Pressure/Height vs. Latitude (high-level plot interface)
Data must be in pressure coordinates!
gsn_csm_pres_hgt is the plot interface that plots height versus latitude plots.
Note, this data is already on pressure levels. If this were model data, it would be necessary to interpolate from the hybrid coefficients to pressure levels.
gsnContourZeroLineThicknessF doubles the thickness of the zero contour, gsnContourPosLineDashPattern dashes the positive contours (not used here), and gsnContourNegLineDashPattern dashes the negative contours.
ShadeLtContour is the shea utility function that shades regions less than a given number. Note: this function has been superceded by the more versatile gsn_contour_shade. We recommend you use this instead.
There are numerous other contour effects to choose from.
ShadeLtGtContour is the shea utility function that shades regions in a less than/greater than context. Note: this function has been superceded by the more versatile gsn_contour_shade. We recommend you use this instead.
vcRefAnnoOrthogonalPosF = -0.165, Moves the reference vector orthogonal from its default position.
gsn_csm_pres_hgt_vector is the plot interface that draws vectors over a pressure height plot. Note that vcMapDirection must be set to False in order for the vectors to be pointing in the right direction. In V6.2.0, this resource will be set to False by default for the gsn_csm_pres_hgt_vector function.
Note, in this example, V is set to zero so that only the vertical velocities are plotted. Additionally, the units of omega (mb/day) and v (m/s) have different units. No scaling is used in this example but the user may wish do do so.
tmYRMode = "Automatic", will override the plot template's explicit setting of the height labels on the right axis.
The point of this script is to allow you more control over the look of pressure-height plot, for example, if you want to change the labels on the right Y axis.
ESMF Example 30 was run twice: bilinear and conservative interpolation. Bilinear interpolation would generally be appropriate for any reasonably smooth variable. Conservation interpolation would be recommended for interpolating flux quantities and variables that can be fractal (eg precipitation).