Despite widespread application in studying climate change impacts, most crop models ignore complex interactions among air temperature, crop and soil water status, CO 2 concentration and atmospheric conditions that influence crop canopy temperature. The current study extended previous studies by evaluating T c simulations 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 simulate T c . Model performance in predicting T c was 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.

Abstract:Crop system models are generally parametrized with daily air temperatures recorded at 1.5 or 2 m height. These data are not able to represent temperatures at the canopy level, which control crop growth, and the impact of heat stress on crop yield, which are modified by canopy characteristics and plant physiological processes Since such data are often not available and current simulation approaches are complex and/or based on unrealistic assumptions, new methods for integrating canopy temperatures in the framework of crop system models are needed. Based on a forward stepwise-based model selection procedure and quantile regression analyses, we developed empirical regression models to predict winter wheat canopy temperatures obtained from thermal infrared observations performed during four growing seasons for three irrigation levels. We used daily meteorological variables and the daily output data of a crop system model as covariates. The standard cross validation revealed a root mean square error (RMSE) of~0.8˝C, 1.5-2˝C and 0.8-1.2˝C for estimating mean, maximum and minimum canopy temperature, respectively. Canopy temperature of both water-deficit and fully irrigated wheat plots significantly differed from air temperature. We suggest using locally calibrated empirical regression models of canopy temperature as a simple approach for including potentially amplifying or mitigating microclimatic effects on plant response to temperature stress in crop system models.

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This data paper contains data from a FACE experiment with winter wheat (Triticum aestivum, c.v. Batis)  carried out over two years at Braunschweig, Germany. The experimental variants included firstly a study on the interaction of two levels of CO2 (393, 600 ppm) and three levels of nitrogen (N) fertilization (ca. 40, 190 and 320 kg N ha-1) and secondly a study on the interaction of these CO2 treatments and three levels of infrared warming during grain filling (ambient, ca. +1.5°C and +3°C). In the second study N supply was only ca. 190 kg N ha-1. The datasets of the two studies assembled herein contain data on weather, management, soil condition, soil moisture, phenology, dry weights and N concentrations of the plant (leaves, stems ears), green area index, stem reserves, final grain yield and yield components as well as canopy temperatures (this only applies to the second study). Most of the experimental findings have already been published in scientific journals. Data provided herein are suited to validate the interaction of elevated CO2 concentration and either N supply or high temperature during grain filling in wheat growth models.

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