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Mesoscale Convective Systems in the Initiation of the MJO

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  1. Mesoscale Convective Systems in the Initiation of the MJO Jian Yuan and Robert A. Houze University of Washington CloudSat/CALIPSO Science Team Meeting Montreal, Quebec, Canada, 16 June 2011

  2. The Madden-Julian Oscillation (MJO): • Play important roles in weather and climate • Current prediction skill, especially for the initial phase of MJO is very limited • Cumulus parameterizations in GCMs is the primary limiting factor in MJO simulation and prediction. • (Zhang et al. 2010, DYNAMO) (Courtesy of US CLIVAR MJO Working Group)

  3. MJO initiation processes • Feedbacks between: • Clouds • Radiative heating • Convection • Precipitation • Ocean • are a key to understanding the MJO. • Fundamental processes related to MCSs that are crucial to understand MJO: • the diabatic heating structure • convective sensitivity to environmental moisture • cloud microphysics • convective organization Courtesy of Zhang et al. 2009, DYNAMO After Stephens et al. 2004, “Humidistat Feedback”

  4. MCSs including both raining and anvil components are identified using A-Train instruments Yuan and Houze 2010

  5. MODIS TB11 + AMSR-E (Yuan and Houze 2010) combined to find“cold centers” & “raining areas” Locate 1st closed contour Use 260 K threshold Associate pixels with nearest cold center Use 1 mm/h threshold for rain rate Use 6 mm/h threshold for heavy rain

  6. MCS Criteria (Yuan and Houze, 2010) • Systems whose largest raining cores have • Area > 2000 km2 • Min TB11 ≤ 220 K • Must have one dominant core • with intense cells, and • accounting for >70% rain area 56% all tropical rain

  7. MCSs are further divided to two groups : Separated(40 % rain fall) Connected (>=3 MCSs share the same rain feature, 16% rain fall) • Separated MCS: Frequently found over all convective zones, especially continents • Connected MCS: more organized convection, primarily found over warm ocean area

  8. MODIS/AMSR-E/CloudSat identifies MCSs obtains the global distribution of MCSs investigates variability of MCSs in MJO (EIO:-15-15oN;75-100oE; Composite of 8 phases; Wheeler and Hendon 2004)

  9. More Connected MCSs observed in MJO active phases OLR

  10. Deeper MCSs observed in pre-onset, initial and active phases

  11. Low level Θe likely determines the Tb_min (“hot tower” hypothesis) • Climatology of EIO: • T150 hp ≈ 205 K • Θe150 hp≈ 352.6 K Phase 1-3 Phase 5-7

  12. Moisture effects need to be better understood More MCSs; more organized Less MCSs; less organized Deeper MCSs

  13. Summary and Conclusions • A-Train instruments make it possible to identify MCSs (raining + anvil components) globally • MJO pre-onset phase  active phases over EIO: • Deeper MCSs & Warmer low level Θe (both) • Less More MCSs • Relatively Less More organized MCSs • Drier Moistermiddle troposphere • The moisture effect needs to be better understood.

  14. End

  15. MJO activities viewed in OLR

  16. MCSs Over the Whole Tropics: oceanic conditions favor larger systems Smallest 25% (<12,000 km2) Largest 25% (>40,000 km2) “Superclusters”