This repository provide a collection of shell scripts to produce a ensemble analysis (2D+time) of altimetric observations.
These scripts make use of the SESAM toolbox (https://github.com/brankart/sesam), which requires the EnsDAM (https://github.com/brankart/ensdam) and FlowSampler (https://github.com/brankart/flowsampler) libraries. The installation of these software also requires a FORTRAN-90 compiler and the NetCDF library (with f90 support).
The scripts also make use of the NCO NetCDF operators.
The scripts can be used to perform the following operations (see the README file in the script directory for more details):
- prepare configuration (grid, mask, ...);
- prepare prior ensemble (unconstrained by observations);
- prepare altimetric observations;
- sample the posterior ensemble (conditioned to observations, using an MCMC sampler);
- diagnose the posterior ensemble (RMS misfit, probabilistic scores, ...).
The scripts use the following datasets:
- along-track altimetric data (L3 product). This corresponds to the tag SEALEVEL_GLO_PHY_L3_MY_008_062 in the CMEMS catalog (https://marine.copernicus.eu/). These data are used as observations to constrain the prior ensemble.
The scripts assume that these data are provided as archives (.tar) of daily files. For instance, the Jason-3 mission should be in a file 'j3.tar' with files like './j3/dt_global_j3_phy_l3_20201231_20210603.nc'.
- mapped altimetric data (L4 product). This corresponds to the tag SEALEVEL_GLO_PHY_L4_MY_008_047 in the CMEMS catalog (https://marine.copernicus.eu/). These data are used as historical data to produce a climatological prior ensemble (not covering the period of interest).
The scripts assume that these data are provided as daily files like 'dt_global_allsat_phy_l4_20201231_20210726.nc'. Instead of these data, the scripts can also generate the prior ensemble by sampling random fields with a specified spectrum in the basis of the spherical harmonics.
The paremeters are specified in the script 'param.ksh', which is sourced in all other scripts so that they all see the same parameters. The parameters include:
- directory settings;
- grid and mask configuration;
- observation parameters (mission, time window, observation error,...);
- multiscale prior ensemble parameters (size, localization scale,...);
- MCMC sampler parameters (sample size, number of iterations, localization,...);
- diagnostic parameters.
The output is an ensemble of possible solutions (in 2D+time), including the following variables: dynamic topography, geostrophic velocity, relative vorticity, and material derivative of potential vorticity.