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Carbon and energy fluxes in cropland ecosystems: a model-data comparison

机译：农田生态系统中的碳和能量通量：模型数据比较

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Croplands are highly productive ecosystems that contribute to land-atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fed sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO2 seasonal uptake over agricultural regions.
机译：农田是高产的生态系统，有助于在其短暂的生长季节中进行土地，大气之间的碳，能量和水交换。我们评估并比较了美国中部（北部）五个农业涡流协方差通量塔站点上一套生态系统模型模拟的净生态系统交换量（NEE），潜热通量（LE）和显热通量（H）。美国碳计划站点综合项目。在生长季节中，大多数模型高估了H而低估了LE，因此与观测值相比，总体Bowen比率更高。大多数模型系统地在预测的NEE之下，特别是在雨水喂养的地区。考虑到特定作物的高生产力和相关生理变化而开发的某些特定于作物的模型可以更好地预测雨养和灌溉地点的NEE和LE。与具有单一通用作物类型的模型相比，针对不同作物的具有特定参数化的模型可以更好地模拟玉米-大豆轮作的NEE的年际变化。根据基本模型制定和物候方法进行的分层未解释这些地点和农作物的模型性能有显着差异。大多数模型对NEE和LE的预测不足，对H的预测较高，这表明针对自然生态系统开发和参数化的模型无法准确预测高度育种和集约经营的作物生态系统的更健壮的生理状况。当与地球系统模型耦合时，很可能在许多陆地表面成分模型中模拟的过度生理应力会导致对温度和大气边界层深度的高估，以及对农业区域的湿度和CO2季节吸收的低估。

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