Articles | Volume 9, issue 8
https://doi.org/10.5194/gmd-9-2639-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/gmd-9-2639-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Model description paper
| 
11 Aug 2016
Model description paper |
| 11 Aug 2016
Integrating peatlands into the coupled Canadian Land Surface Scheme (CLASS) v3.6 and the Canadian Terrestrial Ecosystem Model (CTEM) v2.0
Yuanqiao Wu
CORRESPONDING AUTHOR
Climate Processes Section, Climate Research Division, Environment and
Climate Change Canada, 4905 Dufferin Street, Toronto, ON, M3H 5T4, Canada
Diana L. Verseghy
Climate Processes Section, Climate Research Division, Environment and
Climate Change Canada, 4905 Dufferin Street, Toronto, ON, M3H 5T4, Canada
Joe R. Melton
Climate Processes Section, Climate Research Division, Environment and
Climate Change Canada, University of Victoria, 3800 Finnerty Road,
Victoria, BC, V8P 5C2, Canada
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Matthias Forkel, Niels Andela, Sandy P. Harrison, Gitta Lasslop, Margreet van Marle, Emilio Chuvieco, Wouter Dorigo, Matthew Forrest, Stijn Hantson, Angelika Heil, Fang Li, Joe Melton, Stephen Sitch, Chao Yue, and Almut Arneth
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Atmos. Chem. Phys., 17, 11135–11161, https://doi.org/10.5194/acp-17-11135-2017, https://doi.org/10.5194/acp-17-11135-2017, 2017
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Following the Global Methane Budget 2000–2012 published in Saunois et al. (2016), we use the same dataset of bottom-up and top-down approaches to discuss the variations in methane emissions over the period 2000–2012. The changes in emissions are discussed both in terms of trends and quasi-decadal changes. The ensemble gathered here allows us to synthesise the robust changes in terms of regional and sectorial contributions to the increasing methane emissions.
Joe R. Melton, Reinel Sospedra-Alfonso, and Kelly E. McCusker
Geosci. Model Dev., 10, 2761–2783, https://doi.org/10.5194/gmd-10-2761-2017, https://doi.org/10.5194/gmd-10-2761-2017, 2017
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Climate models have large grid cells due to the computational cost of running these complex models. Within grid cells like these, the land surface can vary dramatically impacting the exchange of water, carbon, and energy between the atmosphere and land. We use a technique to determine natural clusters of high-resolution soil texture within large grid cells and use them as inputs to our model. We find relatively low sensitivity to soil texture changes except in very dry regions and peatlands.
Yuanqiao Wu, Ed Chan, Joe R. Melton, and Diana L. Verseghy
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2017-152, https://doi.org/10.5194/gmd-2017-152, 2017
Preprint withdrawn
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Global vegetation models are important tools for understanding how the Earth system will change in the future, and fire is a critical process to include. A number of different methods have been developed to represent vegetation burning. This paper describes the protocol for the first systematic comparison of global fire models, which will allow the community to explore various drivers and evaluate what mechanisms are important for improving performance. It also includes equations for all models.
Marielle Saunois, Philippe Bousquet, Ben Poulter, Anna Peregon, Philippe Ciais, Josep G. Canadell, Edward J. Dlugokencky, Giuseppe Etiope, David Bastviken, Sander Houweling, Greet Janssens-Maenhout, Francesco N. Tubiello, Simona Castaldi, Robert B. Jackson, Mihai Alexe, Vivek K. Arora, David J. Beerling, Peter Bergamaschi, Donald R. Blake, Gordon Brailsford, Victor Brovkin, Lori Bruhwiler, Cyril Crevoisier, Patrick Crill, Kristofer Covey, Charles Curry, Christian Frankenberg, Nicola Gedney, Lena Höglund-Isaksson, Misa Ishizawa, Akihiko Ito, Fortunat Joos, Heon-Sook Kim, Thomas Kleinen, Paul Krummel, Jean-François Lamarque, Ray Langenfelds, Robin Locatelli, Toshinobu Machida, Shamil Maksyutov, Kyle C. McDonald, Julia Marshall, Joe R. Melton, Isamu Morino, Vaishali Naik, Simon O'Doherty, Frans-Jan W. Parmentier, Prabir K. Patra, Changhui Peng, Shushi Peng, Glen P. Peters, Isabelle Pison, Catherine Prigent, Ronald Prinn, Michel Ramonet, William J. Riley, Makoto Saito, Monia Santini, Ronny Schroeder, Isobel J. Simpson, Renato Spahni, Paul Steele, Atsushi Takizawa, Brett F. Thornton, Hanqin Tian, Yasunori Tohjima, Nicolas Viovy, Apostolos Voulgarakis, Michiel van Weele, Guido R. van der Werf, Ray Weiss, Christine Wiedinmyer, David J. Wilton, Andy Wiltshire, Doug Worthy, Debra Wunch, Xiyan Xu, Yukio Yoshida, Bowen Zhang, Zhen Zhang, and Qiuan Zhu
Earth Syst. Sci. Data, 8, 697–751, https://doi.org/10.5194/essd-8-697-2016, https://doi.org/10.5194/essd-8-697-2016, 2016
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An accurate assessment of the methane budget is important to understand the atmospheric methane concentrations and trends and to provide realistic pathways for climate change mitigation. The various and diffuse sources of methane as well and its oxidation by a very short lifetime radical challenge this assessment. We quantify the methane sources and sinks as well as their uncertainties based on both bottom-up and top-down approaches provided by a broad international scientific community.
Corinne Le Quéré, Robbie M. Andrew, Josep G. Canadell, Stephen Sitch, Jan Ivar Korsbakken, Glen P. Peters, Andrew C. Manning, Thomas A. Boden, Pieter P. Tans, Richard A. Houghton, Ralph F. Keeling, Simone Alin, Oliver D. Andrews, Peter Anthoni, Leticia Barbero, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Philippe Ciais, Kim Currie, Christine Delire, Scott C. Doney, Pierre Friedlingstein, Thanos Gkritzalis, Ian Harris, Judith Hauck, Vanessa Haverd, Mario Hoppema, Kees Klein Goldewijk, Atul K. Jain, Etsushi Kato, Arne Körtzinger, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Danica Lombardozzi, Joe R. Melton, Nicolas Metzl, Frank Millero, Pedro M. S. Monteiro, David R. Munro, Julia E. M. S. Nabel, Shin-ichiro Nakaoka, Kevin O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Christian Rödenbeck, Joe Salisbury, Ute Schuster, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Benjamin D. Stocker, Adrienne J. Sutton, Taro Takahashi, Hanqin Tian, Bronte Tilbrook, Ingrid T. van der Laan-Luijkx, Guido R. van der Werf, Nicolas Viovy, Anthony P. Walker, Andrew J. Wiltshire, and Sönke Zaehle
Earth Syst. Sci. Data, 8, 605–649, https://doi.org/10.5194/essd-8-605-2016, https://doi.org/10.5194/essd-8-605-2016, 2016
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The Global Carbon Budget 2016 is the 11th annual update of emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land, and ocean. This data synthesis brings together measurements, statistical information, and analyses of model results in order to provide an assessment of the global carbon budget and their uncertainties for years 1959 to 2015, with a projection for year 2016.
Stijn Hantson, Almut Arneth, Sandy P. Harrison, Douglas I. Kelley, I. Colin Prentice, Sam S. Rabin, Sally Archibald, Florent Mouillot, Steve R. Arnold, Paulo Artaxo, Dominique Bachelet, Philippe Ciais, Matthew Forrest, Pierre Friedlingstein, Thomas Hickler, Jed O. Kaplan, Silvia Kloster, Wolfgang Knorr, Gitta Lasslop, Fang Li, Stephane Mangeon, Joe R. Melton, Andrea Meyn, Stephen Sitch, Allan Spessa, Guido R. van der Werf, Apostolos Voulgarakis, and Chao Yue
Biogeosciences, 13, 3359–3375, https://doi.org/10.5194/bg-13-3359-2016, https://doi.org/10.5194/bg-13-3359-2016, 2016
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Our ability to predict the magnitude and geographic pattern of past and future fire impacts rests on our ability to model fire regimes. A large variety of models exist, and it is unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. In this paper we summarize the current state of the art in fire-regime modelling and model evaluation, and outline what lessons may be learned from the Fire Model Intercomparison Project – FireMIP.
