Understanding the drivers of marine liquid-water cloud occurrence and properties with global observations using neural networks

Atmospheric Chemistry and Physics

Volumn 17, Issue 15, 2017, Pages 9535-9546

  Andersen, Hendrik ^a   Cermak, Jan ^a   Fuchs, Julia ^a   Knutti, Reto ^b   Lohmann, Ulrike ^b  

^a KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

^b ETH Zurich   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

AEROSOL; ARTIFICIAL NEURAL NETWORK; DROPLET; MARINE ATMOSPHERE; STRATOCUMULUS; TROPOSPHERE;

EID: 85027217508     PISSN: 16807316     EISSN: 16807324     Source Type: Journal    
DOI: 10.5194/acp-17-9535-2017     Document Type: Article

References (63)

1. Ackerman, A. S., Kirkpatrick, M. P., Stevens, D. E., and Toon, O. B.: The impact of humidity above stratiform clouds on indirect aerosol climate forcing, Nature, 432, 1014-1017, https://doi.org/10.1038/nature03174, 2004.
2. Albrecht, B. A.: Aerosols, cloud microphysics, and fractional cloudiness, Science, 245, 1227-1230, https://doi.org/10.1126/science.245.4923.1227, 1989.
3. Andersen, H. and Cermak, J.: How thermodynamic environments control stratocumulus microphysics and interactions with aerosols, Environ. Res. Lett., 10, 24004, https://doi.org/10.1088/1748-9326/10/2/024004, 2015.
4. Andersen, H., Cermak, J., Fuchs, J., and Schwarz, K.: Global observations of cloud-sensitive aerosol loadings in low-level marine clouds, J. Geophys. Res.-Atmos., 121, 12936-12946, https://doi.org/10.1002/2016JD025614, 2016.
5. Andreae, M. O.: Correlation between cloud condensation nuclei concentration and aerosol optical thickness in remote and polluted regions, Atmos. Chem. Phys., 9, 543-556, https://doi.org/10.5194/acp-9-543-2009, 2009.
6. Barahona, D., West, R. E. L., Stier, P., Romakkaniemi, S., Kokkola, H., and Nenes, A.: Comprehensively accounting for the effect of giant CCN in cloud activation parameterizations, Atmos. Chem. Phys., 10, 2467-2473, https://doi.org/10.5194/acp-10-2467-2010, 2010.
7. Bennartz, R. and Rausch, J.: Global and regional estimates of warm cloud droplet number concentration based on 13 years of AQUA-MODIS observations, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2016-1130, in review, 2017.
8. Boucher, O., Randall, D., Artaxo, P., Bretherton, C., Feingold, G., Forster, P., Kerminen, V.-M., Kondo, Y., Liao, H., Lohmann, U., Rasch, P., Satheesh, S. K., Sherwood, S., Stevens, B., and Zhang, X.-Y.: Clouds and Aerosols, in: Climate Change 2013: The Physical Science Basis, Contribution of Working Group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G. K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK, New York, NY, USA, 2013.
9. Brenguier, J.-L., Pawlowska, H., Schüller, L., Preusker, R., Fischer, J., and Fouquart, Y.: Radiative Properties of Boundary Layer Clouds: Droplet Effective Radius versus Number Concentration, J. Atmos. Sci., 57, 803-821, https://doi.org/10.1175/1520-0469(2000)057<0803:RPOBLC>2.0.CO;2, 2000.
10. Bréon, F.-M., Tanré, D., and Generoso, S.: Aerosol effect on cloud droplet size monitored from satellite, Science, 295, 834-838, https://doi.org/10.1126/science.1066434, 2002.
