Wind and Water Distribution over Ocean

W. Timothy Liu, Xiaosu Xie, and Wenqing Tang

Distribution of Wind Power over OceanClosure of Water BalanceMeso-scale Ocean-atmosphere Coupling

SMMR

Center of cyclonic currentsPower density

Using Weibull distribution

Scaling factor

Shape factor

ū is mean wind speedσ is standard deviation of wind speedГ is the gamma function

Generating electric power from wind energy at sea (floating wind farms)

Avoid hazard conditions in shipping Ocean-atmosphere exchanges, in heat,

water, and greenhouse gases

Distribution of Wind Speed

Center of cyclonic currents

Center of cyclonic currents

Center of cyclonic currents

Center of cyclonic currents

Center of cyclonic currents

HYDROLOGIC BALANCE

Ue=f(Us) Liu (1993)-polynomial Liu & Tang (2005) - Neural NetworkUe = U850mb Heta & Mitsuta (1993)Both Us & U850mb Xie et al. (2007) - SVR

HYDROLOGIC BALANCE

E-P

Flux Divergence

E-P

Subtropical South Pacific

CC=0.856

CC=0.913

Equatorial western Pacific

CC=0.81

CC=0.764

Ocean Balance

Land Balance

GRACE Climatology

Global Water Balance - JASON

Global Water Balance-GRACE

Global Water Balance-GRACE

Water Balance over Global Ocean

Ocean’s Influence on Water Balance of South America

The approximate balance of dM/dt with ∫-R bolsters not only the credibity of the spacebased measurements, but supports the characterization of ocean’s influence on continental water balance.

Liu et al., GRL 2006

Center of cyclonic currentsMeridional Heat Transport (MHT)

H: Heat content

ζ: Horizontal heat flux

SW: Short wave radiation

LW: Long wave radiation

LH: Latent heat

SH: Sensible heat

AMSR measures the largest aggregate of water cycle parameters

The high resolution global coverage is conducive to study the coupling of mid-latitude ocean fronts with atmosphere

It provide the distribution of wind power density with unprecedented details

Need continuous and consistent time series New opportunity for science synergism still lies

ahead

Summary

Center of cyclonic currents

Backup

Our knowledge on stress was derived from winds before we have scatterometer

High-resolution AMSR data help to define mesoscale SST gradient where stress could not be derived from wind alone

Because the weak lapse rate, mid-latitude SST anomalies could not generate atmospheric response above boundary layer.

Satellite data contradict such notion and challenge on dynamics and scaling for the modelling community.

Mid-latitude Coupling over Ocean Front

Filtered ENW (color) and SST (contour)

Collocation of ENW magnitude with SST is inherent in the definition of ENW and turbulent mixing theory.

Filtered precipitation (color) and SST (contour)

Precipitation is in quadrature with SST and in phase with surface wind convergence.