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  • A Dataset of Global Ocean Surface Currents for 1999-2010
  • Author:China Argo Real-time Data Center   Source:Argo  Pubtime:2017-05-15 17:24:57   Hit:
  • Jiping XIE and Jiang ZHU
    Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China

            Click hereto get the dataset.

    1.Background

            Since observations of surface trajectories of ARGO floats have location errors from 150m to 1000m, the direct estimation of trajectory-mean surface currents from observations could have errors of 5.4 cm s-1 for u- and v- component in Pacific on average. Based on Kalman Filter, a new method to estimate the surface trajectories of ARGO floats by combining surface trajectory observations and a trajectory prediction model is proposed by Xie and Zhu (2008), as shown in Fig.1. The method aims to improve surface velocity estimation via reducing positioning errors of surface trajectories. Theoretical errors of predicted trajectories are about 1 km that is consistent with innovations (about 1.1 km). By optimal combining information from predictions and observations with their error statistics, the estimated trajectory positioning errors are reduced significantly. The estimated surface velocities have errors of 4.4 cm s-1 for u- and v- component on average.
            Furthermore, the surface currents from the Argo floats are compared with the surface drifter-derived currents and the Tropical Atmosphere Ocean program (TAO) measurements. The comparisons show good agreement for both the current amplitude and the direction of surface currents. Results indicate the feasibility of obtaining ocean surface currents from the Argo array and of combining the surface currents from Argo and the ocean surface drifters for in situ mapping of the global surface currents (ref., Xie and Zhu, 2009).
            A dataset of surface current vectors with error estimate from 1999 to 2010 is derived from the trajectories of the Array for Real-time Geostrophic Oceanography (Argo) drifting on surface over the global ocean.

    Fig.1 Sketch of analyzing the Argo trajectory by Kalman filter (ref. Xie and Zhu, 2008)

    2.Method and data

            The raw data of the Argo floats in delayed mode were obtained from the global data centers (ftp://usgodae1.usgodae.org/pub/outgoing/ARGO and ftp.ifremer.fr/ifremer/ARGO) from 1999 to 2007 in the global oceans. For surface current estimations, many factors that can cause potential errors such as positioning abnormality, miscommunication, etc. should be considered. The Quality Control (QC) measures emphasize on positioning and interval-time check. In the positioning check, we assume that all of the satellite fixes in a surface trajectory should be close to each other. If any fix has a distance to the others of over 200 km, the fix will be deleted. The time between a pair of adjacent fixes in a surface trajectory usually is usually several minutes to several hours. In the interval-time check, if an interval-time is shorter than 10 min, the late fix will be deleted. In addition, if the distance between a pair of fixes in a surface trajectory is shorter than the total positioning error, the late fix is deleted. If each velocity vector between a pair of adjacent fixes is more than 2 m s-1, the trajectory will be neglected.
            The method used in this study was proposed by Xie and Zhu (2008). Briefly, the surface current estimation from the surface trajectory of each Argo float is improved by using the Kalman filter technique.

    Table 1 Specific of the variables in Sur_disc.dat

    Variable

    Definition

    Argo float ID

    WMO float identifier.

    cycle number

    A profiling float performs cycles. The float cycle number is related with this current vector.

    fixed points

    The valid locations in trajectory drifting on surface.

    first location time

    Julian time of the beginning location. The integer part represents the day, the decimal part represents the time of the location in a day. The Julian day is relative to Jan 1 1950. Example:
    18833.8013889885: July 25 2001 19:14:00

    last location time

    Julian time of the last location, but its mean is same with the above mentioned.

    latitude of first location

    Latitude of the fist location in trajectory. (Unit: degree north)

    longitude of first location

    Longitude of the fist location in trajectory. (Unit: degree east)

    latitude of last location

    Latitude of the last location in trajectory. (Unit: degree north)

    longitude of last location

    Longitude of the last location in trajectory. (Unit: degree east)

    u component

    U component of surface current. (Unit: eastward, cm/s)

    RMS error of u

    Evaluation of the uncertainty of u. (unit: cm/s)

    v component

    V component of surface current. (Unit: northward, cm/s)

