Articles | Volume 19, issue 2
https://doi.org/10.5194/acp-19-1147-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-1147-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Cloud feedbacks in extratropical cyclones: insight from long-term satellite data and high-resolution global simulations
Institute of Climate and Atmospheric Sciences, University of Leeds, Leeds, UK
Paul R. Field
Institute of Climate and Atmospheric Sciences, University of Leeds, Leeds, UK
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Gregory S. Elsaesser
Department of Applied Physics and Applied Mathematics, Columbia
University and NASA Goddard Institute for Space Studies, New York, NY, USA
Alejandro Bodas-Salcedo
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Brian H. Kahn
Jet Propulsion Laboratory, California Institute of Technology,
Pasadena, CA, USA
Mark D. Zelinka
Cloud Processes Research and Modeling Group, Lawrence Livermore
National Laboratory, Livermore, CA, USA
Chihiro Kodama
Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan
Thorsten Mauritsen
Max Planck Institute for Meteorology, Hamburg, Germany
Department of Meteorology, Stockholm University, Stockholm, 106 91, Sweden
Benoit Vanniere
National Centre for Atmospheric Science-Climate, Department of
Meteorology, University of Reading, Reading, UK
Malcolm Roberts
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Pier L. Vidale
National Centre for Atmospheric Science-Climate, Department of
Meteorology, University of Reading, Reading, UK
David Saint-Martin
Centre National de Recherches Météorologiques (CNRM),
Météo-France/CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse, France
Aurore Voldoire
Centre National de Recherches Météorologiques (CNRM),
Météo-France/CNRS, 42 Avenue Gaspard Coriolis, 31057 Toulouse, France
Rein Haarsma
Royal Netherlands Meteorological Institute, De Bilt, the Netherlands
Adrian Hill
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Ben Shipway
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
Jonathan Wilkinson
Met Office, Fitzroy Rd, Exeter, EX1 3PB, UK
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11 citations as recorded by crossref.
- Untangling causality in midlatitude aerosol–cloud adjustments D. McCoy et al. 10.5194/acp-20-4085-2020
- Single field-of-view sounder atmospheric product retrieval algorithm: establishing radiometric consistency for hyper-spectral sounder retrievals W. Wu et al. 10.5194/amt-16-4807-2023
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- Hypohydrostatic Simulation of a Quasi-Steady Baroclinic Cyclone T. Hsieh et al. 10.1175/JAS-D-19-0300.1
- Southern Ocean Cloud Properties Derived From CAPRICORN and MARCUS Data G. Mace et al. 10.1029/2020JD033368
- The Role of Thermodynamic Phase Shifts in Cloud Optical Depth Variations With Temperature I. Tan et al. 10.1029/2018GL081590
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- Understanding the Extratropical Liquid Water Path Feedback in Mixed-Phase Clouds with an Idealized Global Climate Model M. Frazer & Y. Ming 10.1175/JCLI-D-21-0334.1
- Detailing cloud property feedbacks with a regime-based decomposition M. Zelinka et al. 10.1007/s00382-022-06488-7
1 citations as recorded by crossref.
Discussed (final revised paper)
Latest update: 20 Nov 2024
Short summary
The largest single source of uncertainty in the climate sensitivity predicted by global climate models is how much low-altitude clouds change as the climate warms. Models predict that the amount of liquid within and the brightness of low-altitude clouds increase in the extratropics with warming. We show that increased fluxes of moisture into extratropical storms in the midlatitudes explain the majority of the observed trend and the modeled increase in liquid water within these storms.
The largest single source of uncertainty in the climate sensitivity predicted by global climate...
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Final-revised paper
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