Climate Dynamics

, Volume 38, Issue 9–10, pp 2037–2053 | Cite as

Changes in extratropical storm track cloudiness 1983–2008: observational support for a poleward shift

  • Frida A-M. BenderEmail author
  • V. Ramanathan
  • George Tselioudis


Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.


Storm Track Cloud Fraction CMIP3 Model International Satellite Cloud Climatology Project Meridional Temperature Gradient 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work was funded by the National Science Foundation, through the Atmospheric Science Division, ATM0721142. We acknowledge the modeling groups, the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and the WCRP’s Working Group on Coupled Modelling (WGCM) for their roles in making available the WCRP CMIP3 multi-model dataset. Support of this dataset is provided by the Office of Science, U.S. Department of Energy. CRU data are obtained from, ERA data from the ECMWF Data Server, ERBE and CERES data from the Atmospheric Science Data Center at NASA Langley Research Center, ISCCP data from


  1. Barkstrom BR (1984) The earth radiation budget experiment (ERBE). Bull Amer Meteor Soc 65:1170–1185CrossRefGoogle Scholar
  2. Barkstrom BR, Smith GL (1986) The earth radiation budget experiment: science and implementation. Rev Geophys 24:379–390CrossRefGoogle Scholar
  3. Bengtsson L, Hodges KI, Roeckner E (2006) Storm tracks and climate change. J Clim 19:3518–3543CrossRefGoogle Scholar
  4. Bond TC, Bhardwaj E, Dong R, Jogani R, Jung S, Roden C, Streets DG, Fernandes S, Trautmann N (2007) Historical emissions of black and organic carbon aerosol from energy-related combustion, 1850–2000. Global Biogeochem Cycles 21:GB2018CrossRefGoogle Scholar
  5. Brest CL, Rossow WB, Roiter M (1997) Update of radiance calibrations for ISCCP. J Atmos Ocean Tech 14:1091–1109CrossRefGoogle Scholar
  6. Brohan P, Kennedy JJ, Harris I, Tett SFB, Jones PD (2006) Uncertainty estimates in regional and global observed temperature changes: a new dataset from 1850. J Geophys Res 111:D12106CrossRefGoogle Scholar
  7. Chang EKM, Lee S, Swanson KL (2002) Storm track dynamics. J Clim 15:2163–2183CrossRefGoogle Scholar
  8. Clement AC, Burgman R, Norris JR (2009) Observational and model evidence for positive low-level cloud feedback. Science 325:460CrossRefGoogle Scholar
  9. Evan AT, Heidinger AK, Vimont DJ (2007) Arguments against a physical long-term trend in global ISCCP cloud amounts. Geophys Res Lett 34:L04701CrossRefGoogle Scholar
  10. Field PR, Wood R (2007) Precipitation and cloud structure in midlatitude cyclones. J Clim 20:233–254CrossRefGoogle Scholar
  11. Field PR, Gettleman A, Neale RB, Wood R, Rasch PJ, Morrison H (2008) Midlatitude cyclone compositing to constrain climate model behavior using satellite obserations. J Clim 21:5887–5903CrossRefGoogle Scholar
  12. Fischer-Bruns I, von Storch H, Gonzalez-Rouco JF, Zorita E (2005) Modelling the variability of midlatitude storm activity on decadal to century time scales. Clim Dyn 25:461–476CrossRefGoogle Scholar
  13. Fyfe J (2003) Extratropical southern hemisphere cyclones: harbingers of climate change?. J Clim 16:2802–2805CrossRefGoogle Scholar
  14. Geng Q, Sugi M (2003) Possible change of extratropical cyclone activity due to enhanced greenhouse gases and sulfate aerosols—study with a high-resolution AGCM. J Clim 16:2262–2274CrossRefGoogle Scholar
  15. Hall NMJ, Hoskins BJ, Valdes PJ, Senior CA (1994) Storm tracks in a high-resolution GCM with doubled carbon dioxide. Q J Royal Meteorol Soc 120:1209–1230CrossRefGoogle Scholar
  16. Hu Y, Fu Q (2007) Observed poleward expansion of the Hadley circulation since 1979. Atmos Chem Phys 7:5229–5236CrossRefGoogle Scholar
  17. Hurrell JW, Deser C (2010) North Atlantic climate variability: the role of the North Atlantic Oscillation. J Mar Syst 79:253–271Google Scholar
  18. IPCC (2007) Climate change 2007: the scientific basis. Contribution of working group 1 to the fourth assessment report of the intergovernmental panel on climate change. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Cambridge University Press, Cambridge. p 996Google Scholar
  19. Johanson CM, Fu Q (2009) Hadley cell widening: model simulations versus observations. J. Clim 22:2713–2725CrossRefGoogle Scholar
  20. King MD, Kaufman YJ, Menzel WP, Tanre D (1992) Remote sensing if cloud, aerosol, and water vapour properties from the moderate resolution imaging spectrometer (MODIS). IEEE Trans Geosci Remote Sens 30:2–27CrossRefGoogle Scholar
  21. Knapp KR (2007) Calibration assessment of ISCCP geostationary infrared observations using HIRS. J Atmos Oceanic Technol 25:183–195CrossRefGoogle Scholar
  22. Loeb NG, Wielicki BA, Rose FG, Doelling DR (2007) Variability in global top-of-atmosphere shortwave radiation between 2000 and 2005. Geophys Res Lett 34:L03704CrossRefGoogle Scholar
