Identifiability of soil and ecosystem states and parameters of integrated subsurface-land surface-atmosphere models by multivariate data assimilation

通过多元数据同化识别土壤和生态系统状态以及综合地下-陆地表面-大气模型的参数

• 批准号: 246182982
• 负责人: Professor Dr. Harrie-Jan Hendricks-Franssen
• 金额: --
• 依托单位: Arbeitsgruppe IBG-3: Agrosphäre
• 依托单位国家: 德国
• 项目类别: Research Units
• 财政年份: 2013
• 资助国家: 德国
• 起止时间: 2012-12-31 至 2020-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/246182982?language=en
• 关键词: Identifiability; soil; ecosystem; states; parameters

We will implement a strategy to assimilate land surface temperature by simultaneously considering multiple observations during a day to update sensitive land surface parameters and states. We will develop an operator to assimilate leaf area index and update the dynamical vegetation states and sensitive ecosystem parameters. Synthetic experiments estimate the value of these data together with observed soil moisture. In particular, we will detect under realistic scenarios including multiple sources of uncertainty and several unknown parameters, whether we can improve parameter estimation, and to what extent the assimilation of certain data types improves the state of other compartments. Synthetic tests are carried out first for the land component of TerrSysMP-PDAF (CLM-ParFlow-PDAF) using a joint test case with P5, P6 and P7. We will contribute to the experiments made with the complete TerrSysMP-PDAF coordinated by C1. Finally, tests will be made for the Rur catchment.

我们将实施一项战略，通过同时考虑一天中的多个观测来同化陆面温度，以更新敏感的陆面参数和状态。我们将发展一个算子来同化叶面积指数和更新动态植被状态和敏感的生态系统参数。合成实验估计这些数据的值与观测到的土壤湿度。特别是，我们将检测现实的情况下，包括多个来源的不确定性和几个未知的参数，我们是否可以提高参数估计，以及在何种程度上某些数据类型的同化改善其他车厢的状态。首先使用P5，P6和P7的联合测试用例对TerrSysMP-PDAF（CLM-ParFlow-PDAF）的陆地组件进行合成测试。我们将为C1协调的完整TerrSysMP-PDAF所做的实验做出贡献。最后，将对鲁尔集水区进行测试。