Journal of the Atmospheric Sciences · 2021 · 29 citations · 78 references
Natural SciencesEarth SciencesMeteorologyAtmospheric ScienceCloud PhysicsPhysical MeteorologyAerosol PhysicsAerosol-cloud InteractionsCloud Condensation NucleiCloud PropertiesCloud StructureCloud-aerosol InteractionsAerosol Effects On Cloud StructureAerosol Indirect EffectsAerosol Indirect Radiative EffectAerosol PropertiesAerosol-cloud Boundary Layer CouplingAtmospheric Aerosol CharacterizationCloud HeightCondensation Nuclei Effects
Abstract An aerosol indirect effect on deep convective cores (DCCs), by which increasing aerosol concentration increases cloud-top height via enhanced latent heating and updraft velocity, has been proposed in many studies. However, the magnitude of this effect remains uncertain due to aerosol measurement limitations, modulation of the effect by meteorological conditions, and difficulties untangling meteorological and aerosol effects on DCCs. The Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign in 2018–19 produced concentrated aerosol and cloud observations in a location with frequent DCCs, providing an opportunity to examine the proposed aerosol indirect effect on DCC depth in a rigorous and robust manner. For periods throughout the campaign with well-mixed boundary layers, we analyze relationships that exist between aerosol variables (condensation nuclei concentration > 10 nm, 0.4% cloud condensation nuclei concentration, 55–1000-nm aerosol concentration, and aerosol optical depth) and meteorological variables [level of neutral buoyancy (LNB), convective available potential energy, midlevel relative humidity, and deep-layer vertical wind shear] with the maximum radar-echo-top height and cloud-top temperature (CTT) of DCCs. Meteorological variables such as LNB and deep-layer shear are strongly correlated with DCC depth. LNB is also highly correlated with three of the aerosol variables. After accounting for meteorological correlations, increasing values of the aerosol variables [with the exception of one formulation of aerosol optical depth (AOD)] are generally correlated at a statistically significant level with a warmer CTT of DCCs. Therefore, for the study region and period considered, increasing aerosol concentration is mostly associated with a decrease in DCC depth.
78
Leo Breiman · Machine Learning · 2001 · 126.2K citations · Full text
Scikit-learn: Machine Learning in Python
Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.7K citations · Full text
scikit-image: image processing in Python
Stéfan van der Walt, Johannes L. Schönberger, Juan Nunez-Iglesias et al. · PeerJ · 2014 · 6.9K citations · Full text
Flood or Drought: How Do Aerosols Affect Precipitation?
Daniel Rosenfeld, Ulrike Lohmann, Graciela B. Raga et al. · Science · 2008 · 2.4K citations
Robert McGill, John W. Tukey, Wayne A. Larsen · The American Statistician · 1978 · 2.2K citations