Assessment of numerical simulations of deep circulation and variability in the Gulf of Mexico using recent observations

Author Posting. © American Meteorological Society, 2020. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Journal of Physical Oceanography 50(4), (2020): 1045-1064, doi:10.1175/JPO-D-19-0137.1.Three simulations of the circulation in the Gulf of Mexico (the “Gulf”) using different numerical general circulation models are compared with results of recent large-scale observational campaigns conducted throughout the deep (>1500 m) Gulf. Analyses of these observations have provided new understanding of large-scale mean circulation features and variability throughout the deep Gulf. Important features include cyclonic flow along the continental slope, deep cyclonic circulation in the western Gulf, a counterrotating pair of cells under the Loop Current region, and a cyclonic cell to the south of this pair. These dominant circulation features are represented in each of the ocean model simulations, although with some obvious differences. A striking difference between all the models and the observations is that the simulated deep eddy kinetic energy under the Loop Current region is generally less than one-half of that computed from observations. A multidecadal integration of one of these numerical simulations is used to evaluate the uncertainty of estimates of velocity statistics in the deep Gulf computed from limited-length (4 years) observational or model records. This analysis shows that the main deep circulation features identified from the observational studies appear to be robust and are not substantially impacted by variability on time scales longer than the observational records. Differences in strengths and structures of the circulation features are identified, however, and quantified through standard error analysis of the statistical estimates using the model solutions.This work was supported by the Gulf Research Program of the National Academy of Sciences under Awards 2000006422 and 2000009966. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Gulf Research Program or the National Academy of Sciences. The authors acknowledge the GLORYS project for providing the ocean reanalysis data used in the ROMS simulation. GLORYS is jointly conducted by MERCATOR OCEAN, CORIOLIS, and CNRS/INSU. Installation, recovery, data acquisition, and processing of the CANEK group current-meter moorings were possible because of CICESE-PetróleosMexicanos Grant PEP-CICESE 428229851 and the dedicated work of the crew of the B/O Justo Sierra and scientists of the CANEK group. The authors thank Dr. Aljaz Maslo, CICESE, for assistance with analysis of model data. The Bureau of Ocean Energy Management (BOEM), U.S. Dept. of the Interior, provided funding for the Lagrangian Study of the Deep Circulation in the Gulf of Mexico and the Observations and Dynamics of the Loop Current study. HYCOM simulation data are available from the HYCOM data server (https://www.hycom.org/data/goml0pt04/expt-02pt2), MITgcm data are available from the ECCO data server (http://ecco.ucsd.edu/gom_results2.html), and the ROMS simulation data are available from GRIIDC (NA.x837.000:0001)

Role of Greenland Freshwater Anomaly in the Recent Freshening of the Subpolar North Atlantic

The cumulative Greenland freshwater flux anomaly has exceeded 5,000 km3 since the 1990s. The volume of this surplus freshwater is expected to cause substantial freshening in the North Atlantic. Analysis of hydrographic observations in the subpolar seas reveals freshening signals in the 2010s. The sources of this freshening are yet to be determined. In this study, the relationship between the surplus Greenland freshwater flux and this freshening is tested by analyzing the propagation of the Greenland freshwater anomaly and its impact on salinity in the subpolar North Atlantic based on observational data and numerical experiments with and without the Greenland runoff. A passive tracer is continuously released during the simulations at freshwater sources along the coast of Greenland to track the Greenland freshwater anomaly. Tracer budget analysis shows that 44% of the volume of the Greenland freshwater anomaly is retained in the subpolar North Atlantic by the end of the simulation. This volume is sufficient to cause strong freshening in the subpolar seas if it stays in the upper 50–100 m. However, in the model the anomaly is mixed down to several hundred meters of the water column resulting in smaller magnitudes of freshening compared to the observations. Therefore, the simulations suggest that the accelerated Greenland melting would not be sufficient to cause the observed freshening in the subpolar seas and other sources of freshwater have contributed to the freshening. Impacts on salinity in the subpolar seas of the freshwater transport through Fram Strait and precipitation are discussed.© The Author(s), 2019. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Dukhovskoy, D. S., Yashayaev, I., Proshutinsky, A., Bamber, J. L., Bashmachnikov, I. L., Chassignet, E. P., Lee, C. M., & Tedstone, A. J. Role of Greenland freshwater anomaly in the recent freshening of