, which is evaluated with satellite data. The new approach leads to cloud ice loss and an improvement in the process rate bias.
Katie R. Blackford, Matthew Kasoar, Chantelle Burton, Eleanor Burke, Iain Colin Prentice, and Apostolos Voulgarakis
Geosci. Model Dev., 17, 3063–3079, https://doi.org/10.5194/gmd-17-3063-2024, https://doi.org/10.5194/gmd-17-3063-2024, 2024
Short summary
Short summary
Peatlands are globally important stores of carbon which are being increasingly threatened by wildfires with knock-on effects on the climate system. Here we introduce a novel peat fire parameterization in the northern high latitudes to the INFERNO global fire model. Representing peat fires increases annual burnt area across the high latitudes, alongside improvements in how we capture year-to-year variation in burning and emissions.
Pengfei Shi, L. Ruby Leung, Bin Wang, Kai Zhang, Samson M. Hagos, and Shixuan Zhang
Geosci. Model Dev., 17, 3025–3040, https://doi.org/10.5194/gmd-17-3025-2024, https://doi.org/10.5194/gmd-17-3025-2024, 2024
Short summary
Short summary
Improving climate predictions have profound socio-economic impacts. This study introduces a new weakly coupled land data assimilation (WCLDA) system for a coupled climate model. We demonstrate improved simulation of soil moisture and temperature in many global regions and throughout the soil layers. Furthermore, significant improvements are also found in reproducing the time evolution of the 2012 US Midwest drought. The WCLDA system provides the groundwork for future predictability studies.
Justin Peter, Elisabeth Vogel, Wendy Sharples, Ulrike Bende-Michl, Louise Wilson, Pandora Hope, Andrew Dowdy, Greg Kociuba, Sri Srikanthan, Vi Co Duong, Jake Roussis, Vjekoslav Matic, Zaved Khan, Alison Oke, Margot Turner, Stuart Baron-Hay, Fiona Johnson, Raj Mehrotra, Ashish Sharma, Marcus Thatcher, Ali Azarvinand, Steven Thomas, Ghyslaine Boschat, Chantal Donnelly, and Robert Argent
Geosci. Model Dev., 17, 2755–2781, https://doi.org/10.5194/gmd-17-2755-2024, https://doi.org/10.5194/gmd-17-2755-2024, 2024
Short summary
Short summary
We detail the production of datasets and communication to end users of high-resolution projections of rainfall, runoff, and soil moisture for the entire Australian continent. This is important as previous projections for Australia were for small regions and used differing techniques for their projections, making comparisons difficult across Australia's varied climate zones. The data will be beneficial for research purposes and to aid adaptation to climate change.
Daniele Visioni, Alan Robock, Jim Haywood, Matthew Henry, Simone Tilmes, Douglas G. MacMartin, Ben Kravitz, Sarah J. Doherty, John Moore, Chris Lennard, Shingo Watanabe, Helene Muri, Ulrike Niemeier, Olivier Boucher, Abu Syed, Temitope S. Egbebiyi, Roland Séférian, and Ilaria Quaglia
Geosci. Model Dev., 17, 2583–2596, https://doi.org/10.5194/gmd-17-2583-2024, https://doi.org/10.5194/gmd-17-2583-2024, 2024
Short summary
Short summary
This paper describes a new experimental protocol for the Geoengineering Model Intercomparison Project (GeoMIP). In it, we describe the details of a new simulation of sunlight reflection using the stratospheric aerosols that climate models are supposed to run, and we explain the reasons behind each choice we made when defining the protocol.
Jose Rafael Guarin, Jonas Jägermeyr, Elizabeth A. Ainsworth, Fabio A. A. Oliveira, Senthold Asseng, Kenneth Boote, Joshua Elliott, Lisa Emberson, Ian Foster, Gerrit Hoogenboom, David Kelly, Alex C. Ruane, and Katrina Sharps
Geosci. Model Dev., 17, 2547–2567, https://doi.org/10.5194/gmd-17-2547-2024, https://doi.org/10.5194/gmd-17-2547-2024, 2024
Short summary
Short summary
The effects of ozone (O3) stress on crop photosynthesis and leaf senescence were added to maize, rice, soybean, and wheat crop models. The modified models reproduced growth and yields under different O3 levels measured in field experiments and reported in the literature. The combined interactions between O3 and additional stresses were reproduced with the new models. These updated crop models can be used to simulate impacts of O3 stress under future climate change and air pollution scenarios.
Jiachen Lu, Negin Nazarian, Melissa Anne Hart, E. Scott Krayenhoff, and Alberto Martilli
Geosci. Model Dev., 17, 2525–2545, https://doi.org/10.5194/gmd-17-2525-2024, https://doi.org/10.5194/gmd-17-2525-2024, 2024
Short summary
Short summary
This study enhances urban canopy models by refining key assumptions. Simulations for various urban scenarios indicate discrepancies in turbulent transport efficiency for flow properties. We propose two modifications that involve characterizing diffusion coefficients for momentum and turbulent kinetic energy separately and introducing a physics-based
mass-fluxterm. These adjustments enhance the model's performance, offering more reliable temperature and surface flux estimates.
