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Stephens 2005

The Annual Cycle of Mid-latitude Cloud Properties: Understanding the Mechanisms Dennis Hartmann, Daniel McCoy. The Importance of Understanding Cloud Feedbacks. Stephens 2005. (Roe 2009). SW feedback. Bony 2006. Zelinka Dissertation 2011. The zonal structure of cloud feedbacks.

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Stephens 2005

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  1. The Annual Cycle of Mid-latitude Cloud Properties: Understanding the MechanismsDennis Hartmann, Daniel McCoy

  2. The Importance of Understanding Cloud Feedbacks Stephens 2005

  3. (Roe 2009)

  4. SW feedback Bony 2006 Zelinka Dissertation 2011

  5. The zonal structure of cloud feedbacks Zelinka 2011b

  6. Zelinka 2011b

  7. Possible Physical Explanations • Clausius-Clapeyron->water vapor -> cloud liquid water ->albedo. (Somerville 1984) (Paltridge 1980) • Thermodynamically we may show that CLWP is dependent on the slope of the moist adiabat with T especially in mid-hi lats(Betts AK 1987)

  8. Possible Physical Explanations • Intensifying and shifting of mid-latitude storm tracks upward and poleward- poleward shift in maximum cloud fraction(Bender 2011)

  9. Possible Physical Explanations No model with lower eq. sensitivity than 3K show meaningful shift

  10. Possible Physical Explanations • THC strong in SH - breaks down due to less dense water in the NH (Manabe 2007) • Increase in estimated inversion strength increase in water rich boundary layer clouds+ CF (Wood 2006)

  11. Possible Physical Explanations • At mid-latitudes the transition from ice to liquid may be of central importance. (Senior 1993)(Zelinka 2011)

  12. Data • Special Sensor Microwave/Imager (SSM/I) • Advanced Microwave Scanning Radiometer (AMSR-E) • Moderate Resolution Imaging Spectroradiometer (MODIS) (Terra and Aqua) (Issues with sun glint at high latitude + sensor zenith angles > 50 but also difficult due to multiple overpasses) • ERA-interim reanalysis products

  13. Use of Seasonal Cycles to Understand Clouds in Climate Change • Limited cloud observational data. • Use annual cycle of temperature as a analog to climate change. • Allow better understanding of models.

  14. Water Vapor over oceans (Note AMSR-E vapor data also used due to it being more reliable over the oceans than ERA-interim) (Trenberth 2005)

  15. MFC

  16. Cloud LWP

  17. Boreal Austral

  18. Boreal Austral

  19. Boreal Austral

  20. Boreal Austral

  21. Further Work • Check models to see if they agree well with observed cycle due to strong weighting of future predictions by current biases. • Retrieve a decent low cloud fraction product.

  22. Acknowledgements • Dr. Robert Wood • Dr. Chris Bretherton • Dr. DarganFrierson • Yen-Ting Hwang • Mark Zelinka • Daniel Grosvenor (MODIS) • Marc Michelsen • Dr. John Fasullo (via Ting, ECMWF - MFC) • Angie, Libby, Paulo (patience and help) • Class of 2011 (For assisting in my survival)

  23. References • Bender FAM et. al. Changes in extratropical storm track cloudiness 1983–2008: observational support for a polewardshift Climate Dynamics (2011) • Bony et. al. How Well Do We Understand and Evaluate Climate Change Feedback Processes? Journal of Climate (2006) • Betts AK et al Thermodynamic Constraint on Cloud Liquid Water Feedback in Climate Models JGR (1987) • Manabe S et. al. Role of Ocean in Global Warming Journal of the Meteorological Society of Japan (2007) • Wood R. Bretherton CS. On the Relationship between Stratiform Low Cloud Cover and Lower-Tropospheric Stability AMS (2006) • Roe G Feedbacks, Timescales, and Seeing Red Annu Rev Earth Planet Sci 2009 • Somerville RCJ et al Cloud Optical Thickness Feedbacks in the Climate Problem JGR (1984) • Stephens, G. L. Cloud feedbacks in the climate system: A critical review Journal of Climate (2005) • Trenberth KE et al Trends and variability in column integrated atmospheric water vapor Climate Dynamics (2005) • Paltridge GW Cloud-radiation Feedback to Climate Notes and Correspondence (1980) • Zelinka, M.D., S.A. Klein and D.L. Hartmann Computing and partitioning Clouds Feedbacks using Cloud property Histograms. Part II: Attribution to the Nature of Cloud Changes. J. Climate (2011b) • Zelinka, M.D., S.A. Klein and D.L. Hartmann, : Computing and partitioning Clouds Feedbacks using Cloud property Histograms. Part I: Cloud Radiative kernels. J. Climate (2011a) • Zelinka, M.D. and D.L. Hartmann, : Climate Feedbacks and their Implications for Poleward Energy Flux Changes in a Warming Climate, J. Climate (2011a) • Senior CA Mitchell JFB Carbon Dioxide and the Climate: Impact of Cloud Parameterization Journal of Climate 1993

  24. H. Chepfer et al: "The GCM Oriented CALIPSO Cloud Product (CALIPSO-GOCCP)", J. Geophys. Res., 105, D00H16, doi:10.1029/2009JD012251,

  25. ECMWF MFC

  26. Feedbacks λo =Climate Sensitivity ΔR=Radiative Forcing

  27. Roe

  28. Soden and Held (2006)

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