Articles | Volume 9, issue 3
https://doi.org/10.5194/gmd-9-1243-2016
© 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-9-1243-2016
© 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
| 
01 Apr 2016
Model description paper |
| 01 Apr 2016
Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) dynamic vegetation–land surface model
Jean-Sébastien Landry
CORRESPONDING AUTHOR
Department of Geography, McGill University, Montréal, Canada
currently at: Department of Geography, Planning and Environment,
Concordia University, Montréal, Canada
David T. Price
Natural Resources Canada, Canadian Forest Service, Northern Forestry Centre, Edmonton, Canada
Navin Ramankutty
Liu Institute for Global Issues and Institute for Resources, Environment, and Sustainability,
University of British Columbia, Vancouver, Canada
Lael Parrott
Earth and Environmental Sciences and Biology, Irving K. Barber School of Arts and Sciences,
University of British Columbia, Kelowna, Canada
H. Damon Matthews
Department of Geography, Planning and Environment, Concordia University, Montréal, Canada
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Jean-Sébastien Landry, Lael Parrott, David T. Price, Navin Ramankutty, and H. Damon Matthews
Biogeosciences, 13, 5277–5295, https://doi.org/10.5194/bg-13-5277-2016, https://doi.org/10.5194/bg-13-5277-2016, 2016
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We simulated mountain pine beetle (MPB) outbreaks under four scenarios for the presence and growth release strength of non-attacked vegetation, and found that: (1) impacts on ecosystem carbon and radiative forcing varied greatly across the four scenarios; (2) the global climatic impact from the current outbreak in British Columbia, Canada, seemed smaller than one month of anthropogenic CO2 emissions; and (3) MPB-killed dead standing trees might hasten post-outbreak vegetation recovery.
Jean-Sébastien Landry and H. Damon Matthews
Biogeosciences, 13, 2137–2149, https://doi.org/10.5194/bg-13-2137-2016, https://doi.org/10.5194/bg-13-2137-2016, 2016
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We simulated both fire pulses and stable fire regimes and found the resulting climatic impacts to be irreconcilable with equivalent amounts of CO2 emissions produced by fossil fuel combustion. Consequently, side-by-side comparisons of fire and fossil fuel CO2 emissions—implicitly implying that they have similar effects—should be avoided. Our study calls for the explicit representation of fire in climate models in order to improve our understanding of its impacts in the Earth system.
Friedrich J. Bohn, Ana Bastos, Romina Martin, Anja Rammig, Niak Sian Koh, Giles B. Sioen, Bram Buscher, Louise Carver, Fabrice DeClerck, Moritz Drupp, Robert Fletcher, Matthew Forrest, Alexandros Gasparatos, Alex Godoy-Faúndez, Gregor Hagedorn, Martin C. Hänsel, Jessica Hetzer, Thomas Hickler, Cornelia B. Krug, Stasja Koot, Xiuzhen Li, Amy Luers, Shelby Matevich, H. Damon Matthews, Ina C. Meier, Mirco Migliavacca, Awaz Mohamed, Sungmin O, David Obura, Ben Orlove, Rene Orth, Laura Pereira, Markus Reichstein, Lerato Thakholi, Peter H. Verburg, and Yuki Yoshida
Biogeosciences, 22, 2425–2460, https://doi.org/10.5194/bg-22-2425-2025, https://doi.org/10.5194/bg-22-2425-2025, 2025
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An interdisciplinary collaboration of 36 international researchers from 35 institutions highlights recent findings in biosphere research. Within eight themes, they discuss issues arising from climate change and other anthropogenic stressors and highlight the co-benefits of nature-based solutions and ecosystem services. Based on an analysis of these eight topics, we have synthesized four overarching insights.
Piers M. Forster, Chris Smith, Tristram Walsh, William F. Lamb, Robin Lamboll, Christophe Cassou, Mathias Hauser, Zeke Hausfather, June-Yi Lee, Matthew D. Palmer, Karina von Schuckmann, Aimée B. A. Slangen, Sophie Szopa, Blair Trewin, Jeongeun Yun, Nathan P. Gillett, Stuart Jenkins, H. Damon Matthews, Krishnan Raghavan, Aurélien Ribes, Joeri Rogelj, Debbie Rosen, Xuebin Zhang, Myles Allen, Lara Aleluia Reis, Robbie M. Andrew, Richard A. Betts, Alex Borger, Jiddu A. Broersma, Samantha N. Burgess, Lijing Cheng, Pierre Friedlingstein, Catia M. Domingues, Marco Gambarini, Thomas Gasser, Johannes Gütschow, Masayoshi Ishii, Christopher Kadow, John Kennedy, Rachel E. Killick, Paul B. Krummel, Aurélien Liné, Didier P. Monselesan, Colin Morice, Jens Mühle, Vaishali Naik, Glen P. Peters, Anna Pirani, Julia Pongratz, Jan C. Minx, Matthew Rigby, Robert Rohde, Abhishek Savita, Sonia I. Seneviratne, Peter Thorne, Christopher Wells, Luke M. Western, Guido R. van der Werf, Susan E. Wijffels, Valérie Masson-Delmotte, and Panmao Zhai
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2025-250, https://doi.org/10.5194/essd-2025-250, 2025
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Rebecca Chloe Evans and H. Damon Matthews
Biogeosciences, 22, 1969–1984, https://doi.org/10.5194/bg-22-1969-2025, https://doi.org/10.5194/bg-22-1969-2025, 2025
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To mitigate our impact on the climate, we must both drastically reduce emissions and perform carbon dioxide removal (CDR). We simulated agriculture as a form of CDR under three future climate scenarios to find out how the climate responds to CDR when the carbon is not permanently stored. We found that agricultural CDR is much more effective at reducing global temperatures if done in a low-emissions scenario and at a high rate, and it becomes less effective as removal continues.
Étienne Guertin and H. Damon Matthews
EGUsphere, https://doi.org/10.5194/egusphere-2022-961, https://doi.org/10.5194/egusphere-2022-961, 2022
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In this research project we add a wildfire model to a model that simulates global vegetation and climate. Our model is simpler and faster than most models. The model simulates wildfire with moderate accuracy but in some areas, the model is very far from reality. This shows that wildfires are highly influenced by climate and vegetation and that these need to be simulated with more accuracy to simulate wildfire. We suggest using a method that compromises between accuracy and speed of simulation.
Philip Goodwin, Martin Leduc, Antti-Ilari Partanen, H. Damon Matthews, and Alex Rogers
Geosci. Model Dev., 13, 5389–5399, https://doi.org/10.5194/gmd-13-5389-2020, https://doi.org/10.5194/gmd-13-5389-2020, 2020
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Numerical climate models are used to make projections of future surface warming for different pathways of future greenhouse gas emissions, where future surface warming will vary from place to place. However, it is so expensive to run complex models using supercomputers that future projections can only be produced for a small number of possible future emissions pathways. This study presents an efficient climate model to make projections of local surface warming using a desktop computer.
Nadine Mengis, David P. Keller, Andrew H. MacDougall, Michael Eby, Nesha Wright, Katrin J. Meissner, Andreas Oschlies, Andreas Schmittner, Alexander J. MacIsaac, H. Damon Matthews, and Kirsten Zickfeld
Geosci. Model Dev., 13, 4183–4204, https://doi.org/10.5194/gmd-13-4183-2020, https://doi.org/10.5194/gmd-13-4183-2020, 2020
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In this paper, we evaluate the newest version of the University of Victoria Earth System Climate Model (UVic ESCM 2.10). Combining recent model developments as a joint effort, this version is to be used in the next phase of model intercomparison and climate change studies. The UVic ESCM 2.10 is capable of reproducing changes in historical temperature and carbon fluxes well. Additionally, the model is able to reproduce the three-dimensional distribution of many ocean tracers.
Andrew H. MacDougall, Thomas L. Frölicher, Chris D. Jones, Joeri Rogelj, H. Damon Matthews, Kirsten Zickfeld, Vivek K. Arora, Noah J. Barrett, Victor Brovkin, Friedrich A. Burger, Micheal Eby, Alexey V. Eliseev, Tomohiro Hajima, Philip B. Holden, Aurich Jeltsch-Thömmes, Charles Koven, Nadine Mengis, Laurie Menviel, Martine Michou, Igor I. Mokhov, Akira Oka, Jörg Schwinger, Roland Séférian, Gary Shaffer, Andrei Sokolov, Kaoru Tachiiri, Jerry Tjiputra, Andrew Wiltshire, and Tilo Ziehn
Biogeosciences, 17, 2987–3016, https://doi.org/10.5194/bg-17-2987-2020, https://doi.org/10.5194/bg-17-2987-2020, 2020
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The Zero Emissions Commitment (ZEC) is the change in global temperature expected to occur following the complete cessation of CO2 emissions. Here we use 18 climate models to assess the value of ZEC. For our experiment we find that ZEC 50 years after emissions cease is between −0.36 to +0.29 °C. The most likely value of ZEC is assessed to be close to zero. However, substantial continued warming for decades or centuries following cessation of CO2 emission cannot be ruled out.
