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3. Quantifying Human‐Mediated Carbon Cycle Feedbacks

Author

Jones, Andrew D, Calvin, Katherine V, Shi, Xiaoying, Di Vittorio, Alan V, Bond‐Lamberty, Ben, Thornton, Peter E, and Collins, William D

Subjects
Climate Change Impacts and Adaptation, Biological Sciences, Ecology, Earth Sciences, Environmental Sciences, Climate Action, Life on Land, Meteorology & Atmospheric Sciences
Abstract

Changes in land and ocean carbon storage in response to elevated atmospheric carbon dioxide concentrations and associated climate change, known as the concentration-carbon and climate-carbon feedbacks, are principal controls on the response of the climate system to anthropogenic greenhouse gas emissions. Such feedbacks have typically been quantified in the context of natural ecosystems, but land management activities are also responsive to future atmospheric carbon and climate changes. Here we show that inclusion of such human-driven responses within an Earth system model shifts both the terrestrial concentration-carbon and climate-carbon feedbacks toward increased carbon storage. We introduce a conceptual framework for decomposing these changes into separate concentration-land cover, climate-land cover, and land cover-carbon effects, providing a parsimonious means to diagnose sources of variation across numerical models capable of estimating such feedbacks.

Published
2018

5. Accounting for radiative forcing from albedo change in future global land-use scenarios

Author

Jones, Andrew D, Calvin, Katherine V, Collins, William D, and Edmonds, James

Subjects
Life on Land, Climate Action, Meteorology & Atmospheric Sciences
Abstract

We demonstrate the effectiveness of a new method for quantifying radiative forcing from land use and land cover change (LULCC) within an integrated assessment model, the Global Change Assessment Model (GCAM). The method relies on geographically differentiated estimates of radiative forcing from albedo change associated with major land cover transitions derived from the Community Earth System Model. We find that conversion of 1 km2 of woody vegetation (forest and shrublands) to non-woody vegetation (crops and grassland) yields between 0 and −0.71 nW/m2 of globally averaged radiative forcing determined by the vegetation characteristics, snow dynamics, and atmospheric radiation environment characteristic within each of 151 regions we consider globally. Across a set of scenarios designed to span a range of potential future LULCC, we find LULCC forcing ranging from −0.06 to −0.29 W/m2 by 2070 depending on assumptions regarding future crop yield growth and whether climate policy favors afforestation or bioenergy crops. Inclusion of this previously uncounted forcing in the policy targets driving future climate mitigation efforts leads to changes in fossil fuel emissions on the order of 1.5 PgC/yr by 2070 for a climate forcing limit of 4.5 Wm−2, corresponding to a 12–67 % change in fossil fuel emissions depending on the scenario. Scenarios with significant afforestation must compensate for albedo-induced warming through additional emissions reductions, and scenarios with significant deforestation need not mitigate as aggressively due to albedo-induced cooling. In all scenarios considered, inclusion of albedo forcing in policy targets increases forest and shrub cover globally.

Published
2015

6. Climate extremes, land–climate feedbacks and land-use forcing at 1.5°C

Author

Seneviratne, Sonia I., Wartenburger, Richard, Guillod, Benoit P., Hirsch, Annette L., Vogel, Martha M., Brovkin, Victor, van Vuuren, Detlef P., Schaller, Nathalie, Boysen, Lena, Calvin, Katherine V., Doelman, Jonathan, Greve, Peter, Havlik, Petr, Humpenöder, Florian, Krisztin, Tamas, Mitchell, Daniel, Popp, Alexander, Riahi, Keywan, Rogelj, Joeri, Schleussner, Carl-Friedrich, Sillmann, Jana, and Stehfest, Elke

Published
2018

8. Scenarios towards limiting global mean temperature increase below 1.5 °C

Author

Rogelj, Joeri, Popp, Alexander, Calvin, Katherine V., Luderer, Gunnar, Emmerling, Johannes, Gernaat, David, Fujimori, Shinichiro, Strefler, Jessica, Hasegawa, Tomoko, Marangoni, Giacomo, Krey, Volker, Kriegler, Elmar, Riahi, Keywan, van Vuuren, Detlef P., Doelman, Jonathan, Drouet, Laurent, Edmonds, Jae, Fricko, Oliver, Harmsen, Mathijs, Havlík, Petr, Humpenöder, Florian, Stehfest, Elke, and Tavoni, Massimo

