Tropical Deforestation as a Testbed for Improving Parameterization and Understanding of Land-Atmosphere Interactions

该项目利用NCAR社区气候模式(CCM)的模拟和对地表参数的简单分析，研究了亚马逊森林转变为草原的气候影响。重点放在水文循环上，特别是降水、蒸散和推定径流。除了完全砍伐森林的情景外，还将使用简短的数值模拟来揭示反照率、地表粗糙度和地表长波发射变化的相对重要性。所研究的问题被用作一个例子，以更好地理解气候模型和陆地过程模型中的运行机制。这项研究很重要，因为由此产生的更多的了解将被用来确定进一步改进气候模型的土地部分的需要。这项研究是在全球变化研究计划的气候建模、分析和预测(CMAP)倡议下资助的。

This project studies the climate effects of the conversion of the Amazon forest to a grassland, using simulations with the NCAR Community Climate Model (CCM) and simple analyses for the surface parametrizations. Emphasis is on the hydrological cycle, in particular precipitation and evapotranspiration and inferred runoff. Besides the full deforestation scenario, short numerical simulations will be used to reveal the relative importance of changes in albedo, surface roughness, and surface longwave emission. The problem studied is used as an example to yield a better understanding of mechanisms operating in a climate model coupled to a land process model. This study is important because the increased understanding derived from it will be used to determine needs for further improvement in the land component of climate models. This research is funded under the Climate Modeling, Analysis and Prediction (CMAP) initiative of the Global Change Research Program.