AOML
NOAA

The GDP Drifter Data Assembly Center (DAC)

Mean Velocity Estimates

Drifter-derived climatology of Global Surface Currents

A drifter-derived seasonal climatology of global near-surface currents

Version number: 2.05. Created on: 28 August 2013. Most recent data included: 31 December 2012. Documentation: Lumpkin and Johnson (2013). Note: This product reflects results of the recent drogue presence reanalysis (Lumpkin et al., 2013).

On this page, you will find a seasonal climatology of near-surface currents and SST for the world, at monthly and one-half degree resolution, derived from satellite-tracked surface drifting buoy observations. Animations of these currents are available here. Maps of these currents in various regions can be seen on the Ocean Surface Currents web site.

Please cite as reference:

Lumpkin, R. and G. C. Johnson, 2013: Global Ocean Surface Velocities from Drifters: Mean, Variance, ENSO Response, and Seasonal Cycle. J. Geophys. Res.-Oceans, 118, pp.2992-3006, doi:10.1002/jgrc.20210 .

For an analysis of the monthly climatology in the Hawaiian Island region, see Lumpkin and Flament, 2013

This version of the climatology is an update of an older climatology previously available on this web page. Archived versions of older climatologies can be found in ftp://ftp.aoml.noaa.gov/phod/pub/lumpkin/drifter_climatology. For more about version 1, see:

Lumpkin, R. and Z. Garraffo, 2005: Evaluating the Decomposition of Tropical Atlantic Drifter Observations. J. Atmos. Oceanic Techn. I 22, 1403-1415.

Lumpkin, R. and S. L. Garzoli, 2005: Near-surface Circulation in the Tropical Atlantic Ocean. Deep-Sea Res. I 52(3),495-518, 10.1016/j.dsr.2004.09.001.

For more information about the drifters, go to the Global Drifter Program information page.

The climatology is available in Matlab, ASCII and NetCDF formats

Three versions of the climatology are available. The first version ( Matlab binary format/ ASCII/ NetCDF ) contains annual mean values of the near-surface currents and sub-skin sea surface temperature. The Matlab file contains the following variables:

Lon (1x720): longitude (degrees), negative=West.
Lat (1x317): latitude (degrees), 73S to 85N.
U (317x720): eastward speed (m/s) vs. Lat/Lon.
V (317x720): northward speed (m/s).
SST (317x720): sea surface temperature (degrees C).
Usoi (317x720): eastward speed coefficient for 5-month averaged SOI (m/s).
Vsoi (317x720): northward speed coefficient for 5-month averaged SOI (m/s).
eU, eV, eSST, eUsoi, eVsoi: standard error for U, V, SST, Usoi and Vsoi.
N (317x720): Number of drifter-days per square degree.

The columns of the ASCII dataset are: Lat, Lon, U, V, SST, eU, eV, eSST, N, Usoi, Vsoi, eUsoi, eVsoi.

The second version ( Matlab binary format/ ASCII/ NetCDF ) contains monthly mean values of surface currents and SST. The variable names of the Matlab file are the same as above (except that no SOI-related variables are included). The third index of matrix U, V, etc. corresponds to the month: 1=January, 2=February, etc. In the ASCII dataset, the first column is the month; the rest of the columns are the same as in the annual climatology file described above (except that no SOI-related variables are included).

The third version ( Matlab binary format/ ASCII/ NetCDF ) contains information about current variance (eddy kinetic energy) derived from residuals with respect to the time-mean, seasonal, spatial gradient, and SOI-related currents. The Matlab file contains the following variables:

Lon (1x720): longitude (degrees), negative=West.
Lat (1x317): latitude (degrees), 73S to 85N.
Up2bar (317x720): Zonal Velocity Variance, mean(u' ^2) (m^2/s^2).
Vp2bar (317x720): Meridional Velocity Variance, mean(v' ^2) (m^2/s^2).
rA (317x720): Variance ellipse semimajor axis (m^2/s^2).
rB (317x720): Variance ellipse semiminor axis (m^2/s^2).
angle (317x720): Orientation angle of variance ellipse (degrees, 0=east/west).
N (317x720): Number of drifter-days per square degree.

Note that Up2bar+Vp2bar=rA+rB, which is twice the eddy kinetic energy.

Description: satellite-tracked SVP drifting buoys (Sybrandy and Niiler, 1991; Niiler, 2001) provide observations of near-surface circulation at unprecedented resolution. In September 2005, the Global Drifter Array became the first fully realized component of the Global Ocean Observing System when it reached an array size of 1250 drifters. A drifter is composed of a surface float which includes a transmitter to relay data, a thermometer that reads temperature a few centimeters below the air/sea interface, and a submergence sensor used to detect when/if the drogue is lost. The surface float is tethered to a holey sock drogue, centered at 15 m depth. The drifter follows the flow integrated over the drogue depth, although some slip with respect to this motion is associated with direct wind forcing (Niiler and Paduan, 1995). This slip is greatly enhanced in drifters that have lost their drogues (Pazan and Niiler, 2000). Drifter velocities are derived from finite differences of their position fixes. These velocities, and the concurrent SST measurements, are archived at AOML's Drifting Buoy Data Assembly Center where the data are quality controlled and interpolated to 1/4-day intervals (Hansen and Herman, 1989; Hansen and Poulain, 1996).