Published
2018
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9. The Impact of Crop Rotation and Spatially Varying Crop Parameters in the E3SM Land Model (ELMv2)

Author

Sinha, Eva, Bond-Lamberty, Ben, Calvin, Katherine V., Drewniak, Beth A., Bisht, Gautam, Bernacchi, Carl, Blakely, Bethany J., Moore, Caitlin E., Sinha, Eva, Bond-Lamberty, Ben, Calvin, Katherine V., Drewniak, Beth A., Bisht, Gautam, Bernacchi, Carl, Blakely, Bethany J., and Moore, Caitlin E.

Abstract

Earth System Models (ESMs) are increasingly representing agriculture due to its impact on biogeochemical cycles, local and regional climate, and fundamental importance for human society. Realistic large scale simulations may require spatially varying crop parameters that capture crop growth at various scales and among different cultivars, as well as common crop management practices, but their importance is uncertain, and they are often not represented in ESMs. In this study, we examine the impact of using constant versus spatially varying crop parameters using a novel, realistic crop rotation scenario in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2). We implemented crop rotation by using ELMv2's dynamic land unit capability, and then calibrated and validated the model against observations collected at three AmeriFlux sites in the US Midwest with corn soybean rotation. The calibrated model closely captured the magnitude and observed seasonality of carbon and energy fluxes across crops and sites. We performed regional simulations for the US Midwest using the calibrated model and found that spatially varying only a few crop parameters across the region, as opposed to using constant parameters, had a large impact, with the carbon fluxes and energy fluxes both varying by up to 40%. These results imply that large scale ESM simulations using spatially invariant crop parameters may result in biased energy and carbon fluxes estimation from agricultural land, and underline the importance of improving human-earth systems interactions in ESMs.

Published
2023

10. Modeling Perennial Bioenergy Crops in the E3SM Land Model (ELMv2)

Author

Sinha, Eva, Calvin, Katherine V., Bond-Lamberty, Ben, Drewniak, Beth A., Ricciuto, Daniel M., Sargsyan, Khachik, Cheng, Yanyan, Bernacchi, Carl, Moore, Caitlin E., Sinha, Eva, Calvin, Katherine V., Bond-Lamberty, Ben, Drewniak, Beth A., Ricciuto, Daniel M., Sargsyan, Khachik, Cheng, Yanyan, Bernacchi, Carl, and Moore, Caitlin E.

Abstract

Perennial bioenergy crops are increasingly important for the production of ethanol and other renewable fuels, and as part of an agricultural system that alters the climate through its impact on biogeophysical and biogeochemical properties of the terrestrial ecosystem. Few Earth System Models (ESMs) represent such crops, however. In this study, we expand the Energy Exascale Earth System Land Model to include perennial bioenergy crops with a high potential for mitigating climate change. We focus on high-productivity miscanthus and switchgrass, estimating various parameters associated with their different growth stages and performing a global sensitivity analysis to identify and optimize these parameters. The sensitivity analysis identifies five parameters associated with phenology, carbon/nitrogen allocation, stomatal conductance, and maintenance respiration as the most sensitive parameters for carbon and energy fluxes. We calibrated and validated the model against observations and found that the model closely captures the observed seasonality and the magnitude of carbon fluxes. The validated model represents the latent heat flux fairly well, but sensible heat flux for miscanthus is not well captured. Finally, we validated the model against observed leaf area index (LAI) and harvest amount and found modeled LAI captured observed seasonality, although the model underestimates LAI and harvest amount. This work provides a foundation for future ESM analyses of the interactions between perennial bioenergy crops and carbon, water, and energy dynamics in the larger Earth system, and sets the stage for studying the impact of future biofuel expansion on climate and terrestrial systems.

