Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions.
Physical robustness of canopy temperature models for crop heat stress simulation across environments and production conditions.
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DOI：
10.1016/j.fcr.2017.11.005
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发表时间：
2018-02
影响因子：
5.8
通讯作者：
H. Webber;Jeffrey W. White;B. A. Kimball;F. Ewert;S. Asseng;Ehsan Eyshi Rezaei;P. Pinter;Jerry L. Hatfield;Matthew P. Reynolds;B. Ababaei;M. Bindi;J. Doltra;R. Ferrise;H. Kage;B. Kassie;K. Kersebaum;A. Luig;Jørgen E. Olesen;Mikhail A. Semenov;Pierre Stratonovitch;A. Ratjen;R. Lamorte;Steven W. Leavitt;D. Hunsaker;G. Wall;P. Martre
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文献类型：
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作者：
H. Webber;Jeffrey W. White;B. A. Kimball;F. Ewert;S. Asseng;Ehsan Eyshi Rezaei;P. Pinter;Jerry L. Hatfield;Matthew P. Reynolds;B. Ababaei;M. Bindi;J. Doltra;R. Ferrise;H. Kage;B. Kassie;K. Kersebaum;A. Luig;Jørgen E. Olesen;Mikhail A. Semenov;Pierre Stratonovitch;A. Ratjen;R. Lamorte;Steven W. Leavitt;D. Hunsaker;G. Wall;P. Martre
尽管在研究气候变化影响方面得到广泛应用，但大多数作物模型忽略了影响作物冠层温度的空气温度、作物和土壤水分状况、CO2浓度和大气条件之间的复杂相互作用。目前的研究扩展了以前的研究，通过评估Tcsimulations从9个作物模型在6个地点的环境和生产条件。每个作物模型实施了一个经验（EMP），能量平衡假设中性稳定（EBN）或能量平衡校正大气稳定性条件（EBSC）的方法来模拟Tc。在预测Tc的模型性能进行了评估，在北美大陆的两个实验，各种水，氮和CO2处理。拟合一个数据集的经验模型具有最佳性能，其次是EBSC模型。稳定性条件解释了建模方法之间的大部分差异。更精确的热应力模拟可能需要使用考虑大气稳定性条件的能量平衡方法。
Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO2concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluatingTcsimulations from nine crop models at six locations across environmental and production conditions. Each crop model implemented one of an empirical (EMP), an energy balance assuming neutral stability (EBN) or an energy balance correcting for atmospheric stability conditions (EBSC) approach to simulateTc. Model performance in predicting Tcwas evaluated for two experiments in continental North America with various water, nitrogen and CO2 treatments. An empirical model fit to one dataset had the best performance, followed by the EBSC models. Stability conditions explained much of the differences between modeling approaches. More accurate simulation of heat stress will likely require use of energy balance approaches that consider atmospheric stability conditions.