Open AccessBiophysical feedback of forest canopy height on land surface temperature over contiguous United States
Author(s) -
Zhijiang Zhang,
Xinxin Li,
Hongguang Liu
Publication year - 2022
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/ac4657
Subject(s) - environmental science , climate change , deciduous , evergreen , canopy , atmospheric sciences , deforestation (computer science) , latent heat , sensible heat , tree canopy , climatology , geography , meteorology , ecology , archaeology , computer science , biology , programming language , geology
Forests are considered important in the mitigation of climate change. Biophysical effects of afforestation and deforestation on land surface temperature (LST) have been extensively documented. As a fundamental variable of forest structure, however, few studies have investigated the biophysical feedback of forest canopy height (FCH) changes on LST at large scale. This study is designed to investigate the impact of FCH changes on local land LST and clarify the biophysical processes controlling LST change from 2003 to 2005 over the contiguous United States, based on satellite observations. To this end, one satellite-based FCH product is selected, and the space-for-time approach, together with the energy balance equation, is applied. Results show that for different forest types, namely evergreen forest (EF), deciduous forest (DF), and mixed forest (MF), taller forests present a greater net cooling effect (0.056–0.448 K) than shorter forests at annual scale. The increase in net radiation and sensible heat flux was less than the increase in the latent heat flux when FCH classes converted from shorter to taller, resulting in annual net cooling effects. Furthermore, the cooling effect of EF is stronger than that of DF and MF, whether for tall, medium, or short FCH classes. Multiple regression analysis reveals that the changes in biophysical components can effectively explain the LST change during the growing season. Our findings provide a new insight for forest management decision-making with the purpose of mitigating climate warming.