Published
2023

14. A Crop Yield Change Emulator for Use in GCAM and Similar Models: Persephone v1.0

Author

Snyder, Abigail, Calvin, Katherine V, Phillips, Meridel, and Ruane, Alex C

Subjects
Earth Resources And Remote Sensing
Abstract

Future changes in Earth system state will impact agricultural yields and, through these changed yields, can have profound impacts on the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields but are often too computationally intensive to dynamically couple into global multisector economic models, such as the Global Change Assessment Model (GCAM) and other similar-in-scale models. Yet, generalizing a faster site-specific crop model’s results to be used globally will introduce inaccuracies, and the question of which model to use is unclear given the wide variation in yield response across crop models. To examine the feedback loop among socioeconomics, Earth system changes, and crop yield changes, rapidly generated yield responses with some quantification of crop response uncertainty are desirable. The Persephone v1.0 response functions presented in this work are based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Climate-Crop Modeling Project (C3MP) sensitivity test data set and are focused on providing GCAM and similar models with a tractable number of rapid to evaluate dynamic yield response functions corresponding to a range of the yield response sensitivities seen in the C3MP data set. With the Persephone response functions, a new variety of agricultural impact experiments will be open to GCAM and other economic models: for example, examining the economic impacts of a multi-year drought in a key agricultural region and how economic changes in response to the drought can, in turn, impact the drought.

Published
2019
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17. Integrated Assessment Modeling

Author

Edmonds, James A., Calvin, Katherine V., Clarke, Leon E., Janetos, Anthony C., Kim, Son H., Wise, Marshall A., McJeon, Haewon C., and Rasch, Philip J., editor

Published
2012
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23. Climate mitigation and the future of tropical landscapes

Author

Thomson, Allison M., Calvin, Katherine V., Chini, Louise P., Hurtt, George, Edmonds, James A., Bond-Lamberty, Ben, Frolking, Steve, Wise, Marshall A., Janetos, Anthony C., and Rosenzweig, Cynthia

Published
2010

25. Supplementary Data: zhao-etal_2022_global_environmental_change

Author

Zhao, Xin, Wise, Marshall A., Waldhoff, Stephanie T., Kyle, G. Page, Huster, Jonathan E., Ramig, Christopher W., Rafelski, Lauren E., Pralit L. Patel, and Calvin, Katherine V.

Subjects
GCAM, Trade modeling, Armington, Integrated assessment, Agroeconomics, Land use change emissions
Abstract

