Ensemble ocean simulations 

Ensemble and probabilistic approaches in numerical ocean modeling :

taking into account uncertainties

Ensemble and probabilistic

approaches in numerical

ocean modeling :

taking into account uncertainties

Comparing satellite and in-situ ocean observations with ocean numerical simulations is a routinely-used approach to either validate models,  calibrate new observation systems, or investigate physical processes and mechanisms.  Such comparison requires some knowledge of the different uncertainties attached to these data, including the model data.

Given the chaotic, non-linear nature of the ocean system, numerical ocean models in the turbulent regime are highly sensitive to initial conditions and spontaneously generate a chaotic intrinsic variability. It is shown that this variability can  be significant  even on interannual and longer time-scale,  and on entire ocean basins.

Performing ensemble simulations is a way to take into account this intrinsic uncertainty, inherent to the ocean circulation, by sampling a range of possible realizations  of equal likelihood of the ocean state and of its  evolution in time.

In other words, it means that simulations from ocean numerical models should come with an “error bar” in the same way  as satellite/in-situ observations are usually provided with given errors (instrument, post-processing, etc).  “Error bars” for numerical ocean simulations can be estimated via ensemble experiments.

At Ocean Next, we develop such probabilistic approaches, based on large-ensemble eddy-permitting ocean simulations. Our goal is to better quantify and characterize the model uncertainty related to the intrinsic variability of the ocean, and to provide useful information to compare to, and interpret satellite and in-situ ocean data. It includes  a quantification of the chaotic variability and a better characterization of the locations, depth, temporal and spatial scales that are the most affected by a chaotic behaviour in models, and which are thus  affected by  the largest uncertainty in any comparison with satellite or in-situ observations.

Fig1 : This scheme presents the setup of a large-ensemble simulation of 50 members performed and analyzed by Ocean Next in collaboration with  IGE/MEOM, Grenoble. It has been designed to take into account the model uncertainty coming  from the initial conditions and the fact that the simulated ocean has a turbulent/chaotic behavior. Instead of a deterministic description of the ocean state with time, the ensemble simulation provides a probabilistic description of the ocean state (i.e. a statistical distribution) at each time step. It allows for the detection of local non-gaussian behaviors  for example (see Fig.2). For more information on this ensemble simulation, see [Bessière et al, 2017](Geosci.Model Dev., 10, 1091-1106, doi:10.5194/gmd-10-1091-2017 Development of a probabilistic ocean modelling system based on NEMO 3.5 : application at eddying resolution).
Fig2 : The probabilistic description of the ocean state  allows for the detection of areas where the ocean has a strongly non-gaussian behavior, such as in the Gulf of Mexico (Figure), where a bi-modal distribution is detected in the loop-current, and an asymmetrical distribution is detected further in the Gulf, along the trajectory of the eddies released by the loop-current with an irregular frequency and then advected westward in the Gulf. The figure above shows the sea-level-height  (SSH) distribution of the 50 members of the large-ensemble simulation, and compare with the AVISO satellite observation time-series. The model spread and its variations with time give an indication of the range of values (and probability) in which the satellite observations are expected to fall at each location.