Scaling Issues in the Direct Use of Satellite Data in Mesoscale Model Land-Surface Parameterizations

中尺度模型地表参数化中直接使用卫星数据的尺度问题

• 批准号: 9904039
• 负责人: William Capehart
• 金额: $ 18.5万
• 依托单位: South Dakota School of Mines and Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2000
• 资助国家: 美国
• 起止时间: 2000-01-15 至 2002-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9904039&HistoricalAwards=false
• 关键词: Scaling; Issues; Direct; Use; Satellite

This project addresses the accurate representation of the surface in mesoscale atmospheric prediction models. The research methodology is to couple a subgrid land-surface parameterization to a proven mesoscale atmospheric model. The subgrid parameterization is specifically designed to estimate surface properties (e.g., albedo; heat and moisture fluxes) from satellite data. In order to assess the effectiveness of this subgrid scheme, results of the coupled atmospheric-subgrid model will be compared to in-situ observations and remotely-derived estimates of surface energy fluxes. Model results will be compared to gridded analyses of atmospheric properties. In addition, the importance of scale effects on the accuracy of the model system will be investigated. These scale effects include (a) sensitivity of model output to the resolution of the subgrid; (b) the method used to distribute atmospheric data to the subgrid and how calculated subgrid fluxes are transferred back to the atmospheric model's grid; (c) the sensitivity of model output to the orientation of the atmospheric model grid and the surface subgrid; and (d) the determination of a physically reasonable ratio between the atmospheric model and subgrid resolutions.This project will benefit the mesoscale modeling community by providing an improved method for introducing subgrid variability into mesoscale models which should lead to improved numerical weather prediction. This study also will benefit the remote sensing community since many of the scale issues to be investigated are of importance in the remote estimation of surface parameters. Improvements in satellite derived surface parameterizations will provide flux data at scales required to validate the surface component of various numerical modeling schemes.

该项目致力于在中尺度大气预测模式中准确地表示地表。 研究方法是耦合一个亚网格陆面参数化一个成熟的中尺度大气模式。 子网格参数化是专门设计来估计表面属性（例如，热量和水分通量）。 为了评估这一次网格方案的有效性，将把大气-次网格耦合模式的结果与地面能量通量的现场观测和远距离估计进行比较。 模型结果将与大气特性的网格分析进行比较。此外，规模效应对模型系统的精度的重要性将进行调查。 这些尺度效应包括：（a）模式输出对次网格分辨率的敏感性;（B）用于将大气数据分配到次网格的方法以及计算的次网格通量如何被传送回大气模式的网格;（c）模式输出对大气模式网格和地面次网格方向的敏感性;及（d）决定大气模式与次网格分辨率之间的物理上合理的比率。这项计划将提供一个改良方法，把次网格变率引入中尺度模式，从而改善数值天气预报，使中尺度模式界受惠。 这项研究也将有利于遥感界，因为许多规模的问题进行调查的重要性，在遥感估计的表面参数。 卫星导出的表面参数化的改进将提供验证各种数值模拟方案的表面部分所需尺度的通量数据。