Articles | Volume 15, issue 12
https://doi.org/10.5194/amt-15-3875-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-15-3875-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
01 Jul 2022
Research article |
| 01 Jul 2022
| 01 Jul 2022
The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data
Edward Gryspeerdt
CORRESPONDING AUTHOR
Space and Atmospheric Physics Group, Imperial College London, London, UK
Grantham Institute – Climate Change and the Environment, Imperial College London, London, UK
Daniel T. McCoy
Department of Atmospheric Science, University of Wyoming, Laramie, WY, USA
Ewan Crosbie
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Science Systems and Applications, Inc., Hampton, VA, USA
Richard H. Moore
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Graeme J. Nott
FAAM, Cranfield, UK
David Painemal
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
Science Systems and Applications, Inc., Hampton, VA, USA
Jennifer Small-Griswold
University of Hawai'i at Mānoa, Honolulu, HI, USA
Armin Sorooshian
Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA
Luke Ziemba
Science Directorate, NASA Langley Research Center, Hampton, VA, USA
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Cited
16 citations as recorded by crossref.
- Uncertainty in aerosol–cloud radiative forcing is driven by clean conditions E. Gryspeerdt et al. 10.5194/acp-23-4115-2023
- Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals A. Varble et al. 10.5194/acp-23-13523-2023
- Nonlinearity of the cloud response postpones climate penalty of mitigating air pollution in polluted regions H. Jia & J. Quaas 10.1038/s41558-023-01775-5
- Robust Susceptibility of Cloud Cover and Radiative Effects to Biases in Retrieved Droplet Concentrations Y. Wang et al. 10.1029/2023JD039145
- Observing short-timescale cloud development to constrain aerosol–cloud interactions E. Gryspeerdt et al. 10.5194/acp-22-11727-2022
- Emission Reductions Significantly Reduce the Hemispheric Contrast in Cloud Droplet Number Concentration in Recent Two Decades Y. Cao et al. 10.1029/2022JD037417
- Daytime variation in the aerosol indirect effect for warm marine boundary layer clouds in the eastern North Atlantic S. Qiu et al. 10.5194/acp-24-2913-2024
- Impact of Cloud Condensation Nuclei Reduction on Cloud Characteristics and Solar Radiation during COVID-19 Lockdown 2020 in Moscow J. Shuvalova et al. 10.3390/atmos13101710
- Global observations of aerosol indirect effects from marine liquid clouds C. Wall et al. 10.5194/acp-23-13125-2023
- Invisible ship tracks show large cloud sensitivity to aerosol P. Manshausen et al. 10.1038/s41586-022-05122-0
- Stratocumulus adjustments to aerosol perturbations disentangled with a causal approach E. Fons et al. 10.1038/s41612-023-00452-w
- Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing D. Rosenfeld et al. 10.1029/2022RG000799
- Assessing effective radiative forcing from aerosol–cloud interactions over the global ocean C. Wall et al. 10.1073/pnas.2210481119
- In situ and satellite-based estimates of cloud properties and aerosol–cloud interactions over the southeast Atlantic Ocean S. Gupta et al. 10.5194/acp-22-12923-2022
- The sensitivity of Southern Ocean atmospheric dimethyl sulfide (DMS) to modeled oceanic DMS concentrations and emissions Y. Bhatti et al. 10.5194/acp-23-15181-2023
- Addressing the difficulties in quantifying droplet number response to aerosol from satellite observations H. Jia et al. 10.5194/acp-22-7353-2022
15 citations as recorded by crossref.
- Uncertainty in aerosol–cloud radiative forcing is driven by clean conditions E. Gryspeerdt et al. 10.5194/acp-23-4115-2023
- Evaluation of liquid cloud albedo susceptibility in E3SM using coupled eastern North Atlantic surface and satellite retrievals A. Varble et al. 10.5194/acp-23-13523-2023
- Nonlinearity of the cloud response postpones climate penalty of mitigating air pollution in polluted regions H. Jia & J. Quaas 10.1038/s41558-023-01775-5
- Robust Susceptibility of Cloud Cover and Radiative Effects to Biases in Retrieved Droplet Concentrations Y. Wang et al. 10.1029/2023JD039145
- Observing short-timescale cloud development to constrain aerosol–cloud interactions E. Gryspeerdt et al. 10.5194/acp-22-11727-2022
- Emission Reductions Significantly Reduce the Hemispheric Contrast in Cloud Droplet Number Concentration in Recent Two Decades Y. Cao et al. 10.1029/2022JD037417
- Daytime variation in the aerosol indirect effect for warm marine boundary layer clouds in the eastern North Atlantic S. Qiu et al. 10.5194/acp-24-2913-2024
- Impact of Cloud Condensation Nuclei Reduction on Cloud Characteristics and Solar Radiation during COVID-19 Lockdown 2020 in Moscow J. Shuvalova et al. 10.3390/atmos13101710
- Global observations of aerosol indirect effects from marine liquid clouds C. Wall et al. 10.5194/acp-23-13125-2023
- Invisible ship tracks show large cloud sensitivity to aerosol P. Manshausen et al. 10.1038/s41586-022-05122-0
- Stratocumulus adjustments to aerosol perturbations disentangled with a causal approach E. Fons et al. 10.1038/s41612-023-00452-w
- Frontiers in Satellite‐Based Estimates of Cloud‐Mediated Aerosol Forcing D. Rosenfeld et al. 10.1029/2022RG000799
- Assessing effective radiative forcing from aerosol–cloud interactions over the global ocean C. Wall et al. 10.1073/pnas.2210481119
- In situ and satellite-based estimates of cloud properties and aerosol–cloud interactions over the southeast Atlantic Ocean S. Gupta et al. 10.5194/acp-22-12923-2022
- The sensitivity of Southern Ocean atmospheric dimethyl sulfide (DMS) to modeled oceanic DMS concentrations and emissions Y. Bhatti et al. 10.5194/acp-23-15181-2023
1 citations as recorded by crossref.
Latest update: 17 Apr 2024
Short summary
Droplet number concentration is a key property of clouds, influencing a variety of cloud processes. It is also used for estimating the cloud response to aerosols. The satellite retrieval depends on a number of assumptions – different sampling strategies are used to select cases where these assumptions are most likely to hold. Here we investigate the impact of these strategies on the agreement with in situ data, the droplet number climatology and estimates of the indirect radiative forcing.
Droplet number concentration is a key property of clouds, influencing a variety of cloud...