This repository includes the following files for replicating the results provided in the paper: "The impact of agricultural trade approaches on global economic modeling" published in Global Environmental Change. (1)GCAM_files/ (2.9 GB is unzipped) *configurations *gcamdata_xml *queries *README.md (2)Visualize_Rproject/ (2.5 GB is unzipped) *Visualize_Rproject.Rproj *R *data *output *README.md GCAM_files/ includes files needed to run GCAM-T (DOI:10.5281/zenodo.4705472) and generate GCAM output database for experiments designed in the paper. The GCAM-T model needs to be downloaded and compiled first. Then copy the two folders, configurations/ and gcamdata_xml/, into the model folder. The configuration files included in the configurations/ folder can be run and generate GCAM output database corresponding to experiments designed in the paper (i.e., E1-E4). Note that Monte Carlo simulations and extreme scenarios under E4 require additional changes of "monte_carlo_logits/ag_trade.xml" in the configuration (an example of positive 2 times SD extreme scenario, ag_tradeposd2.xml, is provided). All data needed are included in the gcamdata_xml folder. Main queries needed are provided in the queries/ folder. Visualize_Rproject/ includes an R project for processing data from GCAM runs and generating figures and tables for the paper. In R/Configuration.R, packages are loaded, data and functions are read. Visualized results can be generated by sourcing R codes and results are saved in output/. Note that GCAM result database was queried into csv results and then converted to RDS files in R by sourcing "R/Source.ProcRDS.R". Note that this part was commented out since RDS files are provided. In case that source csv files are available and RDS files are needed, this script needs to be sourced. The figures and tables are generated by sourcing relevant scripts (the scripts can be modified to generate additional results): Fig & Table Rscript Output folder Fig. 1 "R/Source.ref.3.R" "output/Reference" Fig. 3 "R/Source.ref.1.R" "output/Reference" Fig. 4 "R/Source.ref.3.R" "output/Reference" Fig. 5 & 6 "R/Source.ref.1.R" "output/Reference" Fig. 7 "R/Source.scen.1.R" "output/Scenario_compare" Fig. 8 "R/Source.scen.2.R" "output/Scenario_compare" Fig. 9 & 10 "R/Source.scen.3.R" "output/Scenario_compare" Fig. 11 "R/Source.montecarlo.1.R" "output/MontaCarlo" Table S6 "R/Source.ref.1.R" "output/Reference" Table S7 "R/Source.scen.1.R" "output/Scenario_compare" Table S8 "R/Source.scen.3.R" "output/Scenario_compare" Table S9 "R/Source.montecarlo.1.R" Fig. S1 "R/Source.ref.3.R" "output/Reference" Fig. S2 "R/Source.ref.1.R" "output/Reference" Fig. S5 "R/Source.montecarlo.1.R" "output/MontaCarlo" Fig. S6-11 "R/Source.ref.1.R" "output/Reference" Fig. S12-15 "R/Source.ref.3.R" "output/Reference" Fig. S16-17 "R/Source.ref.2.R" "output/Reference" Fig. S18-24 "R/Source.scen.2.R" "output/Scenario_compare" Fig. S25-27 "R/Source.scen.3.R" "output/Scenario_compare" Fig. S28-29 "R/Source.montecarlo.1.R" "output/MontaCarlo" Fig. S30 "R/Source.agmip.R" "output/Agmip" &nbsp

Published
2021
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30. Integrated Assessment Modeling

Author

Edmonds, James A., primary, Calvin, Katherine V., additional, Clarke, Leon E., additional, Janetos, Anthony C., additional, Kim, Son H., additional, Wise, Marshall A., additional, and McJeon, Haewon C., additional

Published
2012
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33. Future Developments Without Targeted Policies

Author

Lucas, P.L., Hedden, Steve, van Vuuren, D.P., Calvin, Katherine V., Chung, Serena H., Harfoot, Mike, Köberle, Alexandre C., Moyer, Jonathan D., Wada, Yoshhide, Hughes, Barry B., Hurley, Fintan, Keating, Terry, Environment, UN, and Environmental Sciences

Published
2019
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34. Pathways Toward Sustainable Development

Author

van Vuuren, D.P., Lucas, P.L., Calvin, Katherine V., Chung, Serena H., Harfoot, Mike, Hedden, Steve, Köberle, Alexandre C., Wada, Yoshhide, Bouwman, L., He, Chenmin, Hughes, Barry B., Keating, Terry, Moyer, Jonathan D., Rieckmann, Marco, Environment, UN, and Environmental Sciences

Published
2019

35. Future Developments Without Targeted Policies

Author

Environmental Sciences, Lucas, P.L., Hedden, Steve, van Vuuren, D.P., Calvin, Katherine V., Chung, Serena H., Harfoot, Mike, Köberle, Alexandre C., Moyer, Jonathan D., Wada, Yoshhide, Hughes, Barry B., Hurley, Fintan, Keating, Terry, Environment, UN, Environmental Sciences, Lucas, P.L., Hedden, Steve, van Vuuren, D.P., Calvin, Katherine V., Chung, Serena H., Harfoot, Mike, Köberle, Alexandre C., Moyer, Jonathan D., Wada, Yoshhide, Hughes, Barry B., Hurley, Fintan, Keating, Terry, and Environment, UN

