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Added comments to ice shelf figures
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Kaitlin Naughten committed Aug 2, 2017
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54 changes: 48 additions & 6 deletions file_guide.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -1379,12 +1379,12 @@ mip_calc_massloss.py: Calculate the average mass loss for each ice shelf over
mip_regions_1var.py: For each of the 8 ice shelf regions analysed in this
intercomparison paper, make one 3x1 figure for 5 different
variables (ice shelf draft, ice shelf melt rate, bottom
water temperature, bottom water salinity, surface velocity)
where each variable is averaged over the years 2002-2016
and zoomed into the region of interest. The 3 parts of
each figure are MetROMS, FESOM low-res, and FESOM high-res.
The surface velocity figures show absolute value (speed)
in colours, and direction with vector arrows.
water temperature, bottom water salinity, vertically
averaged velocity) where each variable is averaged over
the years 2002-2016 and zoomed into the region of interest.
The 3 parts of each figure are MetROMS, FESOM low-res, and
FESOM high-res. The velocity figures show absolute value
(speed) in colours, and direction with vector arrows.
To run: First clone my "fesomtools" GitHub repository and
replace '/short/y99/kaa561/fesomtools' (near the
top of the file) with the path to the cloned
Expand All @@ -1394,6 +1394,48 @@ mip_regions_1var.py: For each of the 8 ice shelf regions analysed in this
and type "run mip_regions_1var.py". The script
will output a bunch of pngs.

mip_iceshelf_figures.py: This is the giant monster script to generate 8
multi-part figures showing ice shelf processes in the
8 regions defined in the intercomparison paper. Each
figure is size Nx3 where N=3,4,5 is the number of
variables shown (current options are ice shelf melt
rate, ice shelf draft, bottom water temperature or
salinity, vertically averaged velocity, zonal slices
of temperature and salinity) and 3 is the number of
models (MetROMS, low-res FESOM, high-res FESOM). All
variables are averaged over the period 2002-2016, i.e.
the first 10 years of the simulation are discarded as
spinup, and seasonal cycles and interannual
variability are not considered.
In order to avoid unnecessarily repetitive code, this
script contains multiple functions which accept
location bounds as arguments (eg to calculate min/max
over the given region, to plot ice shelf draft over
the given region for each model, etc.) but in order to
prevent the function argument lists from getting out
of control, most of the variables are global and so
the majority of this script is not wrapped within a
function. Be very careful if you are running this
script in an active python session to make sure there
are no conflicting variable names previously defined.
To run: First clone my "fesomtools" GitHub repository
and replace '/short/y99/kaa561/fesomtools'
(near the top of the file) with the path to
the cloned repository on your system. Also
make sure the paths to the ROMS and FESOM
files near the top of the script are correct.
To use the predetermined regions and variable
combinations, simply open python or ipython
and type "run mip_iceshelf_figures.py". The
script will output a bunch of pngs. To modify
for other regions or variable combinations,
scroll down to "USER MODIFIED SECTION" to see
examples of how to call the functions to
create multi-part figures. You will have to
fiddle around with the x and y bounds,
GridSpec arguments, colourbar axes, etc. so
that the positioning looks okay.


***UTILITY FUNCTIONS***

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131 changes: 131 additions & 0 deletions mip_iceshelf_figures.py
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Expand Up @@ -19,6 +19,31 @@
from unrotate_vector import *
from unrotate_grid import *

# This is the giant monster script to generate 8 multi-part figures showing
# ice shelf processes in the 8 regions defined in the intercomparison paper.
# Each figure is size Nx3 where N=3,4,5 is the number of variables shown
# (current options are ice shelf melt rate, ice shelf draft, bottom water
# temperature or salinity, vertically averaged velocity, zonal slices of
# temperature and salinity) and 3 is the number of models (MetROMS, low-res
# FESOM, high-res FESOM). All variables are averaged over the period 2002-2016,
# i.e. the first 10 years of the simulation are discarded as spinup, and
# seasonal cycles and interannual variability are not considered.

# In order to avoid unnecessarily repetitive code, this script contains
# multiple functions which accept location bounds as arguments (eg to calculate
# min/max over the given region, to plot ice shelf draft over the given region
# for each model, etc.) but in order to prevent the function argument lists from
# getting out of control, most of the variables are global and so the majority
# of this script is not wrapped within a function. Be very careful if you are
# running this script in an active python session to make sure there are no
# conflicting variable names previously defined.

# To modify for your purposes, adjust the file paths (immediately below) as
# needed, and then scroll down to "USER MODIFIED SECTION" to see examples of
# how to call the functions to create multi-part figures. You will have to
# fiddle around with the x and y bounds, GridSpec arguments, colourbar axes,
# etc. so that the positioning looks okay.

