MACRO-GOM: Long Term Multi-Resolution Ocean Current Reanalysis Dataset for the Gulf of Mexico

The Gulf of Mexico's unique circulation characteristics pose a particular threat to marine operations and play a significant role in driving the criteria used for design and life extension analyses of offshore infrastructure. Estimates from existing reanalysis datasets used by operators in GOM show less than ideal correlation with in situ measurements and have a limited resolution that disallows for the capture of ocean features of interest. In this paper, we introduce a new high-resolution long-term reanalysis dataset, Multi-resolution Advanced Current Reanalysis for the Ocean – Gulf of Mexico (MACRO-GOM), based on a state-of the-science hydrodynamic model configured specifically for ocean current forecasting and hindcasting services for the offshore industry that assimilates extensive non-conventional observational data. The underlying hydrodynamic model used is the Woods Hole Group – Tendral Ocean Prediction System (WHG-TOPS). MACRO-GOM is being developed at the native resolution of the TOPS-GOM domain, i.e. 1/32° (~3 km) hourly grid for the 1994-2019 time period (25 years). A 3-level downscaling methodology is used wherein observation based estimates are first dynamically interpolated using a 1/4° model before being downscaled to the 1/16° Inter-American Seas (IAS) domain, which in turn is used to generate time-consistent boundary conditions for the 1/32° reanalysis. A multiscale data assimilation technique is used to constrain the model at synoptic and longer time scales. For this paper, a shorter, 5-year reanalysis run was conducted for the 2015-2019 time period for verification against assimilated and unassimilated observations, WHG's proprietary frontal analyses, and other reanalyses. Both the frontal analyses and Notice to Lesses (NTL) rig mounted ADCP data was withheld from assimilation for comparison. Offshore operations in the GOM can benefit from an improved reanalysis dataset capable of assimilating existing non-conventional observational datasets. Existing hindcast and reanalysis model datasets are limited in their ability to comprehensively and reliably quantify the 3D circulation and kinematic properties of the main features partly because of limited assimilation of observational data. MACRO-GOM incorporates all the advantages of available HYCOM-based reanalyses and further enhances the resolution, accuracy, and reliability by the assimilation of over three decades of WHG's proprietary datasets and frontal analyses for continuous model correction and ground-truthing. The final 25-year high resolution dataset will provide highly reliable design and operational criteria for new and existing infrastructure in GOM.