Editorial Type:
Article
Article Type:
Research Article

On the Seasonal and Synoptic Time-Scale Variability of the North Atlantic Trade Wind Region and Its Low-Level Clouds

Matthias Brueck Max Planck Institute for Meteorology, Hamburg, Germany

Search for other papers by Matthias Brueck in
Current site
Google Scholar
PubMed Close
,
Louise Nuijens Max Planck Institute for Meteorology, Hamburg, Germany

Search for other papers by Louise Nuijens in
Current site
Google Scholar
PubMed Close
, and
Bjorn Stevens Max Planck Institute for Meteorology, Hamburg, Germany

Search for other papers by Bjorn Stevens in
Current site
Google Scholar
PubMed Close
Print Publication:
01 Apr 2015
DOI:
https://doi.org/10.1175/JAS-D-14-0054.1
Page(s):
1428–1446
Restricted access

Abstract

The seasonality in large-scale meteorology and low-level cloud amount (CClow) is explored for a 5° × 5° area in the North Atlantic trades, using 12 years of ERA-Interim and MODIS data, supported by 2 years of Barbados Cloud Observatory (BCO) measurements. From boreal winter to summer, large-scale subsiding motion changes to rising motion, along with an increase in sea surface temperature, a clockwise turning and weakening of low-level winds, and reduced cold-air advection, lower-tropospheric stability (LTS), and surface fluxes. However, CClow is relatively invariant around 30%, except for a minimum of 20% in fall. This minimum is only pronounced when MODIS scenes with large high-level cloud amount are excluded, and a winter maximum in CClow is more pronounced at the BCO. On monthly time scales, wind speed has the best correlation with CClow. Existing large-eddy simulations suggest that the wind speed–CClow correlation may be explained by a direct deepening response of the trade wind layer to stronger winds. Large correlations of wind direction and advection with CClow also suggest that large-scale flow patterns matter. Smaller correlations with CClow are observed for LTS and surface evaporation, as well as negligible correlations for relative humidity (RH) and vertical velocity. However, these correlations considerably increase when only summer is considered. On synoptic time scales, all correlations drop substantially, whereby wind speed, RH, and surface sensible heat flux remain the leading parameters. The lack of a single strong predictor emphasizes that the combined effect of parameters is necessary to explain variations in CClow in the trades.

Current affiliation: Universität Leipzig, Leipzig, Germany.

Corresponding author address: Louise Nuijens, Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany. E-mail: louise.nuijens@mpimet.mpg.de

Abstract

The seasonality in large-scale meteorology and low-level cloud amount (CClow) is explored for a 5° × 5° area in the North Atlantic trades, using 12 years of ERA-Interim and MODIS data, supported by 2 years of Barbados Cloud Observatory (BCO) measurements. From boreal winter to summer, large-scale subsiding motion changes to rising motion, along with an increase in sea surface temperature, a clockwise turning and weakening of low-level winds, and reduced cold-air advection, lower-tropospheric stability (LTS), and surface fluxes. However, CClow is relatively invariant around 30%, except for a minimum of 20% in fall. This minimum is only pronounced when MODIS scenes with large high-level cloud amount are excluded, and a winter maximum in CClow is more pronounced at the BCO. On monthly time scales, wind speed has the best correlation with CClow. Existing large-eddy simulations suggest that the wind speed–CClow correlation may be explained by a direct deepening response of the trade wind layer to stronger winds. Large correlations of wind direction and advection with CClow also suggest that large-scale flow patterns matter. Smaller correlations with CClow are observed for LTS and surface evaporation, as well as negligible correlations for relative humidity (RH) and vertical velocity. However, these correlations considerably increase when only summer is considered. On synoptic time scales, all correlations drop substantially, whereby wind speed, RH, and surface sensible heat flux remain the leading parameters. The lack of a single strong predictor emphasizes that the combined effect of parameters is necessary to explain variations in CClow in the trades.

Current affiliation: Universität Leipzig, Leipzig, Germany.

Corresponding author address: Louise Nuijens, Max Planck Institute for Meteorology, Bundesstrasse 53, 20146 Hamburg, Germany. E-mail: louise.nuijens@mpimet.mpg.de
Save
Cover Journal of the Atmospheric Sciences
Journal of the Atmospheric Sciences

  • Ackerman, S., R. Holz, R. Frey, E. Eloranta, B. Maddux, and M. McGill, 2008: Cloud detection with MODIS. Part II: Validation. J. Atmos. Oceanic Technol., 25, 1073–1086, doi:10.1175/2007JTECHA1053.1.

