NOISEDRIFTERS is the jOceans module of jLab.

 NOISEDRIFTERS  Create a noise Lagrangian dataset matching mean and variance.
    Given Lagrangian trajectories and their velocity spectra, NOISEDRIFTERS
    creates a noise dataset that matches, for each trajectory, (i) the
    starting location, (ii) the mean velocity, and (iii) the approximate
    variance or eddy kinetic energy, with a velocity spectrum that is an 
    isotropic version of the spectrum of the input trajectory.
    LON are the latitudes and longitudes of Lagrangian trajectories
    observed at Matlab date number NUM, and with complex velocities CV 
    rotary velocity spectra SPP and SSN, outputs a noise dataset of 
    trajectories with latitudes LATN, longitudes LONN, and velocities CVN.
    All input arguments are cell arrays of the same size, with one
    trajectory per cell, and all output arrays will also be of this size. 
    Note that the units of CV are cm/s, as are those of CVN.  Similarly,
    the spectral SPP and SNN should be computed with CV having those units.
    NOISEDRIFTERS creates an isotropic spectrum by taking, at each
    frequency, the minimum of SPP and SNN.  These are as output by MSPEC, 
    and should be formed with a sufficient degree of smoothing, e.g. not
    the periodogram estimate.  
    Once the spectral shape is established, NOISEDRIFTERS creates a random
    Gaussian time series having exactly this spectral shape.  Each random 
    velocity time series is then set to have the same mean value and 
    variance as the corresponding original time series. 
    The random velocity time series are then integrated to give the output
    trajectories LATN and LONN, using UV2LATLON.  The initial value of LAT 
    and LON are the same as that of LATN and LONN.  
    These noise trajectories are differenced again using LATLON2UV to
    produce CVN, as this is how the velocities are produced from 
    trajectories for the observations.  Because of the differences between 
    numerically integrating with UV2LATLON and differencing with LATLON2UV,
    the variancees of CVN and CV are approximately but not exactly equal.
    NOISEDRIFTERS(NUM,LAT,LON,CV) with no spectra input alternately uses
    white noise velocities to generate the output fields.
    NOISEDRIFTERS(...,'parallel') parallelizes the computation using a 
    PARFOR loop, which requires the Parallel Computing Toolbox.
    Usage: [latn,lonn,cvn]=noisedrifters(num,lat,lon,cv,spp,snn);
    This is part of JLAB --- type 'help jlab' for more information
    (C) 2019 J.M. Lilly --- type 'help jlab_license' for details

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