Biomass burning aerosols produce -2.5 W m^{-2} regional shortwave cooling over the South-East Atlantic, decomposed equally into ARI, ARI adjustments, and ACI after causal removal of confounding biases.
URL https://acp.copernicus.org/ articles/19/3515/2019/
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Particle simulations and path analysis show the 2011 Sargassum bloom originated near West Africa, matching 2009 coastal reports and unusual environmental conditions there.
AIFS-COMPO is a transformer-based data-driven model that delivers medium-range global atmospheric composition forecasts with skill comparable to the operational CAMS system but at much lower computational cost.
SGED-TCD is a lag-resolved causal discovery framework that uses structural gating and perturbation-effect alignment to infer interpretable weighted causal networks from complex time series, shown on heat-pollution extremes in China.
citing papers explorer
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Dissipating the correlation smokescreen: Causal decomposition of the radiative effects of biomass burning aerosols over the South-East Atlantic
Biomass burning aerosols produce -2.5 W m^{-2} regional shortwave cooling over the South-East Atlantic, decomposed equally into ARI, ARI adjustments, and ACI after causal removal of confounding biases.
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Tracing the origin of tropical North Atlantic Sargassum blooms to West Africa
Particle simulations and path analysis show the 2011 Sargassum bloom originated near West Africa, matching 2009 coastal reports and unusual environmental conditions there.
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AIFS-COMPO: A Global Data-Driven Atmospheric Composition Forecasting System
AIFS-COMPO is a transformer-based data-driven model that delivers medium-range global atmospheric composition forecasts with skill comparable to the operational CAMS system but at much lower computational cost.
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Structural Gating and Effect-aligned Lag-resolved Temporal Causal Discovery Framework with Application to Heat-Pollution Extremes
SGED-TCD is a lag-resolved causal discovery framework that uses structural gating and perturbation-effect alignment to infer interpretable weighted causal networks from complex time series, shown on heat-pollution extremes in China.