Evolution of the El Niño Southern Oscillation (ENSO) from the Last Ice Age to Today Andy Bush Dept. of Earth & Atmospheric Sciences University of Alberta.

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Presentation transcript:

Evolution of the El Niño Southern Oscillation (ENSO) from the Last Ice Age to Today Andy Bush Dept. of Earth & Atmospheric Sciences University of Alberta Winds of Change:

Evolution of the El Niño Southern Oscillation (ENSO) from the Last Ice Age to Today Andy Bush Dept. of Earth & Atmospheric Sciences University of Alberta Winds of Change: A.B.G. Bush, 2006, Journal of Climate, in press.

Evolution of the El Niño Southern Oscillation (ENSO) from the Last Ice Age to Today Andy Bush Dept. of Earth & Atmospheric Sciences University of Alberta Winds of Change: A.B.George Bush, 2006, Journal of Climate, in press.

Evolution of the El Niño Southern Oscillation (ENSO) from the Last Ice Age to Today Andy Bush Dept. of Earth & Atmospheric Sciences University of Alberta Winds of Change: A.B.George Bush, 2006, Journal of Climate, in press.

Motivation: To understand the climatological factors that determine the period and intensity of interannual variability (ENSO).

Motivation: To understand the climatological factors that determine the period and intensity of interannual variability (ENSO). Past climates provide altered mean states within which interannual variability exists.

Animation of TOPEX/Poseidon sea surface height data

Some human impacts of ENSO: 1) Impact on disease spread (malaria and dengue) 2) Food production

El Niño winter snow anomalies

Observed Composite Temperature Anomalies El Niño La Niña

SST anomalies, Aug.-Sept. 2006: El Niño’s coming…

Existing numerical models for ENSO prediction are anomaly models in which a background climate state is assumed. Predicted variables are perturbations on that background state. The two climate variables that must be assumed are: 1)Mean depth of the thermocline 2) Strength of the climatological easterly trade winds These quantities are known for today’s climate, so anomaly models work quite well for ENSO prediction.

Existing numerical models for ENSO prediction are anomaly models in which a background climate state is assumed. Predicted variables are perturbations on that background state. The two climate variables that must be assumed are: 1)Mean depth of the thermocline 2) Strength of the climatological easterly trade winds These quantities are known for today’s climate, so anomaly models work quite well for ENSO prediction. However, one or both of these quantities appear to have been different in the past (aeolian deposits, upwelling indices, planktonic foraminifera, etc.). Changes in the strength of the general circulation can cause changes in these quantities.

Our atmosphere exhibits dynamic variability associated with midlatitude baroclinic waves, or eddies.

Our atmosphere exhibits dynamic variability associated with midlatitude baroclinic waves, or eddies. Eddies may be either TRANSIENT (not fixed to a specific geographic location) or STATIONARY (fixed geographically; caused by mountain ranges, continent-ocean contrasts, etc.) Eddies play a very important role in governing the strength of the general circulation.

Atmospheric eddies are the primary mechanism by which low latitude HEAT is transported poleward (v’T’>0). This occurs in the growth phase of baroclinic waves. (Idealized life cycle)Idealized life cycle

Atmospheric eddies are the primary mechanism by which low latitude HEAT is transported poleward (v’T’>0). This occurs in the growth phase of baroclinic waves. They are also the primary mechanism by which the zonal mean (and, by angular momentum conservation, the meridional mean) flow is forced (u’v’>0). This occurs in the Rossby wave decay phase of the baroclinic wave, in which easterly momentum is transported equatorward.

Atmospheric eddies are the primary mechanism by which low latitude HEAT is transported poleward (v’T’>0). This occurs in the growth phase of baroclinic waves. They are also the primary mechanism by which the zonal mean (and, by angular momentum conservation, the meridional mean) flow is forced (u’v’>0). This occurs in the Rossby wave decay phase of the baroclinic wave, in which easterly momentum is transported equatorward. Global Implications?

Atmospheric eddies are the primary mechanism by which low latitude HEAT is transported poleward (v’T’>0). This occurs in the growth phase of baroclinic waves. They are also the primary mechanism by which the zonal mean (and, by angular momentum conservation, the meridional mean) flow is forced (u’v’>0). This occurs in the Rossby wave decay phase of the baroclinic wave, in which easterly momentum is transported equatorward. Global Implications? More Eddy Activity  Stronger Circulation

Eddy activity depends on the meridional temperature gradients of the climatological background state. Stronger temperature gradients increase the rate of eddy formation (can be shown from linear theory).

Eddy activity depends on the meridional temperature gradients of the climatological background state. Stronger temperature gradients increase the rate of eddy formation (can be shown from linear theory). Meridional temperature gradients were quite different in the past for a variety of reasons (ice sheets, orbital parameters, greenhouse gases, etc.).

Eddy activity depends on the meridional temperature gradients of the climatological background state. Stronger temperature gradients increase the rate of eddy formation (can be shown from linear theory). Meridional temperature gradients were quite different in the past for a variety of reasons (ice sheets, orbital parameters, greenhouse gases, etc.). Also, during an Ice Age, topographic forcing of stationary waves was very different because of the massive ice sheets.

The numerical experiments A global coupled atmosphere-ocean general circulation model is used to simulate 80 years of climate for:

The numerical experiments A global coupled atmosphere-ocean general circulation model is used to simulate 80 years of climate for: 1) Last Glacial Maximum (LGM, 21,000 years ago) -massive continental ice sheets -decreased atmospheric carbon dioxide -sea level lowering of 120 m -surface vegetation different

Schematics of ice sheet extent at the Last Glacial Maximum

The numerical experiments A global coupled atmosphere-ocean general circulation model is used to simulate 80 years of climate for: 1) Last Glacial Maximum (LGM, 21,000 years ago) -massive continental ice sheets -decreased atmospheric carbon dioxide -sea level lowering of 120 m -surface vegetation different 2) 9,000 years ago -orbital parameters -remnants of Laurentide ice sheet

Obliquity was high in the early-mid Holocene (9,000-6,000 years ago). This accentuates the seasonal cycle; warmer summers and colder winters.

The numerical experiments A global coupled atmosphere-ocean general circulation model is used to simulate 80 years of climate for: 1) Last Glacial Maximum (LGM, 21,000 years ago) -massive continental ice sheets -decreased atmospheric carbon dioxide -sea level lowering of 120 m -surface vegetation different 2) 9,000 years ago -orbital parameters -remnants of Laurentide ice sheet 3) 6,000 years ago -orbital parameters

The numerical experiments A global coupled atmosphere-ocean general circulation model is used to simulate 80 years of climate for: 1) Last Glacial Maximum (LGM, 21,000 years ago) -massive continental ice sheets -decreased atmospheric carbon dioxide -sea level lowering of 120 m -surface vegetation different 2) 9,000 years ago -orbital parameters -remnants of Laurentide ice sheet 3) 6,000 years ago -orbital parameters 4) Today (control)

The numerical experiments A global coupled atmosphere-ocean general circulation model is used to simulate 80 years of climate for: 1) Last Glacial Maximum (LGM, 21,000 years ago) -massive continental ice sheets -decreased atmospheric carbon dioxide -sea level lowering of 120 m -surface vegetation different 2) 9,000 years ago -orbital parameters -remnants of Laurentide ice sheet 3) 6,000 years ago -orbital parameters 4) Today (control) 5) Doubling of atmospheric carbon dioxide (2xCO 2 )

El Niño and La Niña events are defined by sea surface temperature anomalies in the Nino 3.4 region. Values are typically normalized by the standard deviation.

Control simulation produces good statistics for ENSO.