Scot M. Miller, Roisin Commane, Joe R. Melton, Arlyn E. Andrews, Joshua Benmergui, Edward J. Dlugokencky, Greet Janssens-Maenhout, Anna M. Michalak, Colm Sweeney, and Doug E. J. Worthy
Biogeosciences, 13, 1329–1339, https://doi.org/10.5194/bg-13-1329-2016, https://doi.org/10.5194/bg-13-1329-2016, 2016
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We use atmospheric data from the US and Canada to examine seven wetland methane flux estimates. Relative to existing estimates, we find a methane source that is smaller in magnitude with a broader seasonal cycle. Furthermore, we estimate the largest fluxes over the Hudson Bay Lowlands, a spatial distribution that differs from commonly used remote sensing estimates of wetland location.
J. R. Melton and V. K. Arora
Geosci. Model Dev., 9, 323–361, https://doi.org/10.5194/gmd-9-323-2016, https://doi.org/10.5194/gmd-9-323-2016, 2016
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We use a modified form of the Lotka–Volterra (L–V) equations to simulate competition between plant functional types (PFTs) on a global scale with the Canadian Terrestrial Ecosystem Model (CTEM) version 2.0. Our modified L–V simulations compare well against observation-based records of PFT distributions, while simulations with unmodified L–V equations show significant biases. We include an appendix detailing all aspects of CTEM v. 2.0.
T. J. Bohn, J. R. Melton, A. Ito, T. Kleinen, R. Spahni, B. D. Stocker, B. Zhang, X. Zhu, R. Schroeder, M. V. Glagolev, S. Maksyutov, V. Brovkin, G. Chen, S. N. Denisov, A. V. Eliseev, A. Gallego-Sala, K. C. McDonald, M.A. Rawlins, W. J. Riley, Z. M. Subin, H. Tian, Q. Zhuang, and J. O. Kaplan
Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, https://doi.org/10.5194/bg-12-3321-2015, 2015
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We evaluated 21 forward models and 5 inversions over western Siberia in terms of CH4 emissions and simulated wetland areas and compared these results to an intensive in situ CH4 flux data set, several wetland maps, and two satellite inundation products. In addition to assembling a definitive collection of methane emissions estimates for the region, we were able to identify the types of wetland maps and model features necessary for accurate simulations of high-latitude wetlands.
J. R. Melton, R. K. Shrestha, and V. K. Arora
Biogeosciences, 12, 1151–1168, https://doi.org/10.5194/bg-12-1151-2015, https://doi.org/10.5194/bg-12-1151-2015, 2015
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Net ecosystem productivity (NEP) in seasonally dry Amazon forests varies
greatly between sites with similar precipitation patterns. We ran CLASS-CTEM at two LBA Amazon sites (Tapajós 83km & Jarú Reserve) that exhibit opposite seasonal NEP cycles despite reasonably similar meteorological conditions. We find the influence of soil texture and depth, through soil moisture, on seasonal patterns of GPP and, especially, heterotrophic respiration is important for correctly simulating NEP seasonality.
Y. Wu, C. Blodau, T. R. Moore, J. Bubier, S. Juutinen, and T. Larmola
Biogeosciences, 12, 79–101, https://doi.org/10.5194/bg-12-79-2015, https://doi.org/10.5194/bg-12-79-2015, 2015
J. B. Fisher, M. Sikka, W. C. Oechel, D. N. Huntzinger, J. R. Melton, C. D. Koven, A. Ahlström, M. A. Arain, I. Baker, J. M. Chen, P. Ciais, C. Davidson, M. Dietze, B. El-Masri, D. Hayes, C. Huntingford, A. K. Jain, P. E. Levy, M. R. Lomas, B. Poulter, D. Price, A. K. Sahoo, K. Schaefer, H. Tian, E. Tomelleri, H. Verbeeck, N. Viovy, R. Wania, N. Zeng, and C. E. Miller
Biogeosciences, 11, 4271–4288, https://doi.org/10.5194/bg-11-4271-2014, https://doi.org/10.5194/bg-11-4271-2014, 2014
J. R. Melton and V. K. Arora
Biogeosciences, 11, 1021–1036, https://doi.org/10.5194/bg-11-1021-2014, https://doi.org/10.5194/bg-11-1021-2014, 2014
R. Wania, J. R. Melton, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, G. Chen, A. V. Eliseev, P. O. Hopcroft, W. J. Riley, Z. M. Subin, H. Tian, P. M. van Bodegom, T. Kleinen, Z. C. Yu, J. S. Singarayer, S. Zürcher, D. P. Lettenmaier, D. J. Beerling, S. N. Denisov, C. Prigent, F. Papa, and J. O. Kaplan
Geosci. Model Dev., 6, 617–641, https://doi.org/10.5194/gmd-6-617-2013, https://doi.org/10.5194/gmd-6-617-2013, 2013
J. R. Melton, R. Wania, E. L. Hodson, B. Poulter, B. Ringeval, R. Spahni, T. Bohn, C. A. Avis, D. J. Beerling, G. Chen, A. V. Eliseev, S. N. Denisov, P. O. Hopcroft, D. P. Lettenmaier, W. J. Riley, J. S. Singarayer, Z. M. Subin, H. Tian, S. Zürcher, V. Brovkin, P. M. van Bodegom, T. Kleinen, Z. C. Yu, and J. O. Kaplan
Biogeosciences, 10, 753–788, https://doi.org/10.5194/bg-10-753-2013, https://doi.org/10.5194/bg-10-753-2013, 2013
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DCMIP2016: the tropical cyclone test case
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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)
Accurate assessment of land–atmosphere coupling in climate models requires high-frequency data output
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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
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Quantifying wildfire drivers and predictability in boreal peatlands using a two-step error-correcting machine learning framework in TeFire v1.0
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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
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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
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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
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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
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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
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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.
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
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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.
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
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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
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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
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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.
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
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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
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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
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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
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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
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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
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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
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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.
Rongyun Tang, Mingzhou Jin, Jiafu Mao, Daniel M. Ricciuto, Anping Chen, and Yulong Zhang
Geosci. Model Dev., 17, 1525–1542, https://doi.org/10.5194/gmd-17-1525-2024, https://doi.org/10.5194/gmd-17-1525-2024, 2024
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Carbon-rich boreal peatlands are at risk of burning. The reproducibility and predictability of rare peatland fire events are investigated by constructing a two-step error-correcting machine learning framework to tackle such complex systems. Fire occurrence and impacts are highly predictable with our approach. Factor-controlling simulations revealed that temperature, moisture, and freeze–thaw cycles control boreal peatland fires, indicating thermal impacts on causing peat fires.
Allison B. Collow, Peter R. Colarco, Arlindo M. da Silva, Virginie Buchard, Huisheng Bian, Mian Chin, Sampa Das, Ravi Govindaraju, Dongchul Kim, and Valentina Aquila
Geosci. Model Dev., 17, 1443–1468, https://doi.org/10.5194/gmd-17-1443-2024, https://doi.org/10.5194/gmd-17-1443-2024, 2024
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The GOCART aerosol module within the Goddard Earth Observing System recently underwent a major refactoring and update to the representation of physical processes. Code changes that were included in GOCART Second Generation (GOCART-2G) are documented, and we establish a benchmark simulation that is to be used for future development of the system. The 4-year benchmark simulation was evaluated using in situ and spaceborne measurements to develop a baseline and prioritize future development.
Oksana Guba, Mark A. Taylor, Peter A. Bosler, Christopher Eldred, and Peter H. Lauritzen
Geosci. Model Dev., 17, 1429–1442, https://doi.org/10.5194/gmd-17-1429-2024, https://doi.org/10.5194/gmd-17-1429-2024, 2024
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We want to reduce errors in the moist energy budget in numerical atmospheric models. We study a few common assumptions and mechanisms that are used for the moist physics. Some mechanisms are more consistent with the underlying equations. Separately, we study how assumptions about models' thermodynamics affect the modeled energy of precipitation. We also explain how to conserve energy in the moist physics for nonhydrostatic models.
