Parameterization of Extremely Heterogeneous Land-Surface Processes

陆地表面是气候系统的关键组成部分，因为陆地表面过程影响大气、生物圈和岩石圈之间的能量、质量和动量交换。在过去的几十年里，许多国际研究项目和实地活动都集中在这些过程上，并且开发了许多陆地表面方案，这些方案现在已成为天气和气候模式的重要组成部分。虽然均质陆面过程现在已相当了解，但非均质陆面过程仍有待阐明和充分参数化。我建议将地表划分为三种异质性类别：均匀（HC-I表示异质性类别I），中度异质性（HC-II）和极度异质性（HC-III）地表。本项目以复杂地形的地表为例，重点研究聚集效应和动态效应均显著的HC-III型地表过程的参数化。我们计划开发一种新的HC-III陆地表面参数化方案，将考虑静态非均质性的马赛克方法与考虑动态非均质性的复杂地形上的空气动力学传递的新处理相结合。我们将在青藏高原东南部的一个不规则场地进行大气-陆面耦合大涡模拟，生成与新方案比较的数据。经过测试的方案组件将被构建到社区土地模型中。该项目解决了一个非常具有挑战性的问题，其成果将对改进天气预报和气候预测具有重大意义。

Land surface is a key component of the climate system, as land-surface processes influence the exchanges of energy, mass and momentum between the atmosphere, biosphere and lithosphere. Over the past decades, a number of international research programs and field campaigns have been carried out focusing on these processes, and numerous land-surface schemes have been developed, which are now an essential part of weather and climate models. While homogeneous land-surface processes are now fairly well understood, heterogeneous land-surface processes remain to be elucidated and adequately parameterized. I propose to divide land surfaces into the three heterogeneity categories: homogenous (HC-I for heterogeneity category I), moderate heterogeneous (HC-II) and extremely heterogeneous (HC-III) land surfaces. This project focuses on the parameterization of HC-III land-surface processes when both the aggregation and dynamic effect are significant, as exemplified by the land surface of a complex terrain. We plan to develop a new HC-III land-surface parameterization scheme via a combination of the mosaic approach, accounting for static heterogeneity, with a new treatment of aerodynamic transfer over complex terrains, accounting for dynamic heterogeneity. We will conduct atmosphere-and-land-surface coupled large-eddy simulation over a ragged site of the southeastern Tibetan Plateau to generate data for comparison with the new scheme. The tested scheme component will then build into the Community Land Model. This project tackles a very challenging problem and the outcomes will be of great relevance to improved weather prediction and climate projection.