- 1 Overview
- 2 List of Projections
- 3 Initial state, control run, historical run and projections set up
- 4 Atmospheric forcing: SMB and temperature anomalies
- 5 Oceanic forcing: temperature, salinity, thermal forcing and melt rate parameterization
- 6 Antarctic ice shelf fracture
- 7 Requirements for the projections
- 8 References
- 9 Acknowledgements
- 10 Appendix 1 – Output grid definition and interpolation
- 11 Appendix 2 – Naming conventions, upload and model output data.
- 12 Appendix 3 – Participating Models and Characteristics.
NOTE: THIS PAGE IS UNDER CONSTRUCTION. WHEN IT IS FINISHED, THIS STATEMENT WILL BE REMOVED. LAST UPDATE: March 18th, 2019
This page describes the experimental protocol for the ISMIP6 projections that target the upcoming IPCC AR6 assessment. Due to the delay in CMIP6 climate simulations, the initial set of ISMIP6 simulations are based on CMIP5 projections. As CMIP6 model outputs become available, ISMIP6 will include simulations based on these new models.
The experimental framework was revised in September 2018 during an ISMIP6 workshop held in Sassenheim (NL). The protocol, summarized in Fig 1, allows for:
• Sampling CMIP scenarios: main focus is on the high emission RCP8.5, but ice sheet evolution in response to low emission RCP2.6 is also investigated.
• Sampling CMIP models: 6 AOGCMs have been selected from the CMIP5 model ensemble: CCSM4, CSIRO-Mk3-6-0, HadGEM2-ES, IPSL-CM5A-MR, MIROC-ESM-CHEM and NorESM1-M. The AOGCMs were identified based on the following steps: 1) present-day climate near Antarctica in agreement with observations (evaluated by model biases over the historical period), 2) sample a diversity of forcing (evaluated by differences in projections and code similarities), and 3) allow only models with RCP8.5 and RCP2.6.
• Sampling ice sheet model uncertainty: "standard" and "open" experiments. The "standard" experiments are based on parameterizations developed by the ocean and atmospheric focus groups, while "open" experiments utilize the parameterizations already in use by respective ice sheet models.
• Sampling ocean forcing uncertainty: the standard experiments include "high", "mid" and "low" values for the forcing parameters.
• Experiment ranking: This experimental framework results in a series of projections (divided into core and targeted experiments), a historical run and a control run. Not every ice sheet model will be able to carry out the full set of experiments, but they are requested to participate in the core experiments. The experiments are therefore ranked according to their importance. Groups are encouraged to work through the lists presented below (see Table 1 for core experiments, and targeted experiments will follow soon), starting from the top, and complete as many experiments as possible. This approach is based on Shannon et al. (2013): it ensures that all groups do a subset of identical experiments, while it also allows faster models to explore the targeted experiment space more fully.
Figure 1: Overview of the Antarctic experimental framework
List of Projections
With the help of the atmosphere and ocean focus groups, a number of CMIP5 AOGCMs have been selected for ISMIP6 standalone ice sheet model projections. Table 1 lists the core experiments which are the minimum contribution expected from ISMIP6 models. All groups are expected to contribute to the "standard" experiments. Groups that have their own methods for implementing ocean and atmosphere forcing, are encouraged to do the suite with "open" experiments (1-4), but these are not compulsory. Models that perform the "open" experiments can use the parameterization of their choice to simulate atmospheric and oceanic forcings, but these parameterizations must use the given CMIP5 AOGCM outputs.
Modeling groups that can run many simulations will be encouraged to further explore the ice sheet response using targeted experiments (Table 2, coming soon). These will include three additional CMIP5 AOGCMs under RCP8.5, and experiments that explore the ocean forcing uncertainty. Depending on the results of experiments 3 and 7, which consider RCP2.6, additional AOGCMs may be suggested with RCP2.6 for models that are able to do many simulations, but these would be a lower priority than the completing the set of experiments with the 6 AOGCMs for the RCP8.5 scenario. Once all the datasets are prepared for the additional AOGCMs, the next series of targeted experiments will be announced.
Note: As of March 18, all datasets needed for the core experiments (Table 1) are available on the ftp server: Ocean dataset, mask of ice shelf fracture, and atmospheric datasets for the 3 models (MIROC_ESM_CHEM, NorESM1-M and CCSM4) under RCP8.5. Ocean dataset and atmospheric dataset for NorESM1-M under RCP2.6 are also ready.
|Table 1: Core Experiments based on MIROC_ESM_CHEM, NorESM1-M and CCSM4|
|Expt||RCP||AOGCM||Std/open||Ocean Forcing Coef||Fracture||Note|
|0||N/A||N/A||Control||N/A||None||Model drift evaluation|
|1||8.5||NorESM1-M||Open||Medium||None||Low atmospheric change and mid-to-high ocean warming|
|2||8.5||MIROC_ESM_CHEM||Open||Medium||None||High atmospheric changes and median ocean warming|
|3||2.6||NorESM1-M||Open||Medium||None||Low atmospheric change and mid-to-high ocean warming|
|4||8.5||CCSM4||Open||Medium||None||Large atmospheric warming and variable regional ocean warming|
|5||8.5||NorESM1-M||Standard||Medium||None||Low atmospheric change and mid-to-high ocean warming|
|6||8.5||MIROC_ESM_CHEM||Standard||Medium||None||High atmospheric changes and median ocean warming|
|7||2.6||NorESM1-M||Standard||Medium||None||Low atmospheric change and mid-to-high ocean warming|
|8||8.5||CCSM4||Standard||Medium||None||Large atmospheric warming and variable regional ocean warming|
|9||8.5||NorESM1-M||Standard||High||None||Ocean Forcing Uncertainty, using 95th percentile values|
|10||8.5||NorESM1-M||Standard||Low||None||Ocean Forcing Uncertainty, using 5th percentile values|
|11||8.5||CCSM4||Open||Medium||Yes||Experiment with ice shelf hydrofracture|
|12||8.5||CCSM4||Standard||Medium||Yes||Experiment with ice shelf hydrofracture|
Initial state, control run, historical run and projections set up
The core and targeted experiments all start on January 2015 and end in December 2100. The start date follows the CMIP6 protocol for projections, while the end date is constrained by the availability of forcing. In many cases, modelers will need to run a short historical run to bring their models from the “initialization date” to the “projection start date” of January 2015.
The “initialization date” (or initial state) is left to the modeling groups discretion and can be any time prior to January 2015 (or equal to January 2015). The “initialization date” corresponds to the date assigned to the initialization procedure. Groups can reuse their initMIP initialization configuration or generate a new initial state. In the later case, it is important to redo the initMIP schematic experiments ('asmb' and 'abmb', Seroussi et al. 2019), as it will help understanding how a novel initial state contributes to the uncertainty in ice sheet evolution.
A control run (‘ctrl’) is also needed to evaluate model drift. As for initMIP, the control run is obtained by running the model forward, keeping the surface mass balance and ocean forcing used in the initialization technique unchanged. The control run should last a minimum of 100 years, the same duration as the schematic initMIP experiments. The control run should also be sufficiently long to reach 2100. (See examples below).
A single historical run is required from ice sheet models, from which all the projections will branch off. Groups are free to choose how to run the “historical run”, using a reanalysis, a historical run from an RCM, a historical run from an AOGCM or combination of multiple datasets. ISMIP6 provides a climatology for the SMB and surface temperature for each of the AOGCMs used to generate the projection dataset, as well as anomalies. For Antarctica, the SMB and temperature climatology corresponds to 1995-2014, to align with the reference period used by AR6. The Antarctic SMB and temperature anomalies are available from 1950. For the Antarctic ocean, the datasets start from 1850 and the climate model climatology corresponds to 1995-2014. Groups that would prefer to use an Antarctica dataset provided by ISMIP6 are recommended to use NorESM-M climatology and anomalies for SMB and surface temperature (in the directory Atmosphere_Forcing/noresm1-m_rcp8.5). For the ocean, modelers can use observational climatology (Ocean_Forcing/climatology_from_obs_1995-2017), and/or anomalies (Ocean_Forcing/noresm1-m_rcp8.5/1850-1994). Note that the climate model climatologies (Ocean_Forcing/noresm1-m_rcp8.5/climatology_1995-2014) are not intended for use by modelers, but are simply provided so that user can see what was subtracted during the datasets preparation, as the forcing data (Ocean_Forcing/noresm1-m_rcp8.5/1850-1994) is the sum of the observational climatology and anomalies.
Examples of possible setups:
Case 1: initialization date = start date for control run = start date for projection = Jan 2015
No historical run. Control run = 100 yrs.