Chris D. Jones, Thomas L. Frölicher, Charles Koven, Andrew H. MacDougall, H. Damon Matthews, Kirsten Zickfeld, Joeri Rogelj, Katarzyna B. Tokarska, Nathan P. Gillett, Tatiana Ilyina, Malte Meinshausen, Nadine Mengis, Roland Séférian, Michael Eby, and Friedrich A. Burger
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Global warming is simply related to the total emission of CO2 allowing us to define a carbon budget. However, information on the Zero Emissions Commitment is a key missing link to assess remaining carbon budgets to achieve the climate targets of the Paris Agreement. It was therefore decided that a small targeted MIP activity to fill this knowledge gap would be extremely valuable. This article formalises the experimental design alongside the other CMIP6 documentation papers.
Marc-Olivier Brault, H. Damon Matthews, and Lawrence A. Mysak
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In this paper we describe the development and application of a new spatially explicit weathering scheme within the University of Victoria Earth System Climate Model (UVic ESCM). We integrated a dataset of modern-day lithology with a number of previously devised parameterizations for weathering dependency on temperature, primary productivity, and runoff. We tested the model with simulations of future carbon cycle perturbations and confirmed the importance of silicate weathering in the long term.
Jean-Sébastien Landry, Lael Parrott, David T. Price, Navin Ramankutty, and H. Damon Matthews
Biogeosciences, 13, 5277–5295, https://doi.org/10.5194/bg-13-5277-2016, https://doi.org/10.5194/bg-13-5277-2016, 2016
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We simulated mountain pine beetle (MPB) outbreaks under four scenarios for the presence and growth release strength of non-attacked vegetation, and found that: (1) impacts on ecosystem carbon and radiative forcing varied greatly across the four scenarios; (2) the global climatic impact from the current outbreak in British Columbia, Canada, seemed smaller than one month of anthropogenic CO2 emissions; and (3) MPB-killed dead standing trees might hasten post-outbreak vegetation recovery.
Jean-Sébastien Landry and H. Damon Matthews
Biogeosciences, 13, 2137–2149, https://doi.org/10.5194/bg-13-2137-2016, https://doi.org/10.5194/bg-13-2137-2016, 2016
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We simulated both fire pulses and stable fire regimes and found the resulting climatic impacts to be irreconcilable with equivalent amounts of CO2 emissions produced by fossil fuel combustion. Consequently, side-by-side comparisons of fire and fossil fuel CO2 emissions—implicitly implying that they have similar effects—should be avoided. Our study calls for the explicit representation of fire in climate models in order to improve our understanding of its impacts in the Earth system.
C. T. Simmons, L. A. Mysak, and H. D. Matthews
Clim. Past Discuss., https://doi.org/10.5194/cp-2016-24, https://doi.org/10.5194/cp-2016-24, 2016
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S. Siebert, M. Kummu, M. Porkka, P. Döll, N. Ramankutty, and B. R. Scanlon
Hydrol. Earth Syst. Sci., 19, 1521–1545, https://doi.org/10.5194/hess-19-1521-2015, https://doi.org/10.5194/hess-19-1521-2015, 2015
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We developed the historical irrigation data set (HID) depicting the spatio-temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5arcmin resolution.
The HID reflects very well the spatial patterns of irrigated land as shown on two historical maps for 1910 and 1960.
Global AEI increased from 63 million ha (Mha) in 1900 to 111 Mha in 1950 and 306 Mha in 2005. Mean aridity on irrigated land increased and mean natural river discharge decreased from 1900 to 1950.
M.-O. Brault, L. A. Mysak, H. D. Matthews, and C. T. Simmons
Clim. Past, 9, 1761–1771, https://doi.org/10.5194/cp-9-1761-2013, https://doi.org/10.5194/cp-9-1761-2013, 2013
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Geosci. Model Dev., 18, 2427–2442, https://doi.org/10.5194/gmd-18-2427-2025, https://doi.org/10.5194/gmd-18-2427-2025, 2025
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Teo Price-Broncucia, Allison Baker, Dorit Hammerling, Michael Duda, and Rebecca Morrison
Geosci. Model Dev., 18, 2349–2372, https://doi.org/10.5194/gmd-18-2349-2025, https://doi.org/10.5194/gmd-18-2349-2025, 2025
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The ensemble consistency test (ECT) and its ultrafast variant (UF-ECT) have become powerful tools in the development community for the identification of unwanted changes in the Community Earth System Model (CESM). We develop a generalized setup framework to enable easy adoption of the ECT approach for other model developers and communities. This framework specifies test parameters to accurately characterize model variability and balance test sensitivity and computational cost.
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Geosci. Model Dev., 18, 2161–2192, https://doi.org/10.5194/gmd-18-2161-2025, https://doi.org/10.5194/gmd-18-2161-2025, 2025
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We describe, calibrate and test the Danish Center for Earth System Science (DCESS) II model, a new, broad, adaptable and fast Earth system model. DCESS II is designed for global simulations over timescales of years to millions of years using limited computer resources like a personal computer. With its flexibility and comprehensive treatment of the global carbon cycle, DCESS II is a useful, computationally friendly tool for simulations of past climates as well as for future Earth system projections.
Gang Tang, Zebedee Nicholls, Alexander Norton, Sönke Zaehle, and Malte Meinshausen
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We studied carbon–nitrogen coupling in Earth system models by developing a global carbon–nitrogen cycle model (CNit v1.0) within the widely used emulator MAGICC. CNit effectively reproduced the global carbon–nitrogen cycle dynamics observed in complex models. Our results show persistent nitrogen limitations on plant growth (net primary production) from 1850 to 2100, suggesting that nitrogen deficiency may constrain future land carbon sequestration.
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Geosci. Model Dev., 18, 2079–2109, https://doi.org/10.5194/gmd-18-2079-2025, https://doi.org/10.5194/gmd-18-2079-2025, 2025
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Understanding historical isoprene emission changes is important for predicting future climate, but trends and their controlling factors remain uncertain. This study shows that long-term isoprene trends vary among Earth system models mainly due to partially incorporating CO2 effects and land cover changes rather than to climate. Future models that refine these factors’ effects on isoprene emissions, along with long-term observations, are essential for better understanding plant–climate interactions.
Gang Tang, Zebedee Nicholls, Chris Jones, Thomas Gasser, Alexander Norton, Tilo Ziehn, Alejandro Romero-Prieto, and Malte Meinshausen
Geosci. Model Dev., 18, 2111–2136, https://doi.org/10.5194/gmd-18-2111-2025, https://doi.org/10.5194/gmd-18-2111-2025, 2025
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We analyzed carbon and nitrogen mass conservation in data from various Earth system models. Our findings reveal significant discrepancies between flux and pool size data, where cumulative imbalances can reach hundreds of gigatons of carbon or nitrogen. These imbalances appear primarily due to missing or inconsistently reported fluxes – especially for land-use and fire emissions. To enhance data quality, we recommend that future climate data protocols address this issue at the reporting stage.
Florian Börgel, Sven Karsten, Karoline Rummel, and Ulf Gräwe
Geosci. Model Dev., 18, 2005–2019, https://doi.org/10.5194/gmd-18-2005-2025, https://doi.org/10.5194/gmd-18-2005-2025, 2025
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Forecasting river runoff, which is crucial for managing water resources and understanding climate impacts, can be challenging. This study introduces a new method using convolutional long short-term memory (ConvLSTM) networks, a machine learning model that processes spatial and temporal data. Focusing on the Baltic Sea region, our model uses weather data as input to predict daily river runoff for 97 rivers.
Tao Zhang, Cyril Morcrette, Meng Zhang, Wuyin Lin, Shaocheng Xie, Ye Liu, Kwinten Van Weverberg, and Joana Rodrigues
Geosci. Model Dev., 18, 1917–1928, https://doi.org/10.5194/gmd-18-1917-2025, https://doi.org/10.5194/gmd-18-1917-2025, 2025
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Earth system models (ESMs) struggle with the uncertainties associated with parameterizing subgrid physics. Machine learning (ML) algorithms offer a solution by learning the important relationships and features from high-resolution models. To incorporate ML parameterizations into ESMs, we develop a Fortran–Python interface that allows for calling Python functions within Fortran-based ESMs. Through two case studies, this interface demonstrates its feasibility, modularity, and effectiveness.
Camilla Mathison, Eleanor J. Burke, Gregory Munday, Chris D. Jones, Chris J. Smith, Norman J. Steinert, Andy J. Wiltshire, Chris Huntingford, Eszter Kovacs, Laila K. Gohar, Rebecca M. Varney, and Douglas McNeall
Geosci. Model Dev., 18, 1785–1808, https://doi.org/10.5194/gmd-18-1785-2025, https://doi.org/10.5194/gmd-18-1785-2025, 2025
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We present PRIME (Probabilistic Regional Impacts from Model patterns and Emissions), which is designed to take new emissions scenarios and rapidly provide regional impact information. PRIME allows large ensembles to be run on multi-centennial timescales, including the analysis of many important variables for impact assessments. Our evaluation shows that PRIME reproduces the climate response for known scenarios, providing confidence in using PRIME for novel scenarios.