In this study, daily winds from the NCEP/NCAR reanalysis were interpolated onto the drifter positions and used to estimate and remove the slip (Niiler and Paduan, 1995; Pazan and Niiler, 2000). All velocities and SSTs were lowpassed at five days to remove high frequency variability (diurnal, tidal, inertial).

Drifters sample regions of the ocean inhomogeneously, which can cause aliased time-mean values if strong seasonal or interannual variations are neglected. To address the seasonal cycle, Lumpkin (2003) developed a methodology to simultaneously decompose the drifter observations into time-mean, seasonal and eddy components using a Gauss-Markov approach that produces formal error bars on all components. Lumpkin showed that this methodology produces significantly different results than standard bin averaging. This methodology was further developed and evaluated using SST observations and products, and simulated drifters in the MICOM model (Lumpkin and Garraffo, 2005). The method produces significantly improved estimates of the mean currents and SST, and simultaneously provides the annual and semiannual amplitudes and phases at a nominal resolution of one degree squared.

To address inhomogeneous interannual sampling associated with ENSO, Johnson (2001) added a component proportional to a five-month lowpassed Southern Oscillation Index, and estimated components in elliptical bins with axes scaled and oriented using the residual variability (i.e., the eddy fluctuations).

In Lumpkin and Johnson (2013), the methodologies of Lumpkin (2003) and Johnson (2001) are combined. The observations are projected onto a time mean, annual and semiannual, SOI, and spatial gradient components within elliptical bins scaled and oriented using eddy fluctuations, and error bars are estimated for all terms.

When this methodology is applied to the modern data set of tropical Atlantic drifter observations, many features of the near-surface circulation become apparent which were not resolved by older ship-drift-based climatologies or by SEQUAL/FOCAL drifter trajectories (Lumpkin and Garzoli, 2005). In the Hawaiian Island region, the thousand-kilometer long island wake is revealed at unprecedented detail (Lumpkin and Flament, 2013).

Credits: This climatology was developed by Rick Lumpkin (NOAA/AOML) in collaboration with Gregory Johnson (NOAA/PMEL), Silvia Garzoli and Mayra Pazos (NOAA/AOML), Jessica Redman (CIMAS), and Zulema Garraffo (RSMAS, Univ. Miami).

References

Cuny, J., P. B. Rhines, P. P. Niiler and S. Bacon, 2002: Labrador Sea boundary currents and the fate of the Irminger Sea Water. J. Phys. Oceanogr. 32, 627-647.

Hansen, D. and A. Herman, 1989: Temporal sampling requirements for surface drifting buoys in the tropical Pacific. J. Atmos. Oceanic Technol. 6, 599-607.

Hansen, D. and P.-M. Poulain, 1996: Quality control and interpolations of WOCE-TOGA drifter data. J. Atmos. Oceanic Technol. 13, 900-909.

Johnson, G.C., 2001: The Pacific Ocean Subtropical Cell Surface Limb. Geophys. Res. Lett., 28, 1771-1774.

Lumpkin, R., 2003: Decomposition of surface drifter observations in the Atlantic Ocean. Geophys. Res. Lett. 30(14), 1753, 10.1029/2003GL017519.

Lumpkin, R. and S. L. Garzoli, 2005: Near-surface Circulation in the Tropical Atlantic Ocean. Deep-Sea Res.I 52 (3), 495-518, 10.1016/j.dsr.2004.09.001.

Lumpkin, R. and Z. Garraffo, 2005: Evaluating the Decomposition of Tropical Atlantic Drifter Observations. J. Atm. Oceanic Technol. 22, 1403-1415.

Lumpkin, R. and G. C. Johnson, 2013: Global Ocean Surface Velocities from Drifters: Mean, Variance, ENSO Response, and Seasonal Cycle. J. Geophys. Res.-Oceans, 118, pp 2992-3006, doi:10.1002/jgrc.20210.

Lumpkin, R. and P. Flament, 2013: On the extent and energetics of the Hawaiian Lee Countercurrent. Oceanography, 26(1), 58-65.

Niiler, P. P., 2001: The world ocean surface circulation. In Ocean Circulation and Climate, G. Siedler, J. Church and J. Gould, eds., Academic Press, Volume 77 of International Geophysics Series, 193-204.

Niiler, P. P., R. Davis and H. White, 1987: Water-following characteristics of a mixed-layer drifter. Deep-Sea Res. 34, 1867-1882.

Niiler, P. P. and J. D. Paduan, 1995: Wind-driven motions in the northeast Pacific as measured by Lagrangian drifters. J. Phys. Oceanogr. 25, 2819-2830.

Niiler, P. P., A. Sybrandy, K. Bi, P. Poulain and D. Bitterman, 1995: Measurements of the water-following capability of holey-sock and TRISTAR drifters. Deep-Sea Res. 42, 1951-1964.

Pazan, S. E. and P. P. Niiler, 2000: Recovery of near-surface velocity from undrogued drifters. J. Atmos. Oceanic Technol. 18, 476-489.

Ralph, E. A. and P. P. Niiler, 1999: Wind-driven currents in the Tropical Pacific. J. Phys. Oceanogr. 29, 2121-2129.

Sybrandy, A. L. and P. P. Niiler, 1991: WOCE/TOGA Lagrangian drifter construction manual. WOCE Rep. 63, SOI Ref. 91/6, 58pp, Scripps Inst. of Oceanogr., La Jolla, Calif.