Invisible ship tracks show large cloud sensitivity to aerosol.
Journal
Nature
ISSN: 1476-4687
Titre abrégé: Nature
Pays: England
ID NLM: 0410462
Informations de publication
Date de publication:
10 2022
10 2022
Historique:
received:
15
02
2022
accepted:
19
07
2022
entrez:
5
10
2022
pubmed:
6
10
2022
medline:
6
10
2022
Statut:
ppublish
Résumé
Cloud reflectivity is sensitive to atmospheric aerosol concentrations because aerosols provide the condensation nuclei on which water condenses
Identifiants
pubmed: 36198778
doi: 10.1038/s41586-022-05122-0
pii: 10.1038/s41586-022-05122-0
pmc: PMC9534750
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
101-106Informations de copyright
© 2022. The Author(s).
Références
Twomey, S. The Influence of pollution on the shortwave albedo of clouds. J. Atmos. Sci. 34, 1149–1152 (1977).
Albrecht, B. Fractional cloudiness. Science 245, 1227–1230 (1989).
pubmed: 17747885
doi: 10.1126/science.245.4923.1227
IPCC Climate Change 2021: The Physical Science Basis (eds Masson-Delmotte, V. et al.) (Cambridge Univ. Press, 2021).
Christensen, M. et al. Opportunistic experiments to constrain aerosol effective radiative forcing. Atmos. Chem. Phys. 22, 641–674 (2022).
Schreier, M. Mannstein, H. Eyring, V. & Bovensmann, H. Global ship track distribution and radiative forcing from 1 year of AATSR data. Geophys. Res. Lett. https://doi.org/10.1029/2007GL030664 (2007)
Durkee, P. A., Noone, K. J. & Bluth, R. T. The Monterey Area Ship Track experiment. J. Atmos. Sci. 57, 2523–2541 (2000).
doi: 10.1175/1520-0469(2000)057<2523:TMASTE>2.0.CO;2
Watson-Parris, D. et al. Constraining uncertainty in aerosol direct forcing. Geophys. Res. Lett. 47, 1–7 (2020).
doi: 10.1029/2020GL087141
Bellouin, N. et al. Bounding global aerosol radiative forcing of climate change. Rev. Geophys. 58, 1–45 (2020).
doi: 10.1029/2019RG000660
Bretherton, C. S., Blossey, P. N. & Uchida, J. Cloud droplet sedimentation, entrainment efficiency, and subtropical stratocumulus albedo. Geophys. Res. Lett. 34, 1–5 (2007).
doi: 10.1029/2006GL027648
Hill, A. A., Feingold, G. & Jiang, H. The influence of entrainment and mixing assumption on aerosol–cloud interactions in marine stratocumulus. J. Atmos. Sci. 66, 1450–1464 (2009).
doi: 10.1175/2008JAS2909.1
Malavelle, F. F. et al. Strong constraints on aerosol–cloud interactions from volcanic eruptions. Nature 546, 485–491 (2017).
pubmed: 28640263
doi: 10.1038/nature22974
Toll, V., Christensen, M., Quaas, J. & Bellouin, N. Weak average liquid-cloudwater response to anthropogenic aerosols. Nature 572, 51–55 (2019).
pubmed: 31367029
doi: 10.1038/s41586-019-1423-9
Terai, C. R., Pritchard, M. S., Blossey, P. & Bretherton, C. S. The impact of resolving subkilometer processes on aerosol–cloud interactions of low-level clouds in global model simulations. J. Adv. Model. Earth Syst. 12, e2020MS002274 (2020).
doi: 10.1029/2020MS002274
Conover, J. H. Anomalous cloud lines. J. Atmos. Sci. 23, 778–785 (1966).
doi: 10.1175/1520-0469(1966)023<0778:ACL>2.0.CO;2
Christensen, M. W. & Stephens, G. L. Microphysical and macrophysical responses of marine stratocumulus polluted by underlying ships: evidence of cloud deepening. J. Geophys. Res. Atmos. 116, D03201 (2011).
doi: 10.1029/2010JD014638
Gryspeerdt, E., Smith, T. W., O’Keeffe, E., Christensen, M. W. & Goldsworth, F. W. The impact of ship emission controls recorded by cloud properties. Geophys. Res. Lett. 46, 12547–12555 (2019).