Published
2019

36. Pathways Toward Sustainable Development

Author

Environmental Sciences, van Vuuren, D.P., Lucas, P.L., Calvin, Katherine V., Chung, Serena H., Harfoot, Mike, Hedden, Steve, Köberle, Alexandre C., Wada, Yoshhide, Bouwman, L., He, Chenmin, Hughes, Barry B., Keating, Terry, Moyer, Jonathan D., Rieckmann, Marco, Environment, UN, Environmental Sciences, van Vuuren, D.P., Lucas, P.L., Calvin, Katherine V., Chung, Serena H., Harfoot, Mike, Hedden, Steve, Köberle, Alexandre C., Wada, Yoshhide, Bouwman, L., He, Chenmin, Hughes, Barry B., Keating, Terry, Moyer, Jonathan D., Rieckmann, Marco, and Environment, UN

Published
2019

37. Climate extremes, land–climate feedbacks and land-use forcing at 1.5°C

Author

Seneviratne, Sonia I, Wartenburger, Richard, Guillod, Benoit P, Hirsch, Annette L, Vogel, Martha M, Brovkin, Victor, van Vuuren, Detlef P, Schaller, Nathalie, Boysen, Lena, CALVIN, KATHERINE V., Doelman, Jonathan, Greve, Peter, Havlik, Petr, Humpenöder, Florian, Krisztin, Tamas, Mitchell, Daniel, Popp, Alexander, Riahi, Keywan, Rogelj, Joeri, Schleussner, Carl-Friedrich, Sillmann, Jana, Stehfest, Elke, Environmental Sciences, and Environmental Sciences

Subjects
Climate extremes, land-use changes, 1.5° C scenarios, Regional climate change, climate projections, land–climate interactions, 010504 meteorology & atmospheric sciences, General Mathematics, Yield (finance), General Physics and Astronomy, Forcing (mathematics), 010501 environmental sciences, 01 natural sciences, 11. Sustainability, 1.5°C scenarios, Precipitation, Water cycle, 0105 earth and related environmental sciences, climate extremes, Sustainable development, regional climate change, Land use, Global warming, General Engineering, Articles, 15. Life on land, 13. Climate action, Climatology, Environmental science, Research Article
Abstract

This article investigates projected changes in temperature and water cycle extremes at 1.5°C of global warming, and highlights the role of land processes and land-use changes (LUCs) for these projections. We provide new comparisons of changes in climate at 1.5°C versus 2°C based on empirical sampling analyses of transient simulations versus simulations from the ‘Half a degree Additional warming, Prognosis and Projected Impacts’ (HAPPI) multi-model experiment. The two approaches yield similar overall results regarding changes in climate extremes on land, and reveal a substantial difference in the occurrence of regional extremes at 1.5°C versus 2°C. Land processes mediated through soil moisture feedbacks and land-use forcing play a major role for projected changes in extremes at 1.5°C in most mid-latitude regions, including densely populated areas in North America, Europe and Asia. This has important implications for low-emissions scenarios derived from integrated assessment models (IAMs), which include major LUCs in ambitious mitigation pathways (e.g. associated with increased bioenergy use), but are also shown to differ in the simulated LUC patterns. Biogeophysical effects from LUCs are not considered in the development of IAM scenarios, but play an important role for projected regional changes in climate extremes, and are thus of high relevance for sustainable development pathways. This article is part of the theme issue ‘The Paris Agreement: understanding the physical and social challenges for a warming world of 1.5°C above pre-industrial levels'.

Published
2018
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38. Land-Management Options for Greenhouse Gas Removal and Their Impacts on Ecosystem Services and the Sustainable Development Goals

Author

Smith, Pete, primary, Adams, Justin, additional, Beerling, David J., additional, Beringer, Tim, additional, Calvin, Katherine V., additional, Fuss, Sabine, additional, Griscom, Bronson, additional, Hagemann, Nikolas, additional, Kammann, Claudia, additional, Kraxner, Florian, additional, Minx, Jan C., additional, Popp, Alexander, additional, Renforth, Phil, additional, Vicente Vicente, Jose Luis, additional, and Keesstra, Saskia, additional

Published
2019
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44. Scenarios towards limiting global mean temperature increase below 1.5 °C

