基于物理机制的植被覆盖率参数化方案

IF 1.4 4区 地球科学 Q4 METEOROLOGY & ATMOSPHERIC SCIENCES Russian Meteorology and Hydrology Pub Date : 2024-07-26 DOI:10.3103/s1068373924050066
Ch. Meng, Y. Gu, H. Li, H. Jin, G. Zhang, J. Cui
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引用次数: 0

摘要

摘要叶面积指数(LAI)和植被覆盖率(FVC)是陆地-大气相互作用中非常重要的参数。本研究根据冠层空隙率、叶面积指数和太阳直接消光系数之间的关系,开发了一种非常简单但稳健的基于机制的方法来推导 FVC 数据。为进行验证,将 LAI 数据、基于 NDVI 的 FVC 数据和基于机制的 FVC 数据同化到城市土地综合模型(IUM)中。与使用基于 NDVI 的 FVC 数据作为输入相比,使用基于机制的 FVC 数据作为输入,对北京地区年平均地表温度(LSTs)的模拟得到了改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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A Physical Mechanism-based Scheme for Parameterizing the Fractional Vegetation Cover

Abstract

The leaf area index (LAI) and fractional vegetation cover (FVC) are very important parameters in land–atmosphere interactions. In this study, a very simple but robust and mechanism-based method was developed to derive FVC data based on the relationships between the canopy gap fraction, LAI, and direct solar extinction coefficient. For validation, the LAI data and NDVI-based and mechanism-based FVC data were assimilated into the integrated urban land model (IUM). Using the mechanism-based FVC data as the input, the simulation of the annual average land surface temperatures (LSTs) in the Beijing area were improved compared with those using the NDVI-based FVC data as the input.

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来源期刊
Russian Meteorology and Hydrology
Russian Meteorology and Hydrology METEOROLOGY & ATMOSPHERIC SCIENCES-
CiteScore
1.70
自引率
28.60%
发文量
44
审稿时长
4-8 weeks
期刊介绍: Russian Meteorology and Hydrology is a peer reviewed journal that covers topical issues of hydrometeorological science and practice: methods of forecasting weather and hydrological phenomena, climate monitoring issues, environmental pollution, space hydrometeorology, agrometeorology.
期刊最新文献
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