# File paths
roms_grid = '/short/m68/kaa561/metroms_iceshelf/apps/common/grid/circ30S_quarterdegree.nc'
roms_file = '/short/m68/kaa561/metroms_iceshelf/tmproms/run/intercomparison/2002_2016_avg.nc'
Expand Down Expand Up @@ -727,6 +752,16 @@
fig.savefig('larsen.png')


# For the given variable in MetROMS, low-res FESOM, and high-res FESOM, find
# the max and min values across all 3 models in the given region.
# Input:
# roms_data = 2D field of data on the MetROMS grid (lat x lon)
# fesom_data_lr, fesom_data_hr = data for each 2D element on the FESOM low-res
# and high-res meshes respectively
# x_min, x_max, y_min, y_max = bounds on x and y (using polar coordinate
# transformation from above) for the desired region
# Output:
# var_min, var_max = min and max data values in this region across all 3 models
def get_min_max (roms_data, fesom_data_lr, fesom_data_hr, x_min, x_max, y_min, y_max):

# Start with ROMS
Expand Down Expand Up @@ -757,6 +792,20 @@ def get_min_max (roms_data, fesom_data_lr, fesom_data_hr, x_min, x_max, y_min, y
return var_min, var_max


# Create a 2D vector field for vertically averaged velocity in MetROMS, low-res
# FESOM, and high-res FESOM for the given region. Average velocity over
# horizontal bins (in x and y) for easy plotting.
# Input:
# x_min, x_max, y_min, y_max = bounds on x and y (using polar coordinate
# transformation from above) for the desired region
# num_bins = number of bins to use for both x and y dimensions (try 30 or 40)
# Output:
# x_centres, y_centres = 1D arrays of length num_bins containing x and y
# coordinates of the bin centres
# roms_ubin, roms_vbin = 2D arrays of size num_bins x num_bins containing
# vector components for MetROMS at each bin
# fesom_ubin_lr, fesom_vbin_lr = same for FESOM low-res
# fesom_ubin_hr, fesom_vbin_hr = same for FESOM high-res
def make_vectors (x_min, x_max, y_min, y_max, num_bins):

# Set up bins (edges)
Expand Down Expand Up @@ -847,6 +896,16 @@ def make_vectors (x_min, x_max, y_min, y_max, num_bins):
return x_centres, y_centres, roms_ubin, roms_vbin, fesom_ubin_lr, fesom_vbin_lr, fesom_ubin_hr, fesom_vbin_hr


# Plot ice shelf draft for MetROMS, low-res FESOM, and high-res FESOM for the
# given region, in the given axes.
# Input:
# x_min, x_max, y_min, y_max = bounds on x and y (using polar coordinate
# transformation from above) for the desired region
# gs = GridSpec object of size 1x3 to plot in
# cbaxes = Axes object for location of colourbar
# cbar_ticks = 1D array containing values for ticks on colourbar
# letter = 'a', 'b', 'c', etc. to add before the ice shelf draft title, for
# use in a figure showing multiple variables
def plot_draft (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, letter):

# Set up a grey square for FESOM to fill the background with land
Expand Down Expand Up @@ -905,6 +964,24 @@ def plot_draft (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, letter):
cbar = colorbar(img, cax=cbaxes, ticks=cbar_ticks)


# Plot ice shelf melt rate for MetROMS, low-res FESOM, and high-res FESOM for
# the given region, in the given axes.
# Input:
# x_min, x_max, y_min, y_max = bounds on x and y (using polar coordinate
# transformation from above) for the desired region
# gs = GridSpec object of size 1x3 to plot in
# cbaxes = Axes object for location of colourbar
# cbar_ticks = 1D array containing values for ticks on colourbar
# change_points = list of size 3 containing values where the colourmap should
# transition (1) from yellow to orange, (2) from orange to red,
# (3) from red to magenta. Should not include the minimum value,
# 0, or the maximum value. This way the custom colourmap can be
# adjusted so that all melt rates are visible, particularly
# for ice shelves with strong spatial variations in melt.
# letter = 'a', 'b', 'c', etc. to add before the ice shelf melt rate title, for
# use in a figure showing multiple variables
# y0 = y-coordinate of model titles for the entire plot, assuming melt rate is
# always at the top (i.e. letter='a'). Play around between 1.15 and 1.35.
def plot_melt (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, change_points, letter, y0):

