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Global observations of aerosol-cloud-precipitation-climate interactions

Rosenfeld, Daniel ; Andreae, Meinrat O. ; Asmi, Ari ; Chin, Mian ; de Leeuw, Gerrit ; Donovan, David P. ; Kahn, Ralph ; Kinne, Stefan ; Kivekäs, Niku LU and Kulmala, Markku , et al. (2014) In Reviews of Geophysics 52(4). p.750-808
Abstract
Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects of meteorology from those of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing. Ways to improve... (More)
Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects of meteorology from those of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing. Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing. (Less)
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organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
cloud aerosol interactions, remote sensing, climate change
in
Reviews of Geophysics
volume
52
issue
4
pages
750 - 808
publisher
American Geophysical Union (AGU)
external identifiers
  • wos:000348452000005
  • scopus:84921759191
ISSN
8755-1209
DOI
10.1002/2013RG000441
language
English
LU publication?
yes
id
7a8fce7b-b4d6-482f-aa25-d591b6c70e6f (old id 5066136)
date added to LUP
2016-04-01 14:14:08
date last changed
2022-04-22 01:56:07
@article{7a8fce7b-b4d6-482f-aa25-d591b6c70e6f,
  abstract     = {{Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects of meteorology from those of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing. Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing.}},
  author       = {{Rosenfeld, Daniel and Andreae, Meinrat O. and Asmi, Ari and Chin, Mian and de Leeuw, Gerrit and Donovan, David P. and Kahn, Ralph and Kinne, Stefan and Kivekäs, Niku and Kulmala, Markku and Lau, William and Schmidt, K. Sebastian and Suni, Tanja and Wagner, Thomas and Wild, Martin and Quaas, Johannes}},
  issn         = {{8755-1209}},
  keywords     = {{cloud aerosol interactions; remote sensing; climate change}},
  language     = {{eng}},
  number       = {{4}},
  pages        = {{750--808}},
  publisher    = {{American Geophysical Union (AGU)}},
  series       = {{Reviews of Geophysics}},
  title        = {{Global observations of aerosol-cloud-precipitation-climate interactions}},
  url          = {{http://dx.doi.org/10.1002/2013RG000441}},
  doi          = {{10.1002/2013RG000441}},
  volume       = {{52}},
  year         = {{2014}},
}