Process-Oriented MJO Simulation Diagnostic: Moisture Sensitivity of Simulated Convection

Process-oriented diagnostics for Madden‐Julian oscillation (MJO) simulations are being developed to facilitate improvements in the representation of the MJO in weather and climate models. These processoriented diagnostics are intended to provide insights into how parameterizations of physical processes in climate models should be improved for a better MJO simulation. This paper proposes one such processoriented diagnostic, which is designed to represent sensitivity of simulated convection to environmental moisture: composites of a relative humidity (RH) profile based on precipitation percentiles. The ability of the RH composite diagnostic to represent the diversity of MJO simulation skill is demonstrated using a group of climate model simulations participating in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5). A set of scalar process metrics that captures the key physical attributes of the RH diagnostic is derived and their statistical relationship with indices that quantify the fidelity of the MJO simulation is tested. It is found that a process metric that represents the amount of lower-tropospheric humidity increase required for a transition from weak to strong rain regimes has a robust statistical relationship with MJO simulation skill. The results herein suggest that moisture sensitivity of convection is closely related to a GCM’s ability to simulate the MJO.

[1]  P. R. Julian,et al.  Description of Global-Scale Circulation Cells in the Tropics with a 40–50 Day Period , 1972 .

[2]  A. Arakawa,et al.  Interaction of a Cumulus Cloud Ensemble with the Large-Scale Environment, Part I , 1974 .

[3]  Stephen J. Lord,et al.  Interaction of a Cumulus Cloud Ensemble with the Large-Scale Environment. Part III: Semi-Prognostic Test of the Arakawa-Schubert Cumulus Parameterization , 1982 .

[4]  P. Bougeault,et al.  A Simple Parameterization of the Large-Scale Effects of Cumulus Convection , 1985 .

[5]  A. Betts,et al.  A new convective adjustment scheme. Part II: Single column tests using GATE wave, BOMEX, ATEX and arctic air‐mass data sets , 1986 .

[6]  A. Kitoh,et al.  The equatorial 30-60 day oscillation and the Arakawa-Schubert penetrative cumulus parameterization , 1988 .

[7]  M. Tiedtke A Comprehensive Mass Flux Scheme for Cumulus Parameterization in Large-Scale Models , 1989 .

[8]  P. Rowntree,et al.  A Mass Flux Convection Scheme with Representation of Cloud Ensemble Characteristics and Stability-Dependent Closure , 1990 .

[9]  K. Emanuel A Scheme for Representing Cumulus Convection in Large-Scale Models , 1991 .

[10]  S. Moorthi,et al.  Relaxed Arakawa-Schubert - A parameterization of moist convection for general circulation models , 1992 .

[11]  M. Yao,et al.  Efficient Cumulus Parameterization for Long-Term Climate Studies: The GISS Scheme , 1993 .

[12]  I. Bladé Dynamics, Thermodynamics and Extratropical Interactions of Tropical Intraseasonal Oscillations in a Simple Nonlinear Model. , 1993 .

[13]  D. Randall,et al.  Low-Frequency Oscillations in Radiative-Convective Systems , 1994 .

[14]  N. McFarlane,et al.  Sensitivity of Climate Simulations to the Parameterization of Cumulus Convection in the Canadian Climate Centre General Circulation Model , 1995, Data, Models and Analysis.

[15]  D. Randall,et al.  Low-Frequency Oscillations In Radiative-Convective Systems. Part II: An Idealized Model. , 1995 .

[16]  A. Matthews,et al.  Intraseasonal oscillations in 15 atmospheric general circulation models: results from an AMIP diagnostic subproject , 1996 .

[17]  H. Hendon,et al.  Propagating and Standing Components of the Intraseasonal Oscillation in Tropical Convection , 1997 .

[18]  David A. Randall,et al.  A cumulus parameterization with a prognostic closure , 1998 .