Justin L. Willson, Kevin A. Reed, Christiane Jablonowski, James Kent, Peter H. Lauritzen, Ramachandran Nair, Mark A. Taylor, Paul A. Ullrich, Colin M. Zarzycki, David M. Hall, Don Dazlich, Ross Heikes, Celal Konor, David Randall, Thomas Dubos, Yann Meurdesoif, Xi Chen, Lucas Harris, Christian Kühnlein, Vivian Lee, Abdessamad Qaddouri, Claude Girard, Marco Giorgetta, Daniel Reinert, Hiroaki Miura, Tomoki Ohno, and Ryuji Yoshida
Geosci. Model Dev., 17, 2493–2507, https://doi.org/10.5194/gmd-17-2493-2024, https://doi.org/10.5194/gmd-17-2493-2024, 2024
Short summary
Short summary
Accurate simulation of tropical cyclones (TCs) is essential to understanding their behavior in a changing climate. One way this is accomplished is through model intercomparison projects, where results from multiple climate models are analyzed to provide benchmark solutions for the wider climate modeling community. This study describes and analyzes the previously developed TC test case for nine climate models in an intercomparison project, providing solutions that aid in model development.
Stephanie Fiedler, Vaishali Naik, Fiona M. O'Connor, Christopher J. Smith, Paul Griffiths, Ryan J. Kramer, Toshihiko Takemura, Robert J. Allen, Ulas Im, Matthew Kasoar, Angshuman Modak, Steven Turnock, Apostolos Voulgarakis, Duncan Watson-Parris, Daniel M. Westervelt, Laura J. Wilcox, Alcide Zhao, William J. Collins, Michael Schulz, Gunnar Myhre, and Piers M. Forster
Geosci. Model Dev., 17, 2387–2417, https://doi.org/10.5194/gmd-17-2387-2024, https://doi.org/10.5194/gmd-17-2387-2024, 2024
Short summary
Short summary
Climate scientists want to better understand modern climate change. Thus, climate model experiments are performed and compared. The results of climate model experiments differ, as assessed in the latest Intergovernmental Panel on Climate Change (IPCC) assessment report. This article gives insights into the challenges and outlines opportunities for further improving the understanding of climate change. It is based on views of a group of experts in atmospheric composition–climate interactions.
Yuwen Fan, Zhao Yang, Min-Hui Lo, Jina Hur, and Eun-Soon Im
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-38, https://doi.org/10.5194/gmd-2024-38, 2024
Revised manuscript accepted for GMD
Short summary
Short summary
Irrigated agriculture in the North China Plain (NCP) has a significant impact on the local climate. To better understand this impact, we developed a specialized model specifically for the NCP region. This model allows us to simulate the double-cropping vegetation and the dynamic irrigation practices that are commonly employed in the NCP. This model shows improved performance in capturing the general crop growth, such as crop stages, biomass, crop yield, and vegetation greenness.
Sergey Danilov, Carolin Mehlmann, Dmitry Sidorenko, and Qiang Wang
Geosci. Model Dev., 17, 2287–2297, https://doi.org/10.5194/gmd-17-2287-2024, https://doi.org/10.5194/gmd-17-2287-2024, 2024
Short summary
Short summary
Sea ice models are a necessary component of climate models. At very high resolution they are capable of simulating linear kinematic features, such as leads, which are important for better prediction of heat exchanges between the ocean and atmosphere. Two new discretizations are described which improve the sea ice component of the Finite volumE Sea ice–Ocean Model (FESOM version 2) by allowing simulations of finer scales.
Yangke Liu, Qing Bao, Bian He, Xiaofei Wu, Jing Yang, Yimin Liu, Guoxiong Wu, Tao Zhu, Siyuan Zhou, Yao Tang, Ankang Qu, Yalan Fan, Anling Liu, Dandan Chen, Zhaoming Luo, Xing Hu, and Tongwen Wu
EGUsphere, https://doi.org/10.5194/egusphere-2024-1, https://doi.org/10.5194/egusphere-2024-1, 2024
Short summary
Short summary
This article gives an overview introduction of the IAP-CAS S2S (sub-seasonal to seasonal) ensemble forecasting system and MJO forecast evaluation of the system. Compared to other S2S models, the IAP-CAS model has its advantages but also exhibits some biases, including underdispersive ensemble, overestimated amplitude and faster propagation speed when forecasting MJO. We also provide the explanation towards these biases and prospects for further improvement of this system in the future.