doi: 10.1029/2019GL084700
Coakley, J. A. & Walsh, C. D. Limits to the aerosol indirect radiative effect derived from observations of ship tracks. J. Atmos. Sci. 59, 668–680 (2002).
doi: 10.1175/1520-0469(2002)059<0668:LTTAIR>2.0.CO;2
Chen, Y. C. et al. Occurrence of lower cloud albedo in ship tracks. Atmos. Chem. Phys. 12, 8223–8235 (2012).
doi: 10.5194/acp-12-8223-2012
Glassmeier, F. et al. Aerosol-cloud-climate cooling overestimated by ship-track data. Science 371, 485–489 (2021).
pubmed: 33510021
doi: 10.1126/science.abd3980
Possner, A., Wang, H., Wood, R., Caldeira, K. & Ackerman, T. P. The efficacy of aerosol-cloud radiative perturbations from near-surface emissions in deep open-cell stratocumuli. Atmos. Chem. Phys. 18, 17475–17488 (2018).
doi: 10.5194/acp-18-17475-2018
Diamond, M. S., Director, H. M., Eastman, R., Possner, A. & Wood, R. Substantial cloud brightening from shipping in subtropical low clouds. AGU Adv. 1, e2019AV000111 (2020).
doi: 10.1029/2019AV000111
Gryspeerdt, E., Goren, T. & Smith, T. W. Observing the timescales of aerosol–cloud interactions in snapshot satellite images. Atm. Chem. Phys. 21, 6093–6109 (2021).
Segrin, M. S., Coakley, J. A. & Tahnk, W. R. MODIS observations of ship tracks in summertime stratus off the West Coast of the United States. J. Atmos. Sci. 64, 4330–4345 (2007).
doi: 10.1175/2007JAS2308.1
Stein, A. F. et al. Noaa’s hysplit atmospheric transport and dispersion modeling system. Bull. Am. Meteorol. Soc. 96, 2059–2077 (2015).
doi: 10.1175/BAMS-D-14-00110.1
Durkee, P. A. et al. Composite ship track characteristics. J. Atmos. Sci. 57, 2542–2553 (2000).
doi: 10.1175/1520-0469(2000)057<2542:CSTC>2.0.CO;2
Peters, K., Quaas, J. & Graßl, H. A search for large-scale effects of ship emissions on clouds and radiation in satellite data. J. Geophys. Res. Atmos. 116, D24205 (2011).
doi: 10.1029/2011JD016531
Peters, K., Quaas, J., Stier, P. & Graßl, H. Processes limiting the emergence of detectable aerosol indirect effects on tropical warm clouds in global aerosol-climate model and satellite data. Tellus B: Chem. Phys. Meteorol. 66, 24054 (2014).
doi: 10.3402/tellusb.v66.24054
Gryspeerdt, E. et al. Constraining the aerosol influence on cloud liquid water path. Atmos. Chem. Phys. 19, 5331–5347 (2019).
doi: 10.5194/acp-19-5331-2019
Albrecht, B. A. et al. Surface-based remote sensing of the observed and the Adiabatic liquid water content of stratocumulus clouds. Geophys. Res. Lett. 17, 89–92 (1990).
doi: 10.1029/GL017i001p00089
Painemal, D. & Zuidema, P. Assessment of MODIS cloud effective radius and optical thickness retrievals over the Southeast Pacific with VOCALS-REx in situ measurements. J. Geophys. Res. Atmos. 116, D24206 (2011).
doi: 10.1029/2011JD016155
Toll, V., Christensen, M., Gassó, S. & Bellouin, N. Volcano and ship tracks indicate excessive aerosol-induced cloud water increases in a climate model. Geophys. Res. Lett. 44, 12492–12500 (2017).
pubmed: 29713108
pmcid: 5921053
doi: 10.1002/2017GL075280
Possner, A., Eastman, R., Bender, F. & Glassmeier, F. Deconvolution of boundary layer depth and aerosol constraints on cloud water path in subtropical stratocumulus decks. Atmos. Chem. Phys. 20, 3609–3621 (2020).
