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Quantifying Black Carbon Retrieval in Snow Surface: Remote Sensing, Modeling, and Observations Perspectives
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Black carbon (BC), a short-lived aerosol produced by incomplete combustion of biomass and fossil fuels, exerts profound influences on local, regional, and global cryosphere through snow albedo feedback mechanisms. Accurately estimating BC concentration in the cryosphere using satellite surface reflectance is a pivotal objective of snow optical remote sensing. Over the past two decades, numerous endeavors have developed various retrieval algorithms for cryosphere's BC and conducted small-scale validations to prove their feasibility. However, few studies have focused on evaluating how these algorithms address the enormous challenges of global BC concentration quantification, which has led to the community's limited knowledge of BC loading in snow globally. Considering the mounting obstacles to achieving carbon neutrality goals and the increasing prevalence of global wildfires, it is imperative to extend state-of-the-art black carbon retrieval algorithms to the global scale to achieve more refined quantitative mapping of snow pollutants with enhanced generalizability. To bridge this gap, this work employs six advanced cryospheric snow BC remote sensing algorithms rooted in analytical asymptotic radiative transfer theory to retrieve global BC abundance. The study comprehensively optimized the covariates used by the six commonly adopted BC direct retrieval algorithms from three aspects: inherent optical properties of ice crystals and BC, snow microstructure and scattering characteristics, and BC's intrinsic physical properties. This research quantified uncertainties using over 20,000 high-quality BC concentration measurements (including thermal, optical, and thermo-optical methods) from the global cryosphere (including Asia, Europe, America, and the Polar Regions) and further analyzed the optimal configuration for remote sensing retrieval of BC. Overall, through large-scale critical evaluation of the current state-of-the-art snow BC concentration remote sensing retrieval scheme, this work revealed the tremendous potential of using satellites to quantify BC abundance in the cryosphere, providing a new perspective for estimating the carbon sequestration capacity of the cryosphere.
Title: Quantifying Black Carbon Retrieval in Snow Surface: Remote Sensing, Modeling, and Observations Perspectives
Description:
Black carbon (BC), a short-lived aerosol produced by incomplete combustion of biomass and fossil fuels, exerts profound influences on local, regional, and global cryosphere through snow albedo feedback mechanisms.
Accurately estimating BC concentration in the cryosphere using satellite surface reflectance is a pivotal objective of snow optical remote sensing.
Over the past two decades, numerous endeavors have developed various retrieval algorithms for cryosphere's BC and conducted small-scale validations to prove their feasibility.
However, few studies have focused on evaluating how these algorithms address the enormous challenges of global BC concentration quantification, which has led to the community's limited knowledge of BC loading in snow globally.
Considering the mounting obstacles to achieving carbon neutrality goals and the increasing prevalence of global wildfires, it is imperative to extend state-of-the-art black carbon retrieval algorithms to the global scale to achieve more refined quantitative mapping of snow pollutants with enhanced generalizability.
To bridge this gap, this work employs six advanced cryospheric snow BC remote sensing algorithms rooted in analytical asymptotic radiative transfer theory to retrieve global BC abundance.
The study comprehensively optimized the covariates used by the six commonly adopted BC direct retrieval algorithms from three aspects: inherent optical properties of ice crystals and BC, snow microstructure and scattering characteristics, and BC's intrinsic physical properties.
This research quantified uncertainties using over 20,000 high-quality BC concentration measurements (including thermal, optical, and thermo-optical methods) from the global cryosphere (including Asia, Europe, America, and the Polar Regions) and further analyzed the optimal configuration for remote sensing retrieval of BC.
Overall, through large-scale critical evaluation of the current state-of-the-art snow BC concentration remote sensing retrieval scheme, this work revealed the tremendous potential of using satellites to quantify BC abundance in the cryosphere, providing a new perspective for estimating the carbon sequestration capacity of the cryosphere.
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