Tian Gan, Gregory E. Tucker, Eric W. H. Hutton, Mark D. Piper, Irina Overeem, Albert J. Kettner, Benjamin Campforts, Julia M. Moriarty, Brianna Undzis, Ethan Pierce, and Lynn McCready
Geosci. Model Dev., 17, 2165–2185, https://doi.org/10.5194/gmd-17-2165-2024, https://doi.org/10.5194/gmd-17-2165-2024, 2024
Short summary
Short summary
This study presents the design, implementation, and application of the CSDMS Data Components. The case studies demonstrate that the Data Components provide a consistent way to access heterogeneous datasets from multiple sources, and to seamlessly integrate them with various models for Earth surface process modeling. The Data Components support the creation of open data–model integration workflows to improve the research transparency and reproducibility.
Jérémy Bernard, Erwan Bocher, Matthieu Gousseff, François Leconte, and Elisabeth Le Saux Wiederhold
Geosci. Model Dev., 17, 2077–2116, https://doi.org/10.5194/gmd-17-2077-2024, https://doi.org/10.5194/gmd-17-2077-2024, 2024
Short summary
Short summary
Geographical features may have a considerable effect on local climate. The local climate zone (LCZ) system proposed by Stewart and Oke (2012) is seen as a standard approach for classifying any zone according to a set of geographic indicators. While many methods already exist to map the LCZ, only a few tools are openly and freely available. We present the algorithm implemented in GeoClimate software to identify the LCZ of any place in the world using OpenStreetMap data.
Thomas Extier, Thibaut Caley, and Didier M. Roche
Geosci. Model Dev., 17, 2117–2139, https://doi.org/10.5194/gmd-17-2117-2024, https://doi.org/10.5194/gmd-17-2117-2024, 2024
Short summary
Short summary
Stable water isotopes are used to infer changes in the hydrological cycle for different time periods in climatic archive and climate models. We present the implementation of the δ2H and δ17O water isotopes in the coupled climate model iLOVECLIM and calculate the d- and 17O-excess. Results of a simulation under preindustrial conditions show that the model correctly reproduces the water isotope distribution in the atmosphere and ocean in comparison to data and other global circulation models.
Joseph P. Hollowed, Christiane Jablonowski, Hunter Y. Brown, Benjamin R. Hillman, Diana L. Bull, and Joseph L. Hart
EGUsphere, https://doi.org/10.5194/egusphere-2024-335, https://doi.org/10.5194/egusphere-2024-335, 2024
Short summary
Short summary
Large volcanic eruptions deposit material into the upper-atmosphere, which is capable of altering temperature and wind patterns of the Earth's atmosphere for years following. This research describes a new method of simulating these effects in an idealized, efficient atmospheric model. A volcanic eruption of sulfur dioxide is described with a simplified set of physical rules, which eventually cools the planetary surface. This model has been designed as a testbed for climate attribution studies.
Marit Sandstad, Borgar Aamaas, Ane Nordlie Johansen, Marianne Tronstad Lund, Glen Peters, Bjørn Hallvard Samset, Benjamin M. Sanderson, and Ragnhild Bieltvedt Skeie
EGUsphere, https://doi.org/10.5194/egusphere-2024-196, https://doi.org/10.5194/egusphere-2024-196, 2024
Short summary
Short summary
The CICERO-SCM has existed as a FORTRAN model since 1999 and consists of a part that calculates radiative forcing and concentrations from emissions, and an upwelling diffusion energy balance model of the ocean that calculates temperature change. In this paper we describe an updated version ported to python and publicly available at https://github.com/ciceroOslo/ciceroscm (https://doi.org/10.5281/zenodo.10548720). This version contains functionality for parallel runs and automatic calibration.
Kirsten L. Findell, Zun Yin, Eunkyo Seo, Paul A. Dirmeyer, Nathan P. Arnold, Nathaniel Chaney, Megan D. Fowler, Meng Huang, David M. Lawrence, Po-Lun Ma, and Joseph A. Santanello Jr.
Geosci. Model Dev., 17, 1869–1883, https://doi.org/10.5194/gmd-17-1869-2024, https://doi.org/10.5194/gmd-17-1869-2024, 2024
Short summary
Short summary
We outline a request for sub-daily data to accurately capture the process-level connections between land states, surface fluxes, and the boundary layer response. This high-frequency model output will allow for more direct comparison with observational field campaigns on process-relevant timescales, enable demonstration of inter-model spread in land–atmosphere coupling processes, and aid in targeted identification of sources of deficiencies and opportunities for improvement of the models.
