Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

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欧洲森林模型的准确性、真实性和普遍适用性

森林模型有助于理解和预测气候变化对森林的影响。在过去的几十年里，已经开发出相当多的森林模型。然而，欧洲很少进行系统和全面的模型比较，将模型碳和水通量以及森林结构的评估结合起来。我们评估了 13 个广泛使用的、最先进的、林分规模的森林模型，这些模型与 9 个典型欧洲林分的森林结构实地测量和几十年来跨环境梯度的碳和水通量的涡度协方差数据进行了评估。我们从三个方面测试模型的性能：局部预测的准确性（模拟和观察到的年度数据的一致性），环境响应的真实性（每日总初级生产力对温度、辐射和水蒸气压力不足的模拟和观测响应的一致性）和普遍适用性（涵盖欧洲树种的比例）。我们发现，根据我们模型性能的三个维度，可以使用多种模型。对于局部预测的准确性，与森林结构相关的变量比年度碳和水通量变量具有更低的随机和系统误差。此外，与任何单个模型相比，多模型集成均值为所有站点的环境驱动因素提供了总体上更现实的日常生产力响应。模型的普遍适用性高，目前几乎所有的模型都能够涵盖欧洲常见的树种。我们表明，森林模型在对环境驱动因素的响应中相互补充，并且在某些情况下，单个模型的性能优于模型整体。我们的框架提供了第一步，以捕获超出最常用预测准确性的森林模型之间的本质差异。总的来说，这项研究为未来旨在预测气候影响和支持森林气候减缓和适应措施的模型工作提供了参考点。