    RMS error of v

    Evaluation of the uncertainty of v. (unit: cm/s)

    3.Dataset description

            This dataset version2 of surface currents contains 2 sections:

    1. Discrete current vectors (Sur_disc.dat)
    2. Normal grid currents (Sur_grid???.dat)

            The discrete surface current vectors (total: 562652) which are averaged along their trajectories. The vector file (Sur_disc.dat) is ASCII, and includes 13 variables: Argo float ID, cycle number, fixed points in trajectory, first location time, last location time, latitude of first location, longitude of first location, latitude of last location, longitude of last location, u component, RMS error of u, v component, RMS error of v, as listed in Table 1.
            Based on the discrete current vectors, we further derive the climatology of annual mean surface currents (Sur_grid.dat) in normal grid of 1°x1° and monthly surface currents (Sur_grid_mon.dat) in normal grid of 2°x2°. For annual mean currents, the latitude is increased from 69.5°S by 1° interval, and the longitude from 24.5°E by 1° interval. For monthly mean currents, the latitude begins from 69°S to 69°N, and the longitude begins from 24.5°E eastwardly by the 2° interval. These two unformatted files includes 5 variables: zonal velocity, meridional velocity, uncertainty of zonal velocity, uncertainty of meridional velocity, sampling number. Their details are listed in Table 2.
    Table 2 Specific of the variables in averaging data

    Variable

    Definition

    U

    Zonal currents averaged in little bins. (Unit: eastward, cm/s). The default value: 32767.

    V

    Meridional currents averaged in little bins. (Unit: northward, cm/s). The default value: 32767.

    Eu

    Evaluation of the uncertainty of zonal currents. (unit: cm/s)

    Ev

    Evaluation of the uncertainty of meridional currents. (unit: cm/s)

    Kn

    Numbers of the averaged current vectors in each bin

    For example, to read the averaging file the code of fortran90 is following:
    +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    N0=180; M0=70; NN=12;
    open(2,file=’Sur_grid_mon.dat’, form='unformatted', access='direct', recl=N0*M0, convert=’little_endian’)
    l=0
    do k=1,NN
       l=l+1; read(2,rec=l) ((U(i,j,k),i=1,N0),j=1,M0)
       l=l+1; read(2,rec=l) ((V(i,j,k),i=1,N0),j=1,M0)
       l=l+1; read(2,rec=l) ((Eu(i,j,k),i=1,N0),j=1,M0)
       l=l+1; read(2,rec=l) ((Ev(i,j,k),i=1,N0),j=1,M0)
       l=l+1; read(2,rec=l) ((real(Kn2(i,j,k)),i=1,N0),j=1,M0)
    end do
    close(2)
    +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
    If to read the annual mean current file, you can adjust the first line into:
    N0=360; M0=140; NN=1;
    +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++

    4.General feature

            In this dataset, the surface current vectors nearly cover the global ocean. Figure 2 and Figure 3 respectively show the spatial distributions of the sampling number and the surface currents averaged in 1°x1° bins.

    argo_mean_00.jpg
    Fig.2 Numbers of surface current vectors in each 1°x1° bin from Argo trajectory (1999-2010).

            As shown in Fig.2, the distribution of the derived current vectors is uneven and covers the mostly global ocean. The high densities of the vectors are located near western Pacific ocean and northern Arabian sea. Compared to the previous distribution of the currents in 1999-2007, the present version of the surface currents covers more widely. For instance, the current vectors are increased in the southern Pacific ocean, around the south of Australia, and some marginal seas like in the South China Sea.

    argo_mean_uv00.jpg
    Fig.3 Annual mean surface current speed in 1°x1° bin from Argo trajectory
    (1999-2010, unit: cm s-1).

            Based on the all discrete current vectors, the annual mean speed can be shown in Fig.3. Near the equator, the strong zonal currents more than 40 cm s-1 are clear in the centers of Pacific Ocean and Atlantic Ocean. Outside of the equator, the westward North Equator Currents with 30 cm s-1 are also dominant in Fig.3. Meanwhile, the strong west boundary currents including the currents along the coast of Brazil, the Kuroshio, and the Gulf Stream are prominent in Fig.3.

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