Marlene Klockmann, Udo von Toussaint, and Eduardo Zorita
Geosci. Model Dev., 17, 1765–1787, https://doi.org/10.5194/gmd-17-1765-2024, https://doi.org/10.5194/gmd-17-1765-2024, 2024
Short summary
Short summary
Reconstructions of climate variability before the observational period rely on climate proxies and sophisticated statistical models to link the proxy information and climate variability. Existing models tend to underestimate the true magnitude of variability, especially if the proxies contain non-climatic noise. We present and test a promising new framework for climate-index reconstructions, based on Gaussian processes, which reconstructs robust variability estimates from noisy and sparse data.
Aaron A. Naidoo-Bagwell, Fanny M. Monteiro, Katharine R. Hendry, Scott Burgan, Jamie D. Wilson, Ben A. Ward, Andy Ridgwell, and Daniel J. Conley
Geosci. Model Dev., 17, 1729–1748, https://doi.org/10.5194/gmd-17-1729-2024, https://doi.org/10.5194/gmd-17-1729-2024, 2024
Short summary
Short summary
As an extension to the EcoGEnIE 1.0 Earth system model that features a diverse plankton community, EcoGEnIE 1.1 includes siliceous plankton diatoms and also considers their impact on biogeochemical cycles. With updates to existing nutrient cycles and the introduction of the silicon cycle, we see improved model performance relative to observational data. Through a more functionally diverse plankton community, the new model enables more comprehensive future study of ocean ecology.
Martin Butzin, Ying Ye, Christoph Völker, Özgür Gürses, Judith Hauck, and Peter Köhler
Geosci. Model Dev., 17, 1709–1727, https://doi.org/10.5194/gmd-17-1709-2024, https://doi.org/10.5194/gmd-17-1709-2024, 2024
Short summary
Short summary
In this paper we describe the implementation of the carbon isotopes 13C and 14C into the marine biogeochemistry model FESOM2.1-REcoM3 and present results of long-term test simulations. Our model results are largely consistent with marine carbon isotope reconstructions for the pre-anthropogenic period, but also exhibit some discrepancies.
Sven Karsten, Hagen Radtke, Matthias Gröger, Ha T. M. Ho-Hagemann, Hossein Mashayekh, Thomas Neumann, and H. E. Markus Meier
Geosci. Model Dev., 17, 1689–1708, https://doi.org/10.5194/gmd-17-1689-2024, https://doi.org/10.5194/gmd-17-1689-2024, 2024
Short summary
Short summary
This paper describes the development of a regional Earth System Model for the Baltic Sea region. In contrast to conventional coupling approaches, the presented model includes a flux calculator operating on a common exchange grid. This approach automatically ensures a locally consistent treatment of fluxes and simplifies the exchange of model components. The presented model can be used for various scientific questions, such as studies of natural variability and ocean–atmosphere interactions.
Skyler Graap and Colin M. Zarzycki
Geosci. Model Dev., 17, 1627–1650, https://doi.org/10.5194/gmd-17-1627-2024, https://doi.org/10.5194/gmd-17-1627-2024, 2024
Short summary
Short summary
A key target for improving climate models is how low, bright clouds are predicted over tropical oceans, since they have important consequences for the Earth's energy budget. A climate model has been updated to improve the physical realism of the treatment of how momentum is moved up and down in the atmosphere. By comparing this updated model to real-world observations from balloon launches, it can be shown to more accurately depict atmospheric structure in trade-wind areas close to the Equator.
Marika M. Holland, Cecile Hannay, John Fasullo, Alexandra Jahn, Jennifer E. Kay, Michael Mills, Isla R. Simpson, William Wieder, Peter Lawrence, Erik Kluzek, and David Bailey
Geosci. Model Dev., 17, 1585–1602, https://doi.org/10.5194/gmd-17-1585-2024, https://doi.org/10.5194/gmd-17-1585-2024, 2024
Short summary
Short summary
Climate evolves in response to changing forcings, as prescribed in simulations. Models and forcings are updated over time to reflect new understanding. This makes it difficult to attribute simulation differences to either model or forcing changes. Here we present new simulations which enable the separation of model structure and forcing influence between two widely used simulation sets. Results indicate a strong influence of aerosol emission uncertainty on historical climate.
Cited articles
Amundson, R., Stern, L., Baisden, T., and Wang, Y.: The isotopic
composition of soil and soil-respired CO2, Geoderma, 82, 83–114, 1998.
Atkin, O. K. and Tjoelker, M. G.: Thermal acclimation and the dynamic
response of plant respiration to temperature, Trends Plant Sci., 8,
343–351, 2003.
Bachman, S., Heisler-White, J. L., Pendall, E., Williams, D. G., Morgan, J.
A., and Newcomb, J.: Elevated carbon dioxide alters impacts of precipitation
pulses on ecosystem photosynthesis and respiration in a semi-arid grassland,
Oecologia, 162, 791–802, 2010.
Baldocchi, D., Tang, J., and Xu, L.: How switches and lags in biophysical
regulators affect spatial-temporal variation of soil respiration in an
oak-grass savanna, J. Geophys. Res., 111, G02008, https://doi.org/10.1029/2005JG000063,
2006.
