Land-ice Framework


The landice framework module compass/landice/ contains observational data for various Antarctic basins. These are based on the ISMIP6 basin definitions, but it need not be limited to those. The basins do not need to be mutually exclusive, so more can be added as needed.


The landice framework module compass/landice/ provides a function for extrapolating variables into undefined regions. It is copied from a similar script in MPAS-Tools.


The landice framework module compass/landice/ provides functionality related to ice-shelf basal melting. Currently, there is a single function calc_mean_TF that calculated the mean thermal forcing along the ice-shelf draft in a domain for a given geometry file and thermal forcing file.


The landice framework module compass.landice.mesh provides functions used by all mesh_gen tests cases, which currently exist within the antarctica, crane, greenland, humboldt, kangerlussuaq, koge_bugt_s, and thwaites test groups. These functions include:

compass.landice.mesh.add_bedmachine_thk_to_ais_gridded_data() copies BedMachine thickness to the AIS reference gridded dataset. It replaces thickness field in the compilation dataset with the one we will be using from BedMachine for actual thickness interpolation There are significant inconsistencies between the masking of the two, particularly along the Antarctic Peninsula, that lead to funky mesh extent and culling if we use the thickness from 8km composite dataset to define the cullMask but then actually interpolate thickness from BedMachine. This function uses bilinear interpolation to interpolate from the 500 m resolution of BedMachine to the 8 km resolution of the reference dataset. It is not particularly accurate, but is fast and adequate for generating the flood filled mask for culling the mesh. Highly accurate conservative remapping is performed later for actually interpolating BedMachine thickness to the final MALI mesh.

compass.landice.mesh.clean_up_after_interp() performs some final clean up steps after interpolation for the AIS mesh case.

compass.landice.mesh.gridded_flood_fill() applies a flood-fill algorithm to the gridded dataset in order to separate the ice sheet from peripheral ice.

compass.landice.mesh.interp_ais_bedmachine() interpolates BedMachine thickness and bedTopography dataset to a MALI mesh, accounting for masking of the ice extent to avoid interpolation ramps.

compass.landice.mesh.interp_ais_interp_ais_measures() interpolates MEASURES ice velocity dataset to a MALI mesh, accounting for masking at the ice edge and extrapolation.

compass.landice.mesh.preprocess_ais_data() performs adjustments to gridded AIS datasets needed for rest of compass workflow to utilize them.

compass.landice.mesh.set_rectangular_geom_points_and_edges() sets node and edge coordinates to pass to py:func:mpas_tools.mesh.creation.build_mesh.build_planar_mesh().

compass.landice.mesh.set_cell_width() sets cell widths based on settings in config file to pass to mpas_tools.mesh.creation.build_mesh.build_planar_mesh(). Requires the following options to be set in the given config section: min_spac, max_spac, high_log_speed, low_log_speed, high_dist, low_dist, high_dist_bed, low_dist_bed, high_bed, low_bed, cull_distance, use_speed, use_dist_to_edge, use_dist_to_grounding_line, and use_bed.

compass.landice.mesh.get_dist_to_edge_and_gl() calculates distance from each point to ice edge and grounding line, to be used in mesh density functions in compass.landice.mesh.set_cell_width(). In future development, this should be updated to use a faster package such as scikit-fmm.

compass.landice.mesh.build_cell_width() determine final MPAS mesh cell sizes using desired cell widths calculated by py:func:compass.landice.mesh.set_cell_width(), based on user-defined density functions and config options.

compass.landice.mesh.build_mali_mesh() creates the MALI mesh based on final cell widths determined by py:func:compass.landice.mesh.build_cell_width(), using Jigsaw and MPAS-Tools functions. Culls the mesh based on config options, interpolates all available fields from the gridded dataset to the MALI mesh using the bilinear method, and marks domain boundaries as Dirichlet cells.

compass.landice.mesh.make_region_masks() creates region masks using regions defined in Geometric Features repository. It is only used by the antarctica and greenland test cases.

The following config options should be defined for all mesh_gen test cases (although not necessarily with the same values shown here, which are the defaults for the 1–10km Humboldt mesh):

# config options for humboldt test cases

# number of levels in the mesh
levels = 10

# Bounds of Humboldt domain. If you want the extent
# of the gridded dataset to determine the extent of
# the MALI domain, set these to None.
x_min = -630000.
x_max = 84000.
y_min = -1560000.
y_max = -860000.

# distance from ice margin to cull (km).
# Set to a value <= 0 if you do not want
# to cull based on distance from margin.
cull_distance = 5.0

# mesh density parameters
# minimum cell spacing (meters)
min_spac = 1.e3
# maximum cell spacing (meters)
max_spac = 1.e4
# log10 of max speed (m/yr) for cell spacing
high_log_speed = 2.5
# log10 of min speed (m/yr) for cell spacing
low_log_speed = 0.75
# distance at which cell spacing = max_spac (meters)
high_dist = 1.e5
# distance within which cell spacing = min_spac (meters)
low_dist = 1.e4

# These *_bed settings are only applied when use_bed = True.
# distance at which bed topography has no effect
high_dist_bed = 1.e5
# distance within which bed topography has maximum effect
low_dist_bed = 5.e4
# Bed elev beneath which cell spacing is minimized
low_bed = 50.0
# Bed elev above which cell spacing is maximized
high_bed = 100.0

# mesh density functions
use_speed = True
use_dist_to_grounding_line = False
use_dist_to_edge = True
use_bed = True