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型中准确表示地表。 研究方法是将子网格地表参数化与经过验证的中尺度大气模型结合起来。 子网格参数化专门设计用于根据卫星数据估计表面特性（例如反照率、热量和湿度通量）。 为了评估该子网格方案的有效性，将耦合大气-子网格模型的结果与现场观测和遥测的表面能量通量估计进行比较。 模型结果将与大气特性的网格分析进行比较。此外，还将研究尺度效应对模型系统准确性的重要性。 这些尺度效应包括（a）模型输出对子网格分辨率的敏感性； (b) 用于将大气数据分配到子网格的方法以及如何将计算出的子网格通量传回大气模型的网格； (c) 模型输出对大气模型网格和表面子网格方向的敏感性； (d) 确定大气模型和亚网格分辨率之间物理上合理的比例。该项目将通过提供一种将亚网格变异性引入中尺度模型的改进方法而使中尺度建模界受益，从而改进数值天气预报。 这项研究也将使遥感界受益，因为要研究的许多尺度问题对于表面参数的远程估计非常重要。 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成分所需尺度的通量数据。