Konstantin Aiteew, Jarno Rouhiainen, Claas Nendel, and René Dechow
Geosci. Model Dev., 17, 1349–1385, https://doi.org/10.5194/gmd-17-1349-2024, https://doi.org/10.5194/gmd-17-1349-2024, 2024
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This study evaluated the biogeochemical model MONICA and its performance in simulating soil organic carbon changes. MONICA can reproduce plant growth, carbon and nitrogen dynamics, soil water and temperature. The model results were compared with five established carbon turnover models. With the exception of certain sites, adequate reproduction of soil organic carbon stock change rates was achieved. The MONICA model was capable of performing similar to or even better than the other models.
Jianfeng Li, Kai Zhang, Taufiq Hassan, Shixuan Zhang, Po-Lun Ma, Balwinder Singh, Qiyang Yan, and Huilin Huang
Geosci. Model Dev., 17, 1327–1347, https://doi.org/10.5194/gmd-17-1327-2024, https://doi.org/10.5194/gmd-17-1327-2024, 2024
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By comparing E3SM simulations with and without regional refinement, we find that model horizontal grid spacing considerably affects the simulated aerosol mass budget, aerosol–cloud interactions, and the effective radiative forcing of anthropogenic aerosols. The study identifies the critical physical processes strongly influenced by model resolution. It also highlights the benefit of applying regional refinement in future modeling studies at higher or even convection-permitting resolutions.
Bernd Funke, Thierry Dudok de Wit, Ilaria Ermolli, Margit Haberreiter, Doug Kinnison, Daniel Marsh, Hilde Nesse, Annika Seppälä, Miriam Sinnhuber, and Ilya Usoskin
Geosci. Model Dev., 17, 1217–1227, https://doi.org/10.5194/gmd-17-1217-2024, https://doi.org/10.5194/gmd-17-1217-2024, 2024
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We outline a road map for the preparation of a solar forcing dataset for the upcoming Phase 7 of the Coupled Model Intercomparison Project (CMIP7), considering the latest scientific advances made in the reconstruction of solar forcing and in the understanding of climate response while also addressing the issues that were raised during CMIP6.
Fiona Raphaela Spuler, Jakob Benjamin Wessel, Edward Comyn-Platt, James Varndell, and Chiara Cagnazzo
Geosci. Model Dev., 17, 1249–1269, https://doi.org/10.5194/gmd-17-1249-2024, https://doi.org/10.5194/gmd-17-1249-2024, 2024
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Before using climate models to study the impacts of climate change, bias adjustment is commonly applied to the models to ensure that they correspond with observations at a local scale. However, this can introduce undesirable distortions into the climate model. In this paper, we present an open-source python package called ibicus to enable the comparison and detailed evaluation of bias adjustment methods, facilitating their transparent and rigorous application.
Donghui Xu, Gautam Bisht, Zeli Tan, Chang Liao, Tian Zhou, Hong-Yi Li, and L. Ruby Leung
Geosci. Model Dev., 17, 1197–1215, https://doi.org/10.5194/gmd-17-1197-2024, https://doi.org/10.5194/gmd-17-1197-2024, 2024
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We aim to disentangle the hydrological and hydraulic controls on streamflow variability in a fully coupled earth system model. We found that calibrating only one process (i.e., traditional calibration procedure) will result in unrealistic parameter values and poor performance of the water cycle, while the simulated streamflow is improved. To address this issue, we further proposed a two-step calibration procedure to reconcile the impacts from hydrological and hydraulic processes on streamflow.
Douglas McNeall, Eddy Robertson, and Andy Wiltshire
Geosci. Model Dev., 17, 1059–1089, https://doi.org/10.5194/gmd-17-1059-2024, https://doi.org/10.5194/gmd-17-1059-2024, 2024
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We can run simulations of the land surface and carbon cycle, using computer models to help us understand and predict climate change and its impacts. These simulations are not perfect reproductions of the real land surface, and that can make them less effective tools. We use new statistical and computational techniques to help us understand how different our models are from the real land surface, how to make them more realistic, and how well we can simulate past and future climate.
Genevieve L. Clow, Nicole S. Lovenduski, Michael N. Levy, Keith Lindsay, and Jennifer E. Kay
Geosci. Model Dev., 17, 975–995, https://doi.org/10.5194/gmd-17-975-2024, https://doi.org/10.5194/gmd-17-975-2024, 2024
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Satellite observations of chlorophyll allow us to study marine phytoplankton on a global scale; yet some of these observations are missing due to clouds and other issues. To investigate the impact of missing data, we developed a satellite simulator for chlorophyll in an Earth system model. We found that missing data can impact the global mean chlorophyll by nearly 20 %. The simulated observations provide a more direct comparison to real-world data and can be used to improve model validation.
Jiateng Guo, Xuechuang Xu, Luyuan Wang, Xulei Wang, Lixin Wu, Mark Jessell, Vitaliy Ogarko, Zhibin Liu, and Yufei Zheng
Geosci. Model Dev., 17, 957–973, https://doi.org/10.5194/gmd-17-957-2024, https://doi.org/10.5194/gmd-17-957-2024, 2024
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This study proposes a semi-supervised learning algorithm using pseudo-labels for 3D geological modelling. We establish a 3D geological model using borehole data from a complex real urban local survey area in Shenyang and make an uncertainty analysis of this model. The method effectively expands the sample space, which is suitable for geomodelling and uncertainty analysis from boreholes. The modelling results perform well in terms of spatial morphology and geological semantics.
Shih-Wei Wei, Mariusz Pagowski, Arlindo da Silva, Cheng-Hsuan Lu, and Bo Huang
Geosci. Model Dev., 17, 795–813, https://doi.org/10.5194/gmd-17-795-2024, https://doi.org/10.5194/gmd-17-795-2024, 2024
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This study describes the modeling system and the evaluation results for the first prototype version of a global aerosol reanalysis product at NOAA, prototype NOAA Aerosol ReAnalysis version 1.0 (pNARA v1.0). We evaluated pNARA v1.0 against independent datasets and compared it with other reanalyses. We identified deficiencies in the system (both in the forecast model and in the data assimilation system) and the uncertainties that exist in our reanalysis.
Emma Howard, Chun-Hsu Su, Christian Stassen, Rajashree Naha, Harvey Ye, Acacia Pepler, Samuel S. Bell, Andrew J. Dowdy, Simon O. Tucker, and Charmaine Franklin
Geosci. Model Dev., 17, 731–757, https://doi.org/10.5194/gmd-17-731-2024, https://doi.org/10.5194/gmd-17-731-2024, 2024
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The BARPA-R modelling configuration has been developed to produce high-resolution climate hazard projections within the Australian region. When using boundary driving data from quasi-observed historical conditions, BARPA-R shows good performance with errors generally on par with reanalysis products. BARPA-R also captures trends, known modes of climate variability, large-scale weather processes, and multivariate relationships.
Deepeshkumar Jain, Suryachandra A. Rao, Ramu A. Dandi, Prasanth A. Pillai, Ankur Srivastava, Maheswar Pradhan, and Kiran V. Gangadharan
Geosci. Model Dev., 17, 709–729, https://doi.org/10.5194/gmd-17-709-2024, https://doi.org/10.5194/gmd-17-709-2024, 2024
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The present paper discusses and evaluates the new Monsoon Mission Coupled Forecast System model (MMCFS) version 2.0 which upgrades the currently operational MMCFS v1.0 at the Indian Meteorological Department, India. The individual model components have been substantially upgraded independently by their respective scientific groups. MMCFS v2.0 includes these upgrades in the operational coupled model. The new model shows significant skill improvement in simulating the Indian monsoon.