Barron-Gafford, G. A., Cable, J. M., Bentley, L. P., Scott, R. L., Huxman,
T. E., Jenerette, G. D., and Ogle, K.: Quantifying the timescales over which
exogenous and endogenous conditions affect soil respiration, New
Phytol., 202, 442–454, 2014.
Birch, H.: The effect of soil drying on humus decomposition and nitrogen
availability, Plant Soil, 10, 9–31, 1958.
Borken, W. and Matzner, E.: Reappraisal of drying and wetting effects on C
and N mineralization and fluxes in soils, Glob. Change Biol., 15,
808–824, 2009.
Borken, W., Davidson, E., Savage, K., Gaudinski, J., and Trumbore, S. E.:
Drying and wetting effects on carbon dioxide release from organic horizons,
Soil Sci. Soc. Am. J., 67, 1888–1896, 2003.
Bouma, T. J. and Bryla, D. R.: On the assessment of root and soil
respiration for soils of different textures: interactions with soil moisture
contents and soil CO2 concentrations, Plant Soil, 227, 215–221, 2000.
Brennan, A.: Vegetation and Climate Change Alter Ecosystem Carbon Losses at
the Prairie Heating and CO2 Enrichment Experiment in Wyoming, Department of
Botany, University of Wyoming, 2013.
Cable, J. M., Ogle, K., Williams, D. G., Weltzin, J. F., and Huxman, T. E.:
Soil texture drives responses of soil respiration to precipitation pulses in
the Sonoran Desert: implications for climate change, Ecosystems, 11,
961–979, 2008.
Cable, J. M., Ogle, K., Lucas, R. W., Huxman, T. E., Loik, M. E., Smith, S.
D., Tissue, D. T., Ewers, B. E., Pendall, E., and Welker, J. M.: The
temperature responses of soil respiration in deserts: a seven desert
synthesis, Biogeochemistry, 103, 71–90, 2011.
Cable, J. M., Ogle, K., Barron-Gafford, G. A., Bentley, L. P., Cable, W. L.,
Scott, R. L., Williams, D. G., and Huxman, T. E.: Antecedent conditions
influence soil respiration differences in shrub and grass patches,
Ecosystems, 16, 1230–1247, 2013.
Carrillo, Y. and Pendall, E.: Shifted role of bacteria in soil carbon cycling
under future climate conditions: implications for soil carbon stocks, in
review, 2018.
Carrillo, Y., Dijkstra, F. A., LeCain, D., Morgan, J. A., Blumenthal, D.,
Waldron, S., and Pendall, E.: Disentangling root responses to climate change
in a semiarid grassland, Oecologia, 175, 699–711, 2014a.
Carrillo, Y., Dijkstra, F. A., Pendall, E., LeCain, D., and Tucker, C.: Plant
rhizosphere influence on microbial C metabolism: the role of elevated CO2,
N availability and root stoichiometry, Biogeochemistry, 117,
229–240, 2014b.
Cerling, T. E.: The stable isotopic composition of modern soil carbonate and
its relationship to climate, Earth Planet. Sc. Lett., 71, 229–240, 1984.
Chou, W. W., Silver, W. L., Jackson, R. D., Thompson, A. W., and Allen-Diaz,
B.: The sensitivity of annual grassland carbon cycling to the quantity and
timing of rainfall, Glob. Change Biol., 14, 1382–1394, 2008.
Cox, P. M.: Description of the TRIFFID dynamic global vegetation model,
2001.
Davidson, E. A. and Janssens, I. A.: Temperature sensitivity of soil carbon
decomposition and feedbacks to climate change, Nature, 440, 165–173, 2006.
Davidson, E. A., Savage, K. E., Trumbore, S. E., and Borken, W.: Vertical
partitioning of CO2 production within a temperate forest soil, Glob. Change
Biol., 12, 944–956, 2006.
Davidson, E. A., Samanta, S., Caramori, S. S., and Savage, K.: The Dual
Arrhenius and Michaelis–Menten kinetics model for decomposition of soil
organic matter at hourly to seasonal time scales, Glob. Change Biol., 18,
371–384, 2012.
Fang, C. and Moncrieff, J. B.: A model for soil CO2 production and
transport 1, Model development, Agr. Forest Meteorol., 95,
225–236, 1999.
Friedlingstein, P., Andrew, R. M., Rogelj, J., Peters, G., Canadell, J. G.,
Knutti, R., Luderer, G., Raupach, M. R., Schaeffer, M., and Van Vuuren, D.
P.: Persistent growth of CO2 emissions and implications for reaching
climate targets, Nat. Geosci., 7, 709–715, 2014.
Haberman, R.: Elementary applied partial differential equations, 3rd
Edn., Prentice Hall Englewood Cliffs, NJ, 1998.
