Difference between revisions of "PEM (Planetary Evolution Model)"

Revision as of 09:09, 4 January 2023

Overview of the PEM (Planetary Evolution Model)

The objective of the “Planetary Evolution Model” is to develop numerical climate models to simulate the past environments of Mars, explain the observed landforms, and, on this basis, better understand the past environment on Mars and its evolution.

PEM schematic view ; credit: Francois Forget

To accurately simulate the climate and the fate of volatiles for thousands to millions of years we must couple physical processes with very different timescale, ranging from clouds microphysics and atmospheric dynamics (represented in the GCM) to the evolution of lakes, glacier accumulation, and subsurface ice evolution.

Given the diversity and the complexity of the Martian paleoclimates, the model use an “asynchronous coupling” between the slow ice and water reservoirs models and the GCM. In practice the Planetary evolution model use a horizontal grid identical to that of the PCM, and include the same representation of the microclimate on slopes. In our case, we run the Planetary Evolution Model with an adaptative time step, depending upon the dynamics of the modeled system (smaller timesteps must first be used so that the different volatile reservoirs reach a quasi-equilibrium, then the timestep will depends on the evolution of the forcing, which is slow in the case of obliquity, for instance) . At each timestep, the inputs from the atmosphere (e.g. mean precipitation, sublimation and evaporation, temperatures, dust deposition) is obtained through a multi-annual run of the Global Climate model using the outcome of the Mars Evolution Model as initial state.

The PEM can works in two modes:

• M1 : Search of the steady state given an external forcing and an initial situation
• M2 : Realistic following of orbital forcing

For both modes, the PEM will run and extrapolate tendencies 'as long as it is meaningfull'. This means that for the different physical processes modelled, a criterion is computed

In either way, a run works like this:

• Run 2 years of GCM: From this, we extract data such as daily average pressure, daily averaged vmr of atmospheric components, daily minimum of ice etc...
• The GCM restart file are renamed to be read by the PEM. They are modified by the PEM to be able to start a new GCM simulation.
• If we are in a M2 configuration mode, a beginning year needs to be specified in the run_PEM.def, and the file ob_ex_lsp.asc present.
• The PEM is launched.
• GCM tendencies are computed from the data of the first item. They are applied to the start files and can be adapted to the situation (change of surface pressure etc...). All the physical processes take place.
• ........

Physical processes modelled

✅ Ice accumulation (Improvement possibles like changes of topography, watercaptag etc)

❌ Lag deposit, stratification (See Simon Neviere, Futur intern of Lucas)

∼ Glacier flow (CO2) , ✅ subgrid-scale slope phenomena

∼ Subsurface Ground Ice (In validation)

❌ Hydrology: lake, river, ocean, etc. (Alexandre Gauvain)

PEM inputs and outputs

Inputs:

• start_evol.nc A Dynamical GCM start file
• startfi_evol.nc A physic GCM start file
• startfi_PEM.nc A start file specific to the PEM (optional)
• run.def and run_PEM.def A txt file specifying run parameters
• ob_ex_lsp.asc A txt files specifying orbit parameters (optional - only needed for M2)
• data_GCM_Y1.nc A netcdf file containing information about the first typical year run by the GCM
• data_GCM_Y2.nc A netcdf file containing information about the second typical year run by the GCM

Outputs:

• restart_evol.nc A Dynamical GCM start file to start the next GCM iteration run
• restartfi_evol.nc A physic GCM start file to start the next GCM iteration run
• restartfi_PEM.nc A start file specific to the PEM to start the next PCM run
• diagfi_PEM.nc (optional) A netcdf file containing physical information about the PCM run

Naming convention of variables

Some variables comes from the GCM run. There are 3 cases:

• Constant variables Some variable are not changed during the PEM run, they are named var_cGCM. ex:???
• Adapted variables Some variables are adapted to the current state and recomputed through the PEM run, they are named var_aGCM. ex:???
• Tendencies from GCM Some variables are tendencies obtained from the GCM run, they are named var_tGCM. ex:???

Some variables coming from the GCM can be shaped as the dynamical grid but needs to be used in the physical grid. The change is done via the subroutine grid_dyn_phys. In this routine, the name is changed:

• Dynamical to physical grid the variable is renamed from var to var_phys

Variables that exists in the GCM but that here belong to the PEM are named:

• Exist in the GCM but belong to the PEM var_PEM

Variables that are specific to the PEM are not named following a special convention.

Index in loops:

• Through physical grid : ig (max ngrid)
• Through tracer : iq (max nq)
• Through subslopes : islope (max nslope)

TO DO:

• Rename variables
• Tendencies from the GCM : qsurf_GCM_tend

• Remove _slope

• ini_qsurf

• min_qsurf

Choices of parameters (run_PEM.def)

• evol_orbit_pem: Boolean. Do you want to follow an orbital forcing predefined (read in ob_ex_lsp.asc for example)? (default=false)
• year_bp_ini: Integer. Number of year before present to start the pem run if evol_orbit_pem=.true. , default=0
• Max_iter_pem: Integer. Maximal number of iteration if none of the stopping criterion is reached and if evol_orbit_pem=.false., default=99999999
• dt_pem: Integer. Time step of the PEM in year, default=1
• alpha_criterion: Real. Acceptance rate of sublimating ice surface change, default=0.2
• soil_pem: Boolean. Do you want to run with subsurface physical processes in the PEM? default=.true.