Katherine M. Smith, Alice M. Barthel, LeAnn M. Conlon, Luke P. Van Roekel, Anthony Bartoletti, Jean-Christophe Golaz, Chengzhu Zhang, Carolyn Branecky Begeman, James J. Benedict, Gautam Bisht, Yan Feng, Walter Hannah, Bryce E. Harrop, Nicole Jeffery, Wuyin Lin, Po-Lun Ma, Mathew E. Maltrud, Mark R. Petersen, Balwinder Singh, Qi Tang, Teklu Tesfa, Jonathan D. Wolfe, Shaocheng Xie, Xue Zheng, Karthik Balaguru, Oluwayemi Garuba, Peter Gleckler, Aixue Hu, Jiwoo Lee, Ben Moore-Maley, and Ana C. Ordoñez
Geosci. Model Dev., 18, 1613–1633, https://doi.org/10.5194/gmd-18-1613-2025, https://doi.org/10.5194/gmd-18-1613-2025, 2025
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Version 2.1 of the U.S. Department of Energy's Energy Exascale Earth System Model (E3SM) adds the Fox-Kemper et al. (2011) mixed-layer eddy parameterization, which restratifies the ocean surface layer through an overturning streamfunction. Results include surface layer bias reduction in temperature, salinity, and sea ice extent in the North Atlantic; a small strengthening of the Atlantic meridional overturning circulation; and improvements to many atmospheric climatological variables.
Huilin Huang, Yun Qian, Gautam Bisht, Jiali Wang, Tirthankar Chakraborty, Dalei Hao, Jianfeng Li, Travis Thurber, Balwinder Singh, Zhao Yang, Ye Liu, Pengfei Xue, William J. Sacks, Ethan Coon, and Robert Hetland
Geosci. Model Dev., 18, 1427–1443, https://doi.org/10.5194/gmd-18-1427-2025, https://doi.org/10.5194/gmd-18-1427-2025, 2025
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We integrate the E3SM Land Model (ELM) with the WRF model through the Lightweight Infrastructure for Land Atmosphere Coupling (LILAC) Earth System Modeling Framework (ESMF). This framework includes a top-level driver, LILAC, for variable communication between WRF and ELM and ESMF caps for ELM initialization, execution, and finalization. The LILAC–ESMF framework maintains the integrity of the ELM's source code structure and facilitates the transfer of future ELM model developments to WRF-ELM.
Michael Nole, Jonah Bartrand, Fawz Naim, and Glenn Hammond
Geosci. Model Dev., 18, 1413–1425, https://doi.org/10.5194/gmd-18-1413-2025, https://doi.org/10.5194/gmd-18-1413-2025, 2025
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Safe carbon dioxide (CO2) storage is likely to be critical for mitigating some of the most severe effects of climate change. We present a simulation framework for modeling CO2 storage beneath the seafloor, where CO2 can form a solid. This can aid in permanent CO2 storage for long periods of time. Our models show what a commercial-scale CO2 injection would look like in a marine environment. We discuss what would need to be considered when designing a subsea CO2 injection.
Reyk Börner, Jan O. Haerter, and Romain Fiévet
Geosci. Model Dev., 18, 1333–1356, https://doi.org/10.5194/gmd-18-1333-2025, https://doi.org/10.5194/gmd-18-1333-2025, 2025
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The daily cycle of sea surface temperature (SST) impacts clouds above the ocean and could influence the clustering of thunderstorms linked to extreme rainfall and hurricanes. However, daily SST variability is often poorly represented in modeling studies of how clouds cluster. We present a simple, wind-responsive model of upper-ocean temperature for use in atmospheric simulations. Evaluating the model against observations, we show that it performs significantly better than common slab models.
Malcolm J. Roberts, Kevin A. Reed, Qing Bao, Joseph J. Barsugli, Suzana J. Camargo, Louis-Philippe Caron, Ping Chang, Cheng-Ta Chen, Hannah M. Christensen, Gokhan Danabasoglu, Ivy Frenger, Neven S. Fučkar, Shabeh ul Hasson, Helene T. Hewitt, Huanping Huang, Daehyun Kim, Chihiro Kodama, Michael Lai, Lai-Yung Ruby Leung, Ryo Mizuta, Paulo Nobre, Pablo Ortega, Dominique Paquin, Christopher D. Roberts, Enrico Scoccimarro, Jon Seddon, Anne Marie Treguier, Chia-Ying Tu, Paul A. Ullrich, Pier Luigi Vidale, Michael F. Wehner, Colin M. Zarzycki, Bosong Zhang, Wei Zhang, and Ming Zhao
Geosci. Model Dev., 18, 1307–1332, https://doi.org/10.5194/gmd-18-1307-2025, https://doi.org/10.5194/gmd-18-1307-2025, 2025
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HighResMIP2 is a model intercomparison project focusing on high-resolution global climate models, that is, those with grid spacings of 25 km or less in the atmosphere and ocean, using simulations of decades to a century in length. We are proposing an update of our simulation protocol to make the models more applicable to key questions for climate variability and hazard in present-day and future projections and to build links with other communities to provide more robust climate information.
Jordi Buckley Paules, Simone Fatichi, Bonnie Warring, and Athanasios Paschalis
Geosci. Model Dev., 18, 1287–1305, https://doi.org/10.5194/gmd-18-1287-2025, https://doi.org/10.5194/gmd-18-1287-2025, 2025
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We present and validate enhancements to the process-based T&C model aimed at improving its representation of crop growth and management practices. The updated model, T&C-CROP, enables applications such as analysing the hydrological and carbon storage impacts of land use transitions (e.g. conversions between crops, forests, and pastures) and optimizing irrigation and fertilization strategies in response to climate change.
Sébastien Masson, Swen Jullien, Eric Maisonnave, David Gill, Guillaume Samson, Mathieu Le Corre, and Lionel Renault
Geosci. Model Dev., 18, 1241–1263, https://doi.org/10.5194/gmd-18-1241-2025, https://doi.org/10.5194/gmd-18-1241-2025, 2025
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This article details a new feature we implemented in the popular regional atmospheric model WRF. This feature allows for data exchange between WRF and any other model (e.g. an ocean model) using the coupling library Ocean–Atmosphere–Sea–Ice–Soil Model Coupling Toolkit (OASIS3-MCT). This coupling interface is designed to be non-intrusive, flexible and modular. It also offers the possibility of taking into account the nested zooms used in WRF or in the models with which it is coupled.
Axel Lauer, Lisa Bock, Birgit Hassler, Patrick Jöckel, Lukas Ruhe, and Manuel Schlund
Geosci. Model Dev., 18, 1169–1188, https://doi.org/10.5194/gmd-18-1169-2025, https://doi.org/10.5194/gmd-18-1169-2025, 2025
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Earth system models are important tools to improve our understanding of current climate and to project climate change. Thus, it is crucial to understand possible shortcomings in the models. New features of the ESMValTool software package allow one to compare and visualize a model's performance with respect to reproducing observations in the context of other climate models in an easy and user-friendly way. We aim to help model developers assess and monitor climate simulations more efficiently.
Ulrich G. Wortmann, Tina Tsan, Mahrukh Niazi, Irene A. Ma, Ruben Navasardyan, Magnus-Roland Marun, Bernardo S. Chede, Jingwen Zhong, and Morgan Wolfe
Geosci. Model Dev., 18, 1155–1167, https://doi.org/10.5194/gmd-18-1155-2025, https://doi.org/10.5194/gmd-18-1155-2025, 2025
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The Earth Science Box Modeling Toolkit (ESBMTK) is a user-friendly Python library that simplifies the creation of models to study earth system processes, such as the carbon cycle and ocean chemistry. It enhances learning by emphasizing concepts over programming and is accessible to students and researchers alike. By automating complex calculations and promoting code clarity, ESBMTK accelerates model development while improving reproducibility and the usability of scientific research.
Florian Zabel, Matthias Knüttel, and Benjamin Poschlod
Geosci. Model Dev., 18, 1067–1087, https://doi.org/10.5194/gmd-18-1067-2025, https://doi.org/10.5194/gmd-18-1067-2025, 2025
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CropSuite is a new open-source crop suitability model. It provides a GUI and a wide range of options, including a spatial downscaling of climate data. We apply CropSuite to 48 staple and opportunity crops at a 1 km spatial resolution in Africa. We find that climate variability significantly impacts suitable areas but also affects optimal sowing dates and multiple cropping potential. The results provide valuable information for climate impact assessments, adaptation, and land-use planning.
Kerstin Hartung, Bastian Kern, Nils-Arne Dreier, Jörn Geisbüsch, Mahnoosh Haghighatnasab, Patrick Jöckel, Astrid Kerkweg, Wilton Jaciel Loch, Florian Prill, and Daniel Rieger
Geosci. Model Dev., 18, 1001–1015, https://doi.org/10.5194/gmd-18-1001-2025, https://doi.org/10.5194/gmd-18-1001-2025, 2025
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The ICOsahedral Non-hydrostatic (ICON) model system Community Interface (ComIn) library supports connecting third-party modules to the ICON model. Third-party modules can range from simple diagnostic Python scripts to full chemistry models. ComIn offers a low barrier for code extensions to ICON, provides multi-language support (Fortran, C/C++, and Python), and reduces the migration effort in response to new ICON releases. This paper presents the ComIn design principles and a range of use cases.
Daniel Ries, Katherine Goode, Kellie McClernon, and Benjamin Hillman
Geosci. Model Dev., 18, 1041–1065, https://doi.org/10.5194/gmd-18-1041-2025, https://doi.org/10.5194/gmd-18-1041-2025, 2025
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Machine learning has advanced research in the climate science domain, but its models are difficult to understand. In order to understand the impacts and consequences of climate interventions such as stratospheric aerosol injection, complex models are often necessary. We use a case study to illustrate how we can understand the inner workings of a complex model. We present this technique as an exploratory tool that can be used to quickly discover and assess relationships in complex climate data.
