Vertical Heating Structure of the MJO Based on TRMM Estimates and Multi-model Simulations UCLA Xianan Jiang Joint Institute for Regional Earth System Science.

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Vertical Heating Structure of the MJO Based on TRMM Estimates and Multi-model Simulations UCLA Xianan Jiang Joint Institute for Regional Earth System Science & Engineering (JIFRESSE) / UCLA Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 7 th Latent Heating Workgroup / NASA PMM Science Team Meeting, Aug 05, 2014

Wang (2005) x(East) PBL z y(South) EQ R-Low K-Low Sinking Warm R-Low CONV Wave-CISK Ekman-CISK WISHE Role of Diabatic Heating for the MJO “Stratiform-instability” “Radiation-convection feedback”

Jiang et al MJO Phases hPa Observed Q 1 of the MJO

20 Yr Climatological Simulations ( if AGCM) 6-hr, Global Output Vertical Structure, Physical Tendencies 20 Yr Climatological Simulations ( if AGCM) 6-hr, Global Output Vertical Structure, Physical Tendencies Commitments: About 24 Modeling Groups with 27 AGCM and/or CGCMs Model MJO Fidelity Vertical structure Multi-scale Interactions: (e.g., TCs, Monsoon, ENSO) Model MJO Fidelity Vertical structure Multi-scale Interactions: (e.g., TCs, Monsoon, ENSO) UCLA/JPL X. Jiang D. Waliser UCLA/JPL X. Jiang D. Waliser 2-Day MJO Hindcasts YOTC MJO Cases E & F (winter 2009)* Time Step, Indo-Pacific Domain Output Very Detailed Physical/Model Processes 2-Day MJO Hindcasts YOTC MJO Cases E & F (winter 2009)* Time Step, Indo-Pacific Domain Output Very Detailed Physical/Model Processes Heat and moisture budgets Model Physics Evaluation (e.g. Convection/Cloud/BL) Short range Degradation Heat and moisture budgets Model Physics Evaluation (e.g. Convection/Cloud/BL) Short range Degradation Met Office P. Xavier J. Petch Met Office P. Xavier J. Petch 20-Day MJO Hindcasts YOTC MJO Cases E & F (winter 2009)* 3-hr, Global Output Elements of I & II 20-Day MJO Hindcasts YOTC MJO Cases E & F (winter 2009)* 3-hr, Global Output Elements of I & II MJO Forecast Skill State Evolution/Degradation Elements of I & II MJO Forecast Skill State Evolution/Degradation Elements of I & II NCAS/Walker in. N. Klingaman S. Woolnough NCAS/Walker in. N. Klingaman S. Woolnough *DYNAMO Case TBD I. II. III. Model ExperimentScience FocusExp. POC Vertical Structure and Diabatic Processes of the MJO: Global Model Evaluation Project MJO Task Force/YOTC and GASS

ModelHorizontal Resolution Vertical Resolution Cumulus SchemeNotes 101_NASAGMAO_GEOS o lon x 0.5 o lat72RAS (RAS; Moorthi & Suarez 1992) 203a_SPCCSM (CAM3 + POP)T42 (~2.8 o )30 Super-parameterization (Khairoutdinov & Randall 2003) 303b_SPCAMP_AMIPT4230(Khairoutdinov & Randall 2001) _GISS_ModelE22.75 o lon x 2.2 o lat40Kim et al. (2012), Del Geino et al. (2012) 505_EC_GEM~1.4 o _MIROCT85 (~1.5 o )40Chikira scheme (Chikira and Sugiyama 2010) AMIP SST _MRI-GCMT15948 (Pan and Randall 1998) 811_CWB_GFST119 (~1 o )40 (RAS; Moorthi & Suarez 1992) 914_PNU_CFSv1T62 (~2 o )64 (RAS; Moorthi & Suarez 1992) 1016_MPI_ECHAM6 (ECHAM6 + MPIOM)T63 ( ~2 o )47(Tiedtke 1989; Nordeng 1994) 1117_MetUM_GA3 1221_NCAR_CAM5 1322_NRL_NAVGEMv.01T359 (37km)42(Hong and Pan 1996; Han and Pan 2011) 1424_UCSD_CAMT42 (~ 2.8 o )30(Zhang & McFarlane 1995) 1527_NCEPCPC_CFSv2T126 (~ 1 o )64 (Hong & Pan 1998) 1631a_CNRM_AM T127 (~1.4 o )31Bougeault (1985) 1731b_CNRM_CM (CNRM_AM+ NEMO) 1831c_CNRM_ACM 1934_CCCma_CanCM4T63(?)35(?)(Zhang & McFarlane 1995) 2035_BCCAGCM2.1T42 (~2.8 deg)26(Wu et al 2011) 2136_FGOALS2.0-sR42 (2.8 o lonx1.6 o lat)26 (Tiedtke 1989; Nordeng 1994) 2237_NCHU_ECHAM5-SITT6331 (Tiedtke 1989; Nordeng 1994) 2339_TAMU_Modi-CAM4 (CCSM4)2.5 o lon x 1.9 o lat26 (Zhang & McFarlane 1995) Idealized tilted heating 2440_ACCESS (modified METUM)1.875 o lon x 1.25 o lat85(Gregory and Rowntree 1990) 2543_ISUGCMT42 (~ 2.8 o )18(Zhang & McFarlane 1995) 2644_LLNL_CAM5ZMMicro 2745_SMHI_ecearth3T255(80km)91IFS cy36r4 Participating GCMs for Climate Simulation (Exp Component I)

Lag-regression of rainfall with Indian Ocean ( 70-90E; 5S-5N ) base point day filtered dash line – 5 m/s Jiang et al. 2014

Skill Score by Rainfall Lag-Regression Pattern (Indian Ocean & western Pacific averaged) Top 25% models Bottom 25% models

Vertical MJO Structures in Good and Poor GCMs u ’ (m/s) T’ (k) w’ (hPa/s) Q’ (k/day) q’ (g/kg) (10 o S-10 o N) Good GCMs Poor GCMs ERA-Interim Jiang, X., et al., 2014: Vertical Structure and Physical Processes of the Madden-Julian Oscillation: Exploring Key Model Physics in Climate Simulations, JGR-Atmos, submitted.

GPM Rain/LH for MJO studies 0.1 deg, 30mins, 60S-60N GPM Improved rainfall observations, algorithms for LH estimates, to depict MJO processes and constrain GCM physics

“Pre-conditioning” of the Eastward Propagating MJO Rain (mm day -1 ) Divergence (s -1 ) Cloud water (10 -5 kg kg -1 ) Q’ (k/day) Specific humidity (g/kg) Rain (mm day -1 ) Jiang et al MJO Phase 3

u’ (m/s) T’ (k) w’ (hPa/s) Q’ (k/day) q’(g/kg) Vertical structures of the MJO (ERA-Interim; lag-0 regression) Corr=0.79 Corr=0.77 Corr=0.51 Corr=0.78 Corr=0.70 Corr=0.65 Pattern Correlations of Vertical Profiles MJO Score Average Pattern Correlations of Five Variables Model Skill in Vertical Structure vs MJO Fidelity u’u’ T’ w’ Q’ q’ Jiang et al. 2014