A possible correlation between satellite‐derived cloud and aerosol microphysical parameters

By Teruyuki Nakajima, A. Higurashi, K. Kawamoto, J. Penner. 2001

421 citations recorded by the source corpus.

Subfields: Atmospheric Science, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/527032b311e9b6dee5e0b3a7d73a1c60321ba127

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Citations in the corpus

Drizzle in Stratiform Boundary Layer Clouds. Part I: Vertical and Horizontal Structure (2005, background): “…growth (Austin et al. 1995a; Harrington et al. 2000), and ripening effects (Celik and Marwitz 1999; Wood et al. 2002) all complicate this relationship and need to be better quantified, particularly on the large-scale using satellites (Nakajima et al. 2001; Breon et al. 2002; Schuller et al. 2003).”
Global observations of aerosol‐cloud‐precipitation‐climate interactions (2014, methodology): “To enhance the suitability of retrieved AOD as a CCN proxy, it has been suggested to calculate the product of the AOD and the Ångström exponent, the so-called aerosol index, AI [Deuzé et al., 2001; Nakajima et al., 2001].”
Effect of aerosol on warm convective clouds: Aerosol‐cloud‐surface flux feedbacks in a new coupled large eddy model (2006, background): “remote sensors [Kaufman and Nakajima, 1993; Han et al., 1998; Bréon et al., 2002; Nakajima et al., 2001] and surface-based remote sensors [e.”
Aerosol indirect effects – general circulation model intercomparison and evaluation with satellite data (2009, background): “…such as relationships between column aerosol concentrations (measured, e.g. by the aerosol optical depth, τ a ) and either r e , N d or L (Nakajima et al., 2001; Br´eon et al., 2002; Sekiguchi et al., 2003; Quaas et al., 2004; Kaufman et al., 2005; Quaas et al., 2006; Storelvmo et al.,…”
Potential of polarization lidar to provide profiles of CCN- and INP-relevant aerosol parameters (2015, background): “In this context, it is also noteworthy to mention that1020 Liu and Li (2014) showed that the product of σ×AE (denoted as Aerosol Index AI, introduced by Nakajima et al., 2001) provides a better correlation with nCCN than nCCN with σ.”
Bounding Global Aerosol Radiative Forcing of Climate Change (2020, methodology): “…droplets.576 Relationships have been found between τa in cloud-free air and a variety of properties577 of nearby clouds: cloud droplet size (Nakajima et al., 2001; Sekiguchi et al., 2003), cloud578 fraction (Kaufman et al., 2005), cloud top pressure (Koren et al., 2005), shortwave ra-579…”
Aerosol indirect effects in a multi-scale aerosol-climate model PNNL-MMF (2011, background): “…are shown for MODIS Terra (TerraAOD: cloud parameters vs. AOD); MODIS Aqua (AquaAOD: cloud parameters vs. AOD); CAM5 (CAM5AOD: cloud parameters vs. AOD, CAM5AI: cloud parameters vs. AI); MMF (MMFAOD: cloud parameters vs. AOD, MMFAI: cloud parameters vs. AI). particles (Nakajima et al., 2001).”
Constraining the aerosol influence on cloud liquid water path (2018, background): “Comparing a year with strong SO2 emissions (2008) with a low-emissions year (2007) shows that the variation in aerosol index (AI; AOD times Ångström exponent; Nakajima et al., 2001) downwind from the volcano comes primarily from the variation in aerosol (Fig.”
On the precipitation susceptibility of clouds to aerosol perturbations (2009, background): “Aerosol index (AI = AOD Ångstrom exponent) has been shown to correlate better with cloud properties and columnar aerosol concentrations as compared to AOD [Nakajima et al., 2001].”