Development of a resolution-dependent parameterisation for surface fluxes with inclusion of sub-grid-scale land-use effects

开发与分辨率相关的表面通量参数化，其中包含亚网格尺度的土地利用效应

• 批准号: 5426309
• 负责人: Professorin Dr. Katharina Heinke Schlünzen
• 金额: --
• 依托单位: Meteorologisches Institut (MI)
• 依托单位国家: 德国
• 项目类别: Priority Programmes
• 财政年份: 2004
• 资助国家: 德国
• 起止时间: 2003-12-31 至 2008-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/5426309?language=en
• 关键词: Development; resolution; dependent; parameterisation; surface

Evaporation from soil, water and vegetation is the source of water in the atmosphere. It depends an several factors; very relevant ones are atmospheric stratification and (subgrid-scale) land-use. This project aims to develop a resolution-dependent parameterisation for surface fluxes that considers subgrid-scale land-use effects. The parameterisation should work for grid sizes of 1 to 8 km for all meteorological situations. For developing the parameterisation the well-established mesoscale model METRAS will be used that already includes three different resolution-independent schemes to consider sub-gridscale land-use effects an the surface fluxes. Model performance will be rated by comparing with routine surface and flux measurements for meteorological situations that have a distinct difference in the relevance of local effects. This will be expressed by a newly introduced locality number lld which is also put in relation to the amount of precipitation. Idealised case studies with the obstacle resolving micro-scale model MITRAS will aid the parameterisation development. The parameterisation will be optimised for its use in weather forecast models. The new parameterisation will be implemented in LM and its performance be tested with respect to precipitation forecast.

土壤、水和植被的蒸发是大气中水分的来源。这取决于几个因素;非常相关的是大气层结和（次网格尺度）土地使用。该项目旨在为考虑次网格尺度土地利用影响的地表通量制定一个取决于分辨率的参数化。参数化应适用于所有气象情况下1至8公里的网格大小。为了开发参数化，将使用成熟的中尺度模型METRAS，该模型已经包括三种不同的独立于分辨率的方案，以考虑次网格尺度土地利用对地表通量的影响。将通过与当地效应相关性有明显差异的气象情况下的常规地面和通量测量值进行比较来评定模型性能。这将通过新引入的位置号lld来表示，该位置号也与降水量相关。理想的情况下，解决障碍的微观模型MITRAS的研究将有助于参数化的发展。参数化将被优化用于天气预报模型。新的参数化将在LM中实施，并在降水预报方面测试其性能。