Nathan Beech, Thomas Rackow, Tido Semmler, and Thomas Jung
Geosci. Model Dev., 17, 529–543, https://doi.org/10.5194/gmd-17-529-2024, https://doi.org/10.5194/gmd-17-529-2024, 2024
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Cost-reducing modeling strategies are applied to high-resolution simulations of the Southern Ocean in a changing climate. They are evaluated with respect to observations and traditional, lower-resolution modeling methods. The simulations effectively reproduce small-scale ocean flows seen in satellite data and are largely consistent with traditional model simulations after 4 °C of warming. Small-scale flows are found to intensify near bathymetric features and to become more variable.
Karl E. Taylor
Geosci. Model Dev., 17, 415–430, https://doi.org/10.5194/gmd-17-415-2024, https://doi.org/10.5194/gmd-17-415-2024, 2024
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Remapping gridded data in a way that preserves the conservative properties of the climate system can be essential in coupling model components and for accurate assessment of the system’s energy and mass constituents. Remapping packages capable of handling a wide variety of grids can, for some common grids, calculate remapping weights that are somewhat inaccurate. Correcting for these errors, guidelines are provided to ensure conservation when the weights are used in practice.
Pedro M. M. Soares, Frederico Johannsen, Daniela C. A. Lima, Gil Lemos, Virgílio A. Bento, and Angelina Bushenkova
Geosci. Model Dev., 17, 229–259, https://doi.org/10.5194/gmd-17-229-2024, https://doi.org/10.5194/gmd-17-229-2024, 2024
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This study uses deep learning (DL) to downscale global climate models for the Iberian Peninsula. Four DL architectures were evaluated and trained using historical climate data and then used to downscale future projections from the global models. These show agreement with the original models and reveal a warming of 2 ºC to 6 ºC, along with decreasing precipitation in western Iberia after 2040. This approach offers key regional climate change information for adaptation strategies in the region.
Abhiraj Bishnoi, Olaf Stein, Catrin I. Meyer, René Redler, Norbert Eicker, Helmuth Haak, Lars Hoffmann, Daniel Klocke, Luis Kornblueh, and Estela Suarez
Geosci. Model Dev., 17, 261–273, https://doi.org/10.5194/gmd-17-261-2024, https://doi.org/10.5194/gmd-17-261-2024, 2024
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We enabled the weather and climate model ICON to run in a high-resolution coupled atmosphere–ocean setup on the JUWELS supercomputer, where the ocean and the model I/O runs on the CPU Cluster, while the atmosphere is running simultaneously on GPUs. Compared to a simulation performed on CPUs only, our approach reduces energy consumption by 45 % with comparable runtimes. The experiments serve as preparation for efficient computing of kilometer-scale climate models on future supercomputing systems.
Diana R. Gergel, Steven B. Malevich, Kelly E. McCusker, Emile Tenezakis, Michael T. Delgado, Meredith A. Fish, and Robert E. Kopp
Geosci. Model Dev., 17, 191–227, https://doi.org/10.5194/gmd-17-191-2024, https://doi.org/10.5194/gmd-17-191-2024, 2024
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The freely available Global Downscaled Projections for Climate Impacts Research (GDPCIR) dataset gives researchers a new tool for studying how future climate will evolve at a local or regional level, corresponding to the latest global climate model simulations prepared as part of the UN Intergovernmental Panel on Climate Change’s Sixth Assessment Report. Those simulations represent an enormous advance in quality, detail, and scope that GDPCIR translates to the local level.
Yuying Zhang, Shaocheng Xie, Yi Qin, Wuyin Lin, Jean-Christophe Golaz, Xue Zheng, Po-Lun Ma, Yun Qian, Qi Tang, Christopher R. Terai, and Meng Zhang
Geosci. Model Dev., 17, 169–189, https://doi.org/10.5194/gmd-17-169-2024, https://doi.org/10.5194/gmd-17-169-2024, 2024
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We performed systematic evaluation of clouds simulated in the Energy
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Exascale Earth System Model (E3SMv2) to document model performance and understand what updates in E3SMv2 have caused changes in clouds from E3SMv1 to E3SMv2. We find that stratocumulus clouds along the subtropical west coast of continents are dramatically improved, primarily due to the retuning done in CLUBB. This study offers additional insights into clouds simulated in E3SMv2 and will benefit future E3SM developments.
Ting Sun, Hamidreza Omidvar, Zhenkun Li, Ning Zhang, Wenjuan Huang, Simone Kotthaus, Helen C. Ward, Zhiwen Luo, and Sue Grimmond
Geosci. Model Dev., 17, 91–116, https://doi.org/10.5194/gmd-17-91-2024, https://doi.org/10.5194/gmd-17-91-2024, 2024
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For the first time, we coupled a state-of-the-art urban land surface model – Surface Urban Energy and Water Scheme (SUEWS) – with the widely-used Weather Research and Forecasting (WRF) model, creating an open-source tool that may benefit multiple applications. We tested our new system at two UK sites and demonstrated its potential by examining how human activities in various areas of Greater London influence local weather conditions.
Katja Frieler, Jan Volkholz, Stefan Lange, Jacob Schewe, Matthias Mengel, María del Rocío Rivas López, Christian Otto, Christopher P. O. Reyer, Dirk Nikolaus Karger, Johanna T. Malle, Simon Treu, Christoph Menz, Julia L. Blanchard, Cheryl S. Harrison, Colleen M. Petrik, Tyler D. Eddy, Kelly Ortega-Cisneros, Camilla Novaglio, Yannick Rousseau, Reg A. Watson, Charles Stock, Xiao Liu, Ryan Heneghan, Derek Tittensor, Olivier Maury, Matthias Büchner, Thomas Vogt, Tingting Wang, Fubao Sun, Inga J. Sauer, Johannes Koch, Inne Vanderkelen, Jonas Jägermeyr, Christoph Müller, Sam Rabin, Jochen Klar, Iliusi D. Vega del Valle, Gitta Lasslop, Sarah Chadburn, Eleanor Burke, Angela Gallego-Sala, Noah Smith, Jinfeng Chang, Stijn Hantson, Chantelle Burton, Anne Gädeke, Fang Li, Simon N. Gosling, Hannes Müller Schmied, Fred Hattermann, Jida Wang, Fangfang Yao, Thomas Hickler, Rafael Marcé, Don Pierson, Wim Thiery, Daniel Mercado-Bettín, Robert Ladwig, Ana Isabel Ayala-Zamora, Matthew Forrest, and Michel Bechtold
Geosci. Model Dev., 17, 1–51, https://doi.org/10.5194/gmd-17-1-2024, https://doi.org/10.5194/gmd-17-1-2024, 2024
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Our paper provides an overview of all observational climate-related and socioeconomic forcing data used as input for the impact model evaluation and impact attribution experiments within the third round of the Inter-Sectoral Impact Model Intercomparison Project. The experiments are designed to test our understanding of observed changes in natural and human systems and to quantify to what degree these changes have already been induced by climate change.
Jinkai Tan, Qiqiao Huang, and Sheng Chen
Geosci. Model Dev., 17, 53–69, https://doi.org/10.5194/gmd-17-53-2024, https://doi.org/10.5194/gmd-17-53-2024, 2024
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This study presents a deep learning architecture, multi-scale feature fusion (MFF), to improve the forecast skills of precipitations especially for heavy precipitations. MFF uses multi-scale receptive fields so that the movement features of precipitation systems are well captured. MFF uses the mechanism of discrete probability to reduce uncertainties and forecast errors so that heavy precipitations are produced.
Robert E. Kopp, Gregory G. Garner, Tim H. J. Hermans, Shantenu Jha, Praveen Kumar, Alexander Reedy, Aimée B. A. Slangen, Matteo Turilli, Tamsin L. Edwards, Jonathan M. Gregory, George Koubbe, Anders Levermann, Andre Merzky, Sophie Nowicki, Matthew D. Palmer, and Chris Smith
Geosci. Model Dev., 16, 7461–7489, https://doi.org/10.5194/gmd-16-7461-2023, https://doi.org/10.5194/gmd-16-7461-2023, 2023
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Future sea-level rise projections exhibit multiple forms of uncertainty, all of which must be considered by scientific assessments intended to inform decision-making. The Framework for Assessing Changes To Sea-level (FACTS) is a new software package intended to support assessments of global mean, regional, and extreme sea-level rise. An early version of FACTS supported the development of the IPCC Sixth Assessment Report sea-level projections.
