El-Nino, climatic variability and North El-Nino, climatic variability and North Pacific Surface Temperature Fields Pacific Surface Temperature Fields

AnalysisAnalysis

Prof. Victor I.KuzinProf. Victor I.Kuzin

Institute of Computational Institute of Computational Mathematics & Mathematical Mathematics & Mathematical

Geophysics SD RAS,Geophysics SD RAS,

Novosibirsk, 2005Novosibirsk, 2005

ObjectivesObjectives

The Pacific Ocean is the source of the climatic variability influencing to the atmospheric processes not only in local, but also in global scales. The mostly strong signal is the El-Nino/Southern Oscillation (ENSO) representing the inter-annual variability in tropics. In the middle latitude there exist the inter-decadal signal, so called the Pacific Decadal Oscillations (PDO) centered over the Pacific Ocean and North America. This variability can be analyzed in the sea surface temperature patterns with the use some statistical processing.

ContentContent

• El-Nino phenomenonEl-Nino phenomenon• Climatic variability in the tropical and North PacificClimatic variability in the tropical and North Pacific• EOF analysis of the SST during the period 1981-1999EOF analysis of the SST during the period 1981-1999• Cluster analysis of the SST during the period 1948-Cluster analysis of the SST during the period 1948-

2002:2002:- Spatial classification- Spatial classification- Temporal classification- Temporal classification

• Numerical modeling of the ocean response to the Numerical modeling of the ocean response to the atmospheric forcing during periods of El-Nino & La-atmospheric forcing during periods of El-Nino & La-Nina Nina

• ConclusionConclusion

The flooding in California after El-Nino The flooding in California after El-Nino 19971997

The forest fire in Australia in The forest fire in Australia in 19981998

Pacific oceanPacific ocean

El-Nino/Southern Oscillation El-Nino/Southern Oscillation (J. Bierknes hypothesis)(J. Bierknes hypothesis)

• Arising of the positive SST anomaly in the tropical Pacific Arising of the positive SST anomaly in the tropical Pacific (El-Nino phenomenon) is influenced by the variations of the (El-Nino phenomenon) is influenced by the variations of the Walker Circulation of the tropical atmosphere (Southern Walker Circulation of the tropical atmosphere (Southern Oscillation) and vice versa. Oscillation) and vice versa.

• This is a result of strong nonlinear interaction of two This is a result of strong nonlinear interaction of two components of the climatic system, which works like an components of the climatic system, which works like an oscillators: the fast, no inertial atmosphere and the slow, oscillators: the fast, no inertial atmosphere and the slow, inertial ocean, influencing one to another.inertial ocean, influencing one to another.

• In this system ocean, by virtue of its slow adjustment In this system ocean, by virtue of its slow adjustment between the thermocline and surface layer provides the between the thermocline and surface layer provides the “memory” that carries the system oscillations from cold “memory” that carries the system oscillations from cold phase La-Nina to warm phase El-Ninophase La-Nina to warm phase El-Nino

• Over the past and the half decade the modeling results Over the past and the half decade the modeling results have provided strong evidence of this hypothesis have provided strong evidence of this hypothesis

El-Nino – Southern Oscillation (ENSO)El-Nino – Southern Oscillation (ENSO)

Climatic state of the tropical PacificClimatic state of the tropical Pacific

Sequences of the events during El-Sequences of the events during El-NinoNino

Sequence of the events during El-NinoSequence of the events during El-Nino

• Arising of the positive SST anomaly in the eastern Arising of the positive SST anomaly in the eastern part of the part of the tropical Pacific by the redistribution of tropical Pacific by the redistribution of the water masses after strong La-Nina state the water masses after strong La-Nina state

• Weakening of the trade wind in the equatorial Weakening of the trade wind in the equatorial PacificPacific

• Increasing of the positive SST anomalies as a Increasing of the positive SST anomalies as a result of the eastward Kelvin waves propagation result of the eastward Kelvin waves propagation ((El-NinoEl-Nino))

• Shifting of the zone of convection and heat fluxes Shifting of the zone of convection and heat fluxes and output of the strong heat and moisture fluxes and output of the strong heat and moisture fluxes to the atmosphere to the atmosphere

• Redistribution of the heat and moisture anomalies Redistribution of the heat and moisture anomalies in the atmosphere via the teleconnection in the atmosphere via the teleconnection mechanism to the tropical and extra-tropical zones mechanism to the tropical and extra-tropical zones

• Climatic hazards in the tropical and midlatitudes Climatic hazards in the tropical and midlatitudes (flooding, drought, storms, etc.(flooding, drought, storms, etc.))

• Reconstruction of the climatic state and transition Reconstruction of the climatic state and transition of the ocean to the cold La-Nina fazeof the ocean to the cold La-Nina faze

Consequences of the El-Nino eventConsequences of the El-Nino event

• The 1997-98 El-Nino resulted in drought over The 1997-98 El-Nino resulted in drought over Indonesia, Australia & the Amazon basinIndonesia, Australia & the Amazon basin

• The extremely wet conditions with floods was in The extremely wet conditions with floods was in California and FloridaCalifornia and Florida

• The temperature of the Barents Sea upper layer The temperature of the Barents Sea upper layer decreased approximately to one degree (results decreased approximately to one degree (results based on the measurements on the Kolsky based on the measurements on the Kolsky meridian cross-section) meridian cross-section)

• The influence of El-Nino should be for the Siberian The influence of El-Nino should be for the Siberian region, but the evident correlation between the region, but the evident correlation between the temperature, precipitation and this event on the temperature, precipitation and this event on the basis of the one hundred series of the basis of the one hundred series of the meteorological measurements did not found yetmeteorological measurements did not found yet

Analysis of the North & tropical Pacific SST

Data sources:

•ECMRWF SST dataset 1981-1999

•NCEP/NCAR SST dataset 1948-2002

Methods:

•Empirical Orthogonal Function (EOF) Analysis (classical variant without ortogonalization)

•Cluster Analysis (spatial & temporal classification of zones with high correlation

The first four EOFThe first four EOF

Climatically averaged state, the first EOF & Climatically averaged state, the first EOF & temporal behaviortemporal behavior

Reconstruction of the anomalies field during Reconstruction of the anomalies field during La-Nina & El-Nino events (complete set of La-Nina & El-Nino events (complete set of

functions)functions)

Reconstruction of the SST field anomalies with the use of first four Reconstruction of the SST field anomalies with the use of first four EOFEOF

Reconstruction of the SST in September 1984Reconstruction of the SST in September 1984

Cluster analysis of SST for the period 1948-2002 Cluster analysis of SST for the period 1948-2002 (V.Efimov et al.,1995) (V.Efimov et al.,1995)

Cluster analysis is a method of combining of the data by the criterion correlation between the spatial points or the time points. Cluster analysis method allows one to solve the problems:  To classify the objects with taking into account the main features of the objects;   To check some hypothesis about occurrence of some structure in the aggregate of the objects;   Construction of the new classification for the poor investigated events, when it is necessary to establish the relations in the aggregate and to introduce some structure into it.

Two initial classes & temporal behaviorTwo initial classes & temporal behavior

Ten spatial classification Ten spatial classification classes &classes &

temporal behavior temporal behavior

Temporal behavior & spectrum for the classes 7, 8Temporal behavior & spectrum for the classes 7, 8

Six classes of the temporal classificationSix classes of the temporal classification

El-Nino modelling on the basis of the North Pacific El-Nino modelling on the basis of the North Pacific circulation modelcirculation model

Main features of the North Pacific circulation experimentMain features of the North Pacific circulation experiment

      Mathematical model is based on the complete “primitive” nonlinear equations of the thermo-hydrodynamics of the ocean;

       The numerical technique is based on a combination of the finite element and splitting methods;

       The wind-stress & temperature, salinity fluxes at the surface was taken from ECMRWF reanalysis;

Integration period starts from November 1981 until October 1988 (contains el-Nino 1982, 1986 &

La-Nina 1988)

El-Nino 1982 & La-Nina El-Nino 1982 & La-Nina 19881988, model (upper), ECMRWF data , model (upper), ECMRWF data (low)(low)

The first four EOF for the modeling resultsThe first four EOF for the modeling results

ENSO predictabilityENSO predictabilityA hierarchy of ENSO predictions models has been A hierarchy of ENSO predictions models has been

developed, ranging from the statistical forecast models to fully developed, ranging from the statistical forecast models to fully coupled ocean-atmosphere models. coupled ocean-atmosphere models.

Mathematical models gives sufficiently real picture of the Mathematical models gives sufficiently real picture of the oscillations in the Tropical Pacific and its influence to the oscillations in the Tropical Pacific and its influence to the atmospheric circulation, but can skillfully predict strong atmospheric circulation, but can skillfully predict strong equatorial SST anomalies (catastrophical El-Nino) at lead times equatorial SST anomalies (catastrophical El-Nino) at lead times not more then not more then six or twelve monthssix or twelve months.. This forecast needs preliminary the initialization of the models with the use of previous information about ocean–atmosphere state.

Possible reasons: ENSO irregularity

• “Deterministic chaos” – nonlinear interaction of the ENSO with annual cycle;• “Weather noise” – nonlinear interaction of the ENSO low-frequency and high frequency weathr variations;• Changing background state – nonlinear interaction between the ENSO and basic state of the climatic system (for ex. – mean depth of the thermocline)

ConclusionConclusion

The Pacific Ocean is the source of the climatic variability influencing to the atmospheric processes not only in local, but also in global scales. The mostly strong signal is the El-Nino-South Oscillation (ENSO) representing the inter-annual variability in tropics.

Mathematical models gives sufficiently real picture of the Mathematical models gives sufficiently real picture of the oscillations in the Tropical Pacific and its influence to the oscillations in the Tropical Pacific and its influence to the atmospheric circulation, but can skillfully predict equatorial SST atmospheric circulation, but can skillfully predict equatorial SST anomalies at lead times not more then six or twelve months. anomalies at lead times not more then six or twelve months.

 The EOF analysis enables us to separate the strongest signal in the Pacific Ocean and to reconstruct it with a few first harmonics. The periods between the El-Nino and the La-Nina events need a greater number of harmonics for reconstruction of the anomalies. This indicates that the state in these periods is governed by the first two climatic harmonics and finer processes form the anomalies. The spatial-temporal cluster analysis allows us to separate the typical structures if the SST variability, to indicate the inter-annual variability not only in the tropical, but in the subtropical and the subpolar regions and to establish the relations between the regions. It also allows us to indicate the marked signal of the inter-decadal variability in the subpolar-subtropical zones.