Editorial Type:
Article
Article Type:
Research Article

An Estimate of Low-Cloud Feedbacks from Variations of Cloud Radiative and Physical Properties with Sea Surface Temperature on Interannual Time Scales

Zachary A. Eitzen Science Systems and Applications, Inc., Hampton, Virginia

Search for other papers by Zachary A. Eitzen in
Current site
Google Scholar
PubMed Close
,
Kuan-Man Xu NASA Langley Research Center, Hampton, Virginia

Search for other papers by Kuan-Man Xu in
Current site
Google Scholar
PubMed Close
, and
Takmeng Wong NASA Langley Research Center, Hampton, Virginia

Search for other papers by Takmeng Wong in
Current site
Google Scholar
PubMed Close
Print Publication:
15 Feb 2011
DOI:
https://doi.org/10.1175/2010JCLI3670.1
Page(s):
1106–1121
Restricted access

Abstract

Simulations of climate change have yet to reach a consensus on the sign and magnitude of the changes in physical properties of marine boundary layer clouds. In this study, the authors analyze how cloud and radiative properties vary with SST anomaly in low-cloud regions, based on five years (March 2000–February 2005) of Clouds and the Earth’s Radiant Energy System (CERES)–Terra monthly gridded data and matched European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological reanalaysis data. In particular, this study focuses on the changes in cloud radiative effect, cloud fraction, and cloud optical depth with SST anomaly. The major findings are as follows. First, the low-cloud amount (−1.9% to −3.4% K−1) and the logarithm of low-cloud optical depth (−0.085 to −0.100 K−1) tend to decrease while the net cloud radiative effect (3.86 W m−2 K−1) becomes less negative as SST anomalies increase. These results are broadly consistent with previous observational studies. Second, after the changes in cloud and radiative properties with SST anomaly are separated into dynamic, thermodynamic, and residual components, changes in the dynamic component (taken as the vertical velocity at 700 hPa) have relatively little effect on cloud and radiative properties. However, the estimated inversion strength decreases with increasing SST, accounting for a large portion of the measured decreases in cloud fraction and cloud optical depth. The residual positive change in net cloud radiative effect (1.48 W m−2 K−1) and small changes in low-cloud amount (−0.81% to 0.22% K−1) and decrease in the logarithm of optical depth (–0.035 to –0.046 K−1) with SST are interpreted as a positive cloud feedback, with cloud optical depth feedback being the dominant contributor. Last, the magnitudes of the residual changes differ greatly among the six low-cloud regions examined in this study, with the largest positive feedbacks (∼4 W m−2 K−1) in the southeast and northeast Atlantic regions and a slightly negative feedback (−0.2 W m−2 K−1) in the south-central Pacific region. Because the retrievals of cloud optical depth and/or cloud fraction are difficult in the presence of aerosols, the transport of heavy African continental aerosols may contribute to the large magnitudes of estimated cloud feedback in the two Atlantic regions.

Corresponding author address: Z. A. Eitzen, Mail Stop 420, NASA Langley Research Center, Hampton, VA 23681. Email: zachary.a.eitzen@nasa.gov

Abstract

Simulations of climate change have yet to reach a consensus on the sign and magnitude of the changes in physical properties of marine boundary layer clouds. In this study, the authors analyze how cloud and radiative properties vary with SST anomaly in low-cloud regions, based on five years (March 2000–February 2005) of Clouds and the Earth’s Radiant Energy System (CERES)–Terra monthly gridded data and matched European Centre for Medium-Range Weather Forecasts (ECMWF) meteorological reanalaysis data. In particular, this study focuses on the changes in cloud radiative effect, cloud fraction, and cloud optical depth with SST anomaly. The major findings are as follows. First, the low-cloud amount (−1.9% to −3.4% K−1) and the logarithm of low-cloud optical depth (−0.085 to −0.100 K−1) tend to decrease while the net cloud radiative effect (3.86 W m−2 K−1) becomes less negative as SST anomalies increase. These results are broadly consistent with previous observational studies. Second, after the changes in cloud and radiative properties with SST anomaly are separated into dynamic, thermodynamic, and residual components, changes in the dynamic component (taken as the vertical velocity at 700 hPa) have relatively little effect on cloud and radiative properties. However, the estimated inversion strength decreases with increasing SST, accounting for a large portion of the measured decreases in cloud fraction and cloud optical depth. The residual positive change in net cloud radiative effect (1.48 W m−2 K−1) and small changes in low-cloud amount (−0.81% to 0.22% K−1) and decrease in the logarithm of optical depth (–0.035 to –0.046 K−1) with SST are interpreted as a positive cloud feedback, with cloud optical depth feedback being the dominant contributor. Last, the magnitudes of the residual changes differ greatly among the six low-cloud regions examined in this study, with the largest positive feedbacks (∼4 W m−2 K−1) in the southeast and northeast Atlantic regions and a slightly negative feedback (−0.2 W m−2 K−1) in the south-central Pacific region. Because the retrievals of cloud optical depth and/or cloud fraction are difficult in the presence of aerosols, the transport of heavy African continental aerosols may contribute to the large magnitudes of estimated cloud feedback in the two Atlantic regions.

