Articles | Volume 12, issue 10
https://doi.org/10.5194/gmd-12-4443-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-12-4443-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Improving permafrost physics in the coupled Canadian Land Surface Scheme (v.3.6.2) and Canadian Terrestrial Ecosystem Model (v.2.1) (CLASS-CTEM)
Climate Research Division, Environment and Climate Change Canada, Victoria, B.C., Canada
Diana L. Verseghy
Formerly at Climate Research Division, Environment and Climate Change, Toronto, Canada
retired
Reinel Sospedra-Alfonso
Canadian Centre for Climate Modelling and Analysis, Climate Research Division, Environment and Climate Change Canada, Victoria, B.C., Canada
Stephan Gruber
Department of Geography and Environmental Studies, Carleton University, Ottawa, Canada
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This preprint is open for discussion and under review for The Cryosphere (TC).
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Hanyu Liu, Felix R. Vogel, Misa Ishizawa, Zhen Zhang, Benjamin Poulter, Doug E. J. Worthy, Leyang Feng, Anna L. Gagné-Landmann, Ao Chen, Ziting Huang, Dylan C. Gaeta, Joe R. Melton, Douglas Chan, Vineet Yadav, Deborah Huntzinger, and Scot M. Miller
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This preprint is open for discussion and under review for Geoscientific Model Development (GMD).
Short summary
Short summary
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Earth Syst. Sci. Data, 17, 1873–1958, https://doi.org/10.5194/essd-17-1873-2025, https://doi.org/10.5194/essd-17-1873-2025, 2025
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Methane (CH4) is the second most important human-influenced greenhouse gas in terms of climate forcing after carbon dioxide (CO2). A consortium of multi-disciplinary scientists synthesise and update the budget of the sources and sinks of CH4. This edition benefits from important progress in estimating emissions from lakes and ponds, reservoirs, and streams and rivers. For the 2010s decade, global CH4 emissions are estimated at 575 Tg CH4 yr-1, including ~65 % from anthropogenic sources.
Hosein Fereydooni, Stephan Gruber, David Stillman, and Derek Cronmiller
EGUsphere, https://doi.org/10.5194/egusphere-2025-1801, https://doi.org/10.5194/egusphere-2025-1801, 2025
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Detecting ground ice in permafrost is crucial for climate research and infrastructure, but traditional methods often struggle to distinguish it. This study examines the dielectric properties of ground ice as a unique fingerprint. Field measurements were taken at two Yukon permafrost sites: a retrogressive thaw slump and a pingo. Comparing these with electrical resistivity and impedance results, we found relaxation time is a more reliable indicator for ground ice detection.
Libo Wang, Lawrence Mudryk, Joe R. Melton, Colleen Mortimer, Jason Cole, Gesa Meyer, Paul Bartlett, and Mickaël Lalande
EGUsphere, https://doi.org/10.5194/egusphere-2025-1264, https://doi.org/10.5194/egusphere-2025-1264, 2025
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This study shows that an alternate snow cover fraction (SCF) parameterization significantly improves SCF simulated in the CLASSIC model in mountainous areas for all three choices of meteorological datasets. Annual mean bias, unbiased root mean squared area, and correlation improve by 75 %, 32 %, and 7 % when evaluated with MODIS SCF observations over the Northern Hemisphere. We also link relative biases in the meteorological forcing data to differences in simulated snow water equivalent and SCF.
Bin Cao and Stephan Gruber
EGUsphere, https://doi.org/10.5194/egusphere-2025-575, https://doi.org/10.5194/egusphere-2025-575, 2025
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The climate-driven changes in cold regions have an outsized importance for local resilient communities and for global climate through teleconnections. We shows that reanalyses are less accurate in cold regions compared to other more populated regions, coincident with the low density of observations. Our findings likely point to similar gaps in our knowledge and capabilities for climate research and services in cold regions.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
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Atmos. Chem. Phys., 24, 10013–10038, https://doi.org/10.5194/acp-24-10013-2024, https://doi.org/10.5194/acp-24-10013-2024, 2024
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Methane (CH4) emissions in Canada for 2007–2017 were estimated using Canada’s surface greenhouse gas measurements. The estimated emissions show no significant trend, but emission uncertainty was reduced as more measurement sites became available. Notably for climate change, we find the wetland CH4 emissions show a positive correlation with surface air temperature in summer. Canada’s measurement network could monitor future CH4 emission changes and compliance with climate change mitigation goals.
Roberto Bilbao, Pablo Ortega, Didier Swingedouw, Leon Hermanson, Panos Athanasiadis, Rosie Eade, Marion Devilliers, Francisco Doblas-Reyes, Nick Dunstone, An-Chi Ho, William Merryfield, Juliette Mignot, Dario Nicolì, Margarida Samsó, Reinel Sospedra-Alfonso, Xian Wu, and Stephen Yeager
Earth Syst. Dynam., 15, 501–525, https://doi.org/10.5194/esd-15-501-2024, https://doi.org/10.5194/esd-15-501-2024, 2024
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In recent decades three major volcanic eruptions have occurred: Mount Agung in 1963, El Chichón in 1982 and Mount Pinatubo in 1991. In this article we explore the climatic impacts of these volcanic eruptions with a purposefully designed set of simulations from six CMIP6 decadal prediction systems. We analyse the radiative and dynamical responses and show that including the volcanic forcing in these predictions is important to reproduce the observed surface temperature variations.
Salvatore R. Curasi, Joe R. Melton, Elyn R. Humphreys, Txomin Hermosilla, and Michael A. Wulder
Geosci. Model Dev., 17, 2683–2704, https://doi.org/10.5194/gmd-17-2683-2024, https://doi.org/10.5194/gmd-17-2683-2024, 2024
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Canadian forests are responding to fire, harvest, and climate change. Models need to quantify these processes and their carbon and energy cycling impacts. We develop a scheme that, based on satellite records, represents fire, harvest, and the sparsely vegetated areas that these processes generate. We evaluate model performance and demonstrate the impacts of disturbance on carbon and energy cycling. This work has implications for land surface modeling and assessing Canada’s terrestrial C cycle.
Jason Neil Steven Cole, Knut von Salzen, Jiangnan Li, John Scinocca, David Plummer, Vivek Arora, Norman McFarlane, Michael Lazare, Murray MacKay, and Diana Verseghy
Geosci. Model Dev., 16, 5427–5448, https://doi.org/10.5194/gmd-16-5427-2023, https://doi.org/10.5194/gmd-16-5427-2023, 2023
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The Canadian Atmospheric Model version 5 (CanAM5) is used to simulate on a global scale the climate of Earth's atmosphere, land, and lakes. We document changes to the physics in CanAM5 since the last major version of the model (CanAM4) and evaluate the climate simulated relative to observations and CanAM4. The climate simulated by CanAM5 is similar to CanAM4, but there are improvements, including better simulation of temperature and precipitation over the Amazon and better simulation of cloud.
Bo Qu, Alexandre Roy, Joe R. Melton, Jennifer L. Baltzer, Youngryel Ryu, Matteo Detto, and Oliver Sonnentag
EGUsphere, https://doi.org/10.5194/egusphere-2023-1167, https://doi.org/10.5194/egusphere-2023-1167, 2023
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Accurately simulating photosynthesis and evapotranspiration challenges terrestrial biosphere models across North America’s boreal biome, in part due to uncertain representation of the maximum rate of photosynthetic carboxylation (Vcmax). This study used forest stand scale observations in an optimization framework to improve Vcmax values for representative vegetation types. Several stand characteristics well explained spatial Vcmax variability and were useful to improve boreal forest modelling.
Alessandro Cicoira, Samuel Weber, Andreas Biri, Ben Buchli, Reynald Delaloye, Reto Da Forno, Isabelle Gärtner-Roer, Stephan Gruber, Tonio Gsell, Andreas Hasler, Roman Lim, Philippe Limpach, Raphael Mayoraz, Matthias Meyer, Jeannette Noetzli, Marcia Phillips, Eric Pointner, Hugo Raetzo, Cristian Scapozza, Tazio Strozzi, Lothar Thiele, Andreas Vieli, Daniel Vonder Mühll, Vanessa Wirz, and Jan Beutel
Earth Syst. Sci. Data, 14, 5061–5091, https://doi.org/10.5194/essd-14-5061-2022, https://doi.org/10.5194/essd-14-5061-2022, 2022
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This paper documents a monitoring network of 54 positions, located on different periglacial landforms in the Swiss Alps: rock glaciers, landslides, and steep rock walls. The data serve basic research but also decision-making and mitigation of natural hazards. It is the largest dataset of its kind, comprising over 209 000 daily positions and additional weather data.
Francisco José Cuesta-Valero, Hugo Beltrami, Stephan Gruber, Almudena García-García, and J. Fidel González-Rouco
Geosci. Model Dev., 15, 7913–7932, https://doi.org/10.5194/gmd-15-7913-2022, https://doi.org/10.5194/gmd-15-7913-2022, 2022
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Inversions of subsurface temperature profiles provide past long-term estimates of ground surface temperature histories and ground heat flux histories at timescales of decades to millennia. Theses estimates complement high-frequency proxy temperature reconstructions and are the basis for studying continental heat storage. We develop and release a new bootstrap method to derive meaningful confidence intervals for the average surface temperature and heat flux histories from any number of profiles.
