Ocean Mixed Layer Dynamics and its Impact on SST & Climate Variability

Michael Alexander

Earth System Research Labmichael.alexander@noaa.gov

http://www.cdc.noaa.gov/people/

michael.alexander/presentations

Ocean Mixed layer• Turbulence creates a well mixed

surface layer where temperature (T), salinity (S) and density (ρ) are nearly uniform with depth

• Primarily driven by vertical processes (assumed here) but can interact with 3-D circulation

• Density jump usually controlled by temperature but sometimes by salinity (especially in high latitudes)

• Often “ measured” by the depth at which T is some value less than SST (e.g. ∆T = 0.5)

• Under goes large seasonal cycle

• This impacts the evolution of ocean temperature anomalies and has important biological consequences

surface

T s ρ

∆T

∆T=Tb-Tm

Vertical Flux: Entrainment and MLD (h)Entrainment “To pull or draw along after itself”MLD – Mixed Layer Depth or h

When deepening: dh/t = we

we = M + B – D / (ρS)

WhereM - Mechanical Turbulence (wind stirring)B - Buoyancy Forcing

Net surface heating/cooling (Qnet)Precipitation – Evaporation (P-E)

D - Dissipation (h)ρ- Density jump at base of the MLS - Shear across ML (not in all models)

When Shoaling: we = 0 (no detrainment, h reforms closer to the surface)h = M /(B – D)

Seasonal Cycle of Temp & MLD Northeast Pacific (50ºN, 145ºW)

MLD (h)

Climatological Mixed Layer Depth (m)

SST Tendency Equation

Variablesv – velocity (current in ML)Tm – mixed layer temp (SST)Tb – temp just beneath MLh – mixed layer depthw – mean vertical velocitywe – entrainment velocity Qnet – net surface heat fluxQswh – penetrating shortwave radiationA – horizontal eddy viscosity coefficientρ – density of sea waterC – Specific heat of sea water

Integrated heat budget over the mixed layer:

Qnet

Temperature change due to the surface heat flux

• Over March through August a location in the North Pacific typically receives 150 Wm-2 flux through the surface. Assuming a constant mixed layer depth of 50 m, and no other changes in the ocean how much will the SST change over that time?

• dTm/dt = d(SST)/dt = Qnet/ρch

SST = (Qnet/ρch) x t

• ρ = 1025 kg/m3; c = 3850 Joules/(kg °C)

SST = (150 Wm-2 / (1025 kg m-3 x 3850 Joules kg-1 °C-1 x 50 m)) * (184 days * 86400 s day-1)

• SST = 12.1°C

• => Check units (W = J s-1)

• => reasonable value for winter to summer change in SST

Zonal Average

Mean

StandardDeviation

Surface Heat Flux Entrainment Flux

Observed Standard Deviation of SST Anomalies (°C)

August

March

Processes for Generating SST Anomalies

Simple model for generating SST variability“stochastic model”

Heat fluxes associated with weather events,“random forcing”

Ocean response to flux back heatwhich slowly damps SST anomalies

SST anomalies formAir-sea interface

Fixed depth oceanNo currents

Bottom

dTm/dt = F – λTm

ρch

F λTm

dTm/dt = Qnet

ρch

Stochastic SST Anomaly model IIidealized forcing and time series

Null Hypothesis for midlatitude SST variability

Stochastic Model: correspondence to the real world?Observed and Theoretical Spectra for SST anomalies (SSTA)

at a location in the North Pacific Ocean

Te

mp

era

ture

Va

rian

ce

Atmospheric forcing and ocean feedback can be estimated from data. Then can then develop stochastic model and generate multiple time series to look at spread

Period

1yr10 yr

No damping

SS

TA

Var

ianc

e

1 mo

Atm forcingTheoretical spectra (white line) of stochastic model

Observed

Spread (5%-95%)

Patterns of Surface Fluxes and SSTs:example North Atlantic Oscillation

Contours are sea level pressure (SLP); vectors - windsShading left is SST anomalies, on right is the Flux anomaliesNAO north-south SLP anomaly pattern over the Atlantic

The Reemergence Mechanism

• Winter Surface flux anomalies

• Create SST anomalies which spread over ML

• ML reforms close to surface in spring

• Summer SST anomalies strongly damped by air-sea interaction

• Temperature anomalies persist in summer thermocline

• Re-entrained into the ML in the following fall and winter

Namias and Born 1970, 1974; Alexander and Deser (1995, JPO); Alexander et al. 1999 +

Qnet’

MLD

Reemergence in three North Pacific regions

Regression between SST anomalies in April-May with monthly temperature anomalies as a function of depth.

Regions

Alexander et al. (1999, J. Climate)

Reg 2 - Northeast Atlantic (47%)

Reemergence in the North Atlantic

Reg 1 - Subtropical Atlantic (48%)

Timlin, Alexander, Deser, 2002, J.Climate

Watanabe and Kimoto (2000); Timlin et al. 2002, Deser et al 2003, De Coetlogon and Frankignoul 2003 : all in J. Climate

Auto-correlation of EOF PC time series

Level ofsignificance

Degrees Celsius

Reemergence of theSST North Atlantic tripole

Leading EOF of March SST

ERSSTv2 Datasets [1950-2003]

Reemergence of SST Tripole

Impact of reemergence on SST Persistence:Augmenting the Stochastic SST model

Deser et al. 2003

Heat content (EM)

Obs (dashed)

EntrainingModel (EM)

SST (EM)SST (OBS)

North Atlantic

Heff = winter MLD for interannual variability in a stochastic model

Deser et al. 2003

Heat content (EM)

Obs (dashed)

EntrainingModel (EM)

SST (EM)

SST (OBS)

Main Concepts

• Mixed Layers– Processes that control its depth– Wind stirring buoyancy forcing, density jump at base of ML– Processes that control its temperature (SST)

• Surface heat flux• Entrainment heat flux

• Mechanisms for the behavior of SST anomalies• Stochastic model• Reemergence• Large scale patterns of atmospheric forcing organizes fluxes, shapes

SST Anomaly and reemergence patterns

• Questions?

