Estimates of the aerosol indirect effect over the Baltic Sea region derived from 12 years of MODIS observations

Saponaro, Giulia; Kolmonen, Pekka; Sogacheva, Larisa; Rodríguez, Edith; Virtanen, Timo; Leeuw, Gerrit de

doi:10.5194/acp-17-3133-2017

Cited by 38 publications

(45 citation statements)

References 33 publications

(32 reference statements)

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“…By virtue of their large coverage and high spatial and temporal resolution, satellite-borne instruments have become a promising observational tool in studying ACIs. Previous studies using a large amount of satellite data and/or multiple satellite instruments have shown that aerosol particles can affect cloud properties significantly (Krüger and Grassl, 2002;Menon et al, 2008;Sporre et al, 2014;Rosenfeld et al, 2014;Saponaro et al, 2017). Satellite measurements suggest that the CDR tends to decrease with increasing aerosol loading, which is consistent with Twomey's theory (Matheson et al, 2005;Meskhidze and Nenes, 2010;Koren et al, 2005).…”

Section: Introductionsupporting

confidence: 75%

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

et al. 2017

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Abstract. Aerosol effects on low warm clouds over the Yangtze River Delta (YRD, eastern China) are examined using co-located MODIS, CALIOP and CloudSat observations. By taking the vertical locations of aerosol and cloud layers into account, we use simultaneously observed aerosol and cloud data to investigate relationships between cloud properties and the amount of aerosol particles (using aerosol optical depth, AOD, as a proxy). Also, we investigate the impact of aerosol types on the variation of cloud properties with AOD. Finally, we explore how meteorological conditions affect these relationships using ERA-Interim reanalysis data. This study shows that the relation between cloud properties and AOD depends on the aerosol abundance, with a different behaviour for low and high AOD (i.e. AOD < 0.35 and AOD > 0.35). This applies to cloud droplet effective radius (CDR) and cloud fraction (CF), but not to cloud optical thickness (COT) and cloud top pressure (CTP). COT is found to decrease when AOD increases, which may be due to radiative effects and retrieval artefacts caused by absorbing aerosol. Conversely, CTP tends to increase with elevated AOD, indicating that the aerosol is not always prone to expand the vertical extension. It also shows that the COT-CDR and CWP (cloud liquid water path)-CDR relationships are not unique, but affected by atmospheric aerosol loading. Furthermore, separation of cases with either polluted dust or smoke aerosol shows that aerosol-cloud interaction (ACI) is stronger for clouds mixed with smoke aerosol than for clouds mixed with dust, which is ascribed to the higher absorption efficiency of smoke than dust. The variation of cloud properties with AOD is analysed for various relative humidity and boundary layer thermodynamic and dynamic conditions, showing that high relative humidity favours larger cloud droplet particles and increases cloud formation, irrespective of vertical or horizontal level. Stable atmospheric conditions enhance cloud cover horizontally. However, unstable atmospheric conditions favour thicker and higher clouds. Dynamically, upward motion of air parcels can also facilitate the formation of thicker and higher clouds. Overall, the present study provides an understanding of the impact of aerosols on cloud properties over the YRD. In addition to the amount of aerosol particles (or AOD), evidence is provided that aerosol types and ambient environmental conditions need to be considered to understand the observed relationships between cloud properties and AOD.

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Section: Introductionsupporting

confidence: 75%

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

et al. 2017

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“…Koren et al () previously suggested an enhancement of cloud vertical structure over the North Atlantic due to aerosol loading. Saponaro et al () also found that the lowest CTP corresponds to the highest classes of AI over the Baltic Sea region. This is not evident over three anthropogenic regions but seems true over the adjacent oceans (Figure ), especially ECO and EUO, where the lowest CTP values (highest cloud top height, CTH) correspond to highest classes of AI.…”

Section: Aerosol‐cloud Correlationsmentioning

confidence: 89%

“…The studies by Dusek et al () and Zhang et al () found that particle size is dominant to determine aerosol activation, but many studies demonstrated that the chemical composition is also critical (Almeida et al, ; Ervens et al, ; Lance et al, ; McFiggans et al, ; Nenes et al, ; Wang et al, ). In addition, dynamical or meteorological conditions will strongly affect aerosol‐cloud interactions by changing vertical velocity or wind shear (Gryspeerdt et al, ; Fan et al, ; Koren et al, ; Loeb & Schuster, ; Mauger & Norris, ; Saponaro et al, ; Su et al, ; Tang et al, ; Wang et al, ). Overall, negative correlations are normally found over oceans while positive over land.…”

