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Madden–Julian Oscillation Cloud Population Dynamics

Explore the influence of the Madden–Julian Oscillation (MJO) on cloud population variability over the Indian and West Pacific Oceans. Learn about the episodic convective bursts, MJO phases, and importance of cloud types.

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Madden–Julian Oscillation Cloud Population Dynamics

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  1. The Precipitating Cloud Population of the Madden – Julian Oscillation over the Indian and West Pacific Oceans Hannah C. Barnes Dynamics Seminar 24 January 2013, University of Washington, Seattle, Washington

  2. What is the Madden-Julian Oscillation? • Episodic convective burst • Along equator • Indian Ocean -> dateline • 30-90 day period • Boreal Winter • Deep baroclinic circulation Madden and Julian 1972

  3. MJO in Indian and West Pacific Oceans 1 • Wheeler and Hendon Index (2004) • EOF analysis of 200 and 850 hPa zonal winds and OLR • Two PC time series • 8 phases • Significant MJO 2 3 4 5 6 7 8 OLR and 850 hPa Winds

  4. Importance of the MJO Lin et al. 2006

  5. MJO and Pacific Northwest • More precipitation, floods when convection near dateline Floods in Western Washington (Bond and Vecchi 2003) Precipitation rate anomalies

  6. MJO Structure • Convectively coupled Kelvin and Rossby waves • Eastward ~ 5 ms-1 • Air-sea interaction Rossby Wave Kelvin Wave Rui and Wang 1990

  7. Tropical Cloud Population MESOSCALE CONVECTIVE SYSTEMS (MCSs) Houze et al. 1980

  8. Importance of Cloud Population Satellite obs. • Models unrealistic without including shallow convection (Zhang and Song 2009) • MJO sensitive to deep and shallow heating (Haertel et al. 2008) Entire population No shallow Zhang and Song 2009

  9. Objectives • Variability of precipitating clouds in MJO using TRMM Precipitation Radar • Associated humidity and wind shear

  10. TRMM Satellite Instrumentation λ= 2 cm Important! PR measures 3D structure of radar echoes Kummerow et al, 1998

  11. Data and Methodology • TRMM PR • 2A23 (rain type classification) • 2A25 (attenuated corrected reflectivity) • ERA-interim reanalysis • 1999 – 2011, October – February, Wheeler and Hendon Index > 1 • Bootstrapping TRMM orbit

  12. Geographic Regions Central Indian Ocean SoutheastWest Pacific

  13. TRMM PR Identification Identify each contiguous 3D echo objectseen by TRMM PR Convective component Stratiform component Extreme characteristic Contiguous stratiform echowith horizontal area > 50 000 km2 “Broad stratiform region (BSR)” Extreme characteristic Contiguous 3D volume ofconvective echo > 30 dBZ Top height > 8 km “Deep convective core (DCC)” Horizontal area > 800 km2 “Wide convective core (WCC)” “Isolated shallow echo (ISE)” Echo top > 1 km below freezing level and separate from deeper convection Houze et al, 2007, Romatschke et al. 2010, Rasmussen and Houze 2011, Zuluaga and Houze 2013

  14. Central Indian Ocean (CIO) Analysis

  15. The MJO in the CIO 1 Transition to Active 2 Active 3 Transition to Suppressed 4 5 Suppressed 6 7 8

  16. Isolated Shallow Echoes 10N 0 % Pixels 10S 90E 60E MJO Phase % Frequency (%) 20 samples (blue), average (black), and 99% confidence interval (red)

  17. Deep Convective Cores % Pixels 0.025 MJO Phase % Frequency (%) 20 samples (blue), average (black), and 99% confidence interval (red)

  18. Broad Stratiform Regions % Pixels MJO Phase % Frequency (%) 20 samples (blue), average (black), and 99% confidence interval (red)

  19. MJO Precipitating Cloud Population • All cloud types vary significantly • ISE suppressed, 2 phases after active • DCC, WCC, and BSR simultaneous active • Areal variability - BSR dominate • Number variability • ISE dominate • WCC > DCC > BSR x104 % ISE DCC WCC BSR x10^4 250 MJO Phase MJO Phase

