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SUMMARY:A unified nonlinear stochastic time series analysis for climate sc
 ience - Dr. Woosok Moon\, BAS Cambridge
DTSTART:20161101T140000Z
DTEND:20161101T150000Z
UID:TALK68828@talks.cam.ac.uk
CONTACT:Dr Alexandra Weiss
DESCRIPTION:Earth's orbit and axial tilt imprint a strong seasonal cycle o
 n climatological data.  Climate variability is typically viewed in terms o
 f fluctuations in the seasonal cycle induced by higher frequency processes
 .  We can interpret this as a competition between the orbitally enforced m
 onthly stability and the fluctuations/noise induced by weather.  Here we i
 ntroduce a new time-series method that determines these contributions from
  monthly-averaged data.  We find that the spatio-temporal distribution of 
 the monthly stability and the magnitude of the noise reveal key fingerprin
 ts of several important climate phenomena\, including the evolution of the
  Arctic sea ice cover\, the El Nino Southern Oscillation (ENSO)\, the Atla
 ntic Nino and the Indian Dipole Mode.  In analogy with the classical desta
 bilising influence of the ice-albedo feedback on summertime sea ice\, we f
 ind that during some period of the season a destabilising process operates
  in all of these climate phenomena.  The interaction between the destabili
 sation and the accumulation of noise\, which we term the memory effect\, u
 nderlies phase locking to the seasonal cycle and the statistical nature of
  seasonal predictability. 
LOCATION:British Antarctic Survey\, Room 330B
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