Bo Dong, Paul Ullrich, Jiwoo Lee, Peter Gleckler, Kristin Chang, and Travis A. O'Brien
Geosci. Model Dev., 18, 961–976, https://doi.org/10.5194/gmd-18-961-2025, https://doi.org/10.5194/gmd-18-961-2025, 2025
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A metrics package designed for easy analysis of atmospheric river (AR) characteristics and statistics is presented. The tool is efficient for diagnosing systematic AR bias in climate models and useful for evaluating new AR characteristics in model simulations. In climate models, landfalling AR precipitation shows dry biases globally, and AR tracks are farther poleward (equatorward) in the North and South Atlantic (South Pacific and Indian Ocean).
Panagiotis Adamidis, Erik Pfister, Hendryk Bockelmann, Dominik Zobel, Jens-Olaf Beismann, and Marek Jacob
Geosci. Model Dev., 18, 905–919, https://doi.org/10.5194/gmd-18-905-2025, https://doi.org/10.5194/gmd-18-905-2025, 2025
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In this paper, we investigated performance indicators of the climate model ICON (ICOsahedral Nonhydrostatic) on different compute architectures to answer the question of how to generate high-resolution climate simulations. Evidently, it is not enough to use more computing units of the conventionally used architectures; higher memory throughput is the most promising approach. More potential can be gained from single-node optimization rather than simply increasing the number of compute nodes.
Jonah K. Shaw, Dustin J. Swales, Sergio DeSouza-Machado, David D. Turner, Jennifer E. Kay, and David P. Schneider
EGUsphere, https://doi.org/10.5194/egusphere-2025-169, https://doi.org/10.5194/egusphere-2025-169, 2025
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Satellites have observed earth's emission of infrared radiation since the 1970s. Because infrared wavelengths interact with the atmosphere in distinct ways, these observations contain information about the earth and atmosphere. We present a tool that runs alongside global climate models and produces output that can be directly compared with satellite measurements of infrared radiation. We then use this tool for climate model evaluation, climate change detection, and satellite mission design.
Kangari Narender Reddy, Somnath Baidya Roy, Sam S. Rabin, Danica L. Lombardozzi, Gudimetla Venkateswara Varma, Ruchira Biswas, and Devavat Chiru Naik
Geosci. Model Dev., 18, 763–785, https://doi.org/10.5194/gmd-18-763-2025, https://doi.org/10.5194/gmd-18-763-2025, 2025
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The study aimed to improve the representation of wheat and rice in a land model for the Indian region. The modified model performed significantly better than the default model in simulating crop phenology, yield, and carbon, water, and energy fluxes compared to observations. The study highlights the need for global land models to use region-specific crop parameters for accurately simulating vegetation processes and land surface processes.
Giovanni Di Virgilio, Fei Ji, Eugene Tam, Jason P. Evans, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Yue Li, and Matthew L. Riley
Geosci. Model Dev., 18, 703–724, https://doi.org/10.5194/gmd-18-703-2025, https://doi.org/10.5194/gmd-18-703-2025, 2025
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We evaluate the skill in simulating the Australian climate of some of the latest generation of regional climate models. We show when and where the models simulate this climate with high skill versus model limitations. We show how new models perform relative to the previous-generation models, assessing how model design features may underlie key performance improvements. This work is of national and international relevance as it can help guide the use and interpretation of climate projections.
Giovanni Di Virgilio, Jason P. Evans, Fei Ji, Eugene Tam, Jatin Kala, Julia Andrys, Christopher Thomas, Dipayan Choudhury, Carlos Rocha, Stephen White, Yue Li, Moutassem El Rafei, Rishav Goyal, Matthew L. Riley, and Jyothi Lingala
Geosci. Model Dev., 18, 671–702, https://doi.org/10.5194/gmd-18-671-2025, https://doi.org/10.5194/gmd-18-671-2025, 2025
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We introduce new climate models that simulate Australia’s future climate at regional scales, including at an unprecedented resolution of 4 km for 1950–2100. We describe the model design process used to create these new climate models. We show how the new models perform relative to previous-generation models and compare their climate projections. This work is of national and international relevance as it can help guide climate model design and the use and interpretation of climate projections.
Nathan P. Gillett, Isla R. Simpson, Gabi Hegerl, Reto Knutti, Dann Mitchell, Aurélien Ribes, Hideo Shiogama, Dáithí Stone, Claudia Tebaldi, Piotr Wolski, Wenxia Zhang, and Vivek K. Arora
EGUsphere, https://doi.org/10.5194/egusphere-2024-4086, https://doi.org/10.5194/egusphere-2024-4086, 2025
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Climate model simulations of the response to human and natural influences together, natural climate influences alone, and greenhouse gases alone, among others, are key to quantifying human influence on the climate. The last set of such coordinated simulations underpinned key findings in the last Intergovernmental Panel on Climate Change (IPCC) report. Here we propose a new set of such simulations to be used in the next generation of attribution studies, and to underpin the next IPCC report.
Jiawang Feng, Chun Zhao, Qiuyan Du, Zining Yang, and Chen Jin
Geosci. Model Dev., 18, 585–603, https://doi.org/10.5194/gmd-18-585-2025, https://doi.org/10.5194/gmd-18-585-2025, 2025
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In this study, we improved the calculation of how aerosols in the air interact with radiation in WRF-Chem. The original model used a simplified method, but we developed a more accurate approach. We found that this method significantly changes the properties of the estimated aerosols and their effects on radiation, especially for dust aerosols. It also impacts the simulated weather conditions. Our work highlights the importance of correctly representing aerosol–radiation interactions in models.
Eduardo Moreno-Chamarro, Thomas Arsouze, Mario Acosta, Pierre-Antoine Bretonnière, Miguel Castrillo, Eric Ferrer, Amanda Frigola, Daria Kuznetsova, Eneko Martin-Martinez, Pablo Ortega, and Sergi Palomas
Geosci. Model Dev., 18, 461–482, https://doi.org/10.5194/gmd-18-461-2025, https://doi.org/10.5194/gmd-18-461-2025, 2025
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We present the high-resolution model version of the EC-Earth global climate model to contribute to HighResMIP. The combined model resolution is about 10–15 km in both the ocean and atmosphere, which makes it one of the finest ever used to complete historical and scenario simulations. This model is compared with two lower-resolution versions, with a 100 km and a 25 km grid. The three models are compared with observations to study the improvements thanks to the increased resolution.
Catherine Guiavarc'h, David Storkey, Adam T. Blaker, Ed Blockley, Alex Megann, Helene Hewitt, Michael J. Bell, Daley Calvert, Dan Copsey, Bablu Sinha, Sophia Moreton, Pierre Mathiot, and Bo An
Geosci. Model Dev., 18, 377–403, https://doi.org/10.5194/gmd-18-377-2025, https://doi.org/10.5194/gmd-18-377-2025, 2025
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The Global Ocean and Sea Ice configuration version 9 (GOSI9) is the new UK hierarchy of model configurations based on the Nucleus for European Modelling of the Ocean (NEMO) and available at three resolutions. It will be used for various applications, e.g. weather forecasting and climate prediction. It improves upon the previous version by reducing global temperature and salinity biases and enhancing the representation of Arctic sea ice and the Antarctic Circumpolar Current.
Andy Richling, Jens Grieger, and Henning W. Rust
Geosci. Model Dev., 18, 361–375, https://doi.org/10.5194/gmd-18-361-2025, https://doi.org/10.5194/gmd-18-361-2025, 2025
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The performance of weather and climate prediction systems is variable in time and space. It is of interest how this performance varies in different situations. We provide a decomposition of a skill score (a measure of forecast performance) as a tool for detailed assessment of performance variability to support model development or forecast improvement. The framework is exemplified with decadal forecasts to assess the impact of different ocean states in the North Atlantic on temperature forecast.
Maria R. Russo, Sadie L. Bartholomew, David Hassell, Alex M. Mason, Erica Neininger, A. James Perman, David A. J. Sproson, Duncan Watson-Parris, and Nathan Luke Abraham
Geosci. Model Dev., 18, 181–191, https://doi.org/10.5194/gmd-18-181-2025, https://doi.org/10.5194/gmd-18-181-2025, 2025
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Observational data and modelling capabilities have expanded in recent years, but there are still barriers preventing these two data sources from being used in synergy. Proper comparison requires generating, storing, and handling a large amount of data. This work describes the first step in the development of a new set of software tools, the VISION toolkit, which can enable the easy and efficient integration of observational and model data required for model evaluation.
Bijan Fallah, Masoud Rostami, Emmanuele Russo, Paula Harder, Christoph Menz, Peter Hoffmann, Iulii Didovets, and Fred F. Hattermann
Geosci. Model Dev., 18, 161–180, https://doi.org/10.5194/gmd-18-161-2025, https://doi.org/10.5194/gmd-18-161-2025, 2025
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We tried to contribute to a local climate change impact study in central Asia, a region that is water-scarce and vulnerable to global climate change. We use regional models and machine learning to produce reliable local data from global climate models. We find that regional models show more realistic and detailed changes in heavy precipitation than global climate models. Our work can help assess the future risks of extreme events and plan adaptation strategies in central Asia.
