Stand alone 3km model		Nested 1km model
hops_sa_TS.mat		hops_nst_TS.mat

Each of the Matlab (*.mat) files contains the HOPS temperature and salinity output at the grid points nearest to the specified set of moorings. If you were to load the stand alone HOPS file,

   load hops_sa_TS

you'd see the following variables:

   hops_sa_TS_S   hops_sa_TS_lat     hops_sa_TS_time
   hops_sa_TS_T   hops_sa_TS_lon     hops_sa_TS_z

where:

*_time is a 3D array (14 × Ntimes × Ndepths) of times in Matlab's serial date number convention (see the documentation for Matlab's datenum function). Technically, this could have been a 1D array (time doesn't vary with depth) but making it 2D simplifies the plotting.

*_z is a 3D array (14 × Ntimes × Ndepths) of depths from the ocean surface in meters. This does need to be 2D, since the results came from our free-surface model, so depth does vary with time.

*_T & *_S are 3D arrays (14 × Ntimes × Ndepths) of temperature and salinity.

*_lat & *_lon are vectors of length 14, indicating the actual sampling positions of these data (i.e. the position of the nearest grid point).

Note that this extra dimension corresponds to the order of the specified mooring locations:

A final note: in the output from the large domain (3km resolution), moorings 31 and 6 are mapped to the same point, so their output is identical.

array mooring latitude longitude index id 1 30 39.025017 -73.066783 2 31 39.042483 -73.053567 3 06 39.042868 -73.076867 4 03 39.071300 -73.170000 5 29 39.119582 -73.277332 6 35 39.160000 -73.367500 7 36 38.988667 -72.986667 8 23 38.975217 -72.956133 9 24 38.957317 -72.916050 10 34 38.939500 -72.876100 11 43 38.926533 -72.844517 12 32 39.098400 -72.998700 13 45 39.182623 -72.942917 14 33 39.215333 -72.911750