multimelt provides three types of “services”. (1)It can produce masks of the different circum-Antarctic ice shelves and geometric properties on each ice shelf level (neede for the pdifferent parameterisations). (2) It computes mean profiles of temperature and salinity in front of the ice shelves in given domains of interest. (3) It computes 2D and 1D metrics related to basal melt of ice shelves.

The procedure to create the masks and box and plume characteristics is shown in the notebook prepare_mask_example.ipynb. The steps are also explained more in detail in Preparing masks to identify ice shelf and main ice shelf characteristics around Antarctica, Preparing the box characteristics and Preparing the plume characteristics.

The procedure to compute and format the input temperature (T) and salinity (S) profiles from 2D fields is shown in the notebook T_S_profiles_per_ice_shelf.ipynb. The steps are also explained more in detail in prepare_prof. !BE CAREFUL! If your 2D fields are in conservative temperature and absolute salinity, do not forget to convert them with the script conversion_CTtoPT_SAtoSP.ipynb.

The procedure to compute melt rates from temperature and salinity profiles is shown in the notebook compute_melt_example.ipynb. The steps are also explained more in detail in prod_melt.

How to run (3) : Computing basal melt rates¶

The melt function is designed to receive information about the ice-shelf geometry (formatted with multimelt.create_isf_mask_functions.create_mask_and_metadata_isf(), multimelt.plume_functions.prepare_plume_charac(), and multimelt.box_functions.box_charac_file()), and about temperature and salinity profiles in front of one or several ice shelves (formatted in T_S_profiles_per_ice_shelf.ipynb). The output is a range of 2D and 1D variables describing the melt rates at the base of the ice shelf or ice shelves, if you have several.

Input data¶

To compute the melt, in multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf()), you need

> the list of ice shelf IDs you are interested in (nisf_list)

> 2D geometric info (geometry_info_2D :

The variables contained in 'plume_charac_file.nc' created as shown in Preparing the plume characteristics

The variables 'ISF_mask', 'latitude' and 'longitude' contained in 'mask_file.nc' created as shown in Preparing masks to identify ice shelf and main ice shelf characteristics around Antarctica

ice_draft_pos: ice draft depth (positive downwards)

grid_cell_area_weighted: area of the grid cells weighted with the ice shelf concentration

isfdraft_conc: ice shelf concentration

> a stacked mask of the ice shelf regions to reduce calculation time and only select ice shelf point (isf_stack_mask). Can be created as follows:

isf_stack_mask = multimelt.useful_functions.create_stacked_mask(ISF_mask, nisf_list, ['y','x'], 'mask_coord')

> 1D geometric info (geometry_info_1D) :

The variables 'front_bot_depth_avg', 'front_bot_depth_max', and 'isf_name' contained in 'mask_file.nc' created as shown in Preparing masks to identify ice shelf and main ice shelf characteristics around Antarctica

> Temperature and salinity profiles (T_S_profile): one dataset containing theta_ocean, the potential temperature in °C, and salinity_ocean, the practical salinity in psu, both over at least the dimensions Nisf and depth.

> Input parameters to the different parameterisations: e.g. gamma, E0, C

If you want to use the box or PICOP parameterisation

> The variables contained in 'box_charac_file.nc' created as shown in Preparing the box characteristics

Running¶

To run the simple parameterisations, use the following command

nisf_list = geometry_info_1D.Nisf
T_S_profile = file_TS.ffill(dim='depth')

mparam = # POSSIBILITIES: ['linear_local', 'quadratic_local', 'quadratic_local_locslope', 'quadratic_local_cavslope', 'quadratic_mixed_mean', 'quadratic_mixed_locslope','quadratic_mixed_cavslope']

gamma = # fill in
ds_2D, ds_1D = meltf.calculate_melt_rate_1D_and_2D_all_isf(nisf_list,
                                                            T_S_profile, g
                                                            geometry_info_2D,
                                                            geometry_info_1D,
                                                            isf_stack_mask,
                                                            mparam,
                                                            gamma,
                                                            U_param=True)

ds_2D.to_netcdf(outputpath_melt+'melt_rates_2D_'+mparam+'.nc')
ds_1D.to_netcdf(outputpath_melt+'melt_rates_1D_'+mparam+'.nc')

