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

TitleA Crop Yield Change Emulator for Use in GCAM and Similar Models: Persephone v1.0
Publication TypeJournal Article
Year of Publication2019
AuthorsSnyder, Abigail, Calvin Katherine V., Phillips Meridel, and Ruane Alex C.
JournalGeoscientific Model Development
Volume12
Pages1319-1350
Date Published04/2019
Abstract / Summary

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 multi-sector 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.

URLhttp://doi.org/10.5194/gmd-12-1319-2019
DOI10.5194/gmd-12-1319-2019
Funding Program: 
Journal: Geoscientific Model Development
Year of Publication: 2019
Volume: 12
Pages: 1319-1350
Date Published: 04/2019

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 multi-sector 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.

DOI: 10.5194/gmd-12-1319-2019
Citation:
Snyder, A, KV Calvin, M Phillips, and AC Ruane.  2019.  "A Crop Yield Change Emulator for Use in GCAM and Similar Models: Persephone v1.0."  Geoscientific Model Development 12: 1319-1350.  https://doi.org/10.5194/gmd-12-1319-2019.