Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, Matthias Tesche
{"title":"在卫星观测中研究气溶胶-云相互作用的逐云方法","authors":"Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, Matthias Tesche","doi":"10.5194/egusphere-2023-2773","DOIUrl":null,"url":null,"abstract":"<strong>Abstract.</strong> The effective radiative forcing (ERF) due to aerosol-cloud interactions (ACI) and rapid adjustments (ERFaci) still causes the largest uncertainty in the assessment of climate change. It is understood only with medium confidence and studied primarily for warm clouds. Here, we present a novel cloud-by-cloud (C×C) approach for studying ACI in satellite observations that combines the concentration of cloud condensation nuclei (<em>n</em><sub>CCN</sub>) and ice nucleating particles (<em>n</em><sub>INP</sub>) from polar-orbiting lidar measurements with the development of the properties of individual clouds from tracking them in geostationary observations. We present a step-by-step description for obtaining matched aerosol-cloud cases. The application to satellite observations over Central Europe and Northern Africa during 2014 together with rigorous quality assurance leads to 399 liquid-only clouds and 95 ice-containing clouds that can be matched to surrounding <em>n</em><sub>CCN</sub> and <em>n</em><sub>INP</sub>, respectively, at cloud level. We use this initial data set for assessing the impact of changes in cloud-relevant aerosol concentrations on the cloud droplet number concentration (<em>N</em><sub>d</sub>) and effective radius (<em>r</em><sub>eff</sub>) of liquid clouds and the phase of clouds in the regime of heterogeneous ice formation. We find a Δ ln <em>N</em><sub>d</sub>/Δ ln <em>n</em><sub>CCN</sub> of 0.13 to 0.30 which is at the lower end of commonly inferred values of 0.3 to 0.8. The Δ ln <em>r</em><sub>eff</sub>/Δ ln <em>n</em><sub>CCN</sub> between -0.09 and -0.21 suggests that <em>r</em><sub>eff</sub> decreases by -0.81 to -3.78 nm per increase in <em>n</em><sub>CCN</sub> of 1 cm<sup>-3</sup>. We also find a tendency towards more cloud ice and more fully glaciated clouds with increasing <em>n</em><sub>INP</sub> that cannot be explained by the increasingly lower cloud-top temperature of super-cooled liquid, mixed-phase, and fully glaciated clouds alone. Applied to a larger amount of observations, the C×C approach has the potential to enable the systematic investigation of warm and cold clouds. This marks a step change in the quantification of ERFaci from space.","PeriodicalId":8619,"journal":{"name":"Atmospheric Measurement Techniques","volume":"32 1","pages":""},"PeriodicalIF":3.2000,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A cloud-by-cloud approach for studying aerosol-cloud interaction in satellite observations\",\"authors\":\"Fani Alexandri, Felix Müller, Goutam Choudhury, Peggy Achtert, Torsten Seelig, Matthias Tesche\",\"doi\":\"10.5194/egusphere-2023-2773\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Abstract.</strong> The effective radiative forcing (ERF) due to aerosol-cloud interactions (ACI) and rapid adjustments (ERFaci) still causes the largest uncertainty in the assessment of climate change. It is understood only with medium confidence and studied primarily for warm clouds. Here, we present a novel cloud-by-cloud (C×C) approach for studying ACI in satellite observations that combines the concentration of cloud condensation nuclei (<em>n</em><sub>CCN</sub>) and ice nucleating particles (<em>n</em><sub>INP</sub>) from polar-orbiting lidar measurements with the development of the properties of individual clouds from tracking them in geostationary observations. We present a step-by-step description for obtaining matched aerosol-cloud cases. The application to satellite observations over Central Europe and Northern Africa during 2014 together with rigorous quality assurance leads to 399 liquid-only clouds and 95 ice-containing clouds that can be matched to surrounding <em>n</em><sub>CCN</sub> and <em>n</em><sub>INP</sub>, respectively, at cloud level. We use this initial data set for assessing the impact of changes in cloud-relevant aerosol concentrations on the cloud droplet number concentration (<em>N</em><sub>d</sub>) and effective radius (<em>r</em><sub>eff</sub>) of liquid clouds and the phase of clouds in the regime of heterogeneous ice formation. We find a Δ ln <em>N</em><sub>d</sub>/Δ ln <em>n</em><sub>CCN</sub> of 0.13 to 0.30 which is at the lower end of commonly inferred values of 0.3 to 0.8. The Δ ln <em>r</em><sub>eff</sub>/Δ ln <em>n</em><sub>CCN</sub> between -0.09 and -0.21 suggests that <em>r</em><sub>eff</sub> decreases by -0.81 to -3.78 nm per increase in <em>n</em><sub>CCN</sub> of 1 cm<sup>-3</sup>. We also find a tendency towards more cloud ice and more fully glaciated clouds with increasing <em>n</em><sub>INP</sub> that cannot be explained by the increasingly lower cloud-top temperature of super-cooled liquid, mixed-phase, and fully glaciated clouds alone. 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A cloud-by-cloud approach for studying aerosol-cloud interaction in satellite observations
Abstract. The effective radiative forcing (ERF) due to aerosol-cloud interactions (ACI) and rapid adjustments (ERFaci) still causes the largest uncertainty in the assessment of climate change. It is understood only with medium confidence and studied primarily for warm clouds. Here, we present a novel cloud-by-cloud (C×C) approach for studying ACI in satellite observations that combines the concentration of cloud condensation nuclei (nCCN) and ice nucleating particles (nINP) from polar-orbiting lidar measurements with the development of the properties of individual clouds from tracking them in geostationary observations. We present a step-by-step description for obtaining matched aerosol-cloud cases. The application to satellite observations over Central Europe and Northern Africa during 2014 together with rigorous quality assurance leads to 399 liquid-only clouds and 95 ice-containing clouds that can be matched to surrounding nCCN and nINP, respectively, at cloud level. We use this initial data set for assessing the impact of changes in cloud-relevant aerosol concentrations on the cloud droplet number concentration (Nd) and effective radius (reff) of liquid clouds and the phase of clouds in the regime of heterogeneous ice formation. We find a Δ ln Nd/Δ ln nCCN of 0.13 to 0.30 which is at the lower end of commonly inferred values of 0.3 to 0.8. The Δ ln reff/Δ ln nCCN between -0.09 and -0.21 suggests that reff decreases by -0.81 to -3.78 nm per increase in nCCN of 1 cm-3. We also find a tendency towards more cloud ice and more fully glaciated clouds with increasing nINP that cannot be explained by the increasingly lower cloud-top temperature of super-cooled liquid, mixed-phase, and fully glaciated clouds alone. Applied to a larger amount of observations, the C×C approach has the potential to enable the systematic investigation of warm and cold clouds. This marks a step change in the quantification of ERFaci from space.
期刊介绍:
Atmospheric Measurement Techniques (AMT) is an international scientific journal dedicated to the publication and discussion of advances in remote sensing, in-situ and laboratory measurement techniques for the constituents and properties of the Earth’s atmosphere.
The main subject areas comprise the development, intercomparison and validation of measurement instruments and techniques of data processing and information retrieval for gases, aerosols, and clouds. The manuscript types considered for peer-reviewed publication are research articles, review articles, and commentaries.