There are still considerable uncertainties related to the numerical simulation and prediction of net primary production (NPP) as an important part of terrestrial carbon sources and sinks over the Tibetan Plateau (TP). To reduce the uncertainty of numerical simulations and improve the ability of predictions, the key physical processes related to the uncertainty of simulated NPP are identified at nine observational stations over the TP. A sensitivity analysis of parameter combinations based on the Conditional Nonlinear Optimal Perturbation related to Parameters (CNOP‐P) approach, which can be used to assess the sensitivity of a parameter subset, is conducted for 28 target physical parameters in the Lund‐Potsdam‐Jena (LPJ) Wetland Hydrology and Methane Dynamic Global Vegetation Model (LPJ‐WHyMe v1.3.1). Firstly, the numerical results show that the uncertainties of physical parameters do lead to a large error in the simulated NPP over the TP, and the range of error varies from 72.4 (MS 3478) to 150.5 g C m⁻² year⁻¹ (Ngari station). Secondly, in areas of moderate precipitation over the TP, the photosynthesis is the main factor leading to high uncertainty in NPP modeling. In areas of low and high precipitation over the TP, the combined influences of hydrological processes and photosynthesis play a key role. Finally, eliminating the errors associated with the most sensitive and important parameter combinations led to the maximum benefit in terms of reducing the uncertainty of simulated NPP, when compared to that obtained with the traditional method. This study suggests that we should prioritize reducing the uncertainty of relatively sensitive parameter combinations among all physical parameters to improve the prediction or simulation ability of NPP over the TP.

中文翻译：

---

识别关键物理过程并改进以模拟和预测青藏高原的净初级生产

净初级生产（NPP）作为青藏高原（TP）陆地碳源和汇的重要组成部分的数值模拟和预测仍存在大量不确定性。为了减少数值模拟的不确定性并提高预测能力，在TP的9个观测站确定了与模拟NPP不确定性相关的关键物理过程。对隆德-波茨坦-耶那的28个目标物理参数进行了基于与参数有关的条件非线性最优摄动（CNOP-P）方法的参数组合敏感性分析，该方法可用于评估参数子集的敏感性。 （LPJ）湿地水文和甲烷动态全球植被模型（LPJ-WHyMe v1.3.1）。首先，^-2年^-1（MS 3478）到150.5克C M ^-2年^-1（建议）。其次，在TP上降水量适中的地区，光合作用是导致NPP建模高度不确定的主要因素。在TP上低降水和高降水的地区，水文过程和光合作用的综合影响起着关键作用。最后，与传统方法相比，消除与最敏感和最重要的参数组合相关的误差在减少模拟NPP的不确定性方面带来了最大的好处。这项研究表明，我们应该优先考虑降低所有物理参数之间相对敏感的参数组合的不确定性，以提高NPP优于TP的预测或模拟能力。