Section: Introductionmentioning

confidence: 99%

Opposite Aerosol Index‐Cloud Droplet Effective Radius Correlations Over Major Industrial Regions and Their Adjacent Oceans

Jia

et al. 2018

Geophysical Research Letters

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The Moderate Resolution Imaging Spectroradiometer (MODIS) C6 L3 and the European Centre for Medium‐Range Weather Forecasts (ECMWF) ERA‐Interim reanalysis data from 2003 to 2016 are employed to study aerosol‐cloud correlations over three industrial regions and their adjacent oceans, as well as explore the impact of meteorological conditions on the correlations. The analysis focusing on liquid and single‐layer clouds indicates an opposite aerosol‐cloud correlation between land and ocean; namely, cloud effective radius is positively correlated with aerosol index over industrial regions (positive slopes), but negatively correlated over their adjacent oceans (negative slopes), for a quasi‐constant liquid water path. The positive slopes are relatively large under low lower‐tropospheric stability (LTS; weakly stable condition), but much weaker or even become negative under high LTS (stable conditions) and high liquid water path. The occurrence frequency of cloud top height (CTH) and LTS suggests that positive correlations are more likely corresponding to relatively high CTH and low LTS, while negative to low CTH and high LTS.

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“…The sensitivity of cloud properties to aerosol perturbation is usually used to quantify ACI (Bai et al, 2018; Saponaro et al, 2017), such as the sensitivity of CDNC to aerosol loading (usually expressed by AOD or AI) (e.g., Ban‐Weiss et al, 2014; Grandey & Stier, 2010; Gryspeerdt & Stier, 2012; Ma et al, 2014; Quaas et al, 2008). However, most of these studies were based on instantaneous and/or short‐term observations, and results from such studies may have suffered from meteorological covariation (e.g., Mülmenstädt & Feingold, 2018) or effect of inter‐annual variability (Sekiguchi et al, 2003).…”

Section: Introductionmentioning

confidence: 99%

Synergetic Satellite Trend Analysis of Aerosol and Warm Cloud Properties ver Ocean and Its Implication for Aerosol‐Cloud Interactions

et al. 2020

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Decadal‐scale trends in aerosol and cloud properties provide important ways for understanding aerosol‐cloud interactions. In this paper, by using MODIS products (2003–2017), we analyze synergetic trends in aerosol properties and warm cloud properties over global ocean. Cloud droplet number concentration (CDNC) and aerosol parameters (aerosol optical depth, angstrom exponent, and aerosol index) show consistent decreasing trend over East Coast of the United States (EUS), west coast of Europe (WEU), and east coast of China (EC), and no significant trend in liquid water path is found over these regions during the period 2003–2017. Over regions with significant long‐term trends of aerosol loading and CDNC (e.g., EUS and WEU), the sensitivity of CDNC to aerosol loading based on the long‐term trend is closer to those derived from ground and aircraft observations and larger than those derived from instantaneous satellite observations, providing an alternative way for quantifying aerosol‐cloud interactions. A clear shift in the normalized probability density function of CDNC between the first 5 years (2003–2007) and the last 5 years (2013–2017) is found, with a decrease of around 50% in the occurrence frequency of high CDNC (>400 cm−3) over EUS and WEU. The relative variances of cloud droplet effective radius generally decrease with decreasing aerosol loading, providing large‐scale evidence for the effects of anthropogenic aerosols on the dispersion of cloud droplet size distribution. The long‐term satellite data sets provide great opportunities for quantifying aerosol‐cloud interactions and further confronting these interactions in climate models in the future.

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Estimates of the aerosol indirect effect over the Baltic Sea region derived from 12 years of MODIS observations

Cited by 38 publications

References 33 publications

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

Analysis of aerosol effects on warm clouds over the Yangtze River Delta from multi-sensor satellite observations

Opposite Aerosol Index‐Cloud Droplet Effective Radius Correlations Over Major Industrial Regions and Their Adjacent Oceans

Synergetic Satellite Trend Analysis of Aerosol and Warm Cloud Properties ver Ocean and Its Implication for Aerosol‐Cloud Interactions

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