Case 2: initialization date = start date for control run = Jan 2005; start date for projection = Jan 2015
Historical run: from Jan 2005 to Dec 2014. Control run = 100 yrs.
Case 3: initialization date = start date for control run = Jan 1980; start date for projection = Jan 2015
Historical run: from Jan 1980 to Dec 2014. Control run = 120 yrs.
|Table 0: Initialization experiments|
|Expt||RCP||AOGCM||Std/open||Ocean Forcing Coef||Fracture||Note|
|A||N/A||N/A||Control||N/A||None||Model drift evaluation|
Atmospheric forcing: SMB and temperature anomalies
ISMIP6 provides surface forcing datasets for the Antarctic ice sheet (AIS) based on CMIP AOGCM simulations. Two approaches are possible: using AOGCM output directly, or re-interpreting the GCM climates through higher-resolution regional climate models (RCMs). The later allows to capture narrow regions at the periphery of the ice sheet with large surface mass balance (SMB) gradients, which are not captured by CMIP5 AOGCMs, and is the technique used for the Greenland ice sheet. For the Antarctic CMIP5 based projections, RCMs are not used, so SMB anomalies based on AOGCM are directly applied.
For CMIP6, many of the AOGCMs that have indicated participation in ISMIP6, now use multiple elevation classes to downscale SMB to finer grid resolution. Once these models have completed the CMIP6 projections, our goal is to include additional ISMIP6 projections using SMB downscaled via elevation class.
For the ISMIP6 projections based on CMIP5 AOGCMs, the surface forcing consists of anomalies in SMB and surface temperature (Fig 2). SMB is needed by ISMs to compute mass changes at the surface, and surface temperature (i.e., the ice temperature at the base of the snow, as distinct from the 2-m air temperature or skin temperature) is used by many ISMs as an upper boundary condition. SMB and SMB anomalies are given in units of kg m-2 s-1 (water equivalent), and surface temperature in units of deg K. The following remarks refer mostly to SMB, but the same comments would generally apply to surface temperature as well.
The SMB and SMB anomalies are provided on the ISMIP6 standard ice sheet grid for Antarctica. ISMs then horizontally interpolate the anomaly forcing from the standard grid to their native grids. Before applying SMB anomalies, ISMs need to be initialized by applying a baseline SMB (either a time series or a climatology). ISMIP6 provides SMB climatologies for the reference period (January 1995 to December 2014) from the same models used to provide the anomalies. ISMs can use these climatologies for spin-up, if desired, but are free to use their own preferred SMB forcing. Let SMB_ref(x,y) denote the SMB used to initialize the ISM. If a time-dependent SMB is used for spin-up, then SMB_ref(x,y) is the average over the reference period.
ISMIP6 provides yearly averaged surface mass balance anomalies, aSMB(x,y,t), along with its components (precipitation, evaporation and runoff). During the run, SMB is computed as:
SMB(x,y,t) = SMB_ref(x,y) + aSMB(x,y,t).
aSMB(x,y,t) is constant over the entire year and changes stepwise at the beginning of every year. To convert aSMB to units [m yr-1] typically used in an ice sheet model, multiply the netcdf variable by 31556926 s/yr, 1/1000 m3/kg and by the density ratio rho_w/rho_i:
aSMB [m yr-1] = aSMB [kg m-2 s-1] * 31556926 / 1000 * (1000/rho_i), where rho_i is your specific ice density (typically 917.0 or similar).
The datasets can be obtained via the ISMIP6 ftp server (email email@example.com to obtain the login information) under: ftp://cryoftp1.gsfc.nasa.gov/ISMIP6/Projections/AIS/Atmosphere_Forcing
Files are provided for several resolutions (1 km, 2 km, 4 km, 8 km, 16 km, and 32 km). Modeling groups should use the resolution closest to their native grid to conservatively interpolate data to model (see Appendix 1, below).
Figure 2: SMB and surface temperature anomalies for CCSM4, MIROC_ESM_CHEM, and NorESM1-M under RCP8.5 and 2.6 (top). SMB climatology for the reference period (January 1995-December 2014) for these models under RCP8.5 (middle), along with difference in SMB climatology between RCP8.5 and 2.6 (bottom).