Gregory Duveiller, Mark Pickering, Joaquin Muñoz-Sabater, Luca Caporaso, Souhail Boussetta, Gianpaolo Balsamo, and Alessandro Cescatti
Geosci. Model Dev., 16, 7357–7373, https://doi.org/10.5194/gmd-16-7357-2023, https://doi.org/10.5194/gmd-16-7357-2023, 2023
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Some of our best tools to describe the state of the land system, including the intensity of heat waves, have a problem. The model currently assumes that the number of leaves in ecosystems always follows the same cycle. By using satellite observations of when leaves are present, we show that capturing the yearly changes in this cycle is important to avoid errors in estimating surface temperature. We show that this has strong implications for our capacity to describe heat waves across Europe.
Neil C. Swart, Torge Martin, Rebecca Beadling, Jia-Jia Chen, Christopher Danek, Matthew H. England, Riccardo Farneti, Stephen M. Griffies, Tore Hattermann, Judith Hauck, F. Alexander Haumann, André Jüling, Qian Li, John Marshall, Morven Muilwijk, Andrew G. Pauling, Ariaan Purich, Inga J. Smith, and Max Thomas
Geosci. Model Dev., 16, 7289–7309, https://doi.org/10.5194/gmd-16-7289-2023, https://doi.org/10.5194/gmd-16-7289-2023, 2023
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Current climate models typically do not include full representation of ice sheets. As the climate warms and the ice sheets melt, they add freshwater to the ocean. This freshwater can influence climate change, for example by causing more sea ice to form. In this paper we propose a set of experiments to test the influence of this missing meltwater from Antarctica using multiple different climate models.
Christina Asmus, Peter Hoffmann, Joni-Pekka Pietikäinen, Jürgen Böhner, and Diana Rechid
Geosci. Model Dev., 16, 7311–7337, https://doi.org/10.5194/gmd-16-7311-2023, https://doi.org/10.5194/gmd-16-7311-2023, 2023
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Irrigation modifies the land surface and soil conditions. The effects can be quantified using numerical climate models. Our study introduces a new irrigation parameterization, which simulates the effects of irrigation on land, atmosphere, and vegetation. We applied the parameterization and evaluated the results in terms of their physical consistency. We found an improvement in the model results in the 2 m temperature representation in comparison with observational data for our study.
Nanhong Xie, Tijian Wang, Xiaodong Xie, Xu Yue, Filippo Giorgi, Qian Zhang, Danyang Ma, Rong Song, Baiyao Xu, Shu Li, Bingliang Zhuang, Mengmeng Li, Min Xie, Natalya Andreeva Kilifarska, Georgi Gadzhev, and Reneta Dimitrova
EGUsphere, https://doi.org/10.5194/egusphere-2023-1733, https://doi.org/10.5194/egusphere-2023-1733, 2023
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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. The research results show that RegCM-Chem-YIBs model is a valuable tool for studying terrestrial carbon cycle, atmospheric chemistry, and climate change in regional scale.
Michael Meier and Christof Bigler
Geosci. Model Dev., 16, 7171–7201, https://doi.org/10.5194/gmd-16-7171-2023, https://doi.org/10.5194/gmd-16-7171-2023, 2023
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We analyzed >2.3 million calibrations and 39 million projections of leaf coloration models, considering 21 models, 5 optimization algorithms, ≥7 sampling procedures, and 26 climate scenarios. Models based on temperature, day length, and leaf unfolding performed best, especially when calibrated with generalized simulated annealing and systematically balanced or stratified samples. Projected leaf coloration shifts between −13 and +20 days by 2080–2099.
Katharina Gallmeier, J. Xavier Prochaska, Peter Cornillon, Dimitris Menemenlis, and Madolyn Kelm
Geosci. Model Dev., 16, 7143–7170, https://doi.org/10.5194/gmd-16-7143-2023, https://doi.org/10.5194/gmd-16-7143-2023, 2023
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This paper introduces an approach to evaluate numerical models of ocean circulation. We compare the structure of satellite-derived sea surface temperature anomaly (SSTa) instances determined by a machine learning algorithm at 10–80 km scales to those output by a high-resolution MITgcm run. The simulation over much of the ocean reproduces the observed distribution of SSTa patterns well. This general agreement, alongside a few notable exceptions, highlights the potential of this approach.
Angus Fotherby, Harold J. Bradbury, Jennifer L. Druhan, and Alexandra V. Turchyn
Geosci. Model Dev., 16, 7059–7074, https://doi.org/10.5194/gmd-16-7059-2023, https://doi.org/10.5194/gmd-16-7059-2023, 2023
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We demonstrate how, given a simulation of fluid and rock interacting, we can emulate the system using machine learning. This means that, for a given initial condition, we can predict the final state, avoiding the simulation step once the model has been trained. We present a workflow for applying this approach to any fluid–rock simulation and showcase two applications to different fluid–rock simulations. This approach has applications for improving model development and sensitivity analyses.
Rose V. Palermo, J. Taylor Perron, Jason M. Soderblom, Samuel P. D. Birch, Alexander G. Hayes, and Andrew D. Ashton
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2023-223, https://doi.org/10.5194/gmd-2023-223, 2023
Revised manuscript accepted for GMD
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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 by either uniform erosion processes 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.
Yaqi Wang, Lanning Wang, Juan Feng, Zhenya Song, Qizhong Wu, and Huaqiong Cheng
Geosci. Model Dev., 16, 6857–6873, https://doi.org/10.5194/gmd-16-6857-2023, https://doi.org/10.5194/gmd-16-6857-2023, 2023
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In this study, to noticeably improve precipitation simulation in steep mountains, we propose a sub-grid parameterization scheme for the topographic vertical motion in CAM5-SE to revise the original vertical velocity by adding the topographic vertical motion. The dynamic lifting effect of topography is extended from the lowest layer to multiple layers, thus improving the positive deviations of precipitation simulation in high-altitude regions and negative deviations in low-altitude regions.
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
EGUsphere, https://doi.org/10.5194/egusphere-2023-2720, https://doi.org/10.5194/egusphere-2023-2720, 2023
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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.
Cited articles
Adkinson, A. C. and Humphreys, E. R.: The response of carbon dioxide exchange to manipulations of Sphagnum water content in an ombrotrophic bog, Ecohydrology, 4.6, 733-743, 2011.
Adkinson, A. C., Syed, K. H., and Flanagan, L. B.: Contrasting responses of growing season ecosystem CO2 exchange to variation in temperature and water table depth in two peatlands in northern Alberta, Canada, J. Geophys. Res.-Biogeo., 116, G01004, https://doi.org/10.1029/2010JG001512, 2011.
Ångström, A.: A study of the radiation of the atmosphere, Smithson. Misc. Collect., 65, 1–159, 1918.
Arora, V. K.: Simulating energy and carbon fluxes over winter wheat using coupled land surface and terrestrial ecosystem models, Agr. Forest Meteorol., 118, 21–47, 2003.
Arora, V. K. and Boer, G. J.: A parameterization of leaf phenology for the terrestrial ecosystem component of climate models, Glob. Change Biol., 11, 39–59, https://doi.org/10.1111/j.1365-2486.2004.00890.x, 2005.
Aurela, M., Tuovinen, J.-P., and Laurila, T.: Carbon dioxide exchange in a subarctic peatland ecosystem in northern Europe measured by the eddy covariance technique, J. Geophys. Res.-Atmos., 103, 11289–11301, 1998.
Aurela, M., Lohila, A., Tuovinen, J.-P., Hatakka, J., Riutta, T., and Laurila, T.: Carbon dioxide exchange on a northern boreal fen, Boreal Environ. Res., 14, 699–710, 2009.
Bazile, E., Traullé, O., Barral, H., Vihma, T., Holtslag, A. A. M., and Svensson, G.: GABLS4: An intercomparison case for 1D models to study the stable boundary layer at Dome-C on the Antarctic plateau, EMS Annual Meeting Abstracts, Vol. 10, EMS2013-578, 2013.