Manuel Schlund, Bouwe Andela, Jörg Benke, Ruth Comer, Birgit Hassler, Emma Hogan, Peter Kalverla, Axel Lauer, Bill Little, Saskia Loosveldt Tomas, Francesco Nattino, Patrick Peglar, Valeriu Predoi, Stef Smeets, Stephen Worsley, Martin Yeo, and Klaus Zimmermann
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-236, https://doi.org/10.5194/gmd-2024-236, 2025
Revised manuscript accepted for GMD
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The Earth System Model Evaluation Tool (ESMValTool) is a community diagnostics and performance metrics tool for the evaluation of Earth system models. Here, we describe recent significant improvements of ESMValTool’s computational efficiency including parallel, out-of-core, and distributed computing. Evaluations with the enhanced version of ESMValTool are faster, use less computational resources, and can handle input data larger than the available memory.
Thomas Rackow, Xabier Pedruzo-Bagazgoitia, Tobias Becker, Sebastian Milinski, Irina Sandu, Razvan Aguridan, Peter Bechtold, Sebastian Beyer, Jean Bidlot, Souhail Boussetta, Willem Deconinck, Michail Diamantakis, Peter Dueben, Emanuel Dutra, Richard Forbes, Rohit Ghosh, Helge F. Goessling, Ioan Hadade, Jan Hegewald, Thomas Jung, Sarah Keeley, Lukas Kluft, Nikolay Koldunov, Aleksei Koldunov, Tobias Kölling, Josh Kousal, Christian Kühnlein, Pedro Maciel, Kristian Mogensen, Tiago Quintino, Inna Polichtchouk, Balthasar Reuter, Domokos Sármány, Patrick Scholz, Dmitry Sidorenko, Jan Streffing, Birgit Sützl, Daisuke Takasuka, Steffen Tietsche, Mirco Valentini, Benoît Vannière, Nils Wedi, Lorenzo Zampieri, and Florian Ziemen
Geosci. Model Dev., 18, 33–69, https://doi.org/10.5194/gmd-18-33-2025, https://doi.org/10.5194/gmd-18-33-2025, 2025
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Detailed global climate model simulations have been created based on a numerical weather prediction model, offering more accurate spatial detail down to the scale of individual cities ("kilometre-scale") and a better understanding of climate phenomena such as atmospheric storms, whirls in the ocean, and cracks in sea ice. The new model aims to provide globally consistent information on local climate change with greater precision, benefiting environmental planning and local impact modelling.
Yilin Fang, Hoang Viet Tran, and L. Ruby Leung
Geosci. Model Dev., 18, 19–32, https://doi.org/10.5194/gmd-18-19-2025, https://doi.org/10.5194/gmd-18-19-2025, 2025
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Hurricanes may worsen water quality in the lower Mississippi River basin (LMRB) by increasing nutrient runoff. We found that runoff parameterizations greatly affect nitrate–nitrogen runoff simulated using an Earth system land model. Our simulations predicted increased nitrogen runoff in the LMRB during Hurricane Ida in 2021, albeit less pronounced than the observations, indicating areas for model improvement to better understand and manage nutrient runoff loss during hurricanes in the region.
Giovanni Seijo-Ellis, Donata Giglio, Gustavo Marques, and Frank Bryan
Geosci. Model Dev., 17, 8989–9021, https://doi.org/10.5194/gmd-17-8989-2024, https://doi.org/10.5194/gmd-17-8989-2024, 2024
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A CESM–MOM6 regional configuration of the Caribbean Sea was developed in response to the rising need for high-resolution models for climate impact studies. The configuration is validated for the period 2000–2020 and improves significant errors in a low-resolution model. Oceanic properties are well represented. Patterns of freshwater associated with the Amazon River are well captured, and the mean flows of ocean waters across multiple passages in the Caribbean Sea agree with observations.
Yan Bo, Hao Liang, Tao Li, and Feng Zhou
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-212, https://doi.org/10.5194/gmd-2024-212, 2024
Revised manuscript accepted for GMD
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This study proposed an advancing framework for modeling regional rice production, water use, and greenhouse gas emissions. The framework integrated a process-based soil-crop model with key physiological effects, a novel model upscaling method, and the NSGA-II multi-objective optimization algorithm at a parallel computing platform. The framework provides a valuable tool for irrigation optimization to deliver co-benefits of ensuring food production, reducing water use and greenhouse gas emissions.
Elizabeth J. Drenkard, Charles A. Stock, Andrew C. Ross, Yi-Cheng Teng, Theresa Morrison, Wei Cheng, Alistair Adcroft, Enrique Curchitser, Raphael Dussin, Robert Hallberg, Claudine Hauri, Katherine Hedstrom, Albert Hermann, Michael G. Jacox, Kelly A. Kearney, Remi Pages, Darren J. Pilcher, Mercedes Pozo Buil, Vivek Seelanki, and Niki Zadeh
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2024-195, https://doi.org/10.5194/gmd-2024-195, 2024
Revised manuscript accepted for GMD
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We made a new regional ocean model to assist fisheries and ecosystem managers make decisions in the Northeast Pacific Ocean (NEP). We found that the model did well simulating past ocean conditions like temperature, and nutrient and oxygen levels, and can even reproduce metrics used by and important to ecosystem managers.
Deifilia To, Julian Quinting, Gholam Ali Hoshyaripour, Markus Götz, Achim Streit, and Charlotte Debus
Geosci. Model Dev., 17, 8873–8884, https://doi.org/10.5194/gmd-17-8873-2024, https://doi.org/10.5194/gmd-17-8873-2024, 2024
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Pangu-Weather is a breakthrough machine learning model in medium-range weather forecasting that considers 3D atmospheric information. We show that using a simpler 2D framework improves robustness, speeds up training, and reduces computational needs by 20 %–30 %. We introduce a training procedure that varies the importance of atmospheric variables over time to speed up training convergence. Decreasing computational demand increases the accessibility of training and working with the model.
Fang Li, Xiang Song, Sandy P. Harrison, Jennifer R. Marlon, Zhongda Lin, L. Ruby Leung, Jörg Schwinger, Virginie Marécal, Shiyu Wang, Daniel S. Ward, Xiao Dong, Hanna Lee, Lars Nieradzik, Sam S. Rabin, and Roland Séférian
Geosci. Model Dev., 17, 8751–8771, https://doi.org/10.5194/gmd-17-8751-2024, https://doi.org/10.5194/gmd-17-8751-2024, 2024
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This study provides the first comprehensive assessment of historical fire simulations from 19 Earth system models in phase 6 of the Coupled Model Intercomparison Project (CMIP6). Most models reproduce global totals, spatial patterns, seasonality, and regional historical changes well but fail to simulate the recent decline in global burned area and underestimate the fire response to climate variability. CMIP6 simulations address three critical issues of phase-5 models.
Cited articles
Albani, M., Moorcroft, P. M., Ellison, A. M., Orwig, D. A., and Foster, D. R.: Predicting the impact of hemlock woolly adelgid on carbon dynamics of eastern United States forests, Can. J. Forest Res., 40, 119–133, 2010.
Amiro, B. D., Barr, A. G., Barr, J. G., Black, T. A., Bracho, R., Brown, M., Chen, J., Clark, K. L., Davis, K. J., Desai, A. R., Dore, S., Engel, V., Fuentes, J. D., Goldstein, A. H., Goulden, M. L., Kolb, T. E., Lavigne, M. B., Law, B. E., Margolis, H. A., Martin, T., McCaughey, J. H., Misson, L., Montes-Helu, M., Noormets, A., Randerson, J. T., Starr, G., and Xiao, J.: Ecosystem carbon dioxide fluxes after disturbance in forests of North America, J. Geophys. Res., 115, G00K02, https://doi.org/10.1029/2010JG001390, 2010.
Angers, V. A., Drapeau, P., and Bergeron, Y.: Snag degradation pathways of four North American boreal tree species, Forest Ecol. Manag., 259, 246–256, 2010.
Arneth, A. and Niinemets, U.: Induced BVOCs: how to bug our models?, Trends Plant Sci., 15, 118–125, 2010.
Axelson, J. N., Alfaro, R. I., and Hawkes, B. C.: Influence of fire and mountain pine beetle on the dynamics of lodgepole pine stands in British Columbia, Canada, Forest Ecol. Manag., 257, 1874–1882, 2009.
Barlage, M., Zeng, X., Wei, H., and Mitchell, K. E.: A global 0.05° maximum albedo dataset of snow-covered land based on MODIS observation, Geophys. Res. Lett., 32, L17405, https://doi.org/10.1029/2005GL022881, 2005.
Beaudoin, A., Bernier, P. Y., Guindon, L., Villemaire, P., Guo, X. J., Stinson, G., Bergeron, T., Magnussen, S., and Hall, R. J.: Mapping attributes of Canada's forests at moderate resolution through kNN and MODIS imagery, Can. J. Forest Res., 44, 521–532, 2014.
Belovsky, G. E. and Slade, J. B.: Insect herbivory accelerates nutrient cycling and increases plant production, P. Natl. Acad. Sci. USA, 97, 14412–14417, 2000.
Bentz, B. J., Régnière, J., Fettig, C. J., Hansen, E. M., Hayes, J. L., Hicke, J. A., Kelsey, R. G., Negrón, J. F., and Seybold, S. J.: Climate change and bark beetles of the Western United States and Canada: direct and indirect effects, Bioscience, 60, 602–613, 2010.