  20. Large-Scale Relative Humidity Number Frequency (%) 4 Pressure (hPa) 8 2-3 1 MJO Phase ISE DCC WCC BSR Relative Humidity (%) Solid lines = active, dashed = suppressed

  21. Large-Scale 1000-750 hPa Shear Shading = shear magnitude ms-1 Frequency (%) Number ISE DCC WCC BSR MJO Phase

  22. Strong Low-Level Shear Favors Development with Locally Stronger Surface Convergence Stratiform Region Convective Core Houze et al. 1989

  23. Strong Low-Level Shear Favors Development with Locally Stronger Surface Convergence C Houze et al. 1989

  24. Large-Scale 750-200 hPa Shear Shading = shear magnitude ms-1 Frequency (%) ISE DCC WCC BSR MJO Phase

  25. Very Strong Upper-Level Shear Separates Stratiform from Convective Moisture Houze et al. 1989

  26. Very Strong Upper-Level Shear Separates Stratiform from Convective Moisture Houze et al. 1989

  27. Very Strong Upper-Level Shear Separates Stratiform from Convective Moisture Houze et al. 1989

  28. Precipitating Cloud Population and Large-Scale Atmospheric Conditions

  29. Southeast West Pacific (SEWP) Analysis

  30. MJO in the SEWP 1 Suppressed 2 3 Transition to Active 4 5 Active 6 Transition to Suppressed 7 8

  31. Isolated Shallow Echoes 10N 0 % Pixels 10S 140E 170E MJO Phase % Frequency (%) 20 samples (blue), average (black), and 99% confidence interval (red)

  32. Deep Convective Cores % Pixels MJO Phase % Frequency 20 samples (blue), average (black), and 99% confidence interval (red)

  33. Broad Stratiform Regions % Pixels MJO Phase % Frequency (%) 20 samples (blue), average (black), and 99% confidence interval (red)

  34. MJO Precipitating Cloud Population • All cloud types significantly vary • ISE suppressed, 3 phases before active • BSR one phase before DCC and WCC • Areal variability - BSR dominate • Number variability • ISE dominate • DCC > WCC > BSR % x10^4 Area Number Number ISE DCC WCC BSR MJO Phase MJO Phase

  35. Large-Scale Relative Humidity Frequency (%) Number Pressure (hPa) MJO Phase 6-7 4-5 ISE DCC WCC BSR Relative Humidity (%) Solid lines = active, dashed = suppressed

  36. Large-Scale 1000-750 hPa Shear Number ISE DCC WCC BSR Frequency (%) MJO Phase Shading = shear magnitude ms-1

  37. Large-Scale 750-200 hPa Shear ISE DCC WCC BSR Frequency (%) MJO Phase Shading = shear magnitude ms-1

  38. Precipitating Cloud Population and Large-Scale Atmospheric Conditions

  39. Conclusions Precipitating Cloud Population • Precipitating cloud population varies significantly • Areal variability – BSR dominate • Number variability • ISE dominate • DCC & WCC > BSR

  40. Conclusions:Precipitating Cloud Population and Large-Scale Atmosphere • RH leads then positive feedback with the deep convection • Strong low-level shear -> strong surface convergence • Very strong upper-level shear -> stratiform torn from convective source

  41. Future Work • Kinematics and microphysics • 11 rain events, Zuluaga and Houze (2013) • Compare kinematics to TOGA COARE • Expand with microphysical data • Relate storm structure to large-scale • Modeling??? (Kingsmill and Houze 1999a)

  42. Acknowledgements • Bob Houze • Committee • Rob Wood and Mike Wallace • Beth Tully • Houze group • 626 Officemates • Grads 2010 • Family • Funding • DOE DE-SC0001164 / ER-64752 and DE-SC0008452 • DYNAMO – NSF AGS-1059611 • PMM-NASA Grant NNX10AH70.

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