Ballantyne, A. P., Alden, C. B., Miller, J. B., Tans, P. P., and White, J. W. C.: Increase in observed net carbon dioxide uptake by land and oceans during the past 50 years, Nature, 488, 70–72, 2012.
Bellisario, L. M., Dale Boudreau, L., Verseghy, D. L., Rouse, W. R., and Blanken, P. D.: Comparing the performance of the Canadian land surface scheme@ class) for two subarctic terrain types, Atmosphere-Ocean, 38, 181–204, 2000.
Beringer, J., Lynch, A. H., Chapin III, F. S., Mack, M., and Bonan, G. B.: The representation of arctic soils in the land surface model: the importance of mosses, J. Climate, 14, 3324–3335, 2001.
Bohn, T. J., Melton, J. R., Ito, A., Kleinen, T., Spahni, R., Stocker, B. D., Zhang, B., Zhu, X., Schroeder, R., Glagolev, M. V., Maksyutov, S., Brovkin, V., Chen, G., Denisov, S. N., Eliseev, A. V., Gallego-Sala, A., McDonald, K. C., Rawlins, M. A., Riley, W. J., Subin, Z. M., Tian, H., Zhuang, Q., and Kaplan, J. O.: WETCHIMP-WSL: intercomparison of wetland methane emissions models over West Siberia, Biogeosciences, 12, 3321–3349, https://doi.org/10.5194/bg-12-3321-2015, 2015.
Bonan, G. B., Levis, S., Kergoat, L., and Oleson, K. W.: Landscapes as patches of plant functional types: An integrating concept for climate and ecosystem models, Global Biogeochem. Cy., 16, 5–1, 2002.
Bond-Lamberty, B., Gower, S. T., and Ahl, D. E.: Improved simulation of poorly drained forests using Biome-BGC, Tree Physiol., 27, 703–715, 2007.
Bubier, J. L., Moore, T. R., and Crosby, G.: Fine-scale vegetation distribution in a cool temperate peatland, Botany, 84, 910–923, 2006.
Camill, P. and Clark, J. S.: Long-term perspectives on lagged ecosystem responses to climate change: permafrost in boreal peatlands and the grassland/woodland boundary, Ecosystems, 3, 534–544, 2000.
Canada Committee on Ecological (Biophysical) Land Classification: National Wetlands Working Group. The Canadian wetland classification system, edited by: Warner, B. G. and Rubec, C. D. A., Wetlands Research Branch, University of Waterloo, 1997.
Christensen, J. H., Krishna Kumar, K., Aldrian, E., An, S.-I., Cavalcanti, I. F. A., de Castro, M., Dong, W., Goswami, P., Hall, A., Kanyanga, J. K., Kitoh, A., Kossin, J., Lau, N.-C., Renwick, J., Stephenson, D. B., Xie, S.-P., and Zhou, T.: Climate Phenomena and their Relevance for Future Regional Climate Change, in: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, 2013.
Comer, N. T., Lafleur, P. M., Roulet, N. T., Letts, M. G., Skarupa, M., and Verseghy, D.: A test of the Canadian Land Surface Scheme (CLASS) for a variety of wetland types, Atmos.-Ocean, 38, 161–179, 2000.
Crawford, T. M. and Duchon, C. E.: An improved parameterization for estimating effective atmospheric emissivity for use in calculating daytime downwelling longwave radiation, J. Appl. Meteorol., 38, 474–480, 1999.
Davidson, E. A. and Janssens, I. A.: Temperature sensitivity of soil carbon decomposition and feedbacks to climate change, Nature, 440, 165–173, 2006.
Dorrepaal, E., Toet, S., van Logtestijn, R. S. P., Swart, E., van de Weg, M. J., Callaghan, T. V., and Aerts, R.: Carbon respiration from subsurface peat accelerated by climate warming in the subarctic, Nature, 460, 616–619, 2009.
Dimitrov, D. D., Grant, R. F., Lafleur, P. M., and Humphreys, E. R.: Modeling the effects of hydrology on ecosystem respiration at Mer Bleue bog, J. Geophys. Res., 115, G04043, https://doi.org/10.1029/2010JG001312, 2010.
Dinsmore, K. J., Billett, M. F., Skiba, U. M., Rees, R. M., Drewer, J., and Helfter, C.: Role of the aquatic pathway in the carbon and greenhouse gas budgets of a peatland catchment, Glob. Change Biol., 16, 2750–2762, 2010.
Drewer, J., Lohila, A., Aurela, M., Laurila, T., Minkkinen, K., Penttilä, T., Dinsmore, K. J., McKenzie, R. M., Helfter, C., Flechard, C., Sutton, M. A., and Skiba, U. M.: Comparison of greenhouse gas fluxes and nitrogen budgets from an ombotrophic bog in Scotland and a minerotrophic sedge fen in Finland, Eur. J. Soil Sci., 61, 640–650, 2010.
Ekici, A., Beer, C., Hagemann, S., Boike, J., Langer, M., and Hauck, C.: Simulating high-latitude permafrost regions by the JSBACH terrestrial ecosystem model, Geosci. Model Dev., 7, 631–647, https://doi.org/10.5194/gmd-7-631-2014, 2014.
Farquhar, G. D.: Models of Integrated Photosynthesis of Cells and Leaves, Philos. Trans. R. Soc. Lond. B Biol. Sci., 323, 357–367, 1989.
Flanagan, L. B. and Syed, K. H.: Stimulation of both photosynthesis and respiration in response to warmer and drier conditions in a boreal peatland ecosystem, Glob. Change Biol., 17, 2271–2287, 2011.
Frolking, S., Goulden, M. L., Wofsy, S. C., Fan, S.-M., Sutton, D. J., Munger, J. W., Bazzaz, A. M., Daube, B. C., Crill, P. M., Aber, J. D., Band, L. E., Wang, X., Savage, K., Moore, T. and Harriss, R. C.: Modelling temporal variability in the carbon balance of a spruce/moss boreal forest, Glob. Change Biol., 2, 343–366, 1996.
Frolking, S., Roulet, N. T., Moore, T. R., Richard, P. J. H., Lavoie, M., Muller, S. D.: Modeling northern peatland decomposition and peat accumulation, Ecosystems, 4, 479–498, 2001.
Frolking, S., Roulet, N. T., Tuittila, E., Bubier, J. L., Quillet, A., Talbot, J., and Richard, P. J. H.: A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation, Earth Syst. Dynam., 1, 1–21, https://doi.org/10.5194/esd-1-1-2010, 2010.
Givnish, T. J.: Adaptive significance of evergreen vs. deciduous leaves: solving the triple paradox, Silva Fennica, 36, 703–743, 2002.
Gong, J., Kellomäki, S., Wang, K., Zhang, C., Shurpali, N., and Martikainen, P. J.: Modeling CO2 and CH4 flux changes in pristine peatlands of Finland under changing climate conditions, Ecol. Modell., 263, 64–80, 2013.
Granberg, G., Grip, H., Ottosson Löfvenius, M., Sundh, I., Svensson, B. H., and Nilsson, M.: A simple model for simulation of water content, soil frost, and soil temperatures in boreal mixed mires, Water Resour. Res., 35, 3771–3782, 1999.
Hayward, P. M. and Clymo, R. S.: Profiles of water content and pore size in Sphagnum and peat, and their relation to peat bog ecology, P. Roy. Soc. Lond. B Bio., 215, 299–325, 1982.
Kaplan, J. O., Bigelow, N. H., Prentice, I. C., Harrison, S. P., Bartlein, P. J., Christensen, T. R., Cramer, W., Matveyeva, N. V., McGuire, A. D., Murray, D. F., Razzhivin, V. Y., Smith, B., Walker, D. A., Anderson, P. M., Andreev, A. A., Brubaker, L. B., Edwards, M. E., and Lozhkin, A. V.: Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections, J. Geophys. Res.-Atmos., 108, 8171, https://doi.org/10.1029/2002JD002559, 2003.
Kleinen, T., Brovkin, V., and Schuldt, R. J.: A dynamic model of wetland extent and peat accumulation: results for the Holocene, Biogeosciences, 9, 235–248, https://doi.org/10.5194/bg-9-235-2012, 2012.
Kottek, M., Grieser, J., Beck, C., Rudolf, B., and Rubel, F.: World Map of the Köppen-Geiger climate classification updated, Meteorol. Z., 15, 259–263, https://doi.org/10.1127/0941-2948/2006/0130, 2006.
Laine, A. M., Bubier, J., Riutta, T., Nilsson, M. B., Moore, T. R., Vasander, H., and Tuittila, E.-S.: Abundance and composition of plant biomass as potential controls for mire net ecosytem CO2 exchange, Botany, 90, 63–74, 2011.
Lee, T. J. and Pielke, R. A.: Estimating the soil surface specific humidity, J. Appl. Meteorol., 31, 480–484, 1992.
Leith, F. I., Garnett, M. H., Dinsmore, K. J., Billett, M. F., and Heal, K. V.: Source and age of dissolved and gaseous carbon in a peatland–riparian–stream continuum: a dual isotope (14C and δ13C) analysis, Biogeochemistry, 119, 415–433, 2014.
Letts, M. J., Roulet, N. T., Comer, N. T., Skarupa, M. R., and Verseghy, D. L.: Parametrization of peatland hydraulic properties for the Canadian Land Surface Scheme, Atmos.-Ocean, 38, 141–160, 2000.
Loisel, J. and Garneau, M.: Late Holocene paleoecohydrology and carbon accumulation estimates from two boreal peat bogs in eastern Canada: Potential and limits of multi-proxy archives, Palaeogeogr. Palaeocl., 291, 493–533, 2010.
Ise, T., Dunn, A. L., Wofsy, S. C., and Moorcroft, P. R.: High sensitivity of peat decomposition to climate change through water-table feedback, Nat. Geosci., 1, 763–766, 2008.
Lafleur, P. M., Hember, R. A., Admiral, S. W., and Roulet, N. T.: Annual and seasonal variability in evapotranspiration and water table at a shrub-covered bog in southern Ontario, Canada, Hydrol. Process., 19, 3533–3550, 2005.
Lund, M., Lindroth, A., Christensen, T. R., and Ström, L.: Annual CO2 balance of a temperate bog, Tellus B, 59, 804–811, 2007.
Maanavilja, L., Riutta, T., Aurela, M., Pulkkinen, M., Laurila, T., and Tuittila, E.-S.: Spatial variation in CO2 exchange at a northern aapa mire, Biogeochemistry, 104, 325–345, 2011.
McCarter, C. P. R. and Price, J. S.: Ecohydrology of Sphagnum moss hummocks: mechanisms of capitula water supply and simulated effects of evaporation, Ecohydrol., 7, 33–44, https://doi.org/10.1002/eco.1313, 2012.
McCree, K. J.: Test of current definitions of photosynthetically active radiation against leaf photosynthesis data, Agr. Meteorol., 10, 443–453, 1972.
McGuire, A. D., Anderson, L. G., Christensen, T. R., Dallimore, S., Guo, L., Hayes, D. J., Heimann, M., Lorenson, T. D., Macdonald, R. W. and Roulet, N.: Sensitivity of the carbon cycle in the Arctic to climate change, Ecol. Monogr., 79, 523–555, 2009.
Melton, J. R. and Arora, V. K.: Sub-grid scale representation of vegetation in global land surface schemes: implications for estimation of the terrestrial carbon sink, Biogeosciences., 11, 1021–1036, https://doi.org/10.5194/bg-11-1021-2014, 2014.
Melton, J. R. and Arora, V. K.: Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0, Geosci. Model Dev., 9, 323–361, https://doi.org/10.5194/gmd-9-323-2016, 2016.
Melton, J. R., Shrestha, R. K., and Arora, V. K.: The influence of soils on heterotrophic respiration exerts a strong control on net ecosystem productivity in seasonally dry Amazonian forests, Biogeosciences, 12, 1151–1168, https://doi.org/10.5194/bg-12-1151-2015, 2015.
Moore, T. R., Bubier, J. L., Frolking, S. E., Lafleur, P. M., and Roulet, N. T.: Plant biomass and production and CO2 exchange in an ombrotrophic bog, J. Ecol., 90, 25–36, 2002.
Moore, T. R., Lafleur, P. M., Poon, D. M., Heumann, B. W., Seaquist, J. W., and Roulet, N. T.: Spring photosynthesis in a cool temperate bog, Glob. Change Biol., 12, 2323–2335, 2006.
Munir, T. M., Xu, B., Perkins, M., and Strack, M.: Responses of carbon dioxide flux and plant biomass to water table drawdown in a treed peatland in northern Alberta: a climate change perspective, Biogeosciences, 11, 807–820, https://doi.org/10.5194/bg-11-807-2014, 2014.
Murphy, M. T., McKinley, A., and Moore, T. R.: Variations in above-and below-ground vascular plant biomass and water table on a temperate ombrotrophic peatland, Botany, 87, 845–853, 2009.
O'Donnell, J. A., Romanovsky, V. E., Harden, J. W., and McGuire, A. D.: The effect of moisture content on the thermal conductivity of moss and organic soil horizons from black spruce ecosystems in interior Alaska, Soil Sci., 174, 646–651, 2009.
Peichl, M., Öquist, M., Ottosson Löfvenius, M., Ilstedt, U., Sagerfors, J., Grelle, A., Lindroth, A., and Nilsson, M. B.: A 12-year record reveals pre-growing season temperature and water table level threshold effects on the net carbon dioxide exchange in a boreal fen, Environ. Res. Lett., 9, 055006, https://doi.org/10.1088/1748-9326/9/5/055006, 2014.
Porada, P., Weber, B., Elbert, W., Pöschl, U., and Kleidon, A.: Estimating global carbon uptake by lichens and bryophytes with a process-based model, Biogeosciences, 10, 6989–7033, https://doi.org/10.5194/bg-10-6989-2013, 2013.
Price, J. S. and Whittington, P. N.: Water flow in Sphagnum hummocks: Mesocosm measurements and modelling, J. Hydrol., 381, 333–340, 2010.
Price, J. S., Whittington, P. N., Elrick, D. E., Strack, M., Brunet, N., and Faux, E.: A method to determine unsaturated hydraulic conductivity in living and undecomposed moss, Soil Sci. Soc. Am. J., 72, 487–491, 2008.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, available at: http://www.R-project.org/ (last access: 22 October 2015.), 2014.
Reich, P. B., Ellsworth, D. S., and Walters, M. B.: Leaf structure (specific leaf area) modulates photosynthesis–nitrogen relations: evidence from within and across species and functional groups, Funct. Ecol., 12, 948–958, 1998.
Rice, S. K., Aclander, L., and Hanson, D. T.: Do bryophyte shoot systems function like vascular plant leaves or canopies? Functional trait relationships in Sphagnum mosses (Sphagnaceae), Am. J. Bot., 95, 1366–1374, 2008.
Robroek, B. J. M., Schouten, M. G. C., Limpens, J., Berendse, F., and Poorter, H.: Interactive effects of water table and precipitation on net CO2 assimilation of three co-occurring Sphagnum mosses differing in distribution above the water table, Glob. Change Biol., 15, 680–691, 2009.
Roulet, N. T., Lafleur, P. M., Richard, P. J., Moore, T. R., Humphreys, E. R., and Bubier, J. I. L. L.: Contemporary carbon balance and late Holocene carbon accumulation in a northern peatland, Glob. Change Biol., 13, 397–411, 2007.
Rydin, H. and Jeglum, J.: The Biology of Peatlands, Oxford Univ. Press, Oxford, United Kingdom, 2006.
Sagerfors, J., Lindroth, A., Grelle, A., Klemedtsson, L., Weslien, P., and Nilsson, M.: Annual CO2 exchange between a nutrient-poor, minerotrophic, boreal mire and the atmosphere, J. Geophys. Res.-Biogeo., 113, G01001, https://doi.org/10.1029/2006JG000306, 2008.
