Air-sea Interaction in the vicinity of ocean

fronts - Perspective from OAFlux high-resolution analysis

Lisan Yu

Woods Hole Oceanographic Institution

Acknowledgement: Dr. Xiangze Jin (WHOI)

Objectively Analyzed air-sea Fluxes Project:OAFlux is a research project. Website:

http://oaflux.whoi.edu

• 1, 1958 onwards: available online•0.25, 1987 onwards: validation mode

•Net Heat flux•surface radiation

•Evaporation•Latent and •Sensible heat fluxes

•Wind and •Wind Stress

• 0.25 1987 onwards (12 sensor synthesis)

• 1983 onwards: under development

Online release in the coming fall

• OAFlux synthesis takes into account of data errors in constructing air-sea fluxes of heat, moisture, and momentum (least-squares estimation based on the Gauss-Markov theorem)• Global 1°-gridded flux analysis was released in 2008 and is currently maintained with 2-3 updates/year.• Efforts in recent years have been on high-resolution flux analysis for front-scale air-sea interaction.• Matured datasets are distributed freely online.

Spatial resolution matters for resolving atmosphere -ocean front interaction

OAFlux 0.25° versus 1°Gulf Stream

Kuroshio Extension

Agulhas Current

qa/ta derived from satellite sensors need to be bias corrected and gap filled before used in OAFlux synthesis.

The development of OAFlux 0.25° LH/SH analysis benefits from three recent products:(1) OAFlux 0.25° satellite-based vector wind

analysis (1987 – present) (Yu and Jin, 2012, JGR-Oceans)

(2) Jackson and Wick 0.25° satellite-derived qa/ta analysis (1999-2010) (Jackson and Wick, 2010) and GSSTFv3 qa (1987-1999) (Shie 2012).

(3) OISST 0.25° daily analysis (Reynolds et al., 2007).

What is in the OAFlux 0.25° heat flux analysis?

bias is latitude dependent

dry biased

wet biased

wet bias dominates the time series

Improve qa/ta estimates:

What is in the OAFlux 0.25° vector wind analysis?

(1) 9 passive microwave radiometers• SSMI – F08, F10, F11, F13, F14, & F15;• SSMIS – F16 & F17;• AMSRE

(2) 1 passive polarimetric microwave radiometer• WindSat onboard Air Force Coriolis mission

(3) 2 Scatterometers• QuikSCAT – Ku band • ASCAT – C band

Sensor types

QuikSCAT period

A 12-sensor synthesis, daily, 0.25°, 1987-present

Frontal-scale Air-sea fluxes

Latest atmospheric reanalyses have improved spatial resolution

- ERAinterim (0.7°), - MERRA (2/3°x1/3°), - CFSR (0.3°). - By comparison, NCEP/NCAR (1.875°)

Large differences exist between products.

Questions: What can we learn from these products

on the characteristics of frontal –scale atmosphere-ocean interaction?

What new insights can we obtain from OAFlux-0.25°?

Part of research is in collaboration with NCEP/CFSR funded by NOAA MAPP on “Research to advance climate reanalysis”.

Winter-mean Latent and Sensible Heat Fluxes

OAFlux vs Reanalyses

Buoy Perspective

LH (Buoy – Product)

OA-0.25 OA-1 ERAi MERRA CFSR NCEP

OA-0.25 OA-1 ERAi MERRA CFSR NCEP

SH (Buoy – Product)

There are differences between products

Winter Mean LH+SH

Frontal air-sea interaction SST modulation on surface heat fluxes

High correlations between SST and LH+SH during winter seasons are located NW of the GS north wall.

Think black:95% CI outlined

Thick black:Mean position of the 18C isotherm of SST

Correlation <SST, LH+SH> Winter (DJF), 1988-2010

SST winter variability vs. SST-flux correlation

Location of maximum correlation is defined by the location of maximum SST variability.

SST STDWinter, 1988-2010

Corr <SST, LH+SH>Winter, 1988-2010

Winter <SST, LH+SH> superimposed onto the GS topography

1988-2010

SST modulation on Heat Fluxes:Topographic effect

Phase relationship between SST and fluxes

Problem in SST data

SST (from OISST ¼-deg) does not have daily variability; the time series is dictated by weekly variability. Perhaps the weekly 1-deg was used a background.

The lack of daily variability in SST data hampers the determination of the phase relationship.

Flux leads SSTSST leads Flux

Wind stress is also modulated by SST

Corr <SST, LH+SH> Corr <SST, WindStress>

Reanalyzed fluxes have a weaker correlation with their own SST

Winter versus Annual Mean

All months1988-2010

Winter (DJF)1988-2010

Decadal changes in the GS region

winter (DJF), 1988-2012Response of heat fluxes to SST forcing

more heat release;cooling the sea surface

less heat release;warming the sea

surface

Decadal changes in the GS region

winter (DJF), 1988 - 2012Response of wind stress to SST forcing

Global connection: LH+SH

Global connection: wind stresstrends and trend vectors

On annual mean basis, the largest change in wind during the satellite era

(1987 onwards) is the southern hemisphere westerlyWind Speed (W)

Wind Stress ()

W2

Shift in the SH westerly band

Trends in N. Lat(x=0) (°Latitude per 10 yrs)

Linear trends in x

(10-2 Nm-2 per 10 yrs)

(background colors)

Trends in S. Lat(x=0): (°Latitude per 10 yrs)

Poleward displacement of the ACC fronts from SSH

Annual Mean

SSH

ENSO signals included

ENSO signals filtered out

Sokolov & Rintoul (2009):- Each of the ACC fronts has shifted to

the south by about 60km, 1992-2007

- Rate of change = 0.55°/16yrs 0.34°/10 yrs

The ACC front positions

N. Lat (x=0)

SSH front

24-year Mean Wind Stress Curl (1988-2011) (positive: counterclockwise)

Can the ACC fronts influence the winds?

Average of ~ 9000 daily means

Stress curl bear the signature of ocean bathymetry

Drake Passage &South Georgia Ridge

Eltanin and Udintsev Fracture Zone

Eastern Indian Ridge

(Smith and Sandwell, 1994)

(curl negative: clockwise)

Mean Stress Curl (positive: counterclockwise)

Magnitude of Mean SST Gradient (SST)

Magnitude of Mean SSH Gradient (SSH)

Influence of ocean topography on wind stress via SST

24-year average OAFlux

24-year average AVHRR SST

Mean Ocean Dynamic TopographyMaximenko and Niiler (2005)

|SSH|

|SST|

Curl

Summary - 1

On flux data products:

Spatial resolution matters in resolving surface heat fluxes associated with ocean front/eddy variability.

The new high-resolution OAFlux analysis do show improved accuracy and improved physical representation for frontal-scale air-sea interaction in the vicinity of ocean fronts/eddies.

CFSR produces better surface fluxes over the ocean front regions among all reanalyses, perhaps due to the semi coupled nature of the system.

Summary - 2

Perspective on the atmosphere-front interaction from the OAFlux 0.25° analysis: The GF and ACC regions

The GS region:1) Influence of SST on surface flux variability in winter seasons is

maximum in the area confined between the shelfbreak and the north wall of the GS, the area that features the largest SST variability in winter.

2) Significant changes in surface heat and momentum fluxes have been observed in the GS region during the satellite era of past 25 years. The changes are related to both local feedback and large-scale circulation pattern change.

The ACC region:1) Wind stress curl shows the signature of ocean bathymetry.

2) Are SH westerly winds coupled with the ACC or a driver of the ACC?