11. Cermak, J. and Knutti, R.: Beijing Olympics as an Aerosol Field Experiment, Geophys. Res. Lett., 36, L10806, https://doi.org/10.1029/2009GL038572, 2009.
12. Chen, Y.-C., Christensen, M.W., Xue, L., Sorooshian, A., Stephens, G. L., Rasmussen, R. M., and Seinfeld, J. H.: Occurrence of lower cloud albedo in ship tracks, Atmos. Chem. Phys., 12, 8223-8235, https://doi.org/10.5194/acp-12-8223-2012, 2012.
13. Chen, Y.-C., Christensen, M. W., Stephens, G. L., and Seinfeld, J. H.: Satellite-based estimate of global aerosol-cloud radiative forcing by marine warm clouds, Nat. Geosci., 7, 643-646, https://doi.org/10.1038/ngeo2214, 2014.
14. Costantino, L. and Bréon, F.-M.: Aerosol indirect effect on warm clouds over South-East Atlantic, from co-located MODIS and CALIPSO observations, Atmos. Chem. Phys., 13, 69-88, https://doi.org/10.5194/acp-13-69-2013, 2013.
15. Cybenko, G.: Approximation by superpositions of a sigmoidal function, Math. Control Signal., 2, 303-314, https://doi.org/10.1007/BF02551274, 1989.
16. Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, I., Biblot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Greer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Holm, E. V., Isaksen, L., Kallberg, P., Kohler, M., Matricardi, M., McNally, A. P., Mong-Sanz, B. M., Morcette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thepaut, J. N., and Vitart, F.: The ERAInterim reanalysis: Configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553-597, 2011.
17. Di Noia, A., Sellitto, P., Del Frate, F., and de Laat, J.: Global tropospheric ozone column retrievals from OMI data by means of neural networks, Atmos. Meas. Tech., 6, 895-915, https://doi.org/10.5194/amt-6-895-2013, 2013.
18. Engström, A. and Ekman, A. M. L.: Impact of meteorological factors on the correlation between aerosol optical depth and cloud fraction, Geophys. Res. Lett., 37, L18814, https://doi.org/10.1029/2010GL044361, 2010.
19. Funahashi, K.-I.: On the approximate realization of continuous mappings by neural networks, Neural Networks, 2, 183-192, https://doi.org/10.1016/0893-6080(89)90003-8, 1989.
20. Gardner, M. and Dorling, S.: Artificial neural networks (the multilayer perceptron) - a review of applications in the atmospheric sciences, Atmos. Environ., 32, 2627-2636, https://doi.org/10.1016/S1352-2310(97)00447-0, 1998.
21. Glassmeier, F. and Lohmann, U.: Constraining precipitation susceptibility of warm, ice- and mixed-phase clouds with microphysical equations, J. Atmos. Sci., 73, 5003-5023, https://doi.org/10.1175/JAS-D-16-0008.1, 2016.
22. Grandey, B. S., Stier, P., and Wagner, T. M.: Investigating relationships between aerosol optical depth and cloud fraction using satellite, aerosol reanalysis and general circulation model data, Atmos. Chem. Phys., 13, 3177-3184, https://doi.org/10.5194/acp-13-3177-2013, 2013.
23. Gryspeerdt, E. and Stier, P.: Regime-based analysis of aerosolcloud interactions, Geophys. Res. Lett., 39, L21802, https://doi.org/10.1029/2012GL053221, 2012.
24. Gryspeerdt, E., Quaas, J., and Bellouin, N.: Constraining the aerosol influence on cloud fraction, J. Geophys. Res-Atmos., 121, 3566-3583, https://doi.org/10.1002/2015JD023744, 2016.
