Observed Signatures of the Barotropic and Baroclinic Annular Modes in Cloud Vertical Structure and Cloud Radiative Effects

Ying Li Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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David W. J. Thompson Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado

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Abstract

The signatures of large-scale annular variability on the vertical structure of clouds and cloud radiative effects are examined in vertically resolved CloudSat and other satellite and reanalysis data products. The northern and southern “barotropic” annular modes (the NAM and SAM) have a complex vertical structure. Both are associated with a meridional dipole in clouds between subpolar and middle latitudes, but the sign of the anomalies changes between upper, middle, and lower tropospheric levels. In contrast, the northern and southern baroclinic annular modes have a much simpler vertical structure. Both are linked to same-signed anomalies in clouds extending throughout the troposphere at middle to high latitudes. The changes in cloud incidence associated with both the barotropic and baroclinic annular modes are consistent with dynamical forcing by the attendant changes in static stability and/or vertical motion. The results also provide the first observational estimates of the vertically resolved atmospheric cloud radiative effects associated with hemispheric-scale extratropical variability. In general, the anomalies in atmospheric cloud radiative effects associated with the annular modes peak in the middle to upper troposphere, and are consistent with the anomalous trapping of longwave radiation by variations in upper tropospheric clouds. The southern baroclinic annular mode gives rise to periodic behavior in longwave cloud radiative effects at the top of the atmosphere averaged over Southern Hemisphere midlatitudes.

Corresponding author address: Ying Li, Department of Atmospheric Science, Colorado State University, 3915 W. Laporte Ave., Fort Collins, CO 80521. E-mail: yingli@atmos.colostate.edu

Abstract

The signatures of large-scale annular variability on the vertical structure of clouds and cloud radiative effects are examined in vertically resolved CloudSat and other satellite and reanalysis data products. The northern and southern “barotropic” annular modes (the NAM and SAM) have a complex vertical structure. Both are associated with a meridional dipole in clouds between subpolar and middle latitudes, but the sign of the anomalies changes between upper, middle, and lower tropospheric levels. In contrast, the northern and southern baroclinic annular modes have a much simpler vertical structure. Both are linked to same-signed anomalies in clouds extending throughout the troposphere at middle to high latitudes. The changes in cloud incidence associated with both the barotropic and baroclinic annular modes are consistent with dynamical forcing by the attendant changes in static stability and/or vertical motion. The results also provide the first observational estimates of the vertically resolved atmospheric cloud radiative effects associated with hemispheric-scale extratropical variability. In general, the anomalies in atmospheric cloud radiative effects associated with the annular modes peak in the middle to upper troposphere, and are consistent with the anomalous trapping of longwave radiation by variations in upper tropospheric clouds. The southern baroclinic annular mode gives rise to periodic behavior in longwave cloud radiative effects at the top of the atmosphere averaged over Southern Hemisphere midlatitudes.

Corresponding author address: Ying Li, Department of Atmospheric Science, Colorado State University, 3915 W. Laporte Ave., Fort Collins, CO 80521. E-mail: yingli@atmos.colostate.edu
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  • Allan, R. P., 2011: Combining satellite data and models to estimate cloud radiative effect at the surface and in the atmosphere. Meteor. Appl., 18, 324333, doi:10.1002/met.285.

    • Search Google Scholar
    • Export Citation
  • Aumann, H. H., and Coauthors, 2003: AIRS/AMSU/HSB on the Aqua mission: Design, science objectives, data products, and processing systems. IEEE Trans. Geosci. Remote Sens., 41, 253264, doi:10.1109/TGRS.2002.808356.

    • Search Google Scholar
    • Export Citation
  • Bretherton, C. S., M. Widmann, V. P. Dymnikov, J. M. Wallace, and I. Bladé, 1999: The effective number of spatial degrees of freedom of a time-varying field. J. Climate, 12, 19902009, doi:10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Ceppi, P., and D. L. Hartmann, 2015: Connections between clouds, radiation, and midlatitude dynamics: A review. Curr. Climate Change Rep., 1, 94102, doi:10.1007/s40641-015-0010-x.

