期刊
JOURNAL OF CLIMATE
卷 33, 期 19, 页码 8381-8399出版社
AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-19-0725.1
关键词
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资金
- National Key Research and Development Program of China [2019YFA0607203, 2017YFA0604404]
- National Natural Science Foundation of China [41901327]
- Guangdong Basic and Applied Basic Research Foundation [2019A1515010823]
- Fundamental Research Funds for the Central Universities [19lgpy41]
- China Postdoctoral Science Foundation [2020M672937, 2020T130732]
- NSF Established Program to Stimulate Competitive Research [1101245, 1832959]
- EPSCoR
- Office Of The Director [1101245] Funding Source: National Science Foundation
- Office Of The Director
- Office of Integrative Activities [1832959] Funding Source: National Science Foundation
While the significance of quantifying the biophysical effects of deforestation is rarely disputed, the sensitivities of land surface temperature (LST) to deforestation-induced changes in different biophysical factors (e.g., albedo, aerodynamic resistance, and surface resistance) and the relative importance of those biophysical changes remain elusive. Based on the subgrid-scale outputs from two global Earth system models (ESMs, i.e., the Geophysical Fluid Dynamics Laboratory Earth System Model and the Community Earth System Model) and an improved attribution framework, the sensitivities and responses of LST to deforestation are examined. Both models show that changes in aerodynamic resistance are the most important factor responsible for LST changes, with other factors such as albedo and surface resistance playing secondary but important roles. However, the magnitude of the contributions from different biophysical factors to LST changes is quite different for the two ESMs. We find that the differences between the two models in terms of the sensitivities are smaller than those of the corresponding biophysical changes, indicating that the dissimilarity between the two models in terms of LST responses to deforestation is more related to the magnitude of biophysical changes. It is the first time that the attribution of subgrid surface temperature variability is comprehensively compared based on simulations with two commonly used global ESMs. This study yields new insights into the similarity and dissimilarity in terms of how the biophysical processes are represented in different ESMs and further improves our understanding of how deforestation impacts on the local surface climate.
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