25. Hartmann, D. L., Ockert-Bell, M. E., and Michelsen, M. L.: The Effect of Cloud Type on Earth's Energy Balance: Global Analysis, J. Climate, 5, 1281-1304, https://doi.org/10.1175/1520-0442(1992)005<1281:TEOCTO>2.0.CO;2, 1992.
26. Hartmann, H., Becker, S., King, L., and Jiang, T.: Forecasting water levels at the Yangtze River with neural networks, Erdkunde, 62, 231-243, https://doi.org/10.3112/erdkunde.2008.03.04, 2008.
27. Hartmann, H., Snow, J. A., Su, B., and Jiang, T.: Seasonal predictions of precipitation in the Aksu-Tarim River basin for improved water resources management, Global Planet. Change, 147, 86-96, https://doi.org/10.1016/j.gloplacha.2016.10.018, 2016.
28. Hornik, K., Stinchcombe, M., and White, H.: Multilayer feedforward networks are universal approximators, Neural Networks, 2, 359-366, https://doi.org/10.1016/0893-6080(89)90020-8, 1989.
29. Johnson, B., Shine, K., and Forster, P.: The semi-direct aerosol effect: Impact of absorbing aerosols on marine stratocumulus, Q. J. Roy. Meteor. Soc., 130, 1407-1422, https://doi.org/10.1256/qj.03.61, 2004.
30. Kaufman, Y. J., Koren, I., Remer, L., Rosenfeld, D., and Rudich, Y.: The effect of smoke, dust, and pollution aerosol on shallow cloud development over the Atlantic Ocean, P. Natl. Acad. Sci. USA, 102, 11207-11212, https://doi.org/10.1073/pnas.0505191102, 2005.
31. Kecman, V. V. and Vojislav: Learning and soft computing: support vector machines, neural networks, and fuzzy logic models, MIT Press, http://dl.acm.org/citation.cfm?id=559026, 2001.
32. Klein, S. A. and Hartmann, D. L.: The Seasonal Cycle of Low Stratiform Clouds, J. Climate, 6, 1587-1606, https://doi.org/10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2, 1993.
33. Koren, I., Feingold, G., and Remer, L. A.: The invigoration of deep convective clouds over the Atlantic: aerosol effect, meteorology or retrieval artifact?, Atmos. Chem. Phys., 10, 8855-8872, https://doi.org/10.5194/acp-10-8855-2010, 2010.
34. Koren, I., Altaratz, O., Remer, L. A., Feingold, G., Martins, J. V., and Heiblum, R. H.: Aerosol-induced intensification of rain from the tropics to the mid-latitudes, Nat. Geosci., 5, 118-122, https://doi.org/10.1038/ngeo1364, 2012.
35. Koren, I., Dagan, G., and Altaratz, O.: From aerosol-limited to invigoration of warm convective clouds, Science, 344, 1143-1146, https://doi.org/10.1126/science.1252595, 2014.
36. Latham, J., Rasch, P., Chen, C.-C., Kettles, L., Gadian, A., Gettelman, A., Morrison, H., Bower, K., and Choularton, T.: Global temperature stabilization via controlled albedo enhancement of low-level maritime clouds, Philos. T. R. Soc. A, 366, 3969-3987, https://doi.org/10.1098/rsta.2008.0137, 2008.
37. Le, J., El-Askary, H., Allali, M., and Struppa, D.: Application of recurrent neural networks for drought projections in California, Atmos. Res., 188, 100-106, https://doi.org/10.1016/j.atmosres.2017.01.002, 2017.
38. Levin, Z., Teller, A., Ganor, E., and Yin, Y.: On the interactions of mineral dust, sea-salt particles, and clouds: A measurement and modeling study from the Mediterranean Israeli Dust Experiment campaign, J. Geophys. Res.-Atmos., 110, D20202, https://doi.org/10.1029/2005JD005810, 2005.