doi: 10.5194/acp-20-3609-2020
Dagan, G., Koren, I. & Altaratz, O. Competition between core and periphery based processes in warm convective clouds – from invigoration to suppression. Atmos. Chem. Phys. 15, 2749–2760 (2015).
doi: 10.5194/acp-15-2749-2015
Seifert, A., Heus, T., Pincus, R. & Stevens, B. Large-eddy simulation of the transient and near-equilibrium behavior of precipitating shallow convection. J. Adv. Model. Earth Syst. 7, 1918–1937 (2015).
doi: 10.1002/2015MS000489
Spill, G., Stier, P., Field, P. R. & Dagan, G. Effects of aerosol in simulations of realistic shallow cumulus cloud fields in a large domain. Atmos. Chem. Phys. 19, 13507–13517 (2019).
doi: 10.5194/acp-19-13507-2019
Yamaguchi, T., Feingold, G. & Kazil, J. Aerosol–cloud interactions in trade wind cumulus clouds and the role of vertical wind shear. J. Geophys. Res. Atmos. 124, 12244–12261 (2019).
doi: 10.1029/2019JD031073
Marinescu, P. J. et al. Impacts of varying concentrations of cloud condensation nuclei on deep convective cloud updrafts – a multimodel assessment. J. Atmos. Sci. 78, 1147–1172 (2021).
doi: 10.1175/JAS-D-20-0200.1
Seidel, D. J., Feingold, G., Jacobson, A. R. & Loeb, N. Detection limits of albedo changes induced by climate engineering. Nat. Clim. Change 4, 93–98 (2014).
doi: 10.1038/nclimate2076
Wang, H., Rasch, P. J. & Feingold, G. Manipulating marine stratocumulus cloud amount and albedo: a process-modelling study of aerosol-cloud-precipitation interactions in response to injection of cloud condensation nuclei. Atmos. Chem. Phys. 11, 4237–4249 (2011).
doi: 10.5194/acp-11-4237-2011
Seethala, C. & Horváth, A. Global assessment of AMSR-E and MODIS cloud liquid water path retrievals in warm oceanic clouds. J. Geophys. Res. Atmos. 115, D13202 (2010).
doi: 10.1029/2009JD012662
Platnick, S. et al. The MODIS cloud products: algorithms and examples from terra. IEEE Trans. Geosci. Remote Sens. 41, 459–472 (2003).
doi: 10.1109/TGRS.2002.808301
Cartopy: A cartographic python library with a matplotlib interface (Met Office, 2022); http://scitools.org.uk/cartopy
Jalkanen, J. P. et al. Extension of an assessment model of ship traffic exhaust emissions for particulate matter and carbon monoxide. Atmos. Chem. Phys. 12, 2641–2659 (2012).
doi: 10.5194/acp-12-2641-2012
Hersbach, H. et al. The ERA5 global reanalysis. Q. J. R. Meteorolog. Soc. 146, 1999–2049 (2020).
doi: 10.1002/qj.3803
Quaas, J., Boucher, O. & Lohmann, U. Constraining the total aerosol indirect effect in the LMDZ and ECHAM4 GCMs using MODIS satellite data. Atmos. Chem. Phys. 6, 947–955 (2006).
doi: 10.5194/acp-6-947-2006
Grosvenor, D. P. et al. Remote sensing of droplet number concentration in warm clouds: a review of the current state of knowledge and perspectives. Rev. Geophys. 56, 409–453 (2018).
pubmed: 30148283
pmcid: 6099364
doi: 10.1029/2017RG000593
Allan, D. et al. soft-matter/trackpy: Trackpy v.0.4.2. GitHub http://soft-matter.github.io/trackpy/v0.5.0/ (2019).
Gryspeerdt, E. et al. The impact of sampling strategy on the cloud droplet number concentration estimated from satellite data. Atmos. Meas. Tech. 15, 3875–3892 (2022).
Bellouin, N., Quaas, J., Morcrette, J. J. & Boucher, O. Estimates of aerosol radiative forcing from the MACC re-analysis. Atmos. Chem. Phys. 13, 2045–2062 (2013).
doi: 10.5194/acp-13-2045-2013
Kinne, S. Aerosol radiative effects with MACv2. Atmos. Chem. Phys. 19, 10919–10959 (2019).
doi: 10.5194/acp-19-10919-2019