S.D.=0.83 S.D.=0.87 Control Observations

Wavelet analysis Power Spectrum: Averaged in time: Observations

S.D.=0.83 S.D.=0.87 Control Observations

Values Normalized by Their standard Deviation LGM 9,000 B.P. 6,000 B.P. Control Observations 2xCO2

Values Normalized by Their standard Deviation LGM 9,000 B.P. 6,000 B.P. Control Observations 2xCO2

Values Normalized by Their standard Deviation LGM 9,000 B.P. 6,000 B.P. Control Observations 2xCO2

Values Normalized by Their standard Deviation LGM 9,000 B.P. 6,000 B.P. Control Observations 2xCO2

Values NOT Normalized by The standard Deviation S.D.=0.58 S.D.=0.55 S.D.=0.81 S.D.=0.83 S.D.=0.87 S.D.=1.05 Increasing Period of ENSO (decrease in Frequency)

Not much change in mean thermocline depth (except for CO 2 case) Change in east-west tilt of thermocline consistent with change in strength of mean atmospheric trade winds Changes in the climatological mean states

Not much change in mean thermocline depth (except for CO 2 case) Change in east-west tilt of thermocline consistent with change in strength of mean atmospheric trade winds Changes in the climatological mean states ~20% reduction in Easterly trade winds from LGM to today

Linear Stability Analysis of the coupled atmosphere-ocean system (Fedorov and Philander, Science, 2001) (increases with decreasing wind speed) Control Growth Rate PERIOD

Linear Stability Analysis of the coupled atmosphere-ocean system (Fedorov and Philander, Science, 2001) (increases with decreasing wind speed) Control Growth Rate PERIOD * LGM * 9,000 * 6,000 *2xCO2

Is there a reason why the strength of the atmospheric winds should be different in these simulations?

Is there a reason why the strength of the atmospheric winds should be different in these simulations? Yes. The eddy fields are very different.

Is there a reason why the strength of the atmospheric winds should be different in these simulations? Yes. The eddy fields are very different. LGM: enhanced meridional temperature gradient (transient eddies) presence of massive continental ice sheets (stationary eddies)

Is there a reason why the strength of the atmospheric winds should be different in these simulations? Yes. The eddy fields are very different. LGM: enhanced meridional temperature gradient (transient eddies) presence of massive continental ice sheets (stationary eddies) 9,000 and 6,000 B.P.: more seasonal climate because of enhanced obliquity of the planet and summertime perihelion. Effect is stronger at 9,000 B.P. than 6,000 B.P. Hotter summers and colder winters should produce more wintertime transient eddy activity.

Is there a reason why the strength of the atmospheric winds should be different in these simulations? Yes. The eddy fields are very different. LGM: enhanced meridional temperature gradient (transient eddies) presence of massive continental ice sheets (stationary eddies) 9,000 and 6,000 B.P.: more seasonal climate because of enhanced obliquity of the planet and summertime perihelion. Effect is stronger at 9,000 B.P. than 6,000 B.P. Hotter summers and colder winters should produce more wintertime transient eddy activity. CO2: reduced meridional temperature gradient (transient eddies)

The Eliassen-Palm (E-P) flux vector: Z Y Poleward heat flux (v’T’>0) Equatorward momentum flux (u’v’>0) E-P flux

Increased midlatitude eddies drive stronger subtropical subsidence, a stronger Hadley cell and, through angular momentum conservation, stronger equatorial easterlies.

Peak easterly (i.e. negative) winds over the Pacific occur near the solstices of end-December and end-June when baroclinic eddy activity is greatest Coupled model TAO winds Zonally symmetric atmosphere-only integration for a land-covered planet --wind changes are not related to the Asian monsoon.

Changing Teleconnection Patterns: Temperature LGM 9K BP 6K BP Today 2xCO2

LGM 9K BP 6K BP Today 2xCO2 Changing Teleconnection Patterns: Precipitation

Implications of changing teleconnection patterns:

Caution must be used when interpreting paleoclimate proxy records for ENSO. For example, Rodbell et al (1999) interpreted the absence of a distinct ENSO signal from early Holocene sediments of coastal Peru to mean that ENSO was absent between 15,000 and ~6,000 years ago. This assumed “stationarity” of the teleconnection pattern is incorrect.

