Investigation and quantification of feedback processes between the atmosphere and the soil-vegetation system in a changing climate

为了模拟包括极端事件在内的区域气候变化，开发新一代区域气候模式至关重要。目前对欧洲许多地区的温度和降水统计数据的模拟不够准确，特别是在地形复杂的地区。目前的模式评估表明，可以通过改进(a)陆地表面能量平衡的表示，(b)土壤植被-大气（SVA）反馈（包括携带）的模拟，以及(c)通过省略深对流的参数化对云和降水的模拟来实现改进的模拟。本项目将结合这三个方面的研究，开发和改进for1695综合土地系统模型（ILMS）。这将通过三个工作包来实现：(1)通过扫描遥感系统的协同测量和与大气-土地表面-作物模型（ALCM）同步模拟的方法来研究SVA反馈，直至灰色地带。相应的观测和尺度上的模拟可以解决湍流，这将提高对过程的理解，并将用于研究对流边界层中湍流的参数化。利用激光雷达系统的协同作用对各种模型分辨率上的通量进行升级，并与湍流剖面进行详细的比较，将有助于深入了解地表通量的表示，并为湍流参数化的改进提供指导。(2) ALCM验证运行的性能，其中包括中欧地区具有对流允许（CP）分辨率的农业土地覆盖表示方面的最新改进。预计在这个尺度上，异质和农业景观上的SVA反馈将得到更好的体现，它们与云和降水的耦合将更加现实，因为可以避免深对流的参数化。这将通过详细的模型验证来证明，包括温度和降水的极值统计分数。(3)为减少目前全球和区域气候预估的不足，如深层对流参数化带来的误差，进行到2040年的首次cp分辨率气候预估。再次，将研究温度和降水统计的演变。将推导出描述干旱和极端降水特征的指数。模拟将为欧洲气候的发展提供指导，以优化农业活动，重点是德国西南部。在预测中，农业管理和决策过程导致的土地覆盖变化是ILMS的一部分，因此会反馈给气候。这也将使我们能够研究未来几十年土地覆盖变化和温室效应对区域气候演变的各自重要性。

For the simulation of regional climate change including extreme events, the development of a new generation of regional climate models is essential. Current simulations of the statistics of temperature and precipitation are not accurate enough in many regions in Europe particularly over complex terrain. Current model evaluations indicate that improved simulations can be realised by advancing (a) the representation of the energy balance at the land surface, (b) simulations of soilvegetation- atmosphere (SVA) feedback including entrainment, and (c) the simulation of clouds and precipitation by omission of the parameterisation of deep convection. In this project, research in these three areas will be combined for the development and the improvement of FOR 1695 integrated land system model (ILMS).This will be achieved by three work packages: (1) The study of SVA feedback by means of measurements with a synergy of scanning remote sensing systems and simultaneous simulations with the Atmosphere-Land surface-Crop Model (ALCM) down to the grey zone. Corresponding observations and modelling on scales, which resolve turbulence, will improve process understanding and will be used for studying the parameterisation of turbulence in the convective boundary layer. Upscaling of fluxes over a variety of model resolutions and detailed comparisons with turbulence profiling using a synergy of lidar system will give insight in the representation of surface fluxes and guidance for the improvement of turbulence parameterisations. (2) Performance of a verification run of ALCM, which includes recent improvements with respect to the representation of agricultural land cover, over the Central Europe with convection-permitting (CP) resolution. It is expected that at this scale SVA feedback over heterogeneous and agricultural landscapes will be better represented and their coupling to clouds and precipitation will be more realistic as the parameterisation of deep convection can be avoided. This will be proven by detailed model verification including scores for extreme value statistics of temperature and precipitation. (3) Performance of a first CP-resolution climate projection until 2040 in order to reduce the current deficiencies of global and regional climate projections such as errors introduced by the parameterisation of deep convection. Again, the evolution of temperature and precipitation statistics will be studied. Indices for the characterisation of droughts and extreme precipitation will be derived. The simulations will give guidance on the development of the European climate for optimising agricultural activities with a focus on Southwest Germany. Within the projection, changes of land cover by agricultural management and decision processes are part of the ILMS and therefore feed back to the climate. This will also permit to study the respective importance of land cover changes and greenhouse forcing on the evolution of regional climate within the next decades.