Bowler, R., Fredeen, A. L., Brown, M., and Black, T. A.: Residual vegetation importance to net CO2 uptake in pine-dominated stands following mountain pine beetle attack in British Columbia, Canada, Forest Ecol. Manag., 269, 82–91, 2012.
Bright, B. C., Hicke, J. A., and Meddens, A. J. H.: Effects of bark beetle-caused tree mortality on biogeochemical and biogeophysical MODIS products, J. Geophys. Res.-Biogeo., 118, 974–982, 2013.
Brown, M. G., Black, T. A., Nesic, Z., Fredeen, A. L., Foord, V. N., Spittlehouse, D. L., Bowler, R., Burton, P. J., Trofymow, J. A., Grant, N. J., and Lessard, D.: The carbon balance of two lodgepole pine stands recovering from mountain pine beetle attack in British Columbia, Agr. Forest Meteorol., 153, 82–93, 2012.
Brown, M. G., Black, T. A., Nesic, Z., Foord, V. N., Spittlehouse, D. L., Freeden, A. L., Bowler, R., Grant, N. J., Burton, P. J., Trofymow, J. A., Lessard, D., and Meyer, G.: Evapotranspiration and canopy characteristics of two lodgepole pine stands following mountain pine beetle attack, Hydrol. Process., 28, 3326–3340, 2014.
Caldwell, M. K., Hawbaker, T. J., Briggs, J. S., Cigan, P. W., and Stitt, S.: Simulated impacts of mountain pine beetle and wildfire disturbances on forest vegetation composition and carbon stocks in the Southern Rocky Mountains, Biogeosciences, 10, 8203–8222, https://doi.org/10.5194/bg-10-8203-2013, 2013.
Chen, F., Zhang, G., Barlage, M., Zhang, Y., Hicke, J. A., Meddens, A., Zhou, G., Massman, W. J., and Frank, J.: An observational and modeling study of impacts of bark beetle-caused tree mortality on surface energy and hydrological cycles, J. Hydrometeorol., 16, 744–761, 2015.
Clark, K. L., Skowronski, N., and Hom, J.: Invasive insects impact forest carbon dynamics, Glob. Change Biol., 16, 88–101, 2010.
Clark, K. L., Skowronski, N., Gallagher, M., Renninger, H., and Schäfer, K.: Effects of invasive insects and fire on forest energy exchange and evapotranspiration in the New Jersey pinelands, Agr. Forest Meteorol., 166–167, 50–61, 2012.
Cook, B. D., Bolstad, P. V., Martin, J. G., Heinsch, F. A., Davis, J. K., Wang, W., Desai, A. R., and Teclaw, R. M.: Using light-use and production efficiency models to predict photosynthesis and net carbon exchange during forest canopy disturbance, Ecosystems, 11, 26–44, 2008.
Cooke, B. J., Nealis, V. G., and Régnière, J.: Insect Defoliators as Periodic Disturbances in Northern Forest Ecosystems, in: Plant Disturbance Ecology, edited by: Johnson, E. A. and Mihanishi, K., Academic Press, 487–525, 2007.
Couture, J. J. and Lindroth, R. L.: Atmospheric change alters performance of an invasive forest insect, Glob. Change Biol., 18, 3543–3557, 2012.
Cramer, W., Bondeau, A., Woodward, F. I., Prentice, I. C., Betts, R. A., Brovkin, V., Cox, P. M., Fisher, V. A., Foley, J. A., Friend, A. D., Kucharik, C. J., Lomas, M. R., Ramankutty, N., Sitch, S., Smith, B., White, A., and Young-Molling, C.: Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models, Glob. Change Biol., 7, 357–373, 2001.
Delire, C. and Foley, J. A.: Evaluating the performance of a land surface/ecosystem model with biophysical measurements from contrasting environments, J. Geophys. Res., 104, 16895–16909, 1999.
Dietze, M. C. and Matthes, J. H.: A general ecophysiological framework for modelling the impact of pests and pathogens on forest ecosystems, Ecol. Lett., 17, 1418–1426, 2014.
Dukes, J. S., Pontius, J., Orwig, D., Garnas, J. R., Rodgers, V. L., Brazee, N., Cooke, B., Theoharides, K. A., Stange, E. E., Harrington, R., Ehrenfeld, J., Gurevitch, J., Lerdau, M., Stinson, K., Wick, R., and Ayres, M.: Responses of insect pests, pathogens, and invasive plant species to climate change in the forests of northeastern North America: What can we predict?, Can. J. Forest Res., 39, 231–248, 2009.
Edburg, S. L., Hicke, J. A., Lawrence, D. M., and Thornton, P. E.: Simulating coupled carbon and nitrogen dynamics following mountain pine beetle outbreaks in the western United States, J. Geophys. Res., 116, G04033, https://doi.org/10.1029/2011JG001786, 2011.
Edburg, S. L., Hicke, J. A., Brooks, P. D., Pendall, E. G., Ewers, B. E., Norton, U., Gochis, D., Gutmann, E. D., and Meddens, A. J. H.: Cascading impacts of bark beetle-caused tree mortality on coupled biogeophysical and biogeochemical processes, Front. Ecol. Environ., 10, 416–424, 2012.
El Maayar, M., Price, D. T., Delire, C., Foley, J. A., Black, T. A., and Bessemoulin, P.: Validation of the integrated biosphere simulator over Canadian deciduous and coniferous boreal forest stands, J. Geophys. Res., 106, 14339–14355, 2001.
El Maayar, M., Price, D. T., Black, T. A., Humphreys, E. R., and Jork, E.-M.: Sensitivity tests of the integrated biosphere simulator to soil and vegetation characteristics in a Pacific coastal coniferous forest, Atmos. Ocean, 40, 313–332, 2002.
Exbrayat, J.-F., Pitman, A. J., and Abramowitz, G.: Disentangling residence time and temperature sensitivity of microbial decomposition in a global soil carbon model, Biogeosciences, 11, 6999–7008, https://doi.org/10.5194/bg-11-6999-2014, 2014.
Fleming, R. A. and Volney, W. J. A.: Effects of climate change on insect defoliator population processes in Canada's boreal forest: some plausible scenarios, Water Air Soil Poll., 82, 445–454, 1995.
Foley, J. A., Prentice, I. C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., and Haxeltine, A.: An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics, Global Biogeochem. Cy., 10, 603–628, 1996.
Foley, J. A., Levis, S., Prentice, I. C., Pollard, D., and Thompson, S. L.: Coupling dynamic models of climate and vegetation, Glob. Change Biol., 4, 561–579, 1998.
Fosberg, M. A., Cramer, W., Brovkin, V., Fleming, R., Gardner, R., Gill, A. M., Goldammer, J. G., Keane, R., Koehler, P., Lenihan, J., Neilson, R., Sitch, S., Thonicke, K., Venevsky, S., Weber, M. G., and Wittenberg, U.: Strategy for a fire module in dynamic global vegetation models, Int. J. Wildland Fire, 9, 79–84, 1999.
Foster, J. R., Townsend, P. A., and Mladenoff, D. J.: Mapping asynchrony between gypsy moth egg-hatch and forest leaf-out: putting the phenological window hypothesis in a spatial context, Forest Ecol. Manag., 287, 67–76, 2013.
Friedlingstein, P., Cox, P., Betts, R., Bopp, L., von Bloh, W., Brovkin, V., Cadule, P., Doney, S., Eby, M., Fung, I., Bala, G., John, J., Jones, C., Joos, F., Kato, T., Kawamiya, M., Knorr, W., Lindsay, K., Matthews, H. D., Raddatz, T., Rayner, P., Reick, C., Roeckner, E., Schnitzler, K.-G., Schnur, R., Strassmann, K., Weaver, A. J., Yoshikawa, C., and Zeng, N.: Climate–carbon cycle feedback analysis: results from the C4MIP model intercomparison, J. Climate, 19, 3337–3353, 2006.
Gonsamo, A., Chen, J. M., Price, D. T., Kurz, W. A., Liu, J., Boisvenue, C., Hember, R. A., Wu, C., and Chang, K.-H.: Improved assessment of gross and net primary productivity of Canada's landmass, J. Geophys. Res.-Biogeo., 118, 1546–1560, 2013.
Griffin, J. M., Turner, M. G., and Simard, M.: Nitrogen cycling following mountain pine beetle disturbance in lodgepole pine forests of Greater Yellowstone, Forest Ecol. Manag., 261, 1077–1089, 2011.
Guardiola-Claramonte, M., Troch, P. A., Breshears, D. D., Huxman, T. E., Switanek, M. B., Durcik, M., and Cobb, N. S.: Decreased streamflow in semi-arid basins following drought-induced tree die off: a counter-intuitive and indirect climate impact on hydrology, J. Hydrol., 406, 225–233, 2011.
Hansen, E. M.: Forest development and carbon dynamics after mountain pine beetle outbreaks, Forest Sci., 60, 476–488, 2014.
Hawkins, C. D., Dhar, A., Balliet, N. A., and Runzer, K. D.: Residual mature trees and secondary stand structure after mountain pine beetle attack in central British Columbia, Forest Ecol. Manag., 277, 107–115, 2012.