Schuldt, R. J., Brovkin, V., Kleinen, T., and Winderlich, J.: Modelling Holocene carbon accumulation and methane emissions of boreal wetlands – an Earth system model approach, Biogeosciences, 10, 1659–1674, https://doi.org/10.5194/bg-10-1659-2013, 2013.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture–climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, 2010.
Spahni, R., Joos, F., Stocker, B. D., Steinacher, M., and Yu, Z. C.: Transient simulations of the carbon and nitrogen dynamics in northern peatlands: from the Last Glacial Maximum to the 21st century, Clim. Past, 9, 1287–1308, https://doi.org/10.5194/cp-9-1287-2013, 2013.
St-Hilaire, F., Wu, J., Roulet, N. T., Frolking, S., Lafleur, P. M., Humphreys, E. R., and Arora, V.: McGill wetland model: evaluation of a peatland carbon simulator developed for global assessments, Biogeosciences, 7, 3517–3530, https://doi.org/10.5194/bg-7-3517-2010, 2010.
Sulman, B., Desai, A., and Schroeder, N.: Impact of hydrological variations on modeling of peatland CO2 fluxes: Results from the North American Carbon Program site synthesis, J. Geophys. Res., 117, G01031, https://doi.org/10.1029/2011JG001862, 2012.
Syed, K. H., Flanagan, L. B., Carlson, P. J., Glenn, A. J., and Van Gaalen, K. E.: Environmental control of net ecosystem CO2 exchange in a treed, moderately rich fen in northern Alberta, Agr. Forest Meteorol., 140, 97–114, 2006.
Talbot, J., Richard, P. J. H., Roulet, N. T., and Booth, R. K.: Assessing long-term hydrological and ecological responses to drainage in a raised bog using paleoecology and a hydrosequence, J. Veg. Sci., 21, 143–156, 2010.
Tanja, S., Berninger, F., Vesala, T., Markkanen, T., Hari, P., Mäkelä, A., Ilvesniemi, H., Hanninen, H., Nikinmaa, E., Huttula, T., Laurila, T., Aurela, M, Grelle, A., Lindroth, A., Arneth, A., Shibistova, O., and Lloyd, J.: Air temperature triggers the recovery of evergreen boreal forest photosynthesis in spring, Glob. Change Biol., 9, 1410–1426, 2003.
Tarnocai, C.: The effect of climate change on carbon in Canadian peatlands, Glob. Planet. Change, 53, 222–232, 2006.
Taylor, K. E.: Summarizing multiple aspects of model performance in a single diagram, J. Geophys. Res., 106, 7183–7192, https://doi.org/10.1029/2000JD900719, 2001.
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.
Turetsky, M. R.: The role of bryophytes in carbon and nitrogen cycling, The Bryologist, 106, 395–409, 2003.
Turetsky, M. R., Bond-Lamberty, B., Euskirchen, E., Talbot, J., Frolking, S., McGuire, A. D., and Tuittila, E.-S.: The resilience and functional role of moss in boreal and arctic ecosystems, New Phytol., 196, 49–67, https://doi.org/10.1111/j.1469-8137.2012.04254.x, 2012.
Turetsky, M. R., Kotowska, A., Bubier, J., Dise, N. B., Crill, P., Hornibrook, E. R. C., Minkkinen, K., Moore, T. R., Myers-Smith, I. H., Nykänen, H., Olefeldt, D., Rinne, J., Saarnio, S., Shurpali, N., Tuittila, E.-S., Waddington, J. M., White, J. R., Wickland, K. P., and Wilmking, M.: A synthesis of methane emissions from 71 northern, temperate, and subtropical wetlands, Glob. Chane Biol., 20, 2183–2197, 2014.
Verseghy, D.: CLASS – the Canadian Land Surface Scheme (Version 3.6), Technical Documentation, Tech. rep., Science and Technology Branch, Environment Canada, 2012.
Verseghy, D. L.: CLASS – a Canadian land surface scheme for GCMs, I. Soil model, Int. J. Climatol., 11, 111–133, 1991.
Verseghy, D. L., McFarlane, N. A., and Lazare, M.: CLASS – a Canadian land surface scheme for GCMs, II. Vegetation model and coupled runs, Int. J. Climatol., 13, 347–370, 1993.
Vitt, D. H.: A key and review of bryophytes common in North American peatlands, Evansia, 31, 121–158, 2014.
Ward, S. E., Ostle, N. J., Oakley, S., Quirk, H., Henrys, P. A., and Bardgett, R. D.: Warming effects on greenhouse gas fluxes in peatlands are modulated by vegetation composition, Ecol. Lett., 16, 1285–1293, 2013.
Wang, H., Richardson, C. J., and Ho, M.: Dual controls on carbon loss during drought in peatlands, Nature Climate Change, 5, 584–587, 2015.
Wania, R., Ross, I., and Prentice,: Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes, Global Biogeochem. Cy., 23, GB3014, https://doi.org/10.1029/2008GB003412, 2009a.
Wania, R., Ross, I., and Prentice, I. C.: Integrating peatlands and permafrost into a dynamic global vegetation model: 2. Evaluation and sensitivity of vegetation and carbon cycle processes, Global Biogeochem. Cy., 23, GB3015, https://doi.org/10.1029/2008GB003413, 2009b.
Williams, T. G. and Flanagan, L. B.: Measuring and modelling environmental influences on photosynthetic gas exchange in Sphagnum and Pleurozium, Plant Cell Environ., 21, 555–564, 1998.
Wu, J. and Roulet, N. T.: Climate change reduces the capacity of northern peatlands to absorb the atmospheric carbon dioxide: The different responses of bogs and fens, Global Biogeochem. Cy., 28, 1005–1024, 2014.
Wu, J., Roulet, N. T., Sagerfors, J., and Nilsson, M. B.: Simulation of six years of carbon fluxes for a sedge-dominated oligotrophic minerogenic peatland in Northern Sweden using the McGill Wetland Model (MWM), J. Geophys. Res.-Biogeo., 118, 795–807, 2013.
Wu, Y. and Blodau, C.: PEATBOG: a biogeochemical model for analyzing coupled carbon and nitrogen dynamics in northern peatlands, Geosci. Model Dev., 6, 1173–1207, https://doi.org/10.5194/gmd-6-1173-2013, 2013.
Yebra, M., Van Dijk, A. I., Leuning, R., and Guerschman, J. P.: Global vegetation gross primary production estimation using satellite-derived light-use efficiency and canopy conductance, Remote Sens. Environ., 163, 206–216, 2015.
Yu, Z.: Holocene carbon flux histories of the world's peatlands Global carbon-cycle implications, Holocene, 21, 761–774, 2011.
Yu, Z., Loisel, J., Brosseau, D. P., Beilman, D. W., and Hunt, S.J.: Global peatland dynamics since the Last Glacial Maximum, Geophys. Res. Lett., 37, L13402, https://doi.org/10.1029/2010GL043584, 2010.
Yu, Z., Loisel, J., Turetsky, M. R., Cai, S., Zhao, Y., Frolking, S., MacDonald, G. M., and Bubier, J. L.: Evidence for elevated emissions from high-latitude wetlands contributing to high atmospheric CH4 concentration in the early Holocene, Global Biogeochem. Cy., 27, 131–140, 2013.
Yurova, A., Wolf, A., Sagerfors, J., and Nilsson, M.: Variations in net ecosystem exchange of carbon dioxide in a boreal mire: Modeling mechanisms linked to water table position, J. Geophys. Res.-Biogeo., 112, G02025, https://doi.org/10.1029/2006JG000342, 2007.
Short summary
About 20 % of the carbon stored in global soils occurs in peatlands. Warmer and drier conditions will both tend to stimulate the decomposition of peat and increase CO2 and methane emissions, thus potentially enhancing the warming trend. It is important that this feedback mechanism be captured in climate models. This work integrated peatlands into the Canadian Earth system model (CanESM) for global climate predictions and represent a valuable enhancement to the family of Earth system models.
About 20 % of the carbon stored in global soils occurs in peatlands. Warmer and drier...
