Seminar MJO Hamilton

Seminar MJO Hamilton

Extra-tropical impacts of the Madden-Julian-Oscillation over New Zealand from a weather regime perspective


Nicolas Fauchereau

February 15, 2016


  1. Extra-tropical impacts of the Madden-Julian-Oscilla8on over New Zealand from a

    weather regime perspec8ve* Nicolas Fauchereau1 Benjamin Pohl2 Andrew Lorrey3 * Journal of Climate, in press, DOI hEp:// 1: NIWA, Hamilton, New Zealand 2: Centre de Recherches de Climatologie, Dijon, France 3: NIWA, Auckland, New Zealand
  2. Who is this guy ? •  Nicolas (Nico) Fauchereau • 

    Ph. D. in France in 2004 •  One year post-doc in Paris: stats, EVT, Weather Regimes over NA / Europe •  Post-doctoral fellowship at the ocean. dept., University of Cape-Town: scale-interac8ons in the climate system •  Senior Researcher at the CSIR (Cape-Town): climate controls on primary produc]on in the Southern Ocean •  Joined NIWA in 2012 (in Auckland): from paleo-climate reconstruc]ons to seasonal forecas]ng
  3. Interests •  Sta]s]cs •  Time-series analysis (EMD, wavelets, etc.) • 

    Machine Learning •  Scien]fic Compu]ng (Python !) •  Open source and open science (Soaware Carpentry instructor) •  Surf !
  4. Back to science !

  5. What is the Madden-Julian-Oscilla8on (MJO) ?

  6. •  An oscilla8on in tropical climate discovered by Roland Madden

    and Paul Julian in 1971 •  Largest mode of intra-seasonal variability in the tropics •  Involves coupling between deep convec]on, atmospheric circula]on, SSTs •  Propagates eastward at ~ 4 to 8 m/s: typically circles the globe in 30 to 60 days: intra-seasonal
  7. From: hEps:// “dipole” in convec8on, precipita8on, etc.

  8. Measuring and monitoring the MJO Wheeler and Hendon (2004): EOF

    of combined OLR, zonal wind at 850 and 200 hPa in the tropics First 2 PCs (RMM1 & RMM2) are in quadrature Composite OLR anomalies (Nov. – Mar.) Phase space representa]on of the MJO propaga]on
  9. The MJO significance in the tropics – Rainfall – SSTs – Subsurface ocean

    (> 1500m deep !) – Tropical Cyclones – …
  10. The MJO outside the tropics: impacts, predictability Northern Hemisphere: – 

    European sector (Cassou 2008, Nature) –  American sector (Riddle et al 2012, J. Climate) Weather Regime (WR) view (WR~ aEractor basins in the phase space of the atmospheric circula]on / recurrent archetypes in circula]on anomalies) Interac]ons with the Arc]c Oscilla]on (AO) / North Atlan]c Oscilla]on (NAO) regimes Significant source of predictability (Cassou 2008) at ]me-scales > 15 days
  11. Southern Hemisphere: –  South Africa (Pohl, Fauchereau et al, 2010)

    –  South America (Carvalho, 2008) –  Southern high la]tudes (debatable) –  Interac]ons possible with the Southern Annular Mode (debatable) No Weather Regime view No discussion of poten8al for predictability The MJO outside the tropics: impacts, predictability
  12. This study •  Is there a signal of the MJO

    over NZ ? •  Can we explain it adop]ng the paradigm of weather regimes ? •  Is there any poten]al for predictability for NZ climate arising from the MJO ? •  Is the Southern Annular Mode involved ?
  13. The MJO over the NZ sector rainfall circula]on

  14. The MJO over the NZ sector Interac]ons with topography

  15. The MJO over the NZ sector ~ Opposite spa]al PaEerns

    between opposite phases of the MJO Interac]ons with topography
  16. Weather regimes and the Kidson Types •  WRs: aYractors in

    the climate system •  Archetypes in atmospheric circula]on •  Usually extracted using clustering methods •  Provide the link between weather (day to day variability) and climate (e.g. large-scale modes of variability) North Atlan]c / European WRs
  17. •  Kidson (2000): EOF then k-means clustering of 1000 hPa

    NCEP / NCAR field (1958-1997) •  Updated on an opera]onal basis (Renwick, 2011) •  12 “types” (WRs) •  3 “regimes” (groups) Circula]on (1000 hPa) and rainfall anomalies associated with each KT
  18. A regime view of the MJO signal How is the

    probability of the Kidson Types modulated by the MJO ? Test is based on a Monte-Carlo approach using 10000 ar]ficial realiza]ons (discrete ]me Markov Chains) of the Kidson Types sequences MJO phase Kidson Types
  19. A regime view of the MJO signal “Zonal” WRs occurences

    increased during the 1st half of the MJO cycle / reduced during the 2nd half
  20. A regime view of the MJO signal NE type (WR)

    almost 2 8mes more likely than normal during phase 6 of the MJO
  21. A regime view of the MJO signal

  22. Predictability ? Lag (days) Kidson Type

  23. Predictability ? •  Significant changes in the frequency of some

    WRs up to ~ 20 days aaer given MJO phase is observed
  24. Predictability ? •  Significant changes in the frequency of some

    WRs up to ~ 20 days aaer given MJO phase is observed •  Difference (in days) between the ]ming of ~ maximum delayed response consistent with MJO phase speed.
  25. Summary •  Significant impacts of the MJO on NZ • 

    Explained partly by changes in the probability or regional Weather Regimes (Kidson types) •  Lagged rela]onships •  Not primarily mediated by the Southern Annular Mode •  Poten]al for predictability beyond meteorological ]me-scales
  26. Supplementary slides

  27. SAM vs MJO

  28. KT vs SAM

  29. KT vs SAM