    • Search Google Scholar
    • Export Citation
  • Ceppi, P., and D. L. Hartmann, 2016: Clouds and the atmospheric circulation response to warming. J. Climate, 29, 783799, doi:10.1175/JCLI-D-15-0394.1.

    • Search Google Scholar
    • Export Citation
  • Ceppi, P., M. D. Zelinka, and D. L. Hartmann, 2014: The response of the Southern Hemispheric eddy-driven jet to future changes in shortwave radiation in CMIP5. Geophys. Res. Lett., 41, 32443250, doi:10.1002/2014GL060043.

    • Search Google Scholar
    • Export Citation
  • Ceppi, P., D. Hartmann, and M. Webb, 2016: Mechanisms of the negative shortwave cloud feedback in mid to high latitudes. J. Climate, 29, 139157, doi:10.1175/JCLI-D-15-0327.1.

    • Search Google Scholar
    • Export Citation
  • Chahine, M., and Coauthors, 2006: AIRS: Improving weather forecasting and providing new data on greenhouse gases. Bull. Amer. Meteor. Soc., 87, 911926, doi:10.1175/BAMS-87-7-911.

    • Search Google Scholar
    • Export Citation
  • Crueger, T., and B. Stevens, 2015: The effect of atmospheric radiative heating by clouds on the Madden–Julian oscillation. J. Adv. Model. Earth Syst., 7, 854864, doi:10.1002/2015MS000434.

    • Search Google Scholar
    • Export Citation
  • Dee, D. P., and Coauthors, 2011: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Quart. J. Roy. Meteor. Soc., 137, 553597, doi:10.1002/qj.828.

    • Search Google Scholar
    • Export Citation
  • Grise, K. M., and L. M. Polvani, 2014: Southern Hemisphere cloud dynamics biases in CMIP5 models and their implications for climate projections. J. Climate, 27, 60746092, doi:10.1175/JCLI-D-14-00113.1.

    • Search Google Scholar
    • Export Citation
  • Grise, K. M., L. M. Polvani, G. Tselioudis, Y. Wu, and M. D. Zelinka, 2013: The ozone hole indirect effect: Cloud-radiative anomalies accompanying the poleward shift of the eddy-driven jet in the Southern Hemisphere. Geophys. Res. Lett., 40, 36883692, doi:10.1002/grl.50675.

    • Search Google Scholar
    • Export Citation
  • Hartmann, D., and F. Lo, 1998: Wave-driven zonal flow vacillation in the Southern Hemisphere. J. Atmos. Sci., 55, 13031315, doi:10.1175/1520-0469(1998)055<1303:WDZFVI>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Haynes, J. M., T. H. V. Haar, T. L’Ecuyer, and D. Henderson, 2013: Radiative heating characteristics of Earth’s cloudy atmosphere from vertically resolved active sensors. Geophys. Res. Lett., 40, 624630, doi:10.1002/grl.50145.

    • Search Google Scholar
    • Export Citation
  • Henderson, D. S., T. L’Ecuyer, G. Stephens, P. Partain, and M. Sekiguchi, 2013: A multisensor perspective on the radiative impacts of clouds and aerosols. J. Appl. Meteor. Climatol., 52, 853871, doi:10.1175/JAMC-D-12-025.1.

    • Search Google Scholar
    • Export Citation
  • Kato, S., N. G. Loeb, F. G. Rose, D. R. Doelling, D. A. Rutan, T. E. Caldwell, L. Yu, and R. A. Weller, 2013: Surface irradiances consistent with CERES-derived top-of-atmosphere shortwave and longwave irradiances. J. Climate, 26, 27192740, doi:10.1175/JCLI-D-12-00436.1.

