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” Use 260 K threshold Locate 1 st closed contour Use 1 mm/h threshold for rain rate Associate pixels with nearest cold center Use 6 mm/h threshold for heavy rain

6. MCS Criteria (Yuan and Houze, 2010) Systems whose largest raining cores have Area > 2000 km 2 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 : 1.Separated (40 % rain fall) 1.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:-15-15 o N;75-100 o E; 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) Phase 1-3 Phase 5-7 Climatology of EIO: T 150 hp ≈ 205 K Θe 150 hp ≈ 352.6 K

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

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  Moister middle 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 km 2 ) Largest 25% (>40,000 km 2 ) “Superclusters”