Hicke, J. A., Allen, C. D., Desai, A. R., Dietze, M. C., Hall, R. J., Hogg, E. H. T., Kashian, D. M., Moore, D., Raffa, K. F., Sturrock, R. N., and Vogelmann, J.: Effects of biotic disturbances on forest carbon cycling in the United States and Canada, Glob. Change Biol., 18, 7–34, 2012.
Hogg, E. H. and Michaelian, M.: Factors affecting fall down rates of dead aspen (Populus tremuloides) biomass following severe drought in west-central Canada, Glob. Change Biol., 21, 1968–1979, 2015.
Hubbard, R. M., Rhoades, C. C., Elder, K., and Negron, J.: Changes in transpiration and foliage growth in lodgepole pine trees following mountain pine beetle attack and mechanical girdling, Forest Ecol. Manag., 289, 312–317, 2013.
Hunter, M. D.: Insect population dynamics meets ecosystem ecology: effects of herbivory on soil nutrient dynamics, Agr. Forest Entomol., 3, 77–84, 2001.
IBIS–MIM: available at: http://landuse.geog.mcgill.ca/~jean-sebastien.landry2@mail.mcgill.ca/ibismim/, 2015.
Jobbágy, E. G. and Jackson, R. B.: The vertical distribution of soil organic carbon and its relation to climate and vegetation, Ecol. Appl., 10, 423–436, 2000.
Jones, B., Tardif, J., and Westwood, R.: Weekly xylem production in trembling aspen (Populus tremuloides) in response to artificial defoliation, Can. J. Botany, 82, 590–597, 2004.
Keane, R. E., Loehman, R. A., and Holsinger, L. M.: The FireBGCv2 Landscape Fire Succession Model: A Research Simulation Platform for Exploring Fire and Vegetation Dynamics, USDA General Technical Report RMRS-GTR-255, 137 pp., United States Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, Colorado, USA, 2011.
Klutsch, J. G., Negrón, J. F., Costello, S. L., Rhoades, C. C., West, D. R., Popp, J., and Caissie, R.: Stand characteristics and downed woody debris accumulations associated with a mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in Colorado, Forest Ecol. Manag., 258, 641–649, 2009.
Koller, C. N. and Leonard, D. E.: Comparison of energy budgets for spruce budworm Choristoneura fumiferana (Clemens) on balsam fir and white spruce, Oecologia, 49, 14–20, 1981.
Krinner, G., Viovy, N., de Noblet-Ducoudré, N., Ogée, J., Polcher, J., Friedlingstein, P., Ciais, P., Sitch, S., and Prentice, I. C.: A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system, Global Biogeochem. Cy., 19, GB1015, https://doi.org/10.1029/2003GB002199, 2005.
Kucharik, C. J., Foley, J. A., Delire, C., Fisher, V. A., Coe, M. T., Lenters, J. D., Young-Molling, C., Ramankutty, N., Norman, J. M., and Gower, S. T.: Testing the performance of a dynamic global ecosystem model: water balance, carbon balance, and vegetation structure, Global Biogeochem. Cy., 14, 795–825, 2000.
Kucharik, C. J., Barford, C. C., El Maayar, M., Wofsy, S. C., Monson, R. K., and Baldocchi, D. D.: A multiyear evaluation of a dynamic global vegetation model at three AmeriFlux forest sites: vegetation structure, phenology, soil temperature, and CO2 and H2O vapor exchange, Ecol. Model., 196, 1–31, 2006.
Kurz, W. A., Dymond, C. C., Stinson, G., Rampley, G. J., Neilson, E. T., Carroll, A. L., Ebata, T., and Safranyik, L.: Mountain pine beetle and forest carbon feedback to climate change, Nature, 452, 987–990, 2008.
Landry, J.-S. and Parrott, L.: Could the lateral transfer of nutrients by outbreaking insects lead to consequential landscape-scale effects?, Ecosphere, 7, e01265, https://doi.org/10.1002/ecs2.1265, 2016.
Landsberg, J. and Ohmart, C.: Levels of insect defoliation in forests: patterns and concepts, Trends Ecol. Evol., 4, 96–100, 1989.
Lenters, J. D., Coe, M. T., and Foley, J. A.: Surface water balance of the continental United States, 1963–1995: regional evaluation of a terrestrial biosphere model and the NCEP/NCAR reanalysis, J. Geophys. Res., 105, 22393–22425, 2000.
Lewis, K. J. and Hartley, I.: Rate of deterioration, degrade and fall of trees killed by mountain pine beetle: a synthesis of the literature and experiential knowledge, Mountain Pine Beetle Initiative Working Paper 2005–14, Canadian Forest Service, Pacific Forestry Centre, Victoria, British Columbia, 27 pp., 2005.
Lovett, G. M., Christenson, L. M., Groffman, P. M., Jones, C. G., Hart, J. E., and Mitchell, M. J.: Insect defoliation and nitrogen cycling in forests, Bioscience, 52, 335–341, 2002.
Maness, H., Kushner, P. J., and Fung, I.: Summertime climate response to mountain pine beetle disturbance in British Columbia, Nat. Geosci., 6, 65–70, 2013.
Matthews, H. D., Eby, M., Weaver, A. J., and Hawkins, B. J.: Primary productivity control of simulated carbon cycle–climate feedbacks, Geophys. Res. Lett., 32, L14708, https://doi.org/10.1029/2005GL022941, 2005.
Mattson, W. J. and Addy, N. D.: Phytophagous insects as regulators of forest primary production, Science, 190, 515–522, 1975.
McGuire, A. D., Sitch, S., Clein, J. S., Dargaville, R., Esser, G., Foley, J. A., Heimann, M., Joos, F., Kaplan, J., Kicklighter, D. W., Meier, R. A., Melillo, J. M., Moore III, B., Prentice, I. C., Ramankutty, N., Reichenau, T., Schloss, A., Tian, H., Williams, L. J., and Wittenberg, U.: Carbon balance of the terrestrial biosphere in the twentieth century: analyses of CO2, climate and land use effects with four process-based ecosystem models, Global Biogeochem. Cy., 15, 183–206, 2001.
McNaughton, S. J., Oesterheld, M., Frank, D. A., and Williams, K. J.: Ecosystem-level patterns of primary productivity and herbivory in terrestrial habitats, Nature, 341, 142–144, 1989.
Medvigy, D., Wofsy, S. C., Munger, J. W., and Moorcroft, P. R.: Responses of terrestrial ecosystems and carbon budgets to current and future environmental variability, P. Natl. Acad. Sci. USA, 107, 8275–8280, 2010.
Medvigy, D., Clark, K. L., Skowronski, N. S., and Schäfer, K. V. R.: Simulated impacts of insect defoliation on forest carbon dynamics, Environ. Res. Lett., 7, 045703, https://doi.org/10.1088/1748-9326/7/4/045703, 2012.
Metcalfe, D. B., Asner, G. P., Martin, R. E., Silva Espejo, J. E., Huasco, W. H., Farfán Amézquita, F. F., Carranza-Jimenez, L., Galiano Cabrera, D. F., Baca, L. D., Sinca, F., Huaraca Quispe, L. P., Taype, I. A., Mora, L. E., Dávila, A. R., Solórzano, M. M., Puma Vilca, B. L., Laupa Román, J. M., Guerra Bustios, P. C., Revilla, N. S., Tupayachi, R., Girardin, C. A. J., Doughty, C. E., and Malhi, Y.: Herbivory makes major contributions to ecosystem carbon and nutrient cycling in tropical forests, Ecol. Lett., 17, 324–332, 2014.
Mikkelson, K. M., Bearup, L. A., Maxwell, R. M., Stednick, J. D., McCray, J. E., and Sharp, J. O.: Bark beetle infestation impacts on nutrient cycling, water quality and interdependent hydrological effects, Biogeochemistry, 115, 1–21, 2013a.
Mikkelson, K. M., Maxwell, R. M., Ferguson, I., Stednick, J. D., McCray, J. E., and Sharp, J. O.: Mountain pine beetle infestation impacts: modeling water and energy budgets at the hill-slope scale, Ecohydrology, 6, 64–72, 2013b.
Moore, D. J. P., Trahan, N. A., Wilkes, P., Quaife, T., Stephens, B. B., Elder, K., Desai, A. R., Negron, J., and Monson, R. K.: Persistent reduced ecosystem respiration after insect disturbance in high elevation forests, Ecol. Lett., 16, 731–737, 2013.
Morehouse, K., Johns, T., Kaye, J., and Kaye, M.: Carbon and nitrogen cycling immediately following bark beetle outbreaks in southwestern ponderosa pine forests, Forest Ecol. Manag., 255, 2698–2708, 2008.
Mu, Q., Zhao, M., and Running, S. W.: Improvements to a MODIS global terrestrial evapotranspiration algorithm, Remote Sens. Environ., 115, 1781–1800, 2011.
NetCDF utilities: available at: http://www.unidata.ucar.edu/software/netcdf/, 2016.
New, M., Hulme, M., and Jones, P.: Representing twentieth-century space–time climate variability. Part I: Development of a 1961–1990 mean monthly terrestrial climatology, J. Climate, 12, 829–856, 1999.
NRCan: Trees, insects and diseases of Canada's forests, Forest tent caterpillar, Natural Resources Canada, available at: http://tidcf.nrcan.gc.ca/en/insects/factsheet/9374 (last access: 28 January 2013), 2012.