Corresponding author address: Z. A. Eitzen, Mail Stop 420, NASA Langley Research Center, Hampton, VA 23681. Email: zachary.a.eitzen@nasa.gov

Save
Cover Journal of Climate
Journal of Climate

  • Bony, S., and J.-L. 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

  • Bony, S., K.-M. Lau, and Y. C. Sud, 1997: Sea surface temperature and large-scale circulation influences on tropical greenhouse effect and cloud radiative forcing. J. Climate, 10 , 2055–2077.

    • Search Google Scholar
    • Export Citation

  • Bony, S., J-L. Dufresne, H. Le Treut, J-J. Morcrette, and C. Senior, 2004: On dynamic and thermodynamic components of cloud changes. Climate Dyn., 22 , 71–86.

    • Search Google Scholar
    • Export Citation

  • Clement, A. C., R. Burgman, and J. R. Norris, 2009: Observational and model evidence for positive low-level cloud feedback. Science, 325 , 460–464.

    • Search Google Scholar
    • Export Citation

  • Dong, X., P. Minnis, B. Xi, S. Sun-Mack, and Y. Chen, 2008: Comparison of CERES–MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site. J. Geophys. Res., 113 , D03204. doi:10.1029/2007JD008438.

    • Search Google Scholar
    • Export Citation

  • Efron, B., and R. Tibshirani, 1993: An Introduction to the Bootstrap. Chapman & Hall, 456 pp.

  • Eitzen, Z. A., K.-M. Xu, and T. Wong, 2008: Statistical analyses of satellite cloud object data from CERES. Part V: Relationships between physical properties of marine boundary layer clouds. J. Climate, 21 , 6668–6688.

    • Search Google Scholar
    • Export Citation

  • Ghate, V. P., B. A. Albrecht, C. W. Fairall, and R. A. Weller, 2009: Climatology of surface meteorology, surface fluxes, cloud fraction and radiative forcing over the Southeast Pacific from buoy observations. J. Climate, 22 , 5527–5540.

    • Search Google Scholar
    • Export Citation

  • Gordon, N. D., and J. R. Norris, 2010: Cluster analysis of midlatitude oceanic cloud regimes: Mean properties and temperature sensitivity. Atmos. Chem. Phys., 10 , 6435–6459.

    • Search Google Scholar
    • Export Citation

  • Gray, W. M., C. W. Landsea, P. W. Mielke, and K. J. Berry, 1992: Predicting Atlantic seasonal hurricane activity 6–11 months in advance. Wea. Forecasting, 7 , 440–455.

    • Search Google Scholar
    • Export Citation

  • Jensen, M. P., A. M. Vogelmann, W. D. Collins, G. J. Zhang, and E. P. Luke, 2008: Investigation of regional and seasonal variations in marine boundary layer cloud properties from MODIS observations. J. Climate, 21 , 4955–4973.

    • Search Google Scholar
    • Export Citation

  • Klein, S. A., 1997: Synoptic variability of low-cloud properties and meteorological parameters in the subtropical trade wind boundary layer. J. Climate, 10 , 2018–2039.

    • Search Google Scholar
    • Export Citation

  • Klein, S. A., and D. L. Hartmann, 1993: The seasonal cycle of low stratiform clouds. J. Climate, 6 , 1587–1606.

  • Larson, K., D. L. Hartmann, and S. A. Klein, 1999: The role of clouds, water vapor, circulation, and boundary layer structure in the sensitivity of the tropical climate. J. Climate, 12 , 2359–2374.

    • Search Google Scholar
    • Export Citation

  • Lin, W., M. Zhang, and N. Loeb, 2009: Seasonal variation of the physical properties of marine boundary layer clouds off the California coast. J. Climate, 22 , 2624–2638.

