Articles | Volume 15, issue 2
https://doi.org/10.5194/gmd-15-429-2022
https://doi.org/10.5194/gmd-15-429-2022
Development and technical paper
 | 
19 Jan 2022
Development and technical paper |  | 19 Jan 2022

Modeling land use and land cover change: using a hindcast to estimate economic parameters in gcamland v2.0

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

Related authors

GCAM-USA v5.3_water_dispatch: integrated modeling of subnational US energy, water, and land systems within a global framework
Matthew Binsted, Gokul Iyer, Pralit Patel, Neal T. Graham, Yang Ou, Zarrar Khan, Nazar Kholod, Kanishka Narayan, Mohamad Hejazi, Son Kim, Katherine Calvin, and Marshall Wise
Geosci. Model Dev., 15, 2533–2559, https://doi.org/10.5194/gmd-15-2533-2022,https://doi.org/10.5194/gmd-15-2533-2022, 2022
Short summary
Modeling perennial bioenergy crops in the E3SM land model
Eva Sinha, Kate Calvin, Ben Bond-Lamberty, Beth Drewniak, Dan Ricciuto, Khachik Sargsyan, Yanyan Cheng, Carl Bernacchi, and Caitlin Moore
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2021-244,https://doi.org/10.5194/gmd-2021-244, 2021
Preprint withdrawn
Short summary
Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6
George C. Hurtt, Louise Chini, Ritvik Sahajpal, Steve Frolking, Benjamin L. Bodirsky, Katherine Calvin, Jonathan C. Doelman, Justin Fisk, Shinichiro Fujimori, Kees Klein Goldewijk, Tomoko Hasegawa, Peter Havlik, Andreas Heinimann, Florian Humpenöder, Johan Jungclaus, Jed O. Kaplan, Jennifer Kennedy, Tamás Krisztin, David Lawrence, Peter Lawrence, Lei Ma, Ole Mertz, Julia Pongratz, Alexander Popp, Benjamin Poulter, Keywan Riahi, Elena Shevliakova, Elke Stehfest, Peter Thornton, Francesco N. Tubiello, Detlef P. van Vuuren, and Xin Zhang
Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020,https://doi.org/10.5194/gmd-13-5425-2020, 2020
Short summary
Calibration and analysis of the uncertainty in downscaling global land use and land cover projections from GCAM using Demeter (v1.0.0)
Min Chen, Chris R. Vernon, Maoyi Huang, Katherine V. Calvin, and Ian P. Kraucunas
Geosci. Model Dev., 12, 1753–1764, https://doi.org/10.5194/gmd-12-1753-2019,https://doi.org/10.5194/gmd-12-1753-2019, 2019
Short summary
Global emissions pathways under different socioeconomic scenarios for use in CMIP6: a dataset of harmonized emissions trajectories through the end of the century
Matthew J. Gidden, Keywan Riahi, Steven J. Smith, Shinichiro Fujimori, Gunnar Luderer, Elmar Kriegler, Detlef P. van Vuuren, Maarten van den Berg, Leyang Feng, David Klein, Katherine Calvin, Jonathan C. Doelman, Stefan Frank, Oliver Fricko, Mathijs Harmsen, Tomoko Hasegawa, Petr Havlik, Jérôme Hilaire, Rachel Hoesly, Jill Horing, Alexander Popp, Elke Stehfest, and Kiyoshi Takahashi
Geosci. Model Dev., 12, 1443–1475, https://doi.org/10.5194/gmd-12-1443-2019,https://doi.org/10.5194/gmd-12-1443-2019, 2019
Short summary

Related subject area

Climate and Earth system modeling
Linking global terrestrial and ocean biogeochemistry with process-based, coupled freshwater algae–nutrient–solid dynamics in LM3-FANSY v1.0
Minjin Lee, Charles A. Stock, John P. Dunne, and Elena Shevliakova
Geosci. Model Dev., 17, 5191–5224, https://doi.org/10.5194/gmd-17-5191-2024,https://doi.org/10.5194/gmd-17-5191-2024, 2024
Short summary
Validating a microphysical prognostic stratospheric aerosol implementation in E3SMv2 using observations after the Mount Pinatubo eruption
Hunter York Brown, Benjamin Wagman, Diana Bull, Kara Peterson, Benjamin Hillman, Xiaohong Liu, Ziming Ke, and Lin Lin
Geosci. Model Dev., 17, 5087–5121, https://doi.org/10.5194/gmd-17-5087-2024,https://doi.org/10.5194/gmd-17-5087-2024, 2024
Short summary
Implementing detailed nucleation predictions in the Earth system model EC-Earth3.3.4: sulfuric acid–ammonia nucleation
Carl Svenhag, Moa K. Sporre, Tinja Olenius, Daniel Yazgi, Sara M. Blichner, Lars P. Nieradzik, and Pontus Roldin
Geosci. Model Dev., 17, 4923–4942, https://doi.org/10.5194/gmd-17-4923-2024,https://doi.org/10.5194/gmd-17-4923-2024, 2024
Short summary
Modeling biochar effects on soil organic carbon on croplands in a microbial decomposition model (MIMICS-BC_v1.0)
Mengjie Han, Qing Zhao, Xili Wang, Ying-Ping Wang, Philippe Ciais, Haicheng Zhang, Daniel S. Goll, Lei Zhu, Zhe Zhao, Zhixuan Guo, Chen Wang, Wei Zhuang, Fengchang Wu, and Wei Li
Geosci. Model Dev., 17, 4871–4890, https://doi.org/10.5194/gmd-17-4871-2024,https://doi.org/10.5194/gmd-17-4871-2024, 2024
Short summary
Hector V3.2.0: functionality and performance of a reduced-complexity climate model
Kalyn Dorheim, Skylar Gering, Robert Gieseke, Corinne Hartin, Leeya Pressburger, Alexey N. Shiklomanov, Steven J. Smith, Claudia Tebaldi, Dawn L. Woodard, and Ben Bond-Lamberty
Geosci. Model Dev., 17, 4855–4869, https://doi.org/10.5194/gmd-17-4855-2024,https://doi.org/10.5194/gmd-17-4855-2024, 2024
Short summary

Cited articles

Ahmed, S. A., Hertel, T., and Lubowski, R.: Calibration of a land cover supply function using transition probabilities, Purdue, Indiana, available at: https://www.gtap.agecon.purdue.edu/resources/res_display.asp?RecordID=2947 (last access: 2 September 2020), 2009. 
Babcock, B. A.: Extensive and Intensive Agricultural Supply Response, Annu. Rev. Resour. Econ., 7, 333–348, https://doi.org/10.1146/annurev-resource-100913-012424, 2015. 
Baldos, U. L. C. and Hertel, T. W.: Looking back to move forward on model validation: Insights from a global model of agricultural land use, Environ. Res. Lett., 8, 034024, https://doi.org/10.1088/1748-9326/8/3/034024, 2013. 
Barr, K. J., Babcock, B. A., Carriquiry, M. A., Nassar, A. M., and Harfuch, L.: Agricultural Land Elasticities in the United States and Brazil, Appl. Econ. Perspect. P., 33, 449–462, https://doi.org/10.1093/aepp/ppr011, 2011. 
Download
Short summary
Future changes in land use and cover have important implications for agriculture, energy, water use, and climate. In this study, we demonstrate a more systematic and empirically based approach to estimating a few key parameters for an economic model of land use and land cover change, gcamland. We identify parameter combinations that best replicate historical land use in the United States.