    • Search Google Scholar
    • Export Citation

  • Back, L. E., and C. S. Bretherton, 2005: The relationship between wind speed and precipitation in the Pacific ITCZ. J. Climate, 18, 4317–4328, doi:10.1175/JCLI3519.1.

    • Search Google Scholar
    • Export Citation

  • Bellon, G., and B. Stevens, 2013: Time scales of the trade wind boundary layer adjustment. J. Atmos. Sci., 70, 1071–1083, doi:10.1175/JAS-D-12-0219.1.

    • Search Google Scholar
    • Export Citation

  • Bony, S., and J. Dufresne, 2005: Marine boundary layer clouds at the heart of tropical cloud feedback uncertainties in climate models. Geophys. Res. Lett., 32, L20806, doi:10.1029/2005GL023851.

    • Search Google Scholar
    • Export Citation

  • Boucher, O., and Coauthors, 2013: Clouds and aerosols. Climate Change 2013: The Physical Science Basis, T. F. Stocker et al., Eds., Cambridge University Press, 571–657. [Available online at http://www.climatechange2013.org/images/report/WG1AR5_Chapter07_FINAL.pdf.]

  • Bretherton, C., and R. Pincus, 1995: Cloudiness and marine boundary layer dynamics in the ASTEX Lagrangian experiments. Part I: Synoptic setting and vertical structure. J. Atmos. Sci., 52, 2707–2723, doi:10.1175/1520-0469(1995)052<2707:CAMBLD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bretherton, C., and M. Wyant, 1997: Moisture transport, lower-tropospheric stability, and decoupling of cloud-topped boundary layers. J. Atmos. Sci., 54, 148–167, doi:10.1175/1520-0469(1997)054<0148:MTLTSA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bretherton, C., J. McCaa, and H. Grenier, 2004: A new parameterization for shallow cumulus convection and its application to marine subtropical cloud-topped boundary layers. Part I: Description and 1D results. Mon. Wea. Rev., 132, 864–882, doi:10.1175/1520-0493(2004)132<0864:ANPFSC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Bretherton, C., P. Blossey, and C. Jones, 2013: Mechanisms of marine low cloud sensitivity to idealized climate perturbations: A single-LES exploration extending the CGILS cases. J. Adv. Model. Earth Syst., 5, 316–337, doi:10.1002/jame.20019.

    • Search Google Scholar
    • Export Citation

  • Enfield, D., and D. Mayer, 1997: Tropical Atlantic sea surface temperature variability and its relation to El Niño–Southern Oscillation. J. Geophys. Res., 102, 929–945, doi:10.1029/96JC03296.

    • Search Google Scholar
    • Export Citation

  • Fennig, K., A. Andersson, S. Bakan, C.-P. Klepp, and M. Schröder, 2012: Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data—HOAPS 3.2—Monthly means/6-hourly composites. EUMETSAT CM SAF. doi:10.5676/EUM_SAF_CM/HOAPS/V001.

  • Frey, R., S. Ackerman, Y. Liu, K. Strabala, H. Zhang, J. Key, and X. Wang, 2008: Cloud detection with MODIS. Part I: Improvements in the MODIS cloud mask for Collection 5. J. Atmos. Oceanic Technol., 25, 1057–1072, doi:10.1175/2008JTECHA1052.1.

    • Search Google Scholar
    • Export Citation

  • Hartmann, D., M. Ockert-Bell, and M. Michelsen, 1992: The effect of cloud type on Earth’s energy balance: Global analysis. J. Climate, 5, 1281–1304, doi:10.1175/1520-0442(1992)005<1281:TEOCTO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Hinkelman, L., K. Evans, E. Clothiaux, T. Ackerman, and P. Stackhouse Jr., 2007: The effect of cumulus cloud field anisotropy on domain-averaged solar fluxes and atmospheric heating rates. J. Atmos. Sci., 64, 3499–3520, doi:10.1175/JAS4032.1.

    • Search Google Scholar
    • Export Citation

  • Karlsson, J., G. Svensson, S. Cardoso, J. Teixeira, and S. Paradise, 2010: Subtropical cloud-regime transitions: Boundary layer depth and cloud-top height evolution in models and observations. J. Appl. Meteor. Climatol., 49, 1845–1858, doi:10.1175/2010JAMC2338.1.

    • Search Google Scholar
    • Export Citation

  • Kelly, P., and B. Mapes, 2011: Zonal mean wind, the Indian monsoon, and July drying in the western Atlantic subtropics. J. Geophys. Res., 116, D00Q07, doi:10.1029/2010JD015405.