1. What is the oceanic reemergence? 2. Surface signature of reemergence in the Labrador Sea

Sea SurfaceTemperature

e-folding = ~ 4 mths

Auto-correlation of the Labrador SST time series(all months considered), e.g. for lag=1, Jan50/Feb50/…/Dec00values are correlated with Feb50/Mar50/…/Jan01 values

e-folding = ~ 36 mths

e-folding = ~ 4 mths

Auto-correlation of the Labrador SST time series(Starting from March), e.g. for lag=1, March and Apriltime series are correlated, for lag =2 March and May etc.

Reemergence of the latewinter SST anomalies

a year after

Deser et al. 2003 (J.Clim)

ERSSTv2 Datasets [1950-2003]

Degrees Celcius

Level ofsignificance

March SST EOF1 (shade)Regressed JFM SLP (contour)

PC time series: March SST (bars), JFM MSLP (line)

NCEP MSLP [1950-2003]

Correlation=0.63

e.g. Deser and Timlin (1997), J.Clim.

Atmosphere forcing the ocean in winter: NAO & the Atlantic SST tripole

Summary• Forcing of SST (mixed layer temperature

– Net heat flux key term, Ekman transport & entrainment also important

– SST anomalies larger in summer than winer due to shallow MLD

• Processes that impact extratropical SST variability– Stochastic atmospheric forcing– Reemergence

• Atmospheric Bridge– Tropical Pacific => Global SSTs– Impacts in both winter and summer– Influence of air-sea feedback on extratropical atmosphere complex

• Other Processes that influence SST variability– Cloud - SST feedbacks– Ocean currents & Rossby waves in western N. Pacific– Changes in the Thermohaline Circulation

Additional Topics

• The flux components and their variability• Schematic of the mixed layer model• Pattern of atmospheric circulation (SLP) and the

underlying fluxes)• Basin-wide reemergence• The Pacific Decadal Oscillation• Wind generated Rossby waves and its relation to

SSTs• The Latif and Barnett mechanism for the PDO and

“problems” with this mechanism

Atmosphere-Ocean Ice Model

Atmospheric GCM– NCAR CAM2–T42 resolution

Ice Thermodynamic portion of NCAR CSIMv4

Ocean Mixed layer Model (MLM)

• An individual column model with a uniform mixed layer• Atop a layered model that represents conditions in the pycnocline• Prognostic ML depth• Same grids as the atmosphere (128 lon x 64 lat)• 36 vertical levels (from 0m to 1500m depth)

• higher resolution close to surface and a realistic bathymetry• Flux correction needed to get reasonable climate• Cassou et al. 2007 J Clim; Alexander et al. 2000 JGR, Alexander et al 2002 – J.Clim ;

Gaspar 1988 – JPO

Mixed Layer Ocean Model

h (MLD)

Tb1

Tm1

Qnet Qcor

Qswh

Qwe

CA

Mean ML Budget terms (Wm-2) in January From an AGCM couple to a mixed layer ocean model

EntrainmentQwe =

ρcwe(Tb-Tm)

EkmanQek =

ρcvek(Tm)

Surface FluxQnet

Mean Mixed Layer Budget terms (Wm-2)

in August

Standard Deviation of the Mixed

Layer Budget Terms (Wm-2)

in January

Standard Deviation of Fluxes in AugustResults from an AGCM- Ocean MLM

Qwe =

ρcwe(Tb-Tm)

W m-2

Qnet

W m-2

Qwe / Qnet

Wind Generated Rossby Waves

West East

Atmosphere

Ocean

Thermocline

ML

L

Rossby Waves

1) After waves pass ocean currents adjust2) Waves change thermocline depth, if mixed layer reaches that

depth, cold water can be mixed to the surface

Observed Rossby Waves & SST

Schneider and Miller 2001 (J. Climate)

March

KE Region: 40°N, 140°-170°E

SSTOBS

T400SSTfcst

Correlation Obs SST hindcast With thermocline depth anomaly

Forecast equation for SST based on integrating wind stress (curl) forcing and constant propagation speed of the (1st Baroclinic) Rossby wave

Forecast Skill: Correlation with Obs SST Wave Model & Reemergence

Wave Model Reemergence

years

Schneider and Miller 2001 (J. Climate)

Climatological heat fluxes August

Zonal Average of

the standard

deviation of the mixed

layer budget terms

DJF

JAS

Observed SST (C) / SLP (mb) Warm-Cold (50-03)

Evolution of the leading pattern of SST variabilityas indicated by extended EOF analyses

Alexander et al. 2001, Prog. Ocean.

No ENSO;Reemergence

ENSO;No Reemergence

Upper Ocean: Temperature and mixed layer depth

El Niño – La Niña model composite: Central North Pacific

Alexander et al. 2002, J. Climate

ENSO SST & MLD in Western N. Pacific Region

El Niño MLD

La Niña MLD

Niño – Niña: NCEP Ocean Temp & White MLD (1980-2001)

°C