O'Halloran, T. L., Law, B. E., Goulden, M. L., Wang, Z., Barr, J. G., Schaaf, C., Brown, M., Fuentes, J. D., Göckede, M., Black, A., and Engel, V.: Radiative forcing of natural forest disturbances, Glob. Change Biol., 18, 555–565, 2012.
Oleson, K. W., Lawrence, D. M., Bonan, G. B., Flanner, M. G., Kluzek, E., Lawrence, P. J., Levis, S., Swenson, S. C., Thornton, P. E., Dai, A., Decker, M., Dickinson, R., Feddema, J., Heald, C. L., Hoffman, F., Lamarque, J.-F., Mahowald, N., Niu, G.-Y., Qian, T., Randerson, J., Running, S., Sakaguchi, K., Slater, A., Stöckli, R., Wang, A., Yang, Z.-L., Zeng, X., and Zeng, X.: Technical Description of version 4.0 of the Community Land Model (CLM), NCAR Technical Note NCAR/TN-478+STR, 257 pp., National Center for Atmospheric Research, Boulder, Colorado, USA, 2010.
Pfeifer, E. M., Hicke, J. A., and Meddens, A. J. H.: Observations and modeling of aboveground tree carbon stocks and fluxes following a bark beetle outbreak in the western United States, Glob. Change Biol., 17, 339–350, 2011.
Pollard, D. and Thompson, S. L.: Use of a land-surface-transfer scheme (LSX) in a global climate model: the response to doubling stomatal resistance, Global Planet. Change, 10, 129–161, 1995.
Prentice, I. C., Bondeau, A., Cramer, W., Harrison, S. P., Hickler, T., Lucht, W., Sitch, S., Smith, B., and Sykes, M. T.: Dynamic global vegetation modeling: quantifying terrestrial ecosystem responses to large-scale environmental change, in: Terrestrial Ecosystems in a Changing World, edited by: Canadell, J. G., Pataki, D. E., and Pitelka, L. F., Springer, 175–192, 2007.
Pugh, E. and Gordon, E.: A conceptual model of water yield effects from beetle-induced tree death in snow-dominated lodgepole pine forests, Hydrol. Process., 27, 2048–2060, 2013.
Pugh, E. and Small, E.: The impact of pine beetle infestation on snow accumulation and melt in the headwaters of the Colorado River, Ecohydrology, 5, 467–477, 2012.
Quillet, A., Peng, C., and Garneau, M.: Toward dynamic global vegetation models for simulating vegetation-climate interactions and feedbacks: recent developments, limitations, and future challenges, Environ. Rev., 18, 333–353, 2010.
Randerson, J. T., Thompson, M. V., Malmstrom, C. M., Field, C. B., and Fung, I. Y.: Substrate limitations for heterotrophs: implications for models that estimate the seasonal cycle of atmospheric CO2, Global Biogeochem. Cy., 10, 585–602, 1996.
Rebain, S. A., Reinhard, E. D., Crookston, N. L., Beukema, S. J., Kurz, W. A., Greenough, J. A., Robinson, D, C. E., and Lutes, D. C.: The Fire and Fuels Extension to the Forest Vegetation Simulator: Updated Model Documentation, 403 pp., Internal Report, United States Department of Agriculture, Forest Service, Forest Management Service Center, Fort Collins, Colorado, USA, 2010 (revised 2015).
Reed, D. E., Ewers, B. E., and Pendall, E.: Impact of mountain pine beetle induced mortality on forest carbon and water fluxes, Environ. Res. Lett., 9, 105004, https://doi.org/10.1088/1748-9326/9/10/105004, 2014.
Régnière, J. and You, M.: A simulation model of spruce budworm (Lepidoptera: Tortricidae) feeding on balsam fir and white spruce, Ecol. Model., 54, 277–297, 1991.
Romme, W. H., Knight, D. H., and Yavitt, J. B.: Mountain pine beetle outbreaks in the Rocky Mountains: regulators of primary productivity?, Am. Nat., 127, 484–494, 1986.
Royama, T.: Population dynamics of the spruce budworm Choristoneura Fumiferana, Ecol. Monogr., 54, 429–462, 1984.
Royama, T., MacKinnon, W. E., Kettela, E. G., Carter, N. E., and Hartling, L. K.: Analysis of spruce budworm outbreak cycles in New Brunswick, Canada, since 1952, Ecology, 86, 1212–1224, 2005.
Safranyik, L. and Carroll, A. L.: The biology and epidemiology of the mountain pine beetle in lodgepole pine forests, in: The Mountain Pine Beetle: A Synthesis of Biology, Management, and Impacts on Lodgepole Pine, edited by: Safranyik, L. and Wilson, B., Natural Resources Canada, Victoria, Canada, 3–66, 2006.
Schäfer, K. V. R., Clark, K. L., Skowronski, N., and Hamerlynck, E. P.: Impact of insect defoliation on forest carbon balance as assessed with a canopy assimilation model, Glob. Change Biol., 16, 546–560, 2010.
Seidl, R., Rammer, W., Jäger, D., and Lexer, M. J.: Impact of bark beetle (Ips typographus L.) disturbance on timber production and carbon sequestration in different management strategies under climate change, Forest Ecol. Manag., 256, 209–220, 2008.
Seidl, R., Schelhaas, M.-J., Rammer, W., and Verkerk, P. J.: Increasing forest disturbances in Europe and their impact on carbon storage, Nat. Clim. Change, 4, 806–810, 2014.
Simard, M., Romme, W. H., Griffin, J. M., and Turner, M. G.: Do mountain pine beetle outbreaks change the probability of active crown fire in lodgepole pine forests?, Ecol. Monogr., 81, 3–24, 2011.
Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L., Betts, R., Ciais, P., Cox, P., Friedlingstein, P., Jones, C. D., Prentice, I. C., and Woodward, F. I.: Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs), Glob. Change Biol., 14, 2015–2039, 2008.
Stinson, G., Kurz, W. A., Smyth, C. E., Neilson, E. T., Dymond, C. C., Metsaranta, J. M., Boisvenue, C., Rampley, G. J., Li, Q., White, T. M., and Blain, D.: An inventory-based analysis of Canada's managed forest carbon dynamics, 1990 to 2008, Glob. Change Biol., 17, 2227–2244, 2011.
Stone, W. E. and Wolfe, M. L.: Responses of understory vegetation to variable tree mortality following a mountain pine beetle epidemic in lodgepole pine stands in northern Utah, Vegetatio, 122, 1–12, 1996.
Turcotte, M. M., Thomsen, C. J. M., Broadhead, G. T., Fine, P. V. A., Godfrey, R. M., Lamarre, G. P. A., Meyer, S. T., Richards, L. A., and Johnson, M. T. J.: Percentage leaf herbivory across vascular plant species, Ecology, 95, 788, https://doi.org/10.1890/13-1741.1, 2014.
Vanderhoof, M., Williams, C. A., Ghimire, B., and Rogan, J.: Impact of mountain pine beetle outbreaks on forest albedo and radiative forcing, as derived from Moderate Resolution Imaging Spectroradiometer, Rocky Mountains, USA, J. Geophys. Res.-Biogeo., 118, 1461–1471, 2013.
Vanderhoof, M., Williams, C. A., Shuai, Y., Jarvis, D., Kulakowski, D., and Masek, J.: Albedo-induced radiative forcing from mountain pine beetle outbreaks in forests, south-central Rocky Mountains: magnitude, persistence, and relation to outbreak severity, Biogeosciences, 11, 563–575, https://doi.org/10.5194/bg-11-563-2014, 2014.
Walton, A.: Provincial-Level Projection of the Current Mountain Pine Beetle Outbreak: Update of the Infestation Projection Based on the Provincial Aerial Overview Surveys of Forest Health conducted from 1999 through 2012 and the BCMPB model (year 10), BC Forest Service, 2013.
Wang, Z. and Zeng, X.: Snow albedo's dependence on Solar zenith angle from in situ and MODIS data, Atmospheric and Oceanic Science Letters, 1, 45–50, 2008.
Wiedinmyer, C., Barlage, M., Tewari, M., and Chen, F.: Meteorological impacts of forest mortality due to insect infestation in Colorado, Earth Interact., 16, 1–11, 2012.
Wolf, A., Kozlov, M. V., and Callaghan, T. V.: Impact of non-outbreak insect damage on vegetation in northern Europe will be greater than expected during a changing climate, Climatic Change, 87, 91–106, 2008.
Wulder, M. A., Dymond, C. C., White, J. C., Leckie, D. G., and Carroll, A. L.: Surveying mountain pine beetle damage of forests: a review of remote sensing opportunities, Forest Ecol. Manag., 221, 27–41, 2006.
Yang, L. E.: The ecological consequences of insect outbreaks, in: Insect Outbreaks Revisited, edited by: Barbosa, P., Letourneau, D. K., and Agrawal, A. A., Blackwell Publishing, 197–218, Chichester, West Sussex, UK, 2012.
Short summary
Insect-induced plant damage affects the land-atmosphere exchanges of carbon, energy, and water. We developed a module to quantify such effects in process-based models suitable for climate studies. The module can simulate damage from broadleaf defoliators, needleleaf defoliators, and bark beetles. When coupled to an existing terrestrial vegetation model, the module produced reasonable results for vegetation dynamics and land-atmosphere exchanges, from daily to centennial timescales.
Insect-induced plant damage affects the land-atmosphere exchanges of carbon, energy, and water....