    • Search Google Scholar
    • Export Citation

  • King, M., and Coauthors, 2003: Cloud and aerosol properties, precipitable water, and profiles of temperature and water vapor from MODIS. IEEE Trans. Geosci. Remote Sens., 41, 442–458, doi:10.1109/TGRS.2002.808226.

    • Search Google Scholar
    • Export Citation

  • Klein, S., 1997: Synoptic variability of low-cloud properties and meteorological parameters in the subtropical trade wind boundary layer. J. Climate, 10, 2018–2039, doi:10.1175/1520-0442(1997)010<2018:SVOLCP>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Klein, S., and D. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 1587–1606, doi:10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Klein, S., D. Hartmann, and J. Norris, 1995: On the relationships among low-cloud structure, sea surface temperature, and atmospheric circulation in the summertime northeast Pacific. J. Climate, 8, 1140–1155, doi:10.1175/1520-0442(1995)008<1140:OTRALC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Köhler, M., 2005: Improved prediction of boundary layer clouds. ECMWF Newsletter, No. 104, ECMWF, Reading, United Kingdom, 18–22.

  • Li, Y., D. Thompson, G. Stephens, and S. Bony, 2014: A global survey of the instantaneous linkages between cloud vertical structure and large-scale climate. J. Geophys. Res. Atmos., 119, 3770–3792, doi:10.1002/2013JD020669.

    • Search Google Scholar
    • Export Citation

  • Mauger, G. S., and J. R. Norris, 2010: Assessing the impact of meteorological history on subtropical cloud fraction. J. Climate, 23, 2926–2940, doi:10.1175/2010JCLI3272.1.

    • Search Google Scholar
    • Export Citation

  • Medeiros, B., and B. Stevens, 2011: Revealing differences in GCM representations of low clouds. Climate Dyn., 36, 385–399, doi:10.1007/s00382-009-0694-5.

    • Search Google Scholar
    • Export Citation

  • Menzel, W., W. Smith, and T. Stewart, 1983: Improved cloud motion wind vector and altitude assignment using VAS. J. Climate Appl. Meteor., 22, 377–384, doi:10.1175/1520-0450(1983)022<0377:ICMWVA>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Muñoz, E., A. Busalacchi, S. Nigam, and A. Ruiz-Barradas, 2008: Winter and summer structure of the Caribbean low-level jet. J. Climate, 21, 1260–1276, doi:10.1175/2007JCLI1855.1.

    • Search Google Scholar
    • Export Citation

  • Myers, T., and J. Norris, 2013: Observational evidence that enhanced subsidence reduces subtropical marine boundary layer cloudiness. J. Climate, 26, 7507–7524, doi:10.1175/JCLI-D-12-00736.1.

    • Search Google Scholar
    • Export Citation

  • Neggers, R., B. Stevens, and J. D. Neelin, 2006: A simple equilibrium model for shallow-cumulus-topped mixed layers. Theor. Comput. Fluid Dyn., 20, 305–322, doi:10.1007/s00162-006-0030-1.

    • Search Google Scholar
    • Export Citation

  • Nuijens, L., and B. Stevens, 2012: The influence of wind speed on shallow marine cumulus convection. J. Atmos. Sci., 69, 168–184, doi:10.1175/JAS-D-11-02.1.

    • Search Google Scholar
    • Export Citation

  • Nuijens, L., I. Serikov, L. Hirsch, K. Lonitz, and B. Stevens, 2014: The distribution and variability of low-level cloud in the North Atlantic trades. Quart. J. Roy. Meteor. Soc., 140, 2364–2374, doi:10.1002/qj.2307.

    • Search Google Scholar
    • Export Citation

  • Platnick, S., M. King, S. Ackerman, W. Menzel, B. Baum, J. Riédi, and R. Frey, 2003: The MODIS cloud products: Algorithms and examples from Terra. IEEE Trans. Geosci. Remote Sens., 41, 459–473, doi:10.1109/TGRS.2002.808301.

    • Search Google Scholar
    • Export Citation

  • Rodts, S., P. Duynkerke, and H. Jonker, 2003: Size distributions and dynamical properties of shallow cumulus clouds from aircraft observations and satellite data. J. Atmos. Sci., 60, 1895–1912, doi:10.1175/1520-0469(2003)060<1895:SDADPO>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Sandu, I., B. Stevens, and R. Pincus, 2010: On the transitions in marine boundary layer cloudiness. Atmos. Chem. Phys., 10, 2377–2391, doi:10.5194/acp-10-2377-2010.