Hanson, P., Edwards, N., Garten, C., and Andrews, J.: Separating root and
soil microbial contributions to soil respiration: a review of methods and
observations, Biogeochemistry, 48, 115–146, 2000.
Hashimoto, S., Carvalhais, N., Ito, A., Migliavacca, M., Nishina, K., and Reichstein, M.: Global spatiotemporal distribution of soil respiration modeled using a global database, Biogeosciences, 12, 4121–4132, https://doi.org/10.5194/bg-12-4121-2015, 2015.
Hillel, D.: Environmental soil physics: Fundamentals, applications, and
environmental considerations, Academic press, 1998.
Hui, D. and Luo, Y.: Evaluation of soil CO2 production and transport in
Duke Forest using a process-based modeling approach, Global Biogeochem. Cy.,
18, GB4029, https://doi.org/10.1029/2004GB002297, 2004.
Huxman, T. E., Snyder, K. A., Tissue, D., Leffler, A. J., Ogle, K., Pockman,
W. T., Sandquist, D. R., Potts, D. L., and Schwinning, S.: Precipitation
pulses and carbon fluxes in semiarid and arid ecosystems, Oecologia, 141,
254–268, 2004.
Jarvis, P., Rey, A., Petsikos, C., Wingate, L., Rayment, M., Pereira, J.,
Banza, J., David, J., Miglietta, F., and Borghetti, M.: Drying and wetting
of Mediterranean soils stimulates decomposition and carbon dioxide emission:
the “Birch effect”, Tree Physiol., 27, 929–940, 2007.
Jasoni, R. L., Smith, S. D., and Arnone, J. A.: Net ecosystem CO2 exchange
in Mojave Desert shrublands during the eighth year of exposure to elevated
CO2, Glob. Change Biol., 11, 749–756, 2005.
Kayler, Z. E., Sulzman, E. W., Rugh, W. D., Mix, A. C., and Bond, B. J.:
Characterizing the impact of diffusive and advective soil gas transport on
the measurement and interpretation of the isotopic signal of soil
respiration, Soil Biol. Biochem., 42, 435–444, 2010.
Lee, X., Wu, H. J., Sigler, J., Oishi, C., and Siccama, T.: Rapid and
transient response of soil respiration to rain, Glob. Change Biol., 10,
1017–1026, 2004.
Lloyd, J. and Taylor, J.: On the temperature dependence of soil respiration,
Funct. Ecol., 8, 315–323, 1994.
Luo, Y. and Zhou, X.: Soil respiration and the environment, Academic press,
2010.
Maggi, F. and Riley, W. J.: Transient competitive complexation in biological
kinetic isotope fractionation explains nonsteady isotopic effects: Theory and
application to denitrification in soils, J. Geophys. Res., 114, G04012,
https://doi.org/10.1029/2008JG000878, 2009
Mathworks: The MathWorks, Inc. Natick, Massachusetts, USA MATLAB and
Statistics Toolbox Release, 2016.
Meisner, A., Bååth, E., and Rousk, J.: Microbial growth responses
upon rewetting soil dried for four days or one year, Soil Biol.
Biochem., 66, 188–192, 2013.
Millington, R. J. and Quirk, J. P.: Permeability of porous solids, T. Faraday
Soc., 57, 1200–1207, 1961.
Moldrup, P., Olesen, T., Yoshikawa, S., Komatsu, T., and Rolston, D. E.:
Three-porosity model for predicting the gas diffusion coefficient in
undisturbed soil, Soil Sci. Soc. Am. J., 68, 750–759, 2004.
Morgan, J. A., LeCain, D. R., Pendall, E., Blumenthal, D. M., Kimball, B.
A., Carrillo, Y., Williams, D. G., Heisler-White, J., Dijkstra, F. A., and
West, M.: C4 grasses prosper as carbon dioxide eliminates desiccation in
warmed semi-arid grassland, Nature, 476, 202–205, 2011.
Moyes, A. B., Gaines, S. J., Siegwolf, R. T., and Bowling, D. R.: Diffusive
fractionation complicates isotopic partitioning of autotrophic and
heterotrophic sources of soil respiration, Plant Cell Environ., 33,
1804–1819, 2010.
Mueller, K. E., Blumenthal, D. M., Pendall, E., Carrillo, Y., Dijkstra, F.
A., Williams, D. G., Follett, R. F., and Morgan, J. A.: Impacts of warming
and elevated CO2 on a semi-arid grassland are non-additive, shift with
precipitation, and reverse over time, Ecol. Lett., 19, 956–966, 2016.
Nickerson, N. and Risk, D.: Physical controls on the isotopic composition of
soil-respired CO2, J. Geophys. Res., 114, G01013,
https://doi.org/10.1029/2008JG000766, 2009.
