Dataset Information

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers.

ABSTRACT: Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day.

SUBMITTER: Rosenfeld D

PROVIDER: S-EPMC4889349 | biostudies-other | 2016 May

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:Coastal southeast Florida experiences a wide range of aerosol conditions, including African dust, biomass burning (BB) aerosols, as well as sea salt and other locally-emitted aerosols. These aerosols are important sources of cloud condensation nuclei (CCN), which play an essential role in governing cloud radiative properties. As marine environments dominate the surface of Earth, CCN characteristics in coastal southeast Florida have broad implications for other regions with the added feature that this site is perturbed by both natural and anthropogenic emissions. This study investigates the influence of different air mass types on CCN concentrations at 0.2% (CCN0.2%) and 1.0% (CCN1.0%) supersaturation (SS) based on ground site measurements during selected months in 2013, 2017, and 2018. Average CCN0.2% and CCN1.0% concentrations were 373 ± 200 cm-3 and 584 ± 323 cm-3, respectively, for four selected days with minimal presence of African dust and BB (i.e., background days). CCN concentrations were not elevated on the four days with highest influence of African dust (289 ± 104 cm-3 [0.2% SS] and 591 ± 302 cm-3 [1.0% SS]), consistent with high dust mass concentrations comprised of coarse particles that are few in number. In contrast, CCN concentrations were substantially enhanced on the five days with the greatest impact from BB (1408 ± 976 cm-3 [0.2% SS] and 3337 ± 1252 cm-3 [1.0% SS]). Ratios of CCN0.2%:CCN1.0% were used to compare the hygroscopicity of the aerosols associated with African dust, BB, and background days. Average ratios were similar for days impacted by African dust and BB (0.54 ± 0.17 and 0.55 ± 0.17, respectively). A 29% higher average ratio was observed on background days (0.71 ± 0.14), owing in part to a strong presence of sea salt and reduced presence of more hydrophobic species such as those of a carbonaceous or mineral-dust nature. Finally, periods of heavy rainfall were shown to effectively decrease both CCN0.2% and CCN1.0% concentrations. However, the rate varied at which such concentrations increased after the rain. This work contributes knowledge on the nucleating ability of African dust and BB in a marine environment after varying periods of atmospheric transport (days to weeks). The results can be used to understand the hygroscopicity of these air mass types, predict how they may influence cloud properties, and provide a valuable model constraint when predicting CCN concentrations in comparable situations.

Dataset Information

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets