A Simple Model for Land Surface Parameterization and Modeling

9725698 friedl本建议解决了对气候和数值天气预报模式中土壤-植被-大气转移（SVAT）参数化中关键变量常规监测方法的改进需求。为此，本文描述了一个为期两年的研究计划，以改进和验证一个简单的模型，利用遥感数据源在SVAT模型中参数化地表过程。这个框架中的关键变量是地表温度、植被类型和数量以及地表湿度状况。所提出的方法建立在先前的研究和模型开发的基础上，这些研究和模型开发涉及地表能量平衡、植被覆盖和地表温度之间的关系，这些关系使用的是FIFE的数据。这项工作将继续侧重于半干旱地区这些关系的分析和建模。这项研究将改进一种基于陆地表面能量平衡原理的建模策略，其中包括土壤-植被微气象学的处理，但同时也足够简单，可以使用卫星数据与最小的现场地面测量相结合进行操作。本研究的具体工作包括：(1)土壤热温模型与两层地表能量平衡模型的整合与验证；(2)利用卫星数据估算地表性质和能量平衡分量的反演建模策略的开发与试验。提出的研究有可能提供一种简单、可操作且准确的方法来初始化、更新数据和验证水文和大气环流模型中的地表参数化。因此，它与正在进行的全球变化研究计划高度相关，包括GEWEX大陆规模国际项目（GCIP）和地球观测系统（EOS）。

9725698FriedlThis proposal addresses the need for improved methods to routinely monitor key variables within soil-vegetation-atmosphere-transfer (SVAT) parameterizations nested within climate and numerical weather forecasting models. To this end, a two year research plan is described to refine and validate a simple model to parameterize land surface processes in SVAT models using remotely sensed data sources. Key variables within this framework are surface temperature, vegetation type and amount, and surface moisture status. The proposed methodology builds off previous research and model development related to relationships among surface energy balance, vegetation cover, and surface temperature using data from FIFE. This work will continue to focus on analysis and modeling of these relationships in semi-arid regions. The research will refine a modeling strategy that is based on principles of land surface energy balance and which includes treatment of soil-vegetation micrometeorology, but which at the same time is simple enough to be implemented operationally using satellite data in association with minimal in-situ ground measurements. Specific tasks to be performed as part of this research are (1) the integration and validation of a soil heat and temperature model with a two-layer land surface energy balance model; and (2) development and testing of inversion modeling strategies to estimate land surface properties and energy balance components from satellite data. The proposed research has the potential to provide a simple, operational, yet accurate method to initialize, updata and validate land surface parameterizations within hydrologic and atmospheric circulation models. As such it is highly relevant to ongoing global change research programs including the GEWEX continental Scale International Project (GCIP) and the Earth Observing Systems (EOS).