Detecting and Attributing Aerosol-Driven Climate Change: Fingerprints, Extreme Events, and Regional Impacts

Atmospheric aerosols are among the largest sources of uncertainty in our understanding of observed climate change. Because they cool through aerosol–radiation interactions and modify clouds, precipitation, and monsoon circulation, they partly mask greenhouse-gas warming and leave distinct fingerprints in the observational record. Separating those fingerprints from greenhouse-gas forcing and natural variability is a central detection-and-attribution challenge and it is essential for constraining climate sensitivity and guiding evidence-based mitigation.This Research Topic focuses on discerning and quantifying the aerosol contribution to observed changes in climate, weather extremes, and coupled environmental systems. We invite studies that detect statistically significant changes relative to historical records and model simulations, and that attribute those changes to anthropogenic aerosols (biomass burning, fossil-fuel combustion, industrial emissions) as distinct from mineral dust, sea spray, volcanic, and biogenic sources. Regions with strong and rapidly evolving aerosol loading, South Asia, East Asia, Africa, the Arctic, and mountainous cryospheres, such as the Hindu-Kush Himalaya, offer some of the clearest natural laboratories for attribution and are especially welcome.We particularly encourage work that uses observational constraints, formal fingerprinting, causal-inference frameworks, and data-science and machine-learning methods to attribute observed trends and extreme events, and that connects these findings to adaptation and to SDG 13 (Climate Action) and SDG 15 (Life on Land). Studies limited to monitoring, characterization, or forecasting without a detection or attribution component fall outside this section’s scope.Objectives:(i) Detection of aerosol-related climate signals• Detection of significant changes in aerosol optical depth, radiative flux, and related climate variables relative to historical baselines and control simulations• Fingerprint and pattern-based detection separating anthropogenic aerosol signals from internal variability• Observational constraints on aerosol radiative forcing and on climate sensitivity(ii) Attribution of observed climate and environmental change• Attribution of observed temperature, precipitation, and Asian-monsoon changes to aerosol versus greenhouse-gas and natural forcing• Attribution of cryosphere change (glacier and snow-cover loss, albedo reduction from black carbon deposition) to carbonaceous aerosols• Attribution of physical, ecological, and societal impacts — including effects on water resources, agriculture, and ecosystems(iii) Attribution of extreme events and air-quality episodes• Attribution of dust storms, wildfire and biomass-burning smoke, and severe haze episodes to changing emissions and a changing climate• Detection and attribution of transboundary pollution transport and its climatic consequences• Attribution of aerosol-driven changes in cloud microphysics, precipitation, and visibility(iv) Methods for detection and attribution• Data-science methods and machine learning applied to climate-change detection and attribution• Chemical transport and Earth-system models used as attribution tools (e.g., single-forcing and factual/counterfactual experiments)• Novel inferential and causal-inference methods, and comparisons among attribution methodologies• Integration of satellite and ground-based records with model simulations for robust signal detection(v) From attribution to policy and adaptation• Using attribution evidence to inform climate mitigation, adaptation, and air-quality management• Linking attributed aerosol impacts to SDG 13 (Climate Action) and SDG 15 (Life on Land)• Regional and local attribution to guide place-based adaptation in vulnerable regions Topic editors: Umesh Chandra Dumka, Muhammad Bilal, Dimitris G Kaskaoutis Source: https://www.frontiersin.org/research-topics/84493/detecting-and-attributing-aerosol-driven-climate-change-fingerprints-extreme-events-and-regional-impacts