[19]  Michael E. Schlesinger,et al.  The Dependence on Convection Parameterization of the Tropical Intraseasonal Oscillation Simulated by the UIUC 11-Layer Atmospheric GCM , 1999 .

[20]  Misako Kachi,et al.  Abrupt termination of the 1997–98 El Niño in response to a Madden–Julian oscillation , 1999, Nature.

[21]  E. Maloney,et al.  Modulation of hurricane activity in the gulf of mexico by the madden-julian oscillation , 2000, Science.

[22]  Charles Jones,et al.  Occurrence of Extreme Precipitation Events in California and Relationships with the Madden–Julian Oscillation , 2000 .

[23]  B. Weare,et al.  The Onset of Convection in the Madden–Julian Oscillation , 2001 .

[24]  Toru Nozawa,et al.  Importance of Cumulus Parameterization for Precipitation Simulation over East Asia in June , 2001 .

[25]  D. Raymond A New Model of the Madden–Julian Oscillation , 2001 .

[26]  E. Maloney,et al.  The Sensitivity of Intraseasonal Variability in the NCAR CCM3 to Changes in Convective Parameterization , 2001 .

[27]  J. Susskind,et al.  Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations , 2001 .

[28]  G. Meehl,et al.  AGCM simulations of intraseasonal variability associated with the Asian summer monsoon , 2003 .

[29]  K. Sperber Propagation and the Vertical Structure of the Madden Julian Oscillation , 2003 .

[30]  I. Kang,et al.  Impacts of cumulus convection parameterization on aqua-planet AGCM simulations of tropical intraseasonal variability , 2003 .

[31]  A. Sobel,et al.  A Simple Time-Dependent Model of SST Hot Spots , 2003 .

[32]  Jialin Lin,et al.  Radiation Budget of the Tropical Intraseasonal Oscillation , 2004 .

[33]  Pedro M. M. Soares,et al.  Sensitivity of moist convection to environmental humidity , 2004 .

[34]  Matthew E. Peters,et al.  Relationships between Water Vapor Path and Precipitation over the Tropical Oceans , 2004 .

[35]  Chidong Zhang,et al.  Madden‐Julian Oscillation , 2005 .

[36]  Duane E. Waliser,et al.  Intraseasonal Variability in the Atmosphere-Ocean Climate System , 2005 .

[37]  M. Wheeler,et al.  Australian-Indonesian monsoon , 2005 .

[38]  Mingquan Mu,et al.  Simulation of the Madden–Julian Oscillation in the NCAR CCM3 Using a Revised Zhang–McFarlane Convection Parameterization Scheme , 2005 .

[39]  Kerry A. Emanuel,et al.  On the Role of Moist Processes in Tropical Intraseasonal Variability: Cloud–Radiation and Moisture–Convection Feedbacks , 2005 .

[40]  S. Gualdi,et al.  The Madden–Julian oscillation in ECHAM4 coupled and uncoupled general circulation models , 2005 .

[41]  Philip J. Rasch,et al.  Tropical Intraseasonal Variability in 14 IPCC AR4 Climate Models. Part I: Convective Signals , 2006 .

[42]  A. A new convective adjustment scheme. Part I: Observational and theoretical basis , 2006 .

[43]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[44]  John F. B. Mitchell,et al.  THE WCRP CMIP3 Multimodel Dataset: A New Era in Climate Change Research , 2007 .

[45]  R. Neale,et al.  The Impact of Convection on ENSO: From a Delayed Oscillator to a Series of Events , 2008 .

[46]  Philip J. Rasch,et al.  Effects of Convective Momentum Transport on the Atmospheric Circulation in the Community Atmosphere Model, Version 3 , 2008 .

[47]  I. Kang,et al.  The Impacts of Convective Parameterization and Moisture Triggering on AGCM-Simulated Convectively Coupled Equatorial Waves , 2008 .

[48]  Convection in a Parameterized and Superparameterized Model and Its Role in the Representation of the MJO , 2009 .

[49]  J. David Neelin,et al.  Moisture Vertical Structure, Column Water Vapor, and Tropical Deep Convection , 2009 .

