Data Analysis ||
Data files for some examples
Example pages containing:
Sometimes, it is desirable to 'fill' regions containing
missing values [_FillValue] with interpolated values while
leaving the original values unchanged.
performs this task.
Input values are unchanged and act a boundary conditions (constraints).
Generally, in regions bounded by valid data, this function does a
'pretty good job'. This function will extrapolate beyond data boundaries
and, as always, extrapolated values should be used with caution.
For demonstration purposes, create a grid using generate_2d_array
then use array syntax to set regions to missing values [_FillValue].
to fill the missing regions.
The top plot is the original grid; the middle plot shows the regions
which were manually set to _FillValue; the bottom plot show the
plot after poisson_grid_fill
Read SST data which contains missing values (_FillValue) over land.
to fill the missing regions.
The left plot show the global reconstruction; the right plot shows
the result when operating over a limited region. Note that
the values over South America were extrapolted.
Read hybrid model level data; use vinth2p
to interpolate the data
to user specified constant pressure levels. Data below
the surface pressure [PS] are not available. Hence,
extrapolation or grid filling (poisson_grid_fill
must be used.
For demonstration purposes the 950 hPa level was chosen. In each
figure the top plot shows the original grid. The clear areas represent
regions where 950hPa was below the corresponding surface pressure.
The middle plots show the result after using vinth2p_ecmwf
to interpolate temperature, specific humidity and geopotential height.
The bottom plot shows the result after using poisson_grid_fill.
If the clear areas is bounded by valid grid points,
the poisson_grid_fill produces reasonable
patterns. The area where values look unreasonable are the grid points
over the Antarctic. This is because to points are not
bounded. The vinth2p_ecmwf has problems when it is
used to extrapolate at levels well below the surface pressure level.
This is similar to example 3. Here the focus was in a region which
included the Himalaya rather than the globe. It more clearly
illustrates the strengths/weaknesses
The Z3 variable is interpolated to constant pressure levels.
The constant pressure levels include 600, 700, 800, 900, 950, 1000.
Each of the 3 images contains two horizontal rows. The leftmost plot
contains the 600 & 700hPa levels; the middle image the 800 & 900hPa
levels; the rightmost imnage the 950 & 1000 hPa levels. The left
figure of each plot shows the interpolated Z3 with no
extrapolation. Non-colored areas indicate regions (grid points) that
are below the surface pressure. The middle plots show the level after
interpolation by poisson_grid_fill. The rightmost
plots show the result of applying vinth2p_ecmwf.
Note that the poisson_grid_fill (middle) plots
generally look "reasonable" as long as there are boundary
values. Clearly the 1000 hPa level at the northern boundary look
unusual. At the lower levels the vinth2p_ecmwf are
on a different scale.