  23. Lu J, Vecchi GA, Reichler T (2007) Expansion of the Hadley cell under global warming. Geophys Res Lett 34:L06805CrossRefGoogle Scholar
  24. Massie ST, Torres O, Smith SJ (2004) Total ozone mapping spectrometer (TOMS) observations of increases in Asian aerosol in winter from 1979 to 2000. J Geophys Res 109:D18211CrossRefGoogle Scholar
  25. McCabe G, Martyn CP, Serreze MC (2001) Trends in northern hemisphere surface cyclone frequency and intensity. J Clim 14:2763–2768CrossRefGoogle Scholar
  26. Meehl GA, Covey C, Delworth T, Latif M, McAveny B, Mitchell JFB, Stouffer RJ, Taylor KE (2007) The WCRP CMIP3 multimodel dataset: a new era in climate change research. Bull Amer Meteor Soc 88:1383–1394CrossRefGoogle Scholar
  27. Minnis P (1989) Viewing zenith angle dependence of cloudiness determined from coincident GOES east and GOES west data. J Geophys Res 94(D2):2303–2320CrossRefGoogle Scholar
  28. Norris JR (2000) What can cloud observations tell us about climate variability?. Space Sci Rev 94:375–380CrossRefGoogle Scholar
  29. Norris JR (2005) Multidecadal changes in near-global cloud cover and estimated cloud cover radiative forcing. J Geophys Res 110:D08206CrossRefGoogle Scholar
  30. O’Gorman PA (2010) Understanding the varied response of the extratropical storm tracks to climate change. Proc Natl Acad Sci USA 107(45):19176–19180CrossRefGoogle Scholar
  31. Ohara T, Akimoto H, Kurokawa J, Horii N, Yamaji K, Yan X, Hayasaka T (2007) An Asian emission inventory of anthropogenic emission sources for the period 19802020. Atmos Chem Phys 7:4419–4444CrossRefGoogle Scholar
  32. Ramanathan V, Cess RD, Harrison EF, Minnis P, Barkstrom BR, Ahmad E, Hartmann D (1989) Cloud-radiative forcing and climate: results from the earth radiation budget experiment. Science 243:57–63CrossRefGoogle Scholar
  33. Rossow WB, Schiffer RA (1991) ISCCP cloud data products. Bull Amer Meteor Soc 72:2–20CrossRefGoogle Scholar
  34. Rossow WB, Schiffer RA (1999) Advances in understanding clouds from ISCCP. Bull Amer Meteor Soc 80:2261–2287CrossRefGoogle Scholar
  35. Smith SJ, Pitcher H, Wigley TML (2001) Global and regional anthropogenic sulfur dioxide emissions. Global Planet Change 29:99–119CrossRefGoogle Scholar
  36. Streets DG, Yu C, Wu Y, Chin M, Zhao Z, Hayasaka T, Shi G (2008) Aerosol trends over China 1980–2000. Atmos Res 88:174–182CrossRefGoogle Scholar
  37. Tselioudis G, Tromeur E, Rosow WB, Zerefos CS (2010) Decadal changes in tropical convection suggest effects on stratospheric water vapour. Geophys Res Lett 37:L14806CrossRefGoogle Scholar
  38. Tsushima Y, Emori S, Ogura T, Kimoto M, Webb MJ, Williams KD, Ringer MA, Soden BJ, Li B, Andronova N (2006) Importance of the mixed-phase cloud distribution in the control climate for assessing the response of clouds to carbon dioxide increase: a multi-model study. Clim Dyn 27:113–126CrossRefGoogle Scholar
  39. Uppala SM et al (2005) The ERA-40 re-analysis. Q J Roy Meteor Soc 131:2961–3012CrossRefGoogle Scholar
  40. Wang XL, Swail VR, Zwiers FW (2006) Climatology and changes of extratropical cyclone activity: comparison of ERA-40 with NCEP-NCAR reanalysis for 1958–2001. J Clim 19:3145–3166CrossRefGoogle Scholar
  41. Weaver CP, Ramanathan V (1997) Relationships between large-scale vertical velocity, static stability, and cloud radiative forcing over northern hemisphere extratropical oceans. J Clim 10:2871–2887CrossRefGoogle Scholar
  42. Wielicki BA, Barkstrom BR, Harrison EF, Lee RB III, Smith GL, Cooper JE (1996) Clouds and the earth’s radiant energy system (CERES): an earth observing system experiment. Bull Amer Meteor Soc 77:853–868CrossRefGoogle Scholar
  43. Yin J (2005) A consistent poleward shift of the storm tracks in simulations of the 21st century climate. Geophys Res Lett 32:L18701CrossRefGoogle Scholar
  44. Zhang Y-C, Rossow WB, Lacis AA, Oinas V, Mishchenko MI (2004) Calculation of radiative fluxes from the surface to top of atmosphere based on ISCCP and other global data sets: Refinements of the radiative transfer model and the input data. J Geophys Res 109:D19105CrossRefGoogle Scholar
  45. Zhang R, Li G, Fan J, Wu DL, Molina MJ (2007) Intensification of Pacific storm track linked to Asian pollution. Proc Natl Acad Sci USA 104(13):5295–5299CrossRefGoogle Scholar
  46. Zhu A, Ramanathan V, Li F, Kim D (2007) Dust plumes over the Pacific, Indian, and Atlantic oceans: climatology and radiative impact. J Geophys Res 112:D16208CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2011

Authors and Affiliations

  • Frida A-M. Bender
    • 1
    Email author
  • V. Ramanathan
    • 1
  • George Tselioudis
    • 2
  1. 1.Center for Clouds, Chemistry and Climate (C4), Scripps Institution of OceanographyUniversity of CaliforniaSan Diego, La JollaUSA
  2. 2.NASA Goddard Institute for Space StudiesColumbia UniversityNew YorkUSA

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