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Attribution of Local Temperature Response to Deforestation
Author(s) -
Liao Weilin,
Rigden Angela J.,
Li Dan
Publication year - 2018
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1029/2018jg004401
Subject(s) - environmental science , deforestation (computer science) , aerodynamics , atmospheric sciences , daytime , sensible heat , attribution , eddy covariance , meteorology , vegetation (pathology) , climatology , geography , ecosystem , computer science , ecology , engineering , geology , aerospace engineering , psychology , social psychology , programming language , medicine , pathology , biology
Abstract Land use and land cover change such as deforestation can directly induce changes in land surface temperature (LST). Using observational data from four paired eddy covariance sites, we attribute changes in LST induced by deforestation to changes in radiation, aerodynamic resistance, the Bowen ratio or surface resistance, and heat storage using two different methods: the intrinsic biophysical mechanism (IBM) method and the two‐resistance mechanism method. The two models are first optimized to reduce the root‐mean‐square error of the simulated daily LST change by using daily‐averaged inputs and a weighted average approach for computing the sensitivities. Both methods indicate that the daytime warming effect of deforestation is mostly induced by changes in aerodynamic resistance as the surface becomes smoother after deforestation, and the nighttime cooling effect of deforestation is controlled by changes in aerodynamic resistance, surface resistance, radiation, and heat storage. Both methods also indicate that changes in atmospheric temperature have a large impact on LST and need to be included in the LST attribution. However, there are significant differences between the two methods. The IBM method tends to overestimate the contribution of aerodynamic resistance due to the assumption that aerodynamic resistance and the Bowen ratio are independent. Additionally, the IBM method underestimates the contributions of radiation and heat storage during the daytime but overestimates them at night. By highlighting the similarity and dissimilarity between the two methods, this study suggests that acceptable agreement between observed and modeled LST change is the prerequisite for attribution but does not guarantee correct attribution.