Abstract
The Global Gridded Crop Model Intercomparison (GGCMI) phase 1 dataset of the Agricultural Model Intercomparison and Improvement Project (AgMIP) provides an unprecedentedly large dataset of crop model simulations covering the global ice-free land surface. The dataset consists of annual data fields at a spatial resolution of 0.5 arc-degree longitude and latitude. Fourteen crop modeling groups provided output for up to 11 historical input datasets spanning 1901 to 2012, and for up to three different management harmonization levels. Each group submitted data for up to 15 different crops and for up to 14 output variables. All simulations were conducted for purely rainfed and near-perfectly irrigated conditions on all land areas irrespective of whether the crop or irrigation system is currently used there. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts, and insights on how to further improve global gridded crop model frameworks. We describe dataset characteristics and individual model setup narratives.
Highlights
Croplands cover about 11% of the total land area and are responsible for most of the 60% of anthropogenic nitrous oxide (N2O) emissions that are attributed to agriculture and 11% of the anthropogenic methane emissions from rice production[1], summing up to 4.5% of the total anthropogenic greenhouse gas emissions[2]
Croplands are subject to climate change impacts[3], land-use change[4,5], climate mitigation strategies[6,7], interact directly with the climate system[8], consume large quantities of human freshwater withdrawals[9] and are connected to various sustainable development goals[10]
Future agricultural production faces several challenges that need to be understood in scope and implications: (1) growing and increasingly wealthier populations are projected to demand more and different compositions of food commodities[11,12], (2) climate change impacts[3,13] will require adaptation[14,15,16,17,18], and (3) the environmental impact of agricultural production needs to be reduced, including pollution[19,20], water consumption[9], land consumption[21,22] and greenhouse gas emissions[23,24,25]
Summary
Croplands cover about 11% of the total land area and are responsible for most of the 60% of anthropogenic nitrous oxide (N2O) emissions that are attributed to agriculture and 11% of the anthropogenic methane emissions from rice production[1], summing up to 4.5% of the total anthropogenic greenhouse gas emissions[2]. The data were used for economic assessments of climate change impacts on agricultural production systems[5,33,34,35,36] This first global-scale simulation ensemble of AgMIP that was conducted as part of the ISIMIP project[3] revealed a broad range of GGCM results under different climate change scenarios and in response patterns[6,31]. This high level of uncertainty motivated the following GGCMI phase 1 to assess model performance and to identify general fields of model improvement. With the publication of the GGCMI phase 1 dataset we aim to promote further analyses and understanding of crop model performance, potential relationships between productivity and environmental impacts (e.g. water, nutrients), and eventually insights on how to further improve global gridded crop model frameworks and configurations
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