Satellite observations of cloud regime development: the role of aerosol  processes

Gryspeerdt, Edward; Stier, Philip; Partridge, Derek

doi:10.5194/acp-14-1141-2014

Cited by 91 publications

(96 citation statements)

References 60 publications

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“…LTS is defined as the difference in potential temperature between the free troposphere (700 hpa) and the surface, which is representative of typical thermodynamic conditions (Klein and Hartmanm, 1993). It has been suggested that relative humidity, LTS and PVV affect aerosol and cloud interaction (Gryspeerdt et al, 2014;Small et al, 2011). A positive LTS is associated with a stable atmosphere in which vertical mixing is prohibited; negative PVV indicates a local upward motion of air parcels.…”

Section: Data Processingmentioning

confidence: 99%

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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: Data Processingmentioning

confidence: 99%

“…Impacts of aerosols on clouds and precipitation have been reported as introducing the largest uncertainty in quantifying the anthropogenic contribution to climate change (Rosenfeld, 2000;Twomey, 1974;Gryspeerdt et al, 2014;Kaufman et al, 2012). Atmospheric aerosol particles have been recognized as having two effects on Earth's climate.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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“…Actual clouds may not satisfy the homogeneity assumption (Schutgens and Roebeling, 2009). Moreover, the coarse resolution limits the usage in certain aerosol-cloud interaction studies (Sekiguchi, 2003;Gryspeerdt et al, 2014). Based on the above analysis, the following two questions are the focal points of this study.…”

Section: Introductionmentioning

confidence: 99%

Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

et al. 2015

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Abstract. The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR (∼ 1.5 µm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise.Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145 • ) are used to ensure retrievals of large droplet (> 15 µm) and to reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data from June 2008, and the new CDR results are compared with the operational CDRs. The comparison shows that the operational CDRs tend to be underestimated for large droplets because the cloudbow oscillations in the scattering angle region of 145-165 • are weak for cloud fields with CDR > 15 µm. Finally, a sub-grid-scale retrieval case demonstrates that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size distribution parameters from POLDER measurements.

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“…CC BY 4.0 License. (Williams and Webb, 2009;Gryspeerdt et al, 2014). Being based purely on the observed cloud properties, "cloud regimes" do not require assumptions about the impact of local meteorology on the regime occurrence.…”

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confidence: 99%

Technical note: An automated cirrus classification

Gryspeerdt¹,

Quaas²,

Goren³

et al. 2017

Preprint

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Abstract. Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus clouds on the mechanism of formation, which itself is strongly dependent on the local meteorological conditions. In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus 5clouds by their formation mechanisms. Using re-analysis and satellite data, cirrus clouds are separated in four main types: orographic, frontal, convective and in-situ. Through a comparison to convection-permitting model simulations and back-trajectory based analysis, it is shown that the regimes can provide extra information on the properties and origin of cirrus that could not be provided by the retrieved cloud properties or reanalysis data alone. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud 10 processes.

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Satellite observations of cloud regime development: the role of aerosol processes

Cited by 91 publications

References 60 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

Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

Technical note: An automated cirrus classification

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