To run the plume parameterisations, use the following command

nisf_list = geometry_info_1D.Nisf
T_S_profile = file_TS.ffill(dim='depth')

mparam = # POSSIBILITIES: ['lazero19_2', 'lazero19_modif2']

gamma = # fill in
E0 = # fill in

ds_2D, ds_1D = meltf.calculate_melt_rate_1D_and_2D_all_isf(nisf_list,
                                                            T_S_profile,
                                                            geometry_info_2D,
                                                            geometry_info_1D,
                                                            isf_stack_mask,
                                                            mparam,
                                                            gamma,
                                                            E0=E0,
                                                            verbose=True)

ds_2D.to_netcdf(outputpath_melt+'melt_rates_2D_'+mparam+'.nc')
ds_1D.to_netcdf(outputpath_melt+'melt_rates_1D_'+mparam+'.nc')

To run the box parameterisations, use the following command

nisf_list = geometry_info_1D.Nisf
T_S_profile = file_TS.ffill(dim='depth')
picop_opt = 'no'

nD_config = # POSSIBILITIES: 1 to 4
pism_version = # POSSIBILITIES: 'yes' or 'no'

mparam = 'boxes_'+str(nD_config)+'_pism'+pism_version+'_picop'+picop_opt

C = # fill in
gamma = # fill in

ds_2D, ds_1D = meltf.calculate_melt_rate_1D_and_2D_all_isf(nisf_list,
                                                            T_S_profile,
                                                            geometry_info_2D,
                                                            geometry_info_1D,
                                                            isf_stack_mask,
                                                            mparam,
                                                            gamma,
                                                            C=C,
                                                            angle_option='appenB',
                                                            box_charac_2D=box_charac_all_2D,
                                                            box_charac_1D=box_charac_all_1D,
                                                            box_tot=nD_config,
                                                            box_tot_option='nD_config',
                                                            pism_version=pism_version,
                                                            picop_opt=picop_opt)

ds_2D.to_netcdf(outputpath_melt+'melt_rates_2D_'+mparam+'.nc')
ds_1D.to_netcdf(outputpath_melt+'melt_rates_1D_'+mparam+'.nc')

To run the PICOP parameterisations, use the following command

nisf_list = geometry_info_1D.Nisf
T_S_profile = file_TS.ffill(dim='depth')

nD_config = # POSSIBILITIES: 1 to 4
pism_version = # POSSIBILITIES: 'yes' or 'no'
picop_opt = # POSSIBILITIES: '2018' or '2019'

mparam = 'boxes_'+str(nD_config)+'_pism'+pism_version+'_picopyes'

C = # for box part - fill in
gamma = # for box part - fill in

gamma_plume = # for plume part - fill in
E0 = # for plume part - fill in

ds_2D, ds_1D = meltf.calculate_melt_rate_1D_and_2D_all_isf(nisf_list,
                                                            T_S_profile,
                                                            geometry_info_2D,
                                                            geometry_info_1D,
                                                            isf_stack_mask,
                                                            mparam,
                                                            gamma,
                                                            C=C,
                                                            E0=E0,
                                                            angle_option='appenB',
                                                            box_charac_2D=box_charac_all_2D,
                                                            box_charac_1D=box_charac_all_1D,
                                                            box_tot=nD_config,
                                                            box_tot_option='nD_config',
                                                            pism_version=pism_version,
                                                            picop_opt=picop_opt,
                                                            gamma_plume=gamma_plume)

ds_2D.to_netcdf(outputpath_melt+'melt_rates_2D_'+mparam+'.nc')
ds_1D.to_netcdf(outputpath_melt+'melt_rates_1D_'+mparam+'.nc')

Output¶

The xr.Dataset ds_2D contains the following variables on a map (2D):

melt_m_ice_per_s: melt rate in m ice per second
melt_m_ice_per_y: melt rate in m ice per year (computed per default but can also be removed by re-defining the list options_2D given to multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf())
melt_m_we_per_y: melt rate in m water equivalent per year (computed per default but can also be removed by re-defining the list options_2D given to multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf())

The xr.Dataset ds_1D contains the following integrated variables (1D): * melt_m_ice_per_y_tot: total (accumulated) melt over each ice shelf in m ice per year * melt_m_ice_per_y_avg: average melt for each ice shelf in m ice per year (computed per default but can also be removed by re-defining the list options_1D given to multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf()) * melt_m_ice_per_y_min: minimum melt for each ice shelf in m ice per year (computed per default but can also be removed by re-defining the list options_1D given to multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf()) * melt_m_ice_per_y_max: maximum melt for each ice shelf in m ice per year (computed per default but can also be removed by re-defining the list options_1D given to multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf()) * melt_we_per_y_tot: total (accumulated) melt over each ice shelf in m water equivalent per year (computed per default but can also be removed by re-defining the list options_1D given to multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf()) * melt_Gt_per_y_tot: total melt over each ice shelf in Gt per year (computed per default but can also be removed by re-defining the list options_1D given to multimelt.melt_functions.calculate_melt_rate_1D_and_2D_all_isf())