39. Levy, R. C., Mattoo, S., Munchak, L. A., Remer, L. A., Sayer, A. M., Patadia, F., and Hsu, N. C.: The Collection 6 MODIS aerosol products over land and ocean, Atmos. Meas. Tech., 6, 2989-3034, https://doi.org/10.5194/amt-6-2989-2013, 2013.
40. Loeb, N. G. and Schuster, G. L.: An observational study of the relationship between cloud, aerosol and meteorology in broken lowlevel cloud conditions, J. Geophys. Res.-Atmos., 113, D14214, https://doi.org/10.1029/2007JD009763, 2008.
41. Matsui, T., Masunaga, H., and Pielke Sr., R. A.: Impact of aerosols and atmospheric thermodynamics on cloud properties within the climate system, Geophys. Res. Lett., 31, L06109, https://doi.org/10.1029/2003GL019287, 2004.
42. Matsui, T., Masunaga, H., Kreidenweis, S. M., Pielke, R. A., Tao, W.-K., Chin, M., and Kaufman, Y. J.: Satellite-based assessment of marine low cloud variability associated with aerosol, atmospheric stability, and the diurnal cycle, J. Geophys. Res.-Atmos., 111, D17204, https://doi.org/10.1029/2005JD006097, 2006.
43. McComiskey, A. and Feingold, G.: The scale problem in quantifying aerosol indirect effects, Atmos. Chem. Phys., 12, 1031-1049, https://doi.org/10.5194/acp-12-1031-2012, 2012.
44. McComiskey, A., Feingold, G., Frisch, A. S., Turner, D. D., Miller, M. A., Chiu, J. C., Min, Q., and Ogren, J. A.: An assessment of aerosol-cloud interactions in marine stratus clouds based on surface remote sensing, J. Geophys. Res.-Atmospheres, 114, D09203, https://doi.org/10.1029/2008JD011006, 2009.
45. Nakajima, T., Higurashi, A., Kawamoto, K., and Penner, J. E.: A possible correlation between satellite-derived cloud and aerosol microphysical parameters, Geophys. Res. Lett., 28, 1171-1174, https://doi.org/10.1029/2000GL012186, 2001.
46. Norris, J. R. and Leovy, C. B.: Interannual Variability in Stratiform Cloudiness and Sea Surface Temperature, J. Climate, 7, 1915-1925, https://doi.org/10.1175/1520-0442(1994)007<1915:IVISCA>2.0.CO;2, 1994.
47. Olden, J. D. and Jackson, D. A.: Illuminating the "black box": A randomization approach for understanding variable contributions in artificial neural networks, Ecol. Model., 154, 135-150, https://doi.org/10.1016/S0304-3800(02)00064-9, 2002.
48. Oreopoulos, L., Cho, N., Lee, D., and Kato, S.: Radiative effects of global MODIS cloud regimes, J. Geophys. Res.-Atmos., 121, 2299-2317, https://doi.org/10.1002/2015JD024502, 2016.
49. Painemal, D., Kato, S., and Minnis, P.: Boundary layer regulation in the southeast Atlantic cloud microphysics during the biomass burning season as seen by the A-train satellite constellation, J. Geophys. Res.-Atmos., 119, 11288-11302, https://doi.org/10.1002/2014JD022182, 2014.
50. Peters, K., Stier, P., Quaas, J., and Graßl, H.: Aerosol indirect effects from shipping emissions: sensitivity studies with the global aerosol-climate model ECHAM-HAM, Atmos. Chem. Phys., 12, 5985-6007, https://doi.org/10.5194/acp-12-5985-2012, 2012.
51. Pincus, R. and Baker, M. B.: Effect of precipitation on the albedo susceptibility of clouds in the marine boundary layer, Nature, 372, 250-252, https://doi.org/10.1038/372250a0, 1994.
52. Prospero, J. M.: Long-range transport of mineral dust in the global atmosphere: impact of African dust on the environment of the southeastern United States, P. Natl. Acad. Sci. USA, 96, 3396-3403, https://doi.org/10.1073/PNAS.96.7.3396, 1999.