Élise G. Devoie, Stephan Gruber, and Jeffrey M. McKenzie
Earth Syst. Sci. Data, 14, 3365–3377, https://doi.org/10.5194/essd-14-3365-2022, https://doi.org/10.5194/essd-14-3365-2022, 2022
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Soil freezing characteristic curves (SFCCs) relate the temperature of a soil to its ice content. SFCCs are needed in all physically based numerical models representing freezing and thawing soils, and they affect the movement of water in the subsurface, biogeochemical processes, soil mechanics, and ecology. Over a century of SFCC data exist, showing high variability in SFCCs based on soil texture, water content, and other factors. This repository summarizes all available SFCC data and metadata.
Joe R. Melton, Ed Chan, Koreen Millard, Matthew Fortier, R. Scott Winton, Javier M. Martín-López, Hinsby Cadillo-Quiroz, Darren Kidd, and Louis V. Verchot
Geosci. Model Dev., 15, 4709–4738, https://doi.org/10.5194/gmd-15-4709-2022, https://doi.org/10.5194/gmd-15-4709-2022, 2022
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Peat-ML is a high-resolution global peatland extent map generated using machine learning techniques. Peatlands are important in the global carbon and water cycles, but their extent is poorly known. We generated Peat-ML using drivers of peatland formation including climate, soil, geomorphology, and vegetation data, and we train the model with regional peatland maps. Our accuracy estimation approaches suggest Peat-ML is of similar or higher quality than other available peatland mapping products.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Reinel Sospedra-Alfonso, William J. Merryfield, George J. Boer, Viatsheslav V. Kharin, Woo-Sung Lee, Christian Seiler, and James R. Christian
Geosci. Model Dev., 14, 6863–6891, https://doi.org/10.5194/gmd-14-6863-2021, https://doi.org/10.5194/gmd-14-6863-2021, 2021
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CanESM5 decadal predictions that started from observed climate states represent the observed evolution of upper-ocean temperatures, surface climate, and the carbon cycle better than ones not started from observed climate states for several years into the forecast. This is due both to better representations of climate internal variability and to corrections of the model response to external forcing including changes in GHG emissions and aerosols.
Lina Teckentrup, Martin G. De Kauwe, Andrew J. Pitman, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Emilie Joetzjer, Etsushi Kato, Sebastian Lienert, Danica Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Julia Pongratz, Stephen Sitch, Anthony P. Walker, and Sönke Zaehle
Biogeosciences, 18, 5639–5668, https://doi.org/10.5194/bg-18-5639-2021, https://doi.org/10.5194/bg-18-5639-2021, 2021
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The Australian continent is included in global assessments of the carbon cycle such as the global carbon budget, yet the performance of dynamic global vegetation models (DGVMs) over Australia has rarely been evaluated. We assessed simulations by an ensemble of dynamic global vegetation models over Australia and highlighted a number of key areas that lead to model divergence on both short (inter-annual) and long (decadal) timescales.
Claude-Michel Nzotungicimpaye, Kirsten Zickfeld, Andrew H. MacDougall, Joe R. Melton, Claire C. Treat, Michael Eby, and Lance F. W. Lesack
Geosci. Model Dev., 14, 6215–6240, https://doi.org/10.5194/gmd-14-6215-2021, https://doi.org/10.5194/gmd-14-6215-2021, 2021
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In this paper, we describe a new wetland methane model (WETMETH) developed for use in Earth system models. WETMETH consists of simple formulations to represent methane production and oxidation in wetlands. We also present an evaluation of the model performance as embedded in the University of Victoria Earth System Climate Model (UVic ESCM). WETMETH is capable of reproducing mean annual methane emissions consistent with present-day estimates from the regional to the global scale.
Niccolò Tubini, Stephan Gruber, and Riccardo Rigon
The Cryosphere, 15, 2541–2568, https://doi.org/10.5194/tc-15-2541-2021, https://doi.org/10.5194/tc-15-2541-2021, 2021
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We present a new method to compute temperature changes with melting and freezing – a fundamental challenge in cryosphere research – extremely efficiently and with guaranteed correctness of the energy balance for any time step size. This is a key feature since the integration time step can then be chosen according to the timescale of the processes to be studied, from seconds to days.
Gesa Meyer, Elyn R. Humphreys, Joe R. Melton, Alex J. Cannon, and Peter M. Lafleur
Biogeosciences, 18, 3263–3283, https://doi.org/10.5194/bg-18-3263-2021, https://doi.org/10.5194/bg-18-3263-2021, 2021
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Shrub and sedge plant functional types (PFTs) were incorporated in the land surface component of the Canadian Earth System Model to improve representation of Arctic tundra ecosystems. Evaluated against 14 years of non-winter measurements, the magnitude and seasonality of carbon dioxide and energy fluxes at a Canadian dwarf-shrub tundra site were better captured by the shrub PFTs than by previously used grass and tree PFTs. Model simulations showed the tundra site to be an annual net CO2 source.