[50]  Richard Neale,et al.  Application of MJO Simulation Diagnostics to Climate Models , 2009 .

[51]  Patrick T. Haertel,et al.  Convectively coupled equatorial waves , 2009 .

[52]  Katherine Thayer-Calder,et al.  The Role of Convective Moistening in the Madden–Julian Oscillation , 2009 .

[53]  E. Maloney,et al.  Intraseasonal Variability in an Aquaplanet General Circulation Model , 2010 .

[54]  E. Maloney,et al.  Effect of SST Distribution and Radiative Feedbacks on the Simulation of Intraseasonal Variability in , 2011 .

[55]  I. Kang,et al.  A bulk mass flux convection scheme for climate model: description and moisture sensitivity , 2011, Climate Dynamics.

[56]  J. Thepaut,et al.  The ERA‐Interim reanalysis: configuration and performance of the data assimilation system , 2011 .

[57]  E. Maloney,et al.  A Systematic Relationship between Intraseasonal Variability and Mean State Bias in AGCM Simulations , 2011 .

[58]  Eric D. Maloney,et al.  The Role of Moisture-Convection Feedbacks in Simulating the Madden-Julian Oscillation , 2011 .

[59]  S. Schubert,et al.  MERRA: NASA’s Modern-Era Retrospective Analysis for Research and Applications , 2011 .

[60]  E. Maloney,et al.  Intraseasonal moist static energy budget in reanalysis data , 2011 .

[61]  Z. Kuang,et al.  Modulation of radiative heating by the Madden‐Julian Oscillation and convectively coupled Kelvin waves as observed by CloudSat , 2011 .

[62]  Richard Neale,et al.  Temperature–Moisture Dependence of the Deep Convective Transition as a Constraint on Entrainment in Climate Models , 2012 .

[63]  Eric D. Maloney,et al.  An Idealized Semi-Empirical Framework for Modeling the Madden–Julian Oscillation , 2012 .

[64]  P. Xavier Intraseasonal Convective Moistening in CMIP3 Models , 2012 .

[65]  B. Mapes,et al.  Differences between More Divergent and More Rotational Types of Convectively Coupled Equatorial Waves. Part I: Space–Time Spectral Analyses , 2012 .

[66]  Karl E. Taylor,et al.  An overview of CMIP5 and the experiment design , 2012 .

[67]  Daehyun Kim,et al.  Simplified metrics for the identification of the Madden–Julian oscillation in models , 2012 .

[68]  Ali Behrangi,et al.  On the quantification of oceanic rainfall using spaceborne sensors , 2012 .

[69]  Z. Kuang,et al.  Moist Static Energy Budget of MJO-like Disturbances in the Atmosphere of a Zonally Symmetric Aquaplanet , 2012 .

[70]  Yonghua Chen,et al.  CORRIGENDUM of the MJO Transition from Shallow to Deep Convection in Cloudsat-Calipso Data and GISS GCM Simulations , 2012 .

[71]  Daehyun Kim,et al.  The Tropical Subseasonal Variability Simulated in the NASA GISS General Circulation Model , 2012 .

[72]  Eric D. Maloney,et al.  Moisture Modes and the Eastward Propagation of the MJO , 2013 .

[73]  E. Maloney,et al.  Madden-Julian Oscillation Task Force : a joint effort of the climate and weather communities , 2013 .

[74]  Daehyun Kim,et al.  MJO and Convectively Coupled Equatorial Waves Simulated by CMIP5 Climate Models , 2013 .

[75]  B. Stevens,et al.  The Madden-Julian Oscillation in ECHAM6 and the Introduction of an Objective MJO Metric , 2013 .

[76]  Lamont-Doherty Earth Observatory Propagating versus Nonpropagating Madden – Julian Oscillation Events , 2013 .

[77]  A. Sobel,et al.  Propagating versus Nonpropagating Madden–Julian Oscillation Events , 2014 .