1. 6. MJO-TF/GASS Multi-Model Diabatic Processes Experiment Observational products and reanalysis are starting to give estimates of vertical diabatic heating, but what do the models look like? Are the observations good enough? These are some of the questions we hope to answer with this new sub-project. MJO Task Force: Summary of activities and accomplishments Co-chairs: Matthew Wheeler (CAWCR/Bureau of Meteorology/Australia) and Duane Waliser (JPL/Caltech/USA) Members Ken SperberProgram for Climate Model Diagnostics and Intercomparison Harry HendonCentre for Australian Weather and Climate Research Eric MaloneyColorado State University Xiouhua FuUniversity of Hawaii Jon GottschalckNational Centers for Environmental Prediction Richard NealeNational Center for Atmospheric Research Chidong ZhangUniversity of Miami Daehyun KimColumbia University Augustin VintzileosNational Centers for Environmental Prediction Frederic VitartEuropean Centre for Medium-range Weather Forecasting Dave RaymondNew Mexico Institute of Mining & Technology Masaki SatohFrontier Research Center for Global Change Hai LinEnvironment Canada Prince XavierUK Met Office Important others June-Yi Lee, Xianan Jiang, Jon Petch, Steve Woolnough, Nick Klingaman Established in early 2010 for an initial term of 3 years Sponsor: WCRP-WWRP/THORPEX under YOTC Follow on from the US-CLIVAR MJO Working Group Overall goal: Facilitate improvements in the representation of the MJO in weather and climate models in order increase the predictive skill of the MJO and related weather and climate phenomena. 1. Web site - www.ucar.edu/yotc/mjo.html The MJO-TF web site includes teleconference minutes, summary of past and present activities, related papers and presentations, and links to our related activities. 2. Workshop at APCC, South Korea BAMS Summary: Hendon, Sperber, Waliser, and Wheeler (September 2011) 3. Forecast model diagnostics/metrics and verification Continuing work on model MJO forecasts and their verification. 14Nov2011 Operational Dynamical Model Forecasts of the Real-time Multivariate MJO (RMM) index displayed at CPC-NCEP. Development of a similar index focussing on the boreal summer intraseasonal oscillation for the Indian/Asian summer monsoon. ● Co-development of the ISV Hincast Experiment hosted at the IPRC – designed for MJO and other ISV prediction and predictability studies. ● Involvement of MJO-TF members in MJO forecasting for DYNAMO/CINDY. 4. Simple metrics for Climate Metrics Panel Offering guidance on simple MJO performance metrics for assessing CMIP models. Idea #1: Project model data on observed EOF pair and determine the maximum correlation and lag of that correlation between the projection coefficients. Idea #2: Wavenumber- frequency spectral power in a box. 5. Process-oriented diagnostics/metrics Development and continuing refinement of a set of process-oriented diagnostics for the evaluation of the MJO and related processes in dynamical models. One aspect of the treatment of convection that appears important is the relationship between precipitation rate and column saturation fraction. Having precipitation rate increase exponentially with saturation fraction appears to be a necessary, but not sufficient, condition for a good MJO simulation (Zhu et al., 2009) The vertical distribution of moisture as a function of precipitation rate also appears important (Kim et al., 2009) Models that have a better match with the observed RH vertical structure (and as a function of precipitation rate) tend to have a stronger MJO (as measure by the east/west power ratio metric). Vertical-temporal evolution of anomalous heating Q 1 or Q 1 -Q R for TRMM SLH (colour shading) and TRMM 3B42 rainfall (black lines). There are 3 modelling components, allowing for a focus on different aspects of the science. Cases have been selected from YOTC, with DYNAMO/CINDY cases to be determined later. Summary  Please consider utilizing community MJO simulation diagnostics/metrics (see CLIVAR MJO Working Group paper in Journal of Climate, 2009).  Offer suggestions for process-oriented diagnostics associated with the MJO (see box #5).  Refer to, explore uses, and provide feedback on operational MJO/ISV forecast metrics (see box #3).  Participate in, contribute to, and/or analyse the community modelling experiments such as the ISVHE (see box #3) and MJO-TF/GASS projects (see box #6). We are also considering adding another sub-project on the modulation of TCs by the MJO/ISV and the prediction of this modulation. Thankyou for your participation and support of these activities over the last several years. Further information: m.wheeler@bom.gov.au and duane.e.waliser@jpl.nasa.govm.wheeler@bom.gov.auduane.e.waliser@jpl.nasa.gov Jiang et al. (2011)