We develop a novel framework for rigorously evaluating land surface models (LSMs) against observations by recognizing the asymmetry between verification‐ and falsification‐oriented approaches. The former approach cannot completely verify LSMs even though it exhausts every case of consistency between the model predictions and observations, whereas the latter only requires a single case of inconsistency to reveal that there must be something wrong. We argue that it is such an inconsistency that stimulates further development of the models and enhancement of the observations. We therefore propose a falsification‐oriented signature‐based evaluation framework to identify cases of inconsistency between model predictions and observations by extracting signatures based on a set of key assumptions. We apply this framework to evaluate an ensemble of simulations from the Noah‐MP LSM against observations over the continental United States under the three assumptions of water mass conservation, no lateral water flow, and a sufficiently long period of time. Regions showing inconsistencies between the Noah‐MP ensemble simulations and the observations are located in the western mountainous areas, the Yellowstone river basin, the lower Floridan aquifer, the Niobrara river basin at the north tip of the Ogallala aquifer, and the basins downstream of the Balcones fault zones in Texas. These regions coincide with the sites where both advances in theoretical modeling and new observational data (e.g., from the Critical Zone Observatories) have emerged.

中文翻译：

---

基于伪造的基于签名的评估，指导陆面模型的发展和观测值的增强

通过认识到验证和伪造方法之间的不对称性，我们开发了一种新颖的框架，可针对观测结果严格评估地表模型（LSM）。尽管前一种方法穷尽了模型预测和观察值之间的所有一致性情况，但前一种方法仍无法完全验证LSM，而后一种方法仅需要一个不一致的情况就可以揭示出一定存在问题。我们认为，正是这种矛盾激发了模型的进一步发展和观测结果的增强。因此，我们提出了一个基于伪造的基于签名的评估框架，以通过基于一组关键假设提取签名来识别模型预测与观察之间不一致的情况。在水量守恒，无侧向水流和足够长的三个时间假设的基础上，我们应用该框架评估了Noah-MP LSM的模拟结果与美国大陆上的观测结果的对比。显示Noah-MP集成模拟与观测结果不一致的区域位于西部山区，黄石河盆地，佛罗里达下层含水层，Ogallala含水层北端的Niobrara流域以及该盆地下游的盆地德克萨斯州的阳台断层带。这些区域与理论建模方面的进展以及新的观测数据（例如，来自关键地带观测站）的出现位置相吻合。