Carbon–Temperature–Water change analysis for peanut production under climate change: a prototype for the AgMIP Coordinated Climate‐Crop Modeling Project (C3MP)

Abstract

Climate change is projected to push the limits of cropping systems and has the potential to disrupt the agricultural sector from local to global scales. This article introduces the Coordinated Climate-Crop Modeling Project (C3MP), an initiative of the Agricultural Model Intercomparison and Improvement Project (AgMIP) to engage a global network of crop modelers to explore the impacts of climate change via an investigation of crop responses to changes in carbon dioxide concentration ([CO2 ]), temperature, and water. As a demonstration of the C3MP protocols and enabled analyses, we apply the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Peanut crop model for Henry County, Alabama, to evaluate responses to the range of plausible [CO2 ], temperature changes, and precipitation changes projected by climate models out to the end of the 21st century. These sensitivity tests are used to derive crop model emulators that estimate changes in mean yield and the coefficient of variation for seasonal yields across a broad range of climate conditions, reproducing mean yields from sensitivity test simulations with deviations of ca. 2% for rain-fed conditions. We apply these statistical emulators to investigate how peanuts respond to projections from various global climate models, time periods, and emissions scenarios, finding a robust projection of modest (<10%) median yield losses in the middle of the 21st century accelerating to more severe (>20%) losses and larger uncertainty at the end of the century under the more severe representative concentration pathway (RCP8.5). This projection is not substantially altered by the selection of the AgMERRA global gridded climate dataset rather than the local historical observations, differences between the Third and Fifth Coupled Model Intercomparison Project (CMIP3 and CMIP5), or the use of the delta method of climate impacts analysis rather than the C3MP impacts response surface and emulator approach.

Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

“…The delta approach was the most common climate scenario generation methodology used in the White et al (2011) review of agricultural impact models. Many impact sector models also respond strongly to mean temperature and rainfall shifts, allowing for the development of simple but effective emulators (e.g., Ruane et al 2014;McDermid et al 2015a;Howden and Crimp 2005).…”

Evaluation of MODIS Land Surface Temperature Data to Estimate Near-Surface Air Temperature in Northeast China

“…Accurate estimation of T air and mapping its spatial distribution are useful for predicting ecological consequences of climate change. For example, climate warming will lead to higher temperatures and an increase of extreme weather events, which are associated with changes in wildfire regime [6][7][8], forest biomass distribution [9] and crop yield [10,11]. The demand for accurate spatial T air data over large scale has continued to rise [12,13].…”

Evaluating the Sensitivity of Agricultural Model Performance to Different Climate Inputs

“…It is critically important to similarly assess their performance. Some of this assessment is currently underway in AgMIP, which includes efforts to evaluate multi-model sensitivities and to improve the climatological responses of modeled maize (Bassu et al 2014;Ruane et al 2014b;McDermid et al 2015). These continued efforts are especially timely because reliable crop growth representations are vital for decisions on policy and adaptive responses to future climate conditions.…”