Ogle, K. and Pendall, E.: Isotope partitioning of soil respiration: A
Bayesian solution to accommodate multiple sources of variability, J. Geophys.
Res.-Biogeo., 120, 221–236, 2015.
Ogle, K., Wolpert, R. L., and Reynolds, J. F.: Reconstructing plant root
area and water uptake profiles, Ecology, 85, 1967–1978, 2004.
Ogle, K., Barber, J. J., Barron-Gafford, G. A., Bentley, L. P., Young, J.
M., Huxman, T. E., Loik, M. E., and Tissue, D. T.: Quantifying ecological
memory in plant and ecosystem processes, Ecol. Lett., 18, 221–235, 2015.
Ogle, K., Ryan, E., Dijkstra, F. A., and Pendall, E.: Quantifying and
reducing uncertainties in estimated soil CO2 fluxes with hierarchical
data-model integration, J. Geophys. Res.-Biogeo., 121, 2935–2948, 2016.
Oikawa, P., Grantz, D., Chatterjee, A., Eberwein, J., Allsman, L., and
Jenerette, G.: Unifying soil respiration pulses, inhibition, and temperature
hysteresis through dynamics of labile soil carbon and O2, J.
Geophys. Res.-Biogeo., 119, 521–536, 2014.
Oleson, K., Lawrence, D., Bonan, G., Drewniak, B., Huang, M., Koven, C.,
Levis, S., Li, F., Riley, W., and Subin, Z.: Technical description of
version 4.5 of the Community Land Model (CLM), Ncar Tech. Note
NCAR/TN-503+ STR, National Center for Atmospheric Research, Boulder, CO,
422 pp., https://doi.org/10.5065/D6RR1W7M, 2013.
Pendall, E., Del Grosso, S., King, J., LeCain, D., Milchunas, D., Morgan, J.,
Mosier, A., Ojima, D., Parton, W., and Tans, P.: Elevated atmospheric CO2
effects and soil water feedbacks on soil respiration components in a Colorado
grassland, Global Biogeochem. Cy., 17, 1046, https://doi.org/10.1029/2001GB001821,
2003.
Pendall, E., Bridgham, S., Hanson, P. J., Hungate, B., Kicklighter, D. W.,
Johnson, D. W., Law, B. E., Luo, Y., Megonigal, J. P., and Olsrud, M.:
Below-ground process responses to elevated CO2 and temperature: A
discussion of observations, measurement methods, and models, New Phytol.,
162, 311–322, 2004.
Pendall, E., Heisler-White, J. L., Williams, D. G., Dijkstra, F. A.,
Carrillo, Y., Morgan, J. A., and LeCain, D. R.: Warming reduces carbon losses
from grassland exposed to elevated atmospheric carbon dioxide, PloS ONE, 8,
e71921, https://doi.org/10.1371/journal.pone.0071921, 2013.
Penman, H. L.: Gas and vapor movements in soil: The diffusion Soil of vapors
through porous solids, J. Agric. Sci., 30, 437–462, 1940.
Piao, S., Ciais, P., Friedlingstein, P., de Noblet-Ducoudre, N., Cadule, P.,
Viovy, N., and Wang, T.: Spatiotemporal patterns of terrestrial carbon cycle
during the 20th century, Global Biogeochem. Cy., 23, GB4026,
https://doi.org/10.1029/2008GB003339, 2009.
Richards, L. A.: Capillary conduction of liquids through porous mediums,
Physics, 1, 318–333, 1931.
Risk, D., Kellman, L., and Beltrami, H.: A new method for in situ soil gas
diffusivity measurement and applications in the monitoring of subsurface
CO2 production, J. Geophys. Res.-Biogeo., 113, G02018,
https://doi.org/10.1029/2007JG000445, 2008.
Risk, D., Nickerson, N., Creelman, C., McArthur, G., and Owens, J.: Forced
Diffusion soil flux: A new technique for continuous monitoring of soil gas
efflux, Agr. Forest Meteorol., 151, 1622–1631, 2011.
Risk, D., Nickerson, N., Phillips, C., Kellman, L., and Moroni, M.: Drought
alters respired δ13 CO2 from autotrophic, but not heterotrophic
soil respiration, Soil Biol. Biochem., 50, 26–32, 2012.
Ryan, E. and Ogle, K.: Inputs folder contents for DETECT model v1.0 [Data
set], Zenodo, https://doi.org/10.5281/zenodo.926064, 2017a.
Ryan, E. and Ogle, K.: Source code for running DETECT model v1.0. Zenodo,
https://doi.org/10.5281/zenodo.927501, 22 September 2017b.
Ryan, E. M., Ogle, K., Zelikova, T. J., LeCain, D. R., Williams, D. G.,
Morgan, J. A., and Pendall, E.: Antecedent moisture and temperature
conditions modulate the response of ecosystem respiration to elevated CO2
and warming, Glob. Change Biol., 21, 2588–2602, 2015.