Oceanic forcing: temperature, salinity, thermal forcing and melt rate parameterization
ISMIP6 provides datasets of extrapolated ocean "ambient" temperature (T), salinity (S) and thermal forcing (TF) from 1850-2100 that are appropriate for present and future ice-shelf cavities. These datasets originate from CMIP models and have been extrapolated under ice shelves, using rules that account for sills and troughs by Xylar Asay-Davis (Fig 3). The datasets are on the 8 km ISMIP6 Antarctic grid. More information on how the datasets were produced is available in the presentations and webinar that can be retrieved from: ftp://cryoftp1.gsfc.nasa.gov/ISMIP6/Projections/AIS/Ocean_Forcing or at https://github.com/xylar/ismip6-ocean-forcing
Figure 3: Bathymetry and IMBIE2 basins (left) used in the sub-ice shelf extrapolation of ocean temperature (right).
ISMIP6 standard approach was developed by the Antarctic ocean focus group, and consist of two approaches for the parameterization of basal melt. The melt parameterizations, along with the motivation for the uncertainty parameter choices are described in greater details here. These ocean melting parameterizations are evaluated for an idealized geometry of the Pine Island glacier in Favier et al. (2019). Note that example codes for both parameterizations can be found in the "parameterizations" directory.
The first approach, a non-local quadratic melting parameterization, is the preferred method for ISMIP6 simulations for obtaining melt rates m(x,y) in meters of pure water/yr:
However, an alternative (and easier to implement) takes the form of a local quadratic melting parameterization:
The forcing dataset (for example /Ocean_Forcing/noresm1-m_rcp8.5/1995-2100) consist of annual anomalies from the climate models, which were added to the observed climatology (/Ocean_Forcing/climatology_from_obs_1995-2017). Modelers should simply use the data as they are to compute the melt rates using either (1) or (3). In addition to the annual forcing datasets needed for use with these parameterizations, parameters needed to sample the uncertainty in the basal melt are also provided in the /Ocean_Forcing/parameterizations directory. The files with names *median.nc, *5th_percentiles.nc, *95th_percentiles.nc correspond to the median, low and high cases of the gamma_0 and DeltaT values in the core experiments listed in Table 1.
Note that the climate model climatologies (Ocean_Forcing/noresm1-m_rcp8.5/climatology_1995-2014) are provided to allow ISMIP6 members to see what was subtracted in the preparation of the ocean forcing dataset, but are not intended to be used in the initialization for example. Instead it is recommended to use the climatology from the observations.
ISMIP6 open approach is used to sample a larger variety of oceanic forcing parameterizations, as it remains an active field of research. Models are free to continue applying the ocean forcing parameterization they used during the model initialization or their preferred method, but should still rely on the ocean forcing datasets provided by ISMIP6 to simulate future ocean conditions.
Antarctic ice shelf fracture
Surface melting can trigger ice shelf collapse (for example, the Larsen B ice shelf in the Antarctic Peninsula). This mechanism is separate from cliff-collapse, but is a precursor to cliff-collapse. Although the mechanisms for Larsen B-style ice shelf collapse are still poorly understood, ISMIP6 provides dataset for ice shelf collapse in the form of a time dependent mask (Fig 4). These datasets were derived from CMIP5 near surface air temperature (tas) following the method described in Trusel et al. (2015), which results in annual surface melt. For ISMIP6, Luke Trussel prepared the bias corrected annual surface melt, which were used to generate the masks. Ice shelves are assumed to collapse following a 10 year period with annual surface melt above 725 mm (Trusel et al., 2015). Some experiments require to model ice shelf collapse and the ISMIP6 masks provided should be used in this case. For the other experiments, ice shelf collapse should not be included. Models are free to decide on the appropriate method to simulate tributary glaciers' behavior following the collapse of ice shelves.
The datasets can be obtained from: ftp://cryoftp1.gsfc.nasa.gov/ISMIP6/Projections/AIS/Ice_Shelf_fracture
Figure 4: Ice shelf collapse mask for CCSM4 under RCP8.5
Requirements for the projections
• Participants can and are encouraged to contribute with different models and/or initialisation methods
• Models have to be able to prescribe a given SMB anomaly
• Models have to be able to use one of the two ocean parameterizations (non-local or local) proposed for the core experiments.
• Adjustment of SMB due to geometric changes in forward experiments is encouraged.
• Bedrock adjustment in forward experiment is allowed.
• The choice of model input data is unconstrained to allow participants the use of their preferred model setup without modification. Modelers without preferred data set choice can have a look at the ISMIP6 Datasets page for possible options.
• To allow for analysis, any modeling choice needs to be well documented. A README file needs to be submitted along the outputs as an integral part of the contribution to the ISMIP6. It may be obtained here or requested by email to ismip6-at-gmail.com.
Favier, L., Jourdain, N. C., Jenkins, A., Merino, N., Durand, G., Gagliardini, O., Gillet-Chaulet, F., and Mathiot, P.: Assessment of Sub-Shelf Melting Parameterisations Using theOcean-Ice Sheet Coupled Model NEMO(v3.6)-Elmer/Ice(v8.3), Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-26, in review, 2019.
Seroussi, H., Nowicki, S., Simon, E., Abe Ouchi, A., Albrecht, T., Brondex, J., Cornford, S., Dumas, C., Gillet-Chaulet, F., Goelzer, H., Golledge, N. R., Gregory, J. M., Greve, R., Hoffman, M. J., Humbert, A., Huybrechts, P., Kleiner, T., Larour, E., Leguy, G., Lipscomb, W. H., Lowry, D., Mengel, M., Morlighem, M., Pattyn, F., Payne, A. J., Pollard, D., Price, S., Quiquet, A., Reerink, T., Reese, R., Rodehacke, C. B., Schlegel, N.-J., Shepherd, A., Sun, S., Sutter, J., Van Breedam, J., van de Wal, R. S. W., Winkelmann, R., and Zhang, T., initMIP-Antarctica: An ice sheet model initialization experiment of ISMIP6, The Cryosphere Discuss., https://doi.org/10.5194/tc-2018-271, in review, 2019.
Shannon, S.R., Payne A.J., Bartholomew I.D., Van Den Broeke M.R., Edwards T.L., Fettweis X., Gagliardini O., Gillet-Chaulet F., Goelzer H., Hoffman M.J., Huybrechts P. (2013) Enhanced basal lubrication and the contribution of the Greenland ice sheet to future sea-level rise, Proceedings of the National Academy of Sciences, 110(35):14156-61.
The experimental protocol and datasets for the ISMIP6-Projections-Antarctica standalone ice sheet simulations would not have been possible without the effort of many scientists that have given their time and expertise, and have run models to convert the CMIP5 models output into datasets that standalone ice sheet models can use. ISMIP6 would like to thank the ocean focus group under the leadership of Fiamma Straneo, the atmospheric focus group under the leadership of Bill Lipscomb and Robin Smith, and the CMIP5 model evaluation focus group under the leadership of Alice Barthel. Xylar Asay-Davis, Nicolas Jourdain, Tore Hattermann, Chris Little, Helene Seroussi have been instrumental in the development of the ice shelf basal melt rate parameterization and associated datasets. Erika Simon, Richard Cullather and Sophie Nowicki prepared the atmospheric dataset. Luke Trusel and Helene Seroussi prepared the ice shelf fracture dataset. Alice Barthel, Chris Little, Cecile Agosta, Nicolas Jourdain, and Tore Hattermann provided a rigorous analysis of the CMIP5 models against historical data, which allowed the CMIP5 model evaluation group and the ISMIP6 steering committee to select the CMIP5 models used in this effort. Finally, we thank the ISMIP6 ice sheet modelers for their feedback on the design of the protocol and their willingness to participate in ISMIP6.
Appendix 1 – Output grid definition and interpolation
All 2D data is requested on a regular grid with the following description. Polar stereo-graphic projection with standard parallel at 71° S and a central meridian of 0° W on datum WGS84. The lower left corner is at (-3040000 m, -3040000 m) and the upper right at (3040000 m, 3040000 m). This is the same grid used to provide the SMB and basal melting anomaly forcings. The output should be submitted on a resolution adapted to the resolution of the model and can be 32km, 16 km, 8 km, 4 km, 2 km or 1 km. The data will be stored on this resolution for archiving and conservatively interpolated on a 8 km resolution for diagnostic processing by ISMIP6. Output should be provided with single precision.
If interpolation is required in order to transform the SMB forcing (1 km grid data) to your native grid, and transform your model variables to the initMIP output grid (32 km, 16 km, 8 km, 4 km, 2 km, 1 km), it is required that conservative interpolation is used. The motivation for using a common method for all models is to minimize model to model differences due to the choice of interpolation method.
A1.1 Regridding Tools and Tips
- An overview of the regridding process can be found on the Regridding page.
- Regridding_with_CDO contains tools and tips that have been used by ISMIP6 members.
- If you need help with conservative interpolation, please email ismip6-at-gmail.com.
Appendix 2 – Naming conventions, upload and model output data.
COMING SOON: GUIDANCE FOR CMIP6 MODEL REGISTRATION, ADDITIONAL GUIDANCE FOR FILE PREPARATIONS and REVISED FILENAME CONVENTION. HOWEVER, THE CURRENT FILE STRUCTURE AND GUIDANCE BELOW IS DESIGNED TO FACILITATE THE FINAL FILE PREPARATION (NEEDED BEFORE UPLOADING TO THE CMIP6 ARCHIVE). THE EXTRA INFORMATION/FILE RENAMING WILL BE IMPLEMENTED BY SCRIPTS CURRENTLY WRITTEN BY ISMIP6, WHICH WILL ALSO CHECK FOR CF COMPLIANCE ETC. WE WILL PROVIDE HELP TO MODELERS FOR THE FINAL FILE FORMATING PREPARATION, AND MODELERS SHOULD PROCEED WITH SAVING THEIR RESULTS USING THE INFORMATION BELOW
• one variable per file for all 2D fields and scalar variables
• a completed readme file
• single precision should be used for all output
A2.1 File name convention
File name convention for 2D fields and scalar variables:
File name convention for readme file:
<variable> = variable name (e.g. lithk)
<IS> = ice sheet (AIS or GIS)
<GROUP> = group acronym (all upper case or numbers, no special characters)
<MODEL> = model acronym (all upper case or numbers, no special characters)
<EXP> = experiment name (init, ctrl, asmb or abmb)
For example, a file containing the variable "orog" for the Antarctic ice sheet, submitted by group “JPL” with model “ISSM” for experiment “ctrl” would be called: orog_AIS_JPL_ISSM_ctrl.nc
If JPL repeats the experiments with a different version of the model (for example, by changing the sliding law), it could be named ISSM2, and so forth.
A2.2 Uploading your model output
Please upload your model output on the FTP server cryoftp1.gsfc.nasa.gov, and email firstname.lastname@example.org for the user name and latest password.
After log in, go to the ISMIP6/Projections/AIS/output directory via:
ftp> cd /ISMIP6/Projections/AIS/output
and create a directory named <GROUP> with the following sub-directory structure:
<EXP_RES> should include both the experiment name and the output grid used to simplify the processing (e.g., asmb_08). Only the directory name should include this resolution, unlike the output files.
Create additional <MODEL> directories when participating with more than one model or model version.
A2.3 Model output variables and README file
The README file is an important contribution to the ISMIP6 submission. It may be obtained here or requested by email to ismip6-at-gmail.com
The variables requested in the table below serve to evaluate and compare the different models and initialization techniques. Some of the variables may not be applicable for your model, in which case they are to be omitted (with explanation in the README file).
We distinguish between state variables (ST) (e.g. ice thickness, temperatures and velocities) and flux variables (FL) (e.g. SMB). State variables should be given as snapshot information at the end of one year for both scalars and 2D variables (for initMIP, 2D variables were only requested over five year periods), while flux variables are to be averaged over the respective periods. Please specify in your README file how your reported flux data has been averaged over time. Ideally, the standard would be go average over all native time steps.
Flux variables are defined positive when the process adds mass to the ice sheet and negative otherwise.
In compliance with CMIP6, time should be defined in "days since <basetime>", where <basetime> must be specified by the user, typically in the form year-month-day (e.g., "days since 1800-1-1"). For simulations meant to represent a particular historical period, set the ‘base time’ to the time at the beginning of the simulation. A historical run initialized with forcing for year 2007 would, for example, have units of “days since 2007-1-1”. For the future scenario runs, retain the same <basetime> as used in the historical run from which it was initiated. Note the CF definition for years (section 4.4): a common_year is 365 days, a leap_year is 366 days, a Julian_year is 365.25 days, and a Gregorian_year is 365.2425 days.
| Table 2: Variable request for ISMIP6 projections.
Bold names indicate a change compared to initMIP, to align the request with the CMIP6 official MIPtable "IyrAnt" or names in the CF convention.
The first entry should be that from which the simulation starts. Fields such as surface mass balance flux should be what was applied as boundary conditions.
|Variable||Dim||Type||Variable Name||Standard Name||Units||Comment|
|2D variables requested yearly as snapshots (end of the year) for type ST and as yearly average for type FL.|
|Ice thickness||x,y,t||ST||lithk||land_ice_thickness||m||The thickness of the ice sheet|
|Surface elevation||x,y,t||ST||orog||surface_altitude||m||The altitude or surface elevation of the ice sheet|
|Base elevation||x,y,t||ST||base||base_altitude||m||The altitude of the lower ice surface elevation of the ice sheet|
|Bedrock elevation||x,y,t||ST||topg||bedrock_altitude||m||The bedrock topography (may change during the projections)|
|Geothermal heat flux||x,y||C||hfgeoubed||upward_geothermal_heat_flux_in_land_ice alias "upward_geothermal_heat_flux_at_ground_level"||W m-2||Geothermal Heat flux (only needed beneath the grounded ice.)|
|Surface mass balance flux||x,y,t||FL||acabf||land_ice_surface_specific_mass_balance_flux||kg m-2 s-1||Surface Mass Balance flux|
|Basal mass balance flux beneath grounded ice||x,y,t||FL||libmassbfgr alias "libmassbf"||land_ice_basal_specific_mass_balance_flux||kg m-2 s-1||Basal mass balance flux (only beneath grounded ice)|
|Basal mass balance flux beneath floating ice||x,y,t||FL||libmassbffl alias "libmassbf"||land_ice_basal_specific_mass_balance_flux||kg m-2 s-1|| Basal mass balance flux (only beneath floating ice)
|Ice thickness imbalance||x,y,t||FL||dlithkdt||tendency_of_land_ice_thickness||m s-1||dHdt|
|Surface velocity in x||x,y,t||ST||xvelsurf alias "uvelsurf"||land_ice_surface_x_velocity||m s-1||u-velocity at land ice surface|
|Surface velocity in y||x,y,t||ST||yvelsurf alias "vvelsurf"||land_ice_surface_y_velocity||m s-1||v-velocity at land ice surface|
|Surface velocity in z||x,y,t||ST||zvelsurf alias "wvelsurf"||land_ice_surface_upward_velocity||m s-1||w-velocity at land ice surface|
|Basal velocity in x||x,y,t||ST||xvelbase alias "uvelbase"||land_ice_basal_x_velocity||m s-1||u-velocity at land ice base|
|Basal velocity in y||x,y,t||ST||yvelbase alias "vvelbase"||land_ice_basal_y_velocity||m s-1||v-velocity at land ice base|
|Basal velocity in z||x,y,t||ST||zvelbase alias "wvelbase"||land_ice_basal_upward_velocity||m s-1||w-velocity at land ice base|
|Mean velocity in x||x,y,t||ST||xvelmean alias "uvelmean"||land_ice_vertical_mean_x_velocity||m s-1||The vertical mean land ice velocity is the average from the bedrock to the surface of the ice|
|Mean velocity in y||x,y,t||ST||yvelmean alias "vvelmean"||land_ice_vertical_mean_y_velocity||m s-1||The vertical mean land ice velocity is the average from the bedrock to the surface of the ice|
|Surface temperature||x,y,t||ST||litemptop alias "litempsnic"||temperature_at_top_of_ice_sheet_model alias "temperature_at_ground_level_in_snow_or_firn"||K||Ice temperature at surface|
|Basal temperature beneath grounded ice sheet||x,y,t||ST||litempbotgr alias "litempbot"||temperature_at_base_of_ice_sheet_model alias "land_ice_basal_temperature"||K||Ice temperature at base of grounded ice sheet|
|Basal temperature beneath floating ice shelf||x,y,t||ST||litempbotfl alias "litempbot"||temperature_at_base_of_ice_sheet_model alias "land_ice_basal_temperature"||K||Ice temperature at base of floating ice shelf|
|Basal drag||x,y,t||ST||strbasemag||land_ice_basal_drag alias "magnitude_of_land_ice_basal_drag"||Pa||Basal drag|
|Calving flux||x,y,t||FL||licalvf||land_ice_specific_mass_flux_due_to_calving||kg m-1 s-1||Loss of ice mass resulting from iceberg calving. Only for grid cells in contact with ocean|
|Ice front melt flux||x,y,t||FL||lifmassbf||land_ice_specific_mass_flux_due_to_calving_and_ice_front_melting||kg m-1 s-1||Loss of ice mass resulting from ice front melting. Only for grid cells in contact with ocean|
|Grounding line flux||x,y,t||FL||ligroundf||land_ice_specific_mass_flux_at_grounding_line||kg m-1 s-1||Loss of grounded ice mass resulting at grounding line. Only for grid cells in contact with grounding line|
|Land ice area fraction||x,y,t||ST||sftgif||land_ice_area_fraction||1||Fraction of grid cell covered by land ice (ice sheet, ice shelf, ice cap, glacier)|
|Grounded ice sheet area fraction||x,y,t||ST||sftgrf||grounded_ice_sheet_area_fraction||1||Fraction of grid cell covered by grounded ice sheet, where grounded indicates that the quantity correspond to the ice sheet that flows over bedrock|
|Floating ice sheet area fraction||x,y,t||ST||sftflf||floating_ice_shelf_area_fraction alias "floating_ice_sheet_area_fraction"||1||Fraction of grid cell covered by ice sheet flowing over seawater|
|Scalar outputs requested every full year: snapshots for type ST and 1 year averages for type FL.|
|Total ice mass||t||ST||lim||land_ice_mass||kg||spatial integration, volume times density|
|Mass above floatation||t||ST||limnsw||land_ice_mass_not_displacing_sea_water||kg||spatial integration, volume times density|
|Grounded ice area||t||ST||iareagr alias "iareag"||grounded_ice_sheet_area alias "grounded_land_ice_area"||m^2||spatial integration|
|Floating ice area||t||ST||iareafl alias "iareaf"||floating_ice_shelf_area||m^2||spatial integration|
|Total SMB flux||t||FL||tendacabf||tendency_of_land_ice_mass_due_to_surface_mass_balance||kg s-1||spatial integration|
|Total BMB flux||t||FL||tendlibmassbf||tendency_of_land_ice_mass_due_to_basal_mass_balance||kg s-1||spatial integration|
|Total BMB flux beneath floating ice||t||FL||tendlibmassbffl||tendency_of_land_ice_mass_due_to_basal_mass_balance||kg s-1||spatial integration (computed beneath floating ice only)|
|Total calving flux||t||FL||tendlicalvf||tendency_of_land_ice_mass_due_to_calving||kg s-1||spatial integration|
|Total calving and ice front melting flux||t||FL||tendlifmassbf||tendency_of_land_ice_mass_due_to_calving_and_ice_front_melting||kg s-1|| spatial integration
|Total grounding line flux||t||FL||tendligroundf||tendency_of_grounded_ice_mass||kg s-1|| spatial integration
Appendix 3 – Participating Models and Characteristics.
Antarctica Standalone Ice Sheet Modeling
|Thomas Kleiner, Johannes Sutter, Angelika Humbert||PISM||AWI||Alfred Wegener Institute for Polar and Marine Research, DE /University of Bremen, DE|
|Stephen Cornford, Daniel Martin||BISICLESPRELIM||CPOM||University of Bristol, Centre for Polar Observation and Modelling, UK|
|Fabien Gillet-Chaulet||ELMER||IGE||Laboratoire de Glaciologie et Géophysique de l'Environnement, FR|
|Ralf Greve||SICOPOLIS||ILTS||Institute of Low Temperature Science, Hokkaido University, Sapporo, JP|
|Heiko Goelzer||IMAUICE||IMAU||Utrecht University, Institute for Marine and Atmospheric Research (IMAU), Utrecht, NL|
|Helene Seroussi||ISSM||JPL||NASA Jet Propulsion Laboratory, Pasadena, USA|
|Stephen Price, Matthew Hoffman||MALI||LANL||Los Alamos National Laboratory, Los Alamos, USA|
|William Lipscomb, Gunter Leguy||CISM||NCAR||National Center for Atmospheric Research|
|Ronja Reese||PISM||PIK||Potsdam Institute for Climate Impact Research, DE|
|Helene Seroussi, Mathieu Morlighem, Tyler Pelle||ISSM||UCIJPL||NASA Jet Propulsion Laboratory, Pasadena, USA / University of California Irvine, Irvine, USA|
|Sainan Sun and Frank Pattyn||FETISH||ULB||Laboratoire de Glaciologie, Université Libre de Bruxelles, Brussels, BE|
|Chen Zhao, Rupert Gladstone, Ben Galton-Fenzi||ELMER||UTAS||University of Tasmania|
TABLE WILL BE MADE WHEN SUBMISSIONS ARE COMING IN