# Set up a grey square for FESOM to fill the background with land
Expand Down Expand Up @@ -987,6 +1064,16 @@ def plot_melt (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, change_points
text(0.5, y0, 'FESOM (high-res)', fontsize=18, horizontalalignment='center', transform=ax.transAxes)


# Plot bottom water temperature for MetROMS, low-res FESOM, and high-res FESOM
# for the given region, in the given axes.
# Input:
# x_min, x_max, y_min, y_max = bounds on x and y (using polar coordinate
# transformation from above) for the desired region
# gs = GridSpec object of size 1x3 to plot in
# cbaxes = Axes object for location of colourbar
# cbar_ticks = 1D array containing values for ticks on colourbar
# letter = 'a', 'b', 'c', etc. to add before the bottom water temp title, for
# use in a figure showing multiple variables
def plot_bwtemp (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, letter):

# Set up a grey square for FESOM to fill the background with land
Expand Down Expand Up @@ -1045,6 +1132,16 @@ def plot_bwtemp (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, letter):
cbar = colorbar(img, cax=cbaxes, ticks=cbar_ticks)


# Plot bottom water salinity for MetROMS, low-res FESOM, and high-res FESOM
# for the given region, in the given axes.
# Input:
# x_min, x_max, y_min, y_max = bounds on x and y (using polar coordinate
# transformation from above) for the desired region
# gs = GridSpec object of size 1x3 to plot in
# cbaxes = Axes object for location of colourbar
# cbar_ticks = 1D array containing values for ticks on colourbar
# letter = 'a', 'b', 'c', etc. to add before the bottom water salinity title,
# for use in a figure showing multiple variables
def plot_bwsalt (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, letter):

# Set up a grey square for FESOM to fill the background with land
Expand Down Expand Up @@ -1103,6 +1200,22 @@ def plot_bwsalt (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, letter):
cbar = colorbar(img, cax=cbaxes, ticks=cbar_ticks)


# Plot vertically averaged velocity for MetROMS, low-res FESOM, and high-res
# FESOM for the given region, in the given axes.
# Input:
# x_min, x_max, y_min, y_max = bounds on x and y (using polar coordinate
# transformation from above) for the desired region
# gs = GridSpec object of size 1x3 to plot in
# cbaxes = Axes object for location of colourbar
# cbar_ticks = 1D array containing values for ticks on colourbar
# x_centres, y_centres, roms_ubin, roms_vbin, fesom_ubin_lr, fesom_vbin_lr,
# fesom_ubin_hr, fesom_vbin_hr = output variables from the
# "make_vectors" function for the given region
# letter = 'a', 'b', 'c', etc. to add before the bottom water salinity title,
# for use in a figure showing multiple variables
# loc_string = optional string containing location title, in the case of
# velocity being zoomed into a smaller region to the other
# variables (eg "George VI Ice Shelf" for the Bellingshausen plot)
def plot_velavg (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, x_centres, y_centres, roms_ubin, roms_vbin, fesom_ubin_lr, fesom_vbin_lr, fesom_ubin_hr, fesom_vbin_hr, letter, loc_string=None):

# Set up a grey square for FESOM to fill the background with land
Expand Down Expand Up @@ -1169,6 +1282,24 @@ def plot_velavg (x_min, x_max, y_min, y_max, gs, cbaxes, cbar_ticks, x_centres,
cbar = colorbar(img, cax=cbaxes, ticks=cbar_ticks)


# Plot zonal slices (latitude vs depth) of temperature and salinity for
# MetROMS, low-res FESOM, and high-res FESOM through the given longitude, in the
# given axes.
# Input:
# lon0 = longitude to plot (-180 to 180)
# lat_min, lat_max = bounds on latitude to plot (-90 to 90)
# depth_min, depth_max = bounds on depth to plot (negative, in metres)
# gs1, gs2 = GridSpec objects of size 1x3, in which to plot temperature and
# salinity respectively
# cbaxes1, cbaxes2 = Axes objects for locations of temperature and salinity
# colourbars
# cbar_ticks1, cbar_ticks2 = 1D arrays containing values for ticks on
# temperature and salinity colourbars
# letter1, letter2 = 'a', 'b', 'c', etc. to add before the temperature and
# salinity titles
# loc_string = optional string containing location title, in the case of
# plotting slices through a single ice shelf in a large region
# (eg "Fimbul Ice Shelf" for the Eastern Weddell plot)
def plot_zonal_ts (lon0, lat_min, lat_max, depth_min, depth_max, gs1, gs2, cbaxes1, cbaxes2, cbar_ticks1, cbar_ticks2, letter1, letter2, loc_string=None):

# Figure out what to write on the title about longitude
Expand Down
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