Implications of changing teleconnection patterns: Caution must be used when interpreting paleoclimate proxy records for ENSO. For example, Rodbell et al (1999) interpreted the absence of a distinct ENSO signal from early Holocene sediments of coastal Peru to mean that ENSO was absent between 15,000 and ~6,000 years ago. This assumed “stationarity” of the teleconnection pattern is incorrect. Also, Koutavas et al (2002) interpreted a reduced zonal SST gradient in the tropical Pacific at the LGM to mean the glacial climate was in an El Niño state. This assumption does not take into account the changed mean state of the LGM climate.

Implications of changing teleconnection patterns: Caution must be used when interpreting paleoclimate proxy records for ENSO. For example, Rodbell et al (1999) interpreted the absence of a distinct ENSO signal from early Holocene sediments of coastal Peru to mean that ENSO was absent between 15,000 and ~6,000 years ago. This assumed “stationarity” of the teleconnection pattern is incorrect. Also, Koutavas et al (2002) interpreted a reduced zonal SST gradient in the tropical Pacific at the LGM to mean the glacial climate was in an El Niño state. This assumption does not take into account the changed mean state of the LGM climate. Teleconnections produce high latitude fingerprints of ENSO changes.

Conclusions The period of ENSO increases from the LGM to today

Conclusions The period of ENSO increases from the LGM to today The amplitude of ENSO increases from the LGM to today

Conclusions The period of ENSO increases from the LGM to today The amplitude of ENSO increases from the LGM to today These changes are consistent with the decrease in strength of the climatological easterly trade winds over the Pacific

Conclusions The period of ENSO increases from the LGM to today The amplitude of ENSO increases from the LGM to today These changes are consistent with the decrease in strength of the climatological easterly trade winds over the Pacific Decrease in trade wind strength is consistent with the decrease in midlatitude eddy activity

Conclusions The period of ENSO increases from the LGM to today The amplitude of ENSO increases from the LGM to today These changes are consistent with the decrease in strength of the climatological easterly trade winds over the Pacific Decrease in trade wind strength is consistent with the decrease in midlatitude eddy activity Decrease in eddy activity related to topographic forcing at the LGM, to orbital forcing at 9,000 and 6,000 B.P., and to radiative forcing in the 2xCO2 environment

What’s been observed? Increased tropical Pacific wind speeds during the LGM (aeolian deposits, upwelling indices from ocean cores)

What’s been observed? Increased tropical Pacific wind speeds during the LGM (aeolian deposits, upwelling indices from ocean cores) Increased tilt of the tropical Pacific thermocline during the LGM (planktonic foraminifera)

What’s been observed? Increased tropical Pacific wind speeds during the LGM (aeolian deposits, upwelling indices from ocean cores) Increased tilt of the tropical Pacific thermocline during the LGM (planktonic foraminifera) Increase in ENSO amplitude and period from LGM to today from corals (Tudhope et al, 2001)

What’s been observed? Increased tropical Pacific wind speeds during the LGM (aeolian deposits, upwelling indices from ocean cores) Increased tilt of the tropical Pacific thermocline during the LGM (planktonic foraminifera) Increase in ENSO amplitude and period from LGM to today from corals (Tudhope et al, 2001) Decrease in easterly trade wind strength (Nature, May 2006)

With many thanks to… Canadian Foundation for Climate and Atmospheric Research (CFCAS; Polar Climate Stability Network)

With many thanks to… Canadian Foundation for Climate and Atmospheric Research (CFCAS; Polar Climate Stability Network) …and all of you!

Wavelet analysis Power Spectrum: Averaged in time:

Seasonal Cycle

QBO?

Seasonal Cycle QBO? Decadal Variability

Seasonal Cycle QBO? ENSO Decadal Variability

Changing teleconnection patterns: composite temp. anomalies Control6,000 B.P. 9,000 B.P. LGM