    • Search Google Scholar
    • Export Citation
  • Klein, S. A., and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6, 15871606, doi:10.1175/1520-0442(1993)006<1587:TSCOLS>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Li, Y., D. W. J. Thompson, Y. Huang, and M. Zhang, 2014a: Observed linkages between the northern annular mode/North Atlantic Oscillation, cloud incidence, and cloud radiative forcing. Geophys. Res. Lett., 41, 16811688, doi:10.1002/2013GL059113.

    • Search Google Scholar
    • Export Citation
  • Li, Y., D. W. J. Thompson, G. L. Stephens, and S. Bony, 2014b: A global survey of the instantaneous linkages between cloud vertical structure and large-scale climate. J. Geophys. Res. Atmos., 119, 37703792, doi:10.1002/2013JD020669.

    • Search Google Scholar
    • Export Citation
  • Limpasuvan, V., and D. L. Hartmann, 2000: Wave-maintained annular modes of climate variability. J. Climate, 13, 44144429, doi:10.1175/1520-0442(2000)013<4414:WMAMOC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Loeb, N. G., B. A. Wielicki, D. R. Doelling, G. L. Smith, D. F. Keyes, S. Kato, N. Manlo-Smith, and T. Wong, 2009: Toward optimal closure of the Earth’s top-of-atmosphere radiation budget. J. Climate, 22, 748766, doi:10.1175/2008JCLI2637.1.

    • Search Google Scholar
    • Export Citation
  • Mace, G. G., Q. Zhang, M. Vaughn, R. Marchand, G. Stephens, C. Trepte, and D. Winker, 2009: A description of hydrometeor layer occurrence statistics derived from the first year of merged CloudSat and CALIPSO data. J. Geophys. Res., 114, D00A26, doi:10.1029/2007JD009755.

    • Search Google Scholar
    • Export Citation
  • Mace, G. G., S. Houser, S. Benson, S. A. Klein, and Q. Min, 2011: Critical evaluation of the ISCCP simulator using ground-based remote sensing data. J. Climate, 24, 15981612, doi:10.1175/2010JCLI3517.1.

    • Search Google Scholar
    • Export Citation
  • McCoy, D. T., D. L. Hartmann, and D. P. Grosvenor, 2014: Observed Southern Ocean cloud properties and shortwave reflection. Part II: Phase changes and low cloud feedback. J. Climate, 27, 88588868, doi:10.1175/JCLI-D-14-00288.1.

    • 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
  • Thompson, D. W. J., and J. M. Wallace, 2000: Annular modes in the extratropical circulation. Part I: Month-to-month variability. J. Climate, 13, 10001016, doi:10.1175/1520-0442(2000)013<1000:AMITEC>2.0.CO;2.

    • Search Google Scholar
    • Export Citation
  • Thompson, D. W. J., and E. A. Barnes, 2014: Periodic variability in the large-scale Southern Hemisphere atmospheric circulation. Science, 343, 641645, doi:10.1126/science.1247660.

    • Search Google Scholar
    • Export Citation
  • Thompson, D. W. J., and J. D. Woodworth, 2014: Barotropic and baroclinic annular variability in the Southern Hemisphere. J. Atmos. Sci., 71, 14801493, doi:10.1175/JAS-D-13-0185.1.

    • Search Google Scholar
    • Export Citation
  • Thompson, D. W. J., and Y. Li, 2015: Baroclinic and barotropic annular variability in the Northern Hemisphere. J. Atmos. Sci., 72, 11171136, doi:10.1175/JAS-D-14-0104.1.

    • Search Google Scholar
    • Export Citation
  • Zelinka, M., S. Klein, and D. Hartmann, 2012: Computing and partitioning clouds feedbacks using cloud property histograms. Part II: Attribution to changes in cloud amount, altitude, and optical depth. J. Climate, 25, 37363754, doi:10.1175/JCLI-D-11-00249.1.

    • Search Google Scholar
    • Export Citation
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