The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
The GGCMI Phase 2 experiment: global gridded crop model simulations under uniform changes in CO2, temperature, water, and nitrogen levels (protocol version 1.0)
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DOI：
10.5194/gmd-13-2315-2020
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发表时间：
2020-05
影响因子：
5.1
通讯作者：
J. Franke;C. Müller;J. Elliott;A. Ruane;J. Jägermeyr;J. Balkovič;P. Ciais;Marie Dury;P. Falloon-P.
中科院分区：
文献类型：
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作者：
J. Franke;C. Müller;J. Elliott;A. Ruane;J. Jägermeyr;J. Balkovič;P. Ciais;Marie Dury;P. Falloon-P.
抽象。对气候变化下粮食安全的关切促使人们努力更好地了解作物产量的未来变化。基于过程的作物模型代表植物生理和土壤过程，是实现这一目的的必要工具，因为它们可以代表历史记录中未采样的未来气候和管理条件以及种植可能转移的新地点。然而，基于过程的作物模型在许多关键细节上有所不同，它们对不同相互作用因素的反应仍然知之甚少。全球网格作物模型相互比较（GGCMI）第二阶段实验是农业模型相互比较和改进项目（AgMIP）的一项活动，旨在提供一个系统的参数扫描，重点关注气候变化因素及其与整体土壤肥力的相互作用，以便评估模型行为并在影响评估工具中模拟模型响应。在本文中，我们描述了GGCMI第2阶段的实验协议及其模拟数据存档。共有12种作物模型模拟了五种作物，其中包括历史气候的系统性统一扰动，变化的CO2，温度，供水和灌溉农业的施氮（“CTWN”），第二组模拟代表了一种适应，允许调整生长季节长度。我们提出了一些作物产量的结果，以说明模拟的一般特点和潜在的用途GGCMI第2阶段档案。例如，在没有适应的情况下，模拟产量在几乎所有地区都显示出对温暖温度的稳健下降，具有非线性依赖性，这意味着温暖基线位置的产量具有更大的温度敏感性。模型间的不确定性在所有四个输入维度上都是定性相似的，但在未来可能种植作物的高纬度地区最大。
Abstract. Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.