Assimilative Model Assessment of Pioneer Array Data

CGSN: Assimilative Model Assessment of Pioneer Array

DataAmong the goals of the Pioneer Array were to improve understanding of shelf-slope exchange processes and to inform ocean modeling efforts. Recent work by Julia

Levin and colleagues (2020; 2021) explored the impact of Pioneer Array observations on high-resolution modeling, with several interesting conclusions.

The Regional Ocean Modeling System (ROMS) was used in conjunction with a data assimilation scheme known as 4-dimensional variation (4D-Var) – a method of minimizing the error between the output of the model and the observations which the model is meant to predict. ROMS was run for three nested grids (Figure 22) and constrained at the outermost boundaries by data from a global ocean analysis with regional adjustments.

Atmospheric forcing was from the NCEP North American

Mesoscale model.

Among the detailed analyses undertaken in this twopart study was quantification of the impact of observations on the reduction of RMS error for estimates of the volume transport across an along-front transect (Figure 22). Temperature and salinity data from moorings and gliders were impactful for the larger grids (G1, G2). As the grid resolution was increased (G3), submesoscale motions were resolved and velocity data from the moorings became more important for reduction of error variance. An analysis of the sensitivity of shelfslope exchange indices (e.g. volume transport) to removal of an observation, compared to the direct impact of the observation, showed that the majority of observed variables (e.g., SST, SSH, T, S, U, V) were “synergistic” – providing value to the assimilation through their connection with other variables as represented in the model dynamics. For the highest resolution estimates (G3 grid), the Pioneer Array observing assets were more impactful than other observations (e.g., remote sensing, NDBC and IOOS buoys) in reducing uncertainty, with velocity data being the major contributor. This is not a complete surprise, since the Pioneer Array was “tuned” to these scales. Still, it is gratifying to see that the impact on model fidelity is quantifiable. The two-part study undertaken by Levin et al. provides a wealth of additional information about the performance Levin J., H.G. Arango, B. Laughlin, E. Hunter, J. Wilkin, and A.M. Moore, 2020. of assimilative models as well as the utility of in-situ Observation impacts on the Mid-Atlantic Bight front and cross-shelf transport in 4D-Var observations for modeling and prediction. As the ocean state estimates: Part I – Multiplatform analysis, Ocean Modeling, 156, 101721, 117, doi 10.1016/j.ocemod.2020.101721. authors state, they have “just begun to scratch the surface” of approaches that can be applied to the Levin J., H.G. Arango, B. Laughlin, E. Hunter, J. Wilkin, and A.M. Moore, 2021. Observation impacts on the Mid-Atlantic Bight front and cross-shelf transport in 4D-Var 46 assessment of model performance as well as the management of observing systems. ocean stateestimates: Part II – The Pioneer Array, Ocean Modeling, 157, 101731, 1-17, doi 10.1016/j.ocemod.2020.101731.