    • Search Google Scholar
    • Export Citation

  • Serikov, I., and S. Bobrovnikov, 2010: Atmospheric temperature profiling with pure rotational Raman lidars. Recent Advances in Atmospheric Lidars, L. Fiorani and V. Mitev, Eds., Optoelectronic Materials and Devices, Vol. 7, INOE, 149–216.

    • Search Google Scholar
    • Export Citation

  • Siebert, H., and Coauthors, 2013: The fine-scale structure of the trade wind cumuli over Barbados — An introduction to the CARRIBA project. Atmos. Chem. Phys., 13, 10 061–10 077, doi:10.5194/acp-13-10061-2013.

    • Search Google Scholar
    • Export Citation

  • Siebesma, A., and Coauthors, 2003: A large eddy simulation intercomparison study of shallow cumulus convection. J. Atmos. Sci., 60, 1201–1219, doi:10.1175/1520-0469(2003)60<1201:ALESIS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation

  • Simmons, A., S. Uppala, D. Dee, and S. Kobayashi, 2007: ERA‐Interim: New ECMWF reanalysis products from 1989 onwards. ECMWF Newsletter, No. 110, ECMWF, Reading, United Kingdom, 25–35.

    • Search Google Scholar
    • Export Citation

  • Slingo, J., 1987: The development and verification of a cloud prediction scheme for the ECMWF model. Quart. J. Roy. Meteor. Soc., 113, 899–927, doi:10.1002/qj.49711347710.

    • Search Google Scholar
    • Export Citation

  • Small, R., S. de Szoeke, and S. Xie, 2007: The Central American midsummer drought: Regional aspects and large-scale forcing. J. Climate, 20, 4853–4873, doi:10.1175/JCLI4261.1.

    • Search Google Scholar
    • Export Citation

  • Stevens, B., 2005: Atmospheric moist convection. Annu. Rev. Earth Planet. Sci., 33, 605–643, doi:10.1146/annurev.earth.33.092203.122658.

    • Search Google Scholar
    • Export Citation

  • Stevens, B., 2006: Bulk boundary-layer concepts for simplified models of tropical dynamics. Theor. Comput. Fluid Dyn., 20, 279–304, doi:10.1007/s00162-006-0032-z.

    • Search Google Scholar
    • Export Citation

  • Stevens, B., A. Beljaars, S. Bordoni, C. Holloway, M. Köhler, S. Krueger, V. Savic-Jovcic, and Y. Zhang, 2007: On the structure of the lower troposphere in the summertime stratocumulus regime of the northeast Pacific. Mon. Wea. Rev., 135, 985–1005, doi:10.1175/MWR3427.1.

    • Search Google Scholar
    • Export Citation

  • Teixeira, J., and Coauthors, 2011: Tropical and subtropical cloud transitions in weather and climate prediction models: The GCSS/WGNE Pacific Cross-Section Intercomparison (GPCI). J. Climate, 24, 5223–5256, doi:10.1175/2011JCLI3672.1.

    • Search Google Scholar
    • Export Citation

  • Van Zanten, M., and Coauthors, 2011: Controls on precipitation and cloudiness in simulations of trade-wind cumulus as observed during RICO. J. Adv. Model. Earth Syst.,3, M06001, doi:10.1029/2011MS000056.

  • Vial, J., J. Dufresne, and S. Bony, 2013: On the interpretation of inter-model spread in CMIP5 climate sensitivity estimates. Climate Dyn.,41, 3339–3362, doi:10.1007/s00382-013-1725-9.

  • von Engeln, A., and J. Teixeira, 2013: A planetary boundary layer height climatology derived from ECMWF reanalysis data. J. Climate, 26, 6575–6590, doi:10.1175/JCLI-D-12-00385.1.

    • Search Google Scholar
    • Export Citation

  • Warren, S., C. Hahn, J. London, R. Chervin, and R. Jenne, 1988: Global distribution of total cloud cover and cloud type amounts over the ocean. NCAR Tech. Note NCAR/TN-317+STR, 43 pp., doi:10.2172/5415329.

  • Wood, R., and C. Bretherton, 2006: On the relationship between stratiform low cloud cover and lower-tropospheric stability. J. Climate, 19, 6425–6432, doi:10.1175/JCLI3988.1.

    • Search Google Scholar
    • Export Citation

  • Zhao, G., and L. Di Girolamo, 2006: Cloud fraction errors for trade wind cumuli from EOS-Terra instruments. Geophys. Res. Lett., 33, L20802, doi:10.1029/2006GL027088.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 789 260 18
PDF Downloads 551 142 8