53. Quaas, J., Boucher, O., Bellouin, N., and Kinne, S.: Satellite-based estimate of the direct and indirect aerosol climate forcing, J. Geophys. Res., 113, D05204, https://doi.org/10.1029/2007JD008962, 2008.
54. Quaas, J., Ming, Y., Menon, S., Takemura, T., Wang, M., Penner, J. E., Gettelman, A., Lohmann, U., Bellouin, N., Boucher, O., Sayer, A. M., Thomas, G. E., McComiskey, A., Feingold, G., Hoose, C., Kristjánsson, J. E., Liu, X., Balkanski, Y., Donner, L. J., Ginoux, P. A., Stier, P., Grandey, B., Feichter, J., Sednev, I., Bauer, S. E., Koch, D., Grainger, R. G., Kirkevåg, A., Iversen, T., Seland, Ø., Easter, R., Ghan, S. J., Rasch, P. J., Morrison, H., Lamarque, J.-F., Iacono, M. J., Kinne, S., and Schulz, M.: Aerosol indirect effects - general circulation model intercomparison and evaluation with satellite data, Atmos. Chem. Phys., 9, 8697-8717, https://doi.org/10.5194/acp-9-8697-2009, 2009.
55. Quaas, J., Stevens, B., Stier, P., and Lohmann, U.: Interpreting the cloud cover - aerosol optical depth relationship found in satellite data using a general circulation model, Atmos. Chem. Phys., 10, 6129-6135, https://doi.org/10.5194/acp-10-6129-2010, 2010.
56. Russell, L. M., Sorooshian, A., Seinfeld, J. H., Albrecht, B. A., Nenes, A., Ahlm, L., Chen, Y.-C., Coggon, M., Craven, J. S., Flagan, R. C., Frossard, A. A., Jonsson, H., Jung, E., Lin, J. J., Metcalf, A. R., Modini, R., Mülmenstädt, J., Roberts, G., Shingler, T., Song, S., Wang, Z., and Wonaschütz, A.: Eastern Pacific Emitted Aerosol Cloud Experiment, B. Am. Meteorol. Soc., 94, 709-729, https://doi.org/10.1175/BAMS-D-12-00015.1, 2013.
57. Shinozuka, Y., Clarke, A. D., Nenes, A., Jefferson, A., Wood, R., McNaughton, C. S., Ström, J., Tunved, P., Redemann, J., Thornhill, K. L., Moore, R. H., Lathem, T. L., Lin, J. J., and Yoon, Y. J.: The relationship between cloud condensation nuclei (CCN) concentration and light extinction of dried particles: indications of underlying aerosol processes and implications for satellitebased CCN estimates, Atmos. Chem. Phys., 15, 7585-7604, https://doi.org/10.5194/acp-15-7585-2015, 2015.
58. Stevens, B. and Feingold, G.: Untangling aerosol effects on clouds and precipitation in a buffered system, Nature, 461, 607-613, https://doi.org/10.1038/nature08281, 2009.
59. Stier, P.: Limitations of passive remote sensing to constrain global cloud condensation nuclei, Atmos. Chem. Phys., 16, 6595-6607, https://doi.org/10.5194/acp-16-6595-2016, 2016.
60. Su, W., Loeb, N. G., Xu, K.-M., Schuster, G. L., and Eitzen, Z. A.: An estimate of aerosol indirect effect from satellite measurements with concurrent meteorological analysis, Journal of Geophysical Research: Atmospheres, 115, D18219, https://doi.org/10.1029/2010JD013948, 2010.
61. Twomey, S.: The Influence of Pollution on the Shortwave Albedo of Clouds, J. Atmos. Sci., 34, 1149-1152, https://doi.org/10.1175/1520-0469(1977)034<1149:TIOPOT>2.0.CO;2, 1977.
62. Werbos, P.: Backpropagation through time: what it does and how to do it, P. IEEE, 78, 1550-1560, https://doi.org/10.1109/5.58337, 1990.
63. Wood, R.: Stratocumulus Clouds, Mon. Weather Rev., 140, 2373-2423, https://doi.org/10.1175/MWR-D-11-00121.1, 2012.