Wolfgang A. Obermeier, Julia E. M. S. Nabel, Tammas Loughran, Kerstin Hartung, Ana Bastos, Felix Havermann, Peter Anthoni, Almut Arneth, Daniel S. Goll, Sebastian Lienert, Danica Lombardozzi, Sebastiaan Luyssaert, Patrick C. McGuire, Joe R. Melton, Benjamin Poulter, Stephen Sitch, Michael O. Sullivan, Hanqin Tian, Anthony P. Walker, Andrew J. Wiltshire, Soenke Zaehle, and Julia Pongratz
Earth Syst. Dynam., 12, 635–670, https://doi.org/10.5194/esd-12-635-2021, https://doi.org/10.5194/esd-12-635-2021, 2021
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We provide the first spatio-temporally explicit comparison of different model-derived fluxes from land use and land cover changes (fLULCCs) by using the TRENDY v8 dynamic global vegetation models used in the 2019 global carbon budget. We find huge regional fLULCC differences resulting from environmental assumptions, simulated periods, and the timing of land use and land cover changes, and we argue for a method consistent across time and space and for carefully choosing the accounting period.
John Mohd Wani, Renoj J. Thayyen, Chandra Shekhar Prasad Ojha, and Stephan Gruber
The Cryosphere, 15, 2273–2293, https://doi.org/10.5194/tc-15-2273-2021, https://doi.org/10.5194/tc-15-2273-2021, 2021
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We study the surface energy balance from a cold-arid permafrost environment in the Indian Himalayan region. The GEOtop model was used for the modelling of surface energy balance. Our results show that the variability in the turbulent heat fluxes is similar to that reported from the seasonally frozen ground and permafrost regions of the Tibetan Plateau. Further, the low relative humidity could be playing a critical role in the surface energy balance and the permafrost processes.
Zichong Chen, Junjie Liu, Daven K. Henze, Deborah N. Huntzinger, Kelley C. Wells, Stephen Sitch, Pierre Friedlingstein, Emilie Joetzjer, Vladislav Bastrikov, Daniel S. Goll, Vanessa Haverd, Atul K. Jain, Etsushi Kato, Sebastian Lienert, Danica L. Lombardozzi, Patrick C. McGuire, Joe R. Melton, Julia E. M. S. Nabel, Benjamin Poulter, Hanqin Tian, Andrew J. Wiltshire, Sönke Zaehle, and Scot M. Miller
Atmos. Chem. Phys., 21, 6663–6680, https://doi.org/10.5194/acp-21-6663-2021, https://doi.org/10.5194/acp-21-6663-2021, 2021
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NASA's Orbiting Carbon Observatory 2 (OCO-2) satellite observes atmospheric CO2 globally. We use a multiple regression and inverse model to quantify the relationships between OCO-2 and environmental drivers within individual years for 2015–2018 and within seven global biomes. Our results point to limitations of current space-based observations for inferring environmental relationships but also indicate the potential to inform key relationships that are very uncertain in process-based models.
Christian Seiler, Joe R. Melton, Vivek K. Arora, and Libo Wang
Geosci. Model Dev., 14, 2371–2417, https://doi.org/10.5194/gmd-14-2371-2021, https://doi.org/10.5194/gmd-14-2371-2021, 2021
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This study evaluates how well the CLASSIC land surface model reproduces the energy, water, and carbon cycle when compared against a wide range of global observations. Special attention is paid to how uncertainties in the data used to drive and evaluate the model affect model skill. Our results show the importance of incorporating uncertainties when evaluating land surface models and that failing to do so may potentially misguide future model development.
Rupesh Subedi, Steven V. Kokelj, and Stephan Gruber
The Cryosphere, 14, 4341–4364, https://doi.org/10.5194/tc-14-4341-2020, https://doi.org/10.5194/tc-14-4341-2020, 2020
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Permafrost beneath tundra near Lac de Gras (Northwest Territories, Canada) contains more ice and less organic carbon than shown in global compilations. Excess-ice content of 20–60 %, likely remnant Laurentide basal ice, is found in upland till. This study is based on 24 boreholes up to 10 m deep. Findings highlight geology and glacial legacy as determinants of a mosaic of permafrost characteristics with potential for thaw subsidence up to several metres in some locations.
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Short summary
Soils in cold regions store large amounts of carbon that could be released to the atmosphere if the soils thaw. To best simulate these soils, we explored different configurations and parameterizations of the CLASS-CTEM model and compared to observations. The revised model with a deeper soil column, new soil depth dataset, and inclusion of moss simulated greatly improved annual thaw depths and ground temperatures. We estimate subgrid-scale features limit further improvements against observations.
Soils in cold regions store large amounts of carbon that could be released to the atmosphere if...