Author

Environmental Sciences, Rogelj, Joeri, Popp, Alexander, CALVIN, KATHERINE V., Luderer, Gunnar, Emmerling, Johannes, Gernaat, David, Fujimori, Shinichiro, Strefler, Jessica, Hasegawa, Tomoko, Marangoni, Giacomo, Krey, Volker, Kriegler, Elmar, Riahi, Keywan, van Vuuren, Detlef P., Doelman, Jonathan, Drouet, Laurent, Edmonds, Jae, Fricko, Oliver, Harmsen, Mathijs, Havlík, Petr, Humpenöder, Florian, Stehfest, Elke, Tavoni, Massimo, Environmental Sciences, Rogelj, Joeri, Popp, Alexander, CALVIN, KATHERINE V., Luderer, Gunnar, Emmerling, Johannes, Gernaat, David, Fujimori, Shinichiro, Strefler, Jessica, Hasegawa, Tomoko, Marangoni, Giacomo, Krey, Volker, Kriegler, Elmar, Riahi, Keywan, van Vuuren, Detlef P., Doelman, Jonathan, Drouet, Laurent, Edmonds, Jae, Fricko, Oliver, Harmsen, Mathijs, Havlík, Petr, Humpenöder, Florian, Stehfest, Elke, and Tavoni, Massimo

Published
2018

45. Climate extremes, land-climate feedbacks and land-use forcing at 1.5°C

Author

Environmental Sciences, Seneviratne, Sonia I, Wartenburger, Richard, Guillod, Benoit P, Hirsch, Annette L, Vogel, Martha M, Brovkin, Victor, van Vuuren, Detlef P, Schaller, Nathalie, Boysen, Lena, CALVIN, KATHERINE V., Doelman, Jonathan, Greve, Peter, Havlik, Petr, Humpenöder, Florian, Krisztin, Tamas, Mitchell, Daniel, Popp, Alexander, Riahi, Keywan, Rogelj, Joeri, Schleussner, Carl-Friedrich, Sillmann, Jana, Stehfest, Elke, Environmental Sciences, Seneviratne, Sonia I, Wartenburger, Richard, Guillod, Benoit P, Hirsch, Annette L, Vogel, Martha M, Brovkin, Victor, van Vuuren, Detlef P, Schaller, Nathalie, Boysen, Lena, CALVIN, KATHERINE V., Doelman, Jonathan, Greve, Peter, Havlik, Petr, Humpenöder, Florian, Krisztin, Tamas, Mitchell, Daniel, Popp, Alexander, Riahi, Keywan, Rogelj, Joeri, Schleussner, Carl-Friedrich, Sillmann, Jana, and Stehfest, Elke

Published
2018

49. Land-use Leakage

Author

Calvin, Katherine V., primary, Edmonds, James A., additional, Clarke, Leon E., additional, Bond-Lamberty, Benjamin, additional, Kim, Son H., additional, Wise, Marshall A., additional, Thomson, Allison M., additional, and Kyle, G. Page, additional

Published
2009
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50. Modeling Land Use and Land Cover Change: Using a Hindcast to Estimate Economic Parameters in gcamland v2.0.

Author

Calvin, Katherine V., Snyder, Abigail, Xin Zhao, and Wise, Marshall

Subjects
*LAND use, *LAND cover, *ECONOMIC models, *CROP yields, *AGRICULTURAL productivity
Abstract

The world has experienced a vast increase in agricultural production since the middle of the last century. Agricultural land area has also increased at the expense of natural lands over this period, though at a lower rate than production. Future changes in land use and cover have important implications not only for agriculture but for energy, water use, and climate. However, these future changes are driven by a complex combination of uncertain socioeconomic, technological, and other factors. Estimates of future land use and land cover differ significantly across economic models of agricultural production, and efforts to evaluate these economic models over history have been limited. In this study, we use an economic model of land use, gcamland, to systematically explore a large set of model parameter perturbations and alternate methods for forming expectations about uncertain crop yields and prices. We run gcamland simulations with these parameter sets over the historical period in the United States to explore model fitness and to identify combinations that improve fitness. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We conclude with the observation that historical modeling exercises such as this study are valuable both for understanding real world drivers of land use change and for informing modeling of future land use change. [ABSTRACT FROM AUTHOR]

Published
2020
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