    • Search Google Scholar
    • Export Citation

  • Loeb, N. G., N. M. Smith, S. Kato, W. F. Miller, S. K. Gupta, P. Minnis, and B. A. Wielicki, 2003: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Tropical Rainfall Measuring Mission Satellite. Part I: Methodology. J. Appl. Meteor., 42 , 240–265.

    • Search Google Scholar
    • Export Citation

  • Loeb, N. G., S. Kato, K. Loukachine, and N. M. Smith, 2005: Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth’s Radiant Energy System instrument on the Terra satellite. Part I: Methodology. J. Atmos. Oceanic Technol., 22 , 338–351.

    • Search Google Scholar
    • Export Citation

  • Loeb, N. G., B. A. Wielicki, D. R. Doelling, G. L. Smith, D. F. Keyes, S. Kato, N. Manalo-Smith, and T. Wong, 2009: Toward optimal closure of the earth’s top-of-atmosphere radiation budget. J. Climate, 22 , 748–766.

    • 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.

    • Search Google Scholar
    • Export Citation

  • Mielke, P. W., 1991: The application of multivariate permutation methods based on distance functions in the earth sciences. Earth Sci. Rev., 31 , 55–71.

    • Search Google Scholar
    • Export Citation

  • Miller, R. L., 1997: Tropical thermostats and low cloud cover. J. Climate, 10 , 409–440.

  • Minnis, P., D. F. Young, S. Sun-Mack, P. W. Heck, D. R. Doelling, and Q. Trepte, 2003: CERES cloud property retrievals from imagers on TRMM, Terra, and Aqua. Remote Sensing of Clouds and the Atmosphere VIII, K. P. Schaefer et al., Eds., International Society for Optical Engineering (SPIE Proceedings, Vol. 5235), 37–48.

    • Search Google Scholar
    • Export Citation

  • Minnis, P., and Coauthors, 2008: Cloud detection in non-polar regions for CERES using TRMM VIRS and Terra and Aqua MODIS data. IEEE Trans. Geosci. Remote Sens., 46 , 3857–3884.

    • Search Google Scholar
    • Export Citation

  • Norris, J. R., and C. B. Leovy, 1994: Interannual variability in stratiform cloudiness and sea surface temperature. J. Climate, 7 , 1915–1925.

    • Search Google Scholar
    • Export Citation

  • Norris, J. R., and S. F. Iacobellis, 2005: North Pacific cloud feedbacks inferred from synoptic-scale dynamic and thermodynamic relationships. J. Climate, 18 , 4862–4876.

    • Search Google Scholar
    • Export Citation

  • Oreopoulos, L., and R. Davies, 1993: Statistical dependence of albedo and cloud cover on sea surface temperature for two tropical marine stratocumulus regions. J. Climate, 6 , 2434–2447.

    • Search Google Scholar
    • Export Citation

  • Peterson, T. C., T. P. Barnett, E. Roeckner, and T. H. Vonder Haar, 1992: An analysis of the relationship between cloud anomalies and sea surface temperature anomalies in a global circulation model. J. Geophys. Res., 97 , 20497–20506.

    • Search Google Scholar
    • Export Citation

  • Randall, D. A., J. A. Coakley Jr., C. W. Fairall, R. A. Kropfli, and D. H. Lenschow, 1984: Outlook for research on subtropical marine stratiform clouds. Bull. Amer. Meteor. Soc., 65 , 1290–1301.

    • Search Google Scholar
    • Export Citation

  • Randall, D. A., and Coauthors, 2007: Climate models and their evaluation. Climate Change 2007: The Physical Science Basis, S. Solomon et al., Eds., Cambridge University Press, 589–662.

    • Search Google Scholar
    • Export Citation

  • Reynolds, R. W., N. A. Rayner, T. M. Smith, D. C. Stokes, and W. Wang, 2002: An improved in situ and satellite SST analysis for climate. J. Climate, 15 , 1609–1625.

    • Search Google Scholar
    • Export Citation

  • Ringer, M. A., and R. P. Allan, 2004: Evaluating climate model simulations of tropical cloud. Tellus, 56A , 308–327.

  • Seneta, E., 1983: The weighted median and multiple regression. Aust. J. Stat., 25 , 370–377.

  • Stephens, G. L., 2005: Cloud feedbacks in the climate system: A critical review. J. Climate, 18 , 237–273.

  • Stowasser, M., and K. Hamilton, 2006: Relationship between shortwave cloud radiative forcing and local meteorological variables compared in observations and several global climate models. J. Climate, 19 , 4344–4359.

