WGNE MJO Task Force : Current Activities and Next Steps

1. WGNE MJO Task Force:Current Activities and Next Steps Steve Woolnough on Behalf of the WGNE MJO Task Force

2. MJO Task Force: Background • Renewed in early 2013 for a term of 3 years, extend in Dec 2015 for a further 3 years • Sponsor: Working Group on Numerical Experimentation (WGNE) • Follow on from the WCRP-WWRP/THORPEX/YOTC MJOTF and US CLIVAR MJO Working Group • Website: http://www.wmo.int/pages/prog/arep/wwrp/new/MJO_Task_Force_index.html Members Steve Woolnough University of Reading (co-chair) Eric Maloney Colorado State University (co-chair) Charlotte DeMottCMMAP/Colorado State Univ Jon Gottschalck National Centers for Environmental Prediction Daehyun Kim University of Washington Nick Klingaman University of Reading Tieh-Yong KohSIM University June-Yi Lee Pusan National University Adrian Matthews University of East Anglia Tomoki Miyakawa AORI/ University of Tokyo Richard Neale National Center for Atmospheric Research Camille Risi IPSL/Laboratoire de Météorologie Dynamique Ken Sperber PCDMI/Lawrence Livermore National Laboratory Matthew Wheeler Centre for Australian Weather and Climate Research Prince Xavier UK Met Office Important others and former members X. Jiang, D. Waliser, J. Petch, F. Vitart, J. Benedict, H. Hendon, D. Raymond, Xiouhua Fu, Chidong Zhang, Augustin Vintzileos, Masaki Satoh, Hai Lin, Mitch Moncrieff, Min-SeopAhn, Hae-Jeong Kim, Surya Rao, Jerome Vialard

3. Overall Goal: Facilitate improvements in the representation of the MJO in weather and climate models in order to increase the predictive skill of the MJO and related weather and climate phenomena. Organizedinto 5 Subprojects • Development of process-oriented diagnostics/metrics for MJO simulation • Ongoing evaluation of real‐time forecasts and hindcasts of tropical intraseasonal variability, including assessment of hindcasts in the S2S model database • Develop, coordinate, and promote analyses of MJO air-sea interaction • Advance understanding of MJO interactions with the Maritime Continent • Develop, coordinate, and promote analyses of MJO interactions with the extratropics

4. Process Orientated Diagnostics MJO Moisture-convection coupling Cumulus convection Radiation Cloud-radiation interaction Cloud microphysics Cloud macrophysics Surface flux feedback Boundary layer Surface flux Goal: Provide insight into how parameterizations should be improved to enhance MJO simulation for the correct physical reason • Diagnostics should be relevant to: • resolved‑scale processes that are important in MJO dynamics • unresolved‑scale processes (i.e. parameterizations) in GCMs • Activity is ongoing with a focus on the moist static energy budget and contributions to its evolution (dynamical and physical) • Developing ideas around linking to particular theoretical models resolved‑scale processes parameterized processes

5. Evaluation of real‐time forecasts and hindcasts of tropical ISV, including assessment of hindcasts in the S2S model database • Real-time monitoring of operational MJO and BSISO forecasts ongoing at NCEP, APCC • Paper on Boreal Winter Operational MJO in preparation (Gottschalck et al.) • Discussions with S2S on • Real-time production and sharing of MJO, BSISO metrics • assessment of MJO/BSISO forecast skill • Analysis and Assessment of MJO/BSISO as a source of predictability and/or skill in the tropics • What is the spread/skill relationship in sub-seasonal forecasts for MJO/BSISO? • Relationships between forecast skill of large-scale ISV indices and forecast skill local “weather” • An example motivating science questions of interest. • What large-scale factors may control MJO predictability/prediction skill (e.g. interesting but explained relationship with the QBO)?

6. QBO and MJO (figures courtesy of Harry Hendon) Zonal mean zonal wind 50hPa (10N-10S) Amp(t)= sqrt(rmm12+rmm2**2) Filter with 90 d running mean Strongly correlated during austral summer: (sig test takes into account auto correlation of QBO index) Implies predictions of MJO should be better during EQBO, based on previous studies that show predictive skill of MJO varies with MJO amplitude

7. QBO and MJO (figures courtesy of Harry Hendon) From available S2S forecasts, verified with NNR DJF RMM skill for QBOE and QBOW years Days for Bivariate correlation <0.6 Potential predictability =sqrt(ensmnVar/ totensVar) POAMA 1980-2014 Vector auto regressive persistence

8. Air-sea interaction in the MJO Goal: To develop, coordinate, and promote analyses of MJO air‐sea interaction, including development of diagnostics that relate MJO simulation capability to fidelity in simulating key air‐sea interaction processes. • Comprehensive review of air-sea interaction in the MJO (DeMott et al., Rev. Geophys., 2015) • Impact of atmospheric tropical intraseasonal variability on ocean relatively well understood, except in and around Maritime Continent region • Feedback of oceanic variability on tropical atmospheric very much less well understood, need for new diagnostics • How important are SST feedbacks • What are the mechanisms through which the SST variability influences the MJO • Modelling experiments often complicated by combined impacts of coupling and basic state changes • Strong recommendation against the use of experiments with daily evolving prescribed SSTs

9. Air-sea interaction in the MJO • Development of Air-sea interaction diagnostics (De Mott et al., 2016 in review) • Set of diagnostics to describe tropical intraseasonal variability in key surface and atmospheric/ocean fields and their relationship to the MJO • Development of diagnostics to highlight the influence of SST variability on the MJO through a moist static energy budget framework • Currently address influence of SST variability on surface turbulent flux contribution to the MSE budget (we might consider this a local effect) • Does not currently address the impact of non-local effects e.g. changes in SST gradients influencing large-scale circulation and e.g. moisture convergence • Diagnostics coded in ncl and will be made publically available in the future (c.f. MJO simulation diagnostics) • Application of these diagnostics to a set of models (De Mott, Klingaman ongoing activities)

10. Example Diagnostics

11. Example Diagnostics Lag regression of LH flux onto intraseaonsal SST (at a single point) Intraseasonal SST variation • increases thermodynamic component of intraseasonal LH flux and oppose wind driven component • Thermodynamic component and hence total is phase shifted relative to LH flux without intraseasonal SST variability • Can subsequently examine impact on MSE budget • Caveat these effects are, local, and a based on an analysis of the MJO which has felt the coupled feedbacks

12. Interactions of the MJO with the Maritime Continent Goal: To improve our understanding of the MJO with Maritime Continent, its influence on the propagation of the MJO, its modulation of the local “weather”; and the capability of our weather and climate models to capture these interactions • Jointly organized activity with the S2S project • Possibility to interact with the efforts for an internationally coordinated observational and modelling programme (YMC) • Joint MJOTF/S2S Workshop on “Interactions between the MJO and Maritime Continent”, Singapore, 11-13 April, 2016, • hosted by the Meteorological Service of Singapore and the National Environment Agency

13. Interactions of the MJO with the Maritime Continent • Some motivating questions for the joint MJOTF/S2S project • What is the current skill of operation systems at predicting the passage of precipitating/active phases of the MJO into and across the MC, including aspects such as reliability? • What processes determine whether individual MJOs propagate through the Maritime Continent? • How is the simulated propagation of the MJO through the Maritime Continent related to biases in models? • How does the partitioning of variability from diurnal to seasonal, including equatorial wave characteristics, influence the MJO and MC interaction? • Does the above partitioning depend on model resolution, and is accordingly affected by the use of explicitly resolved convection versus parameterized convection? • How does the ocean-atmosphere coupling in the context of the MC influence the MJO and MC interaction? • How does topography versus land-sea contrast play a role in the MJO and MC interaction? • How do land-atmosphere interactions (temperature, soil moisture, diurnal cycle) influence the MJO and MC interaction? • How is forecast skill associated with the MJO over the MC influenced by the above science elements?

14. Workshop on Intraseasonal Processes and Prediction in the Maritime Continent • Goals: • To assess the state of our knowledge and to identify emerging research priorities related to MJO interaction with the Maritime Continent • Advance understanding of MJO – MC interactions with the intention of improving subseasonal prediction in the MC and globally • Key Areas: • Interactions of the MJO in the MC region with: Diurnal cycle, synoptic variability, the monsoons, interannual variability, the land surface, the ocean • NWP and climate model simulations of subseasonal variability in the MC region, focusing on: Model bias and other errors, subseasonal prediction

15. Workshop on Intraseasonal Processes and Prediction in the Maritime Continent • Sessions on • Interactions of the MJO in the MC Region with the Diurnal Cycle • Interactions of the MJO in the MC Region with Synoptic Variability, the Monsoons, and Interannual Variability • Interactions of the MJO in the MC Region with the Ocean • Interactions of the MJO in the MC Region with the Land • Model Simulations of Subseasonal Variability in the MC Region • Discussion: • Assess our state of our knowledge on MJO interactions with the MC • Identify emerging research priorities • Identify strategies to address deficiencies in our understanding • How can weather forecasts and climate model simulations of the MJO and related phenomena be improved?

16. Workshop on Intraseasonal Processes and Prediction in the Maritime Continent • Around 60 invited participants, including from local region (although perhaps not as many as we would like) • Invited and contributed talks, along with posters • Summary in preparation for S2S newsletter

17. Workshop on Intraseasonal Processes and Prediction in the Maritime Continent • Some actions/outcomes/discussion points (note discussions about which activities to take forward and how are still ongoing) • Need for analysis of relationship between MJO and local weather, and an assessment of the MJO related forecast skill • Local Met Services often have (or have access to) good local datasets, possible role for TF/S2S in coordinating consistent analysis of the MJO related variability and forecast skill • Development of process orientated diagnostics related specifically to MJO propagation into and through the Maritime Continent, including e.g. • Air-sea interaction • Diurnal cycle • Extension of existing MJO metrics • Discussion around initiating coordinated modelling case studies within S2S framework

18. Analysis of MJO interactions with the extra-tropics Goal: To improve our understanding of the interactions between the MJO and the extratropics, their dependence on the slowly varying background state; and their representation (and the source of errors in this representation) in weather and climate models • New activity still under development • Joint activity with new S2S teleconnections sub-project • Review paper in preparation (led by S2S sub-project) but with contributions from TF members • A number of TF members have funded projects to address aspects of this questions.

19. Some housekeeping • Eric Maloney is standing down as co-chair with effect from 1st May 2016 and will be replaced by Daehyun Kim • Jon Gottschalck has indicated that because of other commitments he feels he should stand down from the TF and we are discussing an appropriate replacement • We’re discussing the timing and location of our next face to face meeting in 2017, which will be attached to a relevant international meeting.

20. LH component regression maps

21. SST effect summary