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

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

引用次数: 0

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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基于物理机制的植被覆盖率参数化方案

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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来源期刊

Russian Meteorology and Hydrology METEOROLOGY & ATMOSPHERIC SCIENCES-

CiteScore

1.70

自引率

28.60%

发文量

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.