Sala, O., Lauenroth, W., and Parton, W.: Long-Term Soil Water Dynamics in
the Shortgrass Steppe, Ecology, 73, 1175–1181, 1992.
Schwinning, S., Sala, O. E., Loik, M. E., and Ehleringer, J. R.: Thresholds,
memory, and seasonality: understanding pulse dynamics in arid/semi-arid
ecosystems, Oecologia, 141, 191–193, 2004.
Šimůnek, J. and Suarez, D. L.: Modeling of carbon dioxide transport
and production in soil: 1. Model development, Water Resour. Res., 29,
487–497, 1993.
Šimůnek, J., Van Genuchten, M. T., and Sejna, M.: The HYDRUS-1D software
package for simulating the one-dimensional movement of water, heat, and
multiple solutes in variably-saturated media, University of
California-Riverside Research Reports, 3, 1–240, 2005.
Šimůnek, J., van Genuchten, M. T., and Šejna, M.: Development
and applications of the HYDRUS and STANMOD software packages and related
codes, Vadose Zone J., 7, 587–600, 2008.
Šimůnek, J., Van Genuchten, M. T., and Šejna, M.: HYDRUS: Model
use, calibration, and validation, Trans. Asabe, 55, 1261–1274, 2012.
Sitch, S., Huntingford, C., Gedney, N., Levy, P., Lomas, M., Piao, S.,
Betts, R., Ciais, P., Cox, P., and Friedlingstein, P.: Evaluation of the
terrestrial carbon cycle, future plant geography and climate-carbon cycle
feedbacks using five Dynamic Global Vegetation Models (DGVMs), Glob. Change
Biol., 14, 2015–2039, 2008.
Sponseller, R. A.: Precipitation pulses and soil CO2 flux in a Sonoran
Desert ecosystem, Glob. Change Biol., 13, 426–436, 2007.
Tang, J., Baldocchi, D. D., Qi, Y., and Xu, L.: Assessing soil CO2 efflux
using continuous measurements of CO2 profiles in soils with small
solid-state sensors, Agr. Forest Meteorol., 118, 207–220,
2003.
Thomas, A. D., Hoon, S. R., and Linton, P. E.: Carbon dioxide fluxes from
cyanobacteria crusted soils in the Kalahari, Appl. Soil Ecol., 39,
254–263, 2008.
Todd-Brown, K. E., Hopkins, F. M., Kivlin, S. N., Talbot, J. M., and
Allison, S. D.: A framework for representing microbial decomposition in
coupled climate models, Biogeochemistry, 109, 19–33, 2012.
Tucker, C. L., Bell, J., Pendall, E., and Ogle, K.: Does declining
carbon-use efficiency explain thermal acclimation of soil respiration with
warming?, Glob. Change Biol., 19, 252–263, 2013.
Vargas, R., Baldocchi, D. D., Allen, M. F., Bahn, M., Black, T. A., Collins,
S. L., Yuste, J. C., Hirano, T., Jassal, R. S., and Pumpanen, J.: Looking
deeper into the soil: biophysical controls and seasonal lags of soil CO2
production and efflux, Ecol. Appl., 20, 1569–1582, 2010.
Vargas, R., Carbone, M. S., Reichstein, M., and Baldocchi, D. D.: Frontiers
and challenges in soil respiration research: from measurements to model-data
integration, Biogeochemistry, 102, 1–13, 2011.
Xiang, S.-R., Doyle, A., Holden, P. A., and Schimel, J. P.: Drying and
rewetting effects on C and N mineralization and microbial activity in
surface and subsurface California grassland soils, Soil Biol.
Biochem., 40, 2281–2289, 2008.
Xu, L., Baldocchi, D. D., and Tang, J.: How soil moisture, rain pulses, and
growth alter the response of ecosystem respiration to temperature, Global
Biogeochem. Cy., GB4002, https://doi.org/10.1029/2004GB002281, 2004.
Zelikova, T. J., Williams, D. G., Hoenigman, R., Blumenthal, D. M., Morgan,
J. A., and Pendall, E.: Seasonality of soil moisture mediates responses of
ecosystem phenology to elevated CO2 and warming in a semi-arid grassland,
J. Ecol., 103, 1119–1130, 2015.
Short summary
Our work evaluated the appropriateness of the common steady-state (SS) assumption, for example when partitioning soil respiration of CO2 into recently photosynthesized carbon (C) and older C. Using a new model of soil CO2 production and transport we found that the SS assumption is valid most of the time, especially in sand/silt soils. Non-SS conditions occurred mainly for the few days following large rain events in all soil types, but the non-SS period was prolonged and magnified in clay soils.
Our work evaluated the appropriateness of the common steady-state (SS) assumption, for example...