    • Search Google Scholar
    • Export Citation

  • Su, W., A. Bodas-Salcedo, K-M. Xu, and T. P. Charlock, 2010a: Comparison of the tropical radiative flux and cloud radiative effect profiles in a climate model with Clouds and the Earth’s Radiant Energy System (CERES) data. J. Geophys. Res., 115 , D01105. doi:10.1029/2009JD012490.

    • Search Google Scholar
    • Export Citation

  • Su, W., N. G. Loeb, K-M. Xu, G. L. Schuster, and Z. A. Eitzen, 2010b: An estimate of aerosol indirect effect from satellite measurements with concurrent meteorological analysis. J. Geophys. Res., 115 , D18219. doi:10.1029/2010JD013948.

    • Search Google Scholar
    • Export Citation

  • Tselioudis, G., W. B. Rossow, and D. Rind, 1992: Global patterns of cloud optical thickness variation with temperature. J. Climate, 5 , 1484–1495.

    • Search Google Scholar
    • Export Citation

  • Uppala, S., D. Dee, S. Kobayashi, P. Berrisford, and A. Simmons, 2008: Towards a climate data assimilation system: Status update of ERA-Interim. ECMWF Newsletter, No. 115, ECMWF, Reading, United Kingdom, 12–18.

    • Search Google Scholar
    • Export Citation

  • Wagner, T., S. Beirle, T. Deutschmann, M. Grzegorski, and U. Platt, 2008: Dependence of cloud properties derived from spectrally resolved visible satellite observations on surface temperature. Atmos. Chem. Phys., 8 , 2299–2312.

    • Search Google Scholar
    • Export Citation

  • Wielicki, B. A., B. R. Barkstrom, E. F. Harrison, R. B. Lee III, G. L. Smith, and J. E. Cooper, 1996: Clouds and the Earth’s Radiant Energy System (CERES): An Earth Observing System experiment. Bull. Amer. Meteor. Soc., 77 , 853–868.

    • Search Google Scholar
    • Export Citation

  • Wilks, D. S., 2006: Statistical Methods in the Atmospheric Sciences. 2nd ed. Academic Press, 627 pp.

  • Williams, K. D., M. A. Ringer, and C. A. Senior, 2003: Evaluating the cloud response to climate change and current climate variability. Climate Dyn., 20 , 705–721.

    • Search Google Scholar
    • Export Citation

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

    • Search Google Scholar
    • Export Citation

  • Xu, K-M., T. Wong, B. A. Wielicki, L. Parker, and Z. A. Eitzen, 2005: Statistical analyses of cloud object data from CERES. Part I: Methodology and preliminary results of the 1998 El Niño/2000 La Niña. J. Climate, 18 , 2497–2514.

    • Search Google Scholar
    • Export Citation

  • Xu, K-M., T. Wong, B. A. Wielicki, and L. Parker, 2008: Statistical analyses of satellite cloud object data from CERES. Part IV: Boundary layer cloud objects during 1998 El Niño. J. Climate, 21 , 1500–1521.

    • Search Google Scholar
    • Export Citation

  • Xu, K-M., A. Cheng, and M.-H. Zhang, 2010: Cloud-resolving simulation of low-cloud feedback to an increase in sea surface temperature. J. Atmos. Sci., 67 , 730–748.

    • Search Google Scholar
    • Export Citation

  • Young, D. F., P. Minnis, D. R. Doelling, G. G. Gibson, and T. Wong, 1998: Temporal interpolation methods for the Cloud and the Earth’s Radiant Energy System (CERES) experiment. J. Appl. Meteor., 37 , 572–590.

    • Search Google Scholar
    • Export Citation

  • Zhang, M., and C. Bretherton, 2008: Mechanisms of low cloud–climate feedback in idealized single-column simulations with the Community Atmospheric Model, version 3 (CAM3). J. Climate, 21 , 4859–4878.

    • Search Google Scholar
    • Export Citation

  • Zhu, P., J. J. Hack, and J. T. Kiehl, 2007a: Diagnosing cloud feedbacks in general circulation models. J. Climate, 20 , 2602–2622.

  • Zhu, P., J. J. Hack, J. T. Kiehl, and C. S. Bretherton, 2007b: Climate sensitivity of tropical and subtropical marine low cloud amount to ENSO and global warming due to doubled CO2. J. Geophys. Res., 112 , D17108. doi:10.1029/2006JD008174.

    • Search Google Scholar
    • Export Citation
All Time Past Year Past 30 Days
Abstract Views 0 0 0
Full Text Views 1106 609 149
PDF Downloads 154 44 1