weather regime perspec8ve* Nicolas Fauchereau1 Benjamin Pohl2 Andrew Lorrey3 * Journal of Climate, in press, DOI hEp://dx.doi.org/10.1175/JCLI-D-15-0152.1 1: NIWA, Hamilton, New Zealand 2: Centre de Recherches de Climatologie, Dijon, France 3: NIWA, Auckland, New Zealand
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
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
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
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
– 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
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 ?
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
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
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.
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