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Update on stratocumulus simulations by the UCLA AGCM

Update on stratocumulus simulations by the UCLA AGCM. C. R. Mechoso, I. Richter, G. Cazes, and R. Terra University of California, Los Angeles OUTLINE Sensitivity of Sc incidence to African orography A comparison with similar results for South American orography

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Update on stratocumulus simulations by the UCLA AGCM

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  1. Update on stratocumulus simulations by the UCLA AGCM C. R. Mechoso, I. Richter, G. Cazes, and R. Terra University of California, Los Angeles OUTLINE Sensitivity of Sc incidence to African orography A comparison with similar results for South American orography Aspects of PBL parameterization in AGCMs Work in progress Mechoso, C. R., J. -Y. Yu and A. Arakawa, 2000: A coupled GCM pilgrimage: From climate catastrophe to ENSO simulations. General Circulation Model Development: Past, Present and Future. D. A. RandallEd., Academic Press, 539-575

  2. Why Stratocumulus Matter • Stratocumulus cover a large portion of the world’s oceans • Impact on global radiation budget is significant (e.g. Slingo 1990, Hartmann et al. 1992) • Climate of tropical regions strongly depends on subtropical marine stratocumulus: position of the ITCZ, SST gradients (e.g. Philander et al. 1996, Ma et al. 1996) • AGCMs difficulties with stratocumulus lead to  large uncertainties in global warming estimates  severe problems in coupled GCMs (double ITCZ, warm SST bias, weakened trade winds etc.)

  3. Overall Goal of this Study • Increase understanding of the interplay between the large-scale environment and subtropical marine boundary layer clouds concerning their seasonal cycle in different regions of the world oceans. • A first stage of the study focuses on the role that orography plays on the flow over the eastern tropical oceans.

  4. Seasonal Cycle of Stratocumulus Surface observations of the five major marine stratocumulus regions (from Klein and Hartmann, 1993) Peruvian and Namibian stratus peak in October

  5. Model Description • UCLA AGCM, version 7.1 • Resolution: 2.5ºlon x 2ºlat x 29  levels • Harshvardhan (1987) radiation scheme • Prognostic version (Pan and Randall 1998) of the Arakawa-Schubert (1974) cumulus parameterization • Mixed-layer PBL parameterization based on Deardorff (1972), as designed by (Suarez et al. 1983) and revised by Li et al. (1999, 2002). The PBL top is a coordinate surface; a cloudy sublayer develops is this top is above condensation level. • Climatological monthly-mean SSTs prescribed

  6. Experiment Design • Test the impact of orography on stratocumulus by using the UCLA AGCM • Contrast pairs of simulations: • Control: realistic orography everywhere • No-Orography: orographic surface heights set to sea-level over the African (South American) continent • Control is 20-year long.No-Orography runs are 3-year long.

  7. African Orography Contour Interval = 500m

  8. Stratocumulus Incidence in Control AGCM v7.1 2.5x2x29L

  9. Verification using NCEP Reanalysis Control NCEP Contour Int. = 2 K

  10. Impact on TOA Radiative BudgetAugust SW + LW  positive CI = 20 W/m2

  11. Annual Cycle in the Namibian Stratus Region Stratocumulus Incidence [%] Lower Tropospheric Stability [K]

  12. Longitude-Height Section of TemperatureDifference Control - No-OrographyAverage 20S-10S Pressure [mb] Longitude Contour Int. = 1K

  13. Thermodynamic Energy Equation 1 2 3 4 1: Temperature Tendency 2: Diabatic Effects 3: Vertical Advection 4: Horizontal Advection

  14. Calculation of terms in the thermodynamic equation • Monthly accumulated value of diabatic effects is provided by the model. • Monthly temperature tendency is provided by the instantaneous model output. • Horizontal advection is computed off-line from monthly-mean model output. • Vertical advection is obtained as a residual.

  15. Horizontal Temperature Advection at 700 mbAugust Control Difference NAfO Contour Interval = 0.5 K/day

  16. Annual Cycle of Thermodynamic Balance Terms700 mb Level NAfO Diabatic Heating Control Vertical Advection Horizontal Advection

  17. Anti-Cyclonic CirculationWind and Temperature at 700 mb, August Control Difference NAfO Contour Interval = 2 K Contour Interval = 0.5 K

  18. Difference Control minus NAfO900 mb Contour Interval = 1 K

  19. Thermodynamic Balance TermsPeruvian Stratus Region Control Diabatic Heating NSAO Vertical Advection Horizontal Advection

  20. Linear vs. Non-Linear Mountain Effect(after Rodwell and Hoskins 2001) Linear Response: Anti-cyclone over the mountain Non-Linear Response: Anti-cyclones to the west and east of the mountain

  21. Orographic Effects on Marine Stratocumulus • Peruvian case (“nonlinear”) West of the Andes, conservation of potential vorticity for parcels descending equatorwards along the isentropes results in increased static stability at lower levels. • Namibian case (“linear”) West of the African mountains, warm air advected polewards results in increased static stability at lower levels. The warm advection is a component of the anti-cyclonic circulation centered above the mountains. • In both cases, mountains contribute to cold advection near the surface of the ocean.

  22. Seasonal Cycle of Stratus • California stratocumulus peak in the northern summer, under the subsidence associated with the North American monsoon • Peruvian and Namibian stratocumulus have broad peaks in the austral spring. • Continental orography seems to contribute to the early start by increasing the temperature in the lower troposphere. • Continental orography also seems to contribute to the late end by advection of cold air near the surface. • Convection over the adjacent continents appears to play a minor role

  23. Annual Cycle of Simulated Stratocumulus (after AGCM revisions) 3/19/04

  24. Work in Progress • Explore role of convection over continents on marine stratocumulus; i.e., by modifying continental convection through surface boundary conditions on land surfaces. • Assess the sensitivity of AGCM simulations to different, yet realistic”, orographic distributions. • Explore these sensitivities in the context of the coupled atmosphere-ocean system. • Explore these sensitivities in the context of the PBL parameterization of PBL clouds.

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