DART Data Assimilation¶
Ensemble data assimilation for regional MOM6 in CESM using DART: the Data Assimilation Research Testbed from NSF NCAR. Constrain your model with observations to produce improved ocean state estimates.
Get Started →What You Can Do With DART¶
Ensemble Filter¶
Configure DART's Ensemble Filters, adaptive inflation and localization for regional ocean domains.
Observation Preparation¶
Convert SST, SSH, Argo T/S profiles and sea-ice observations into DART's obs_sequence format using the built-in observation converters.
Assimilation Cycling¶
Run forecast–assimilate–update cycles via the DART–CESM interface, fully integrated with the standard CESM job-submission workflow.
Diagnostics¶
Assess assimilation quality with observation-space RMSE/spread diagnostics and state-space increment maps.
The Tutorial Series¶
Three notebooks, designed to be run in order - each one’s output feeds the next. You can skip synthetic observations if you are only interested in real observations.
1. Creating Observations¶
Turn real Argo profiles from CrocoLake into DART obs_seq files with dartobsgen, and trim them to your CrocoDash model domain. You leave with a directory of observations ready to assimilate.
2. Synthetic Observations¶
Sample a model state with DART's perfect_model_obs at the Tutorial 1 locations plus random ones you design. You leave with a synthetic observing network for an OSSE.
3. Cycling DART–CESM¶
Build a multi-instance regional MOM6 ensemble in CESM, assimilate your observations every six hours, and diagnose the results. You leave with a running DA experiment.