Cosmic Sense – Hydrological Modeling:Coupled distributed modeling of soil moisture, snow and atmosphere interaction – tuned by cosmic-ray neutron sensing

宇宙感知 â 水文建模：土壤湿度、雪和大气相互作用的耦合分布式建模 â 通过宇宙射线中子传感调整

• 批准号: 413986044
• 负责人: Professor Dr. Harrie-Jan Hendricks-Franssen
• 金额: --
• 依托单位: Lehrstuhl für Regionales Klima und Hydrologie
• 依托单位国家: 德国
• 项目类别: Research Units
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/413986044?language=en
• 关键词: Cosmic; Sense; Hydrological; Modeling; Coupled

In the first phase of the Cosmic Sense research unit, we developed a consistent framework for the assimilation of field-scale stationary CRNS observations into the Noah-MP land surface model coupled with the Weather Research and Forecasting model WRF and its hydrologically enhanced derivative WRF-Hydro. Stationary CRNS observations are limited with respect to their spatial support as local precipitation and latent heat flux patterns exhibit weakening dependence with larger distances. To achieve larger scale coverage the assimilation framework shall now be extended to allow for the assimilation of mobile CRNS observations in the state- and parameter estimation process. Furthermore, because of temperature biases in the models, the seasonal course of the simulated snow water storage often differs significantly from reality and leads to poor model initializations during the snowy season. Here, extending the assimilation framework for snow water equivalent (SWE) estimates from CRNS could be a remedy for the problem. To address these objectives in phase II, in a first step, and in close cooperation with the partners from Cosmic Sense, the COSMIC forward operator that translates between simulated water layers and neutron counts, will be extended and evaluated for the incorporation of neutron observations with mobile sensors and CRNS measurements over snow. In parallel efforts, an optimal way to combine stationary and mobile CRNS soil moisture observations for data assimilation will be investigated. Based on this setup, spatially distributed CRNS observations from mobile platforms will be used to estimate sensitive parameters of the Noah-MP land surface model in 2D space for soil moisture and SWE estimations with the state augmentation method of the assimilation framework. Furthermore, the modeling domain will be extended beyond the Rott and Ammer catchment, also to include the new field campaign sites of phase II which are planned to be located in North Rhine Westphalia and in the region of the Harz/Central German Lowland. The investigations with respect to SWE will focus on the Alpine region of the Ammer and Isar river catchments, both of which were already included in the model setup of phase I. We will further refine the methods with respect to elevation dependence and sub-grid heterogeneity effects. The updated parametrization will then be used for distributed regional model simulations to study the effect on coupled land atmospheric interactions within the DART-WRF-Hydro modeling framework. These fully coupled simulations will particularly allow us to investigate in detail the impact of assimilated CRNS observations on atmospheric variables in the boundary layer.

在宇宙感研究单元的第一阶段，我们开发了一个一致的框架，用于将场尺度固定CRNS观测同化到Noah-MP陆面模型中，再加上天气研究和预报模型WRF及其水文增强衍生物WRF-Hydro。固定的CRNS观测是有限的，就其空间支持为本地降水和潜热通量模式表现出减弱的依赖与较大的距离。为了实现更大规模的覆盖同化框架，现在应扩展到允许同化的移动的CRNS观测的状态和参数估计过程。此外，由于模型中的温度偏差，模拟的雪水储存的季节性过程往往与现实显着不同，并导致在下雪季节模型初始化差。在这里，扩展同化框架雪水当量（SWE）估计CRNS可能是一个补救措施的问题。为了在第二阶段实现这些目标，第一步，将与Cosmic Sense的合作伙伴密切合作，对在模拟水层和中子计数之间进行转换的COSMIC正演算子进行扩展和评估，以便将中子观测与移动的传感器和CRNS测量结合起来。在平行的努力，最佳的方式结合联合收割机固定和移动的CRNS土壤水分观测数据同化将进行调查。在此基础上，空间分布的CRNS观测从移动的平台将被用来估计敏感参数的Noah-MP陆面模式在2D空间的土壤水分和SWE估计与同化框架的状态增强方法。此外，建模领域将扩展到罗特和阿默尔流域以外，还包括计划位于北莱茵河威斯特伐利亚和哈茨/德国中部低地地区的第二阶段新的现场活动地点。SWE的调查将集中在Ammer和Isar河流域的阿尔卑斯地区，这两个流域都已包括在第一阶段的模型设置中。我们将进一步完善高程依赖性和子网格异质性影响的方法。更新后的参数化将用于分布式区域模型模拟，以研究DART-WRF-Hydro模型框架内耦合陆地大气相互作用的影响。这些完全耦合的模拟将特别使我们能够详细研究同化CRNS观测对边界层大气变量的影响。