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Evolution of the 1997 and 2002 El Nino Events: Role of Initial State versus Forcing. Eric Hackert, Joaquim Ballabrera, Antonio J. Busalacchi, Rong-Hua Zhang, and Ragu Murtugudde. Initial Conditions Prior to El Nino Year. Outline.
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Evolution of the 1997 and 2002 El Nino Events: Role of Initial State versus Forcing Eric Hackert, Joaquim Ballabrera, Antonio J. Busalacchi, Rong-Hua Zhang, and Ragu Murtugudde
Outline • Why was the evolution of the 1997 and 2002 El Nino events so different? • What was the relative role of Initial Conditions versus Forcing in these events? • Consider an OGCM simulation intialized with assimilated observations of sea level, SST, T(z), and S(z) in November of the year before El Nino • Forced with observed winds for the next 14 months, and another with climatological forcing • Conversely, the OGCM is initialized with November climatology • Forced with observed winds for the next 14 months, and another with climatological forcing • Lastly, SST simulated by these runs will be used to force a statistical atmosphere to isolate the extent of ocean-atmosphere coupling and feedback
November 1996 SST Sea Level Observed Model Data Assim SL,SST, T(z), S(z)
November 2001 Sea Level SST Observed Model Data Assim SL,SST, T(z), S(z)
Role of Initial Conditions in OGCM • November 1996 initial conditions with climatological forcing for 14 months minus Climatological initial conditions with climatological forcing • November 2002 initial conditions with climatological forcing for 14 months minus Climatological initial conditions with climatological forcing
December, 1997 December, 2002 Sea Level SST
1997 Sea Level I.C. 2002 Sea Level I.C.
Sea Level 1997 2002
SST 2002 1997
Role of Forcing in OGCM • Climatological initial conditions with 1997 forcing minus Climatological initial conditions with climatological forcing • Climatological initial conditions with 2002 forcing minus Climatological initial conditions with climatological forcing
December, 1997 December, 2002 Sea Level SST
Sea Level 1997 2002
SST 2002 1997
Role of Ocean-Atmosphere Coupling Derived from Initial Conditions • Although the role of initial conditions and forcing have been separated up to this point, it is difficult to gain information about ocean-atmosphere coupling as that signal is already built into the observed wind forcing used to drive the stand-alone ocean model • Therefore we will now force a statistical atmospheric model with the SSTs derived solely from the evolution of the initial conditions
SST 2002 1997
τx τx 1997 τx 2002
Role of SST Forcing • Some insight into the ocean to atmosphere feedback can be gained when taking the SSTs from the forcing experiment and use them to force the statistical atmosphere
SST 2002 1997
τx τx 1997 2002
ECMWF Analysis Statistical Atmosphere Role of Forcing Role of Initial Conditions τx τx τx } } { { 2002 2002 2002 { τx τx τx { 1997 1997 1997
Summary • Off-equatorial western Pacific heat content anomalies in the initial conditions prior to 1997 induce eastern equatorial warming in mid-1997 • This in turn induces a positive feedback in the ocean-atmosphere coupling giving rise to eastward propagating westerly wind anomalies and further warming • In contrast, weaker off-equatorial heat content anomalies extending further to the east prior to 2002 induce western equatorial warming in early 2002 and eastern equatorial warming in late 2002 • These initial conditions prevent the eastward extension of westerly wind anomalies in early 2002, hence most of the warming in 2002 derives from the initial conditions
Ocean Model and Forcing • Reduced-gravity, primitive equation, sigma coordinate model [Gent and Cane, 1989] • Hybrid variable depth mixed layer [Chen et al., 1994] • Advective AML coupled to OGCM [Seager et al., 1995] • Realistic coastlines for tropical Pacific (124oE-280oE, 30oN-30oS), 20 layers, roughly 1/3o at equator • Interannual Forcing: • ECMWF Analysis wind stress • Xie and Arkin + GPCP rainfall anomalies added to ISCCP seasonal cycle • NCEP reanalysis clouds • ERBE solar radiation climatology
Atmospheric Model • Statistical SVD model used to relate wind stress (τ) with sea surface temperature anomaly (SST’) • Monthly τ model formulated from ensemble mean of 24 member ECHAM 4.5 atmospheric GCM simulations for period 1963-1996 forced by observed SST’ • SVD model used routinely by hybrid coupled model [eg. Zhang and Zebiak, 2004]
MULTIVARIATE REDUCED ORDER KALMAN FILTER Truncation of error covariance: Kalman filter analysis equation: Ensemble estimate Parameterization truncation error
Assimilation Data • Sea Surface Height - TOPEX/Poseidon/Jason [Lagerloef et al., 1999] kindly provided by G. Mitchum • Sea Surface Temperature – OI of in situ and satellite observations [Reynolds and Smith, 1994] • Subsurface Temperature and Salinity – all available data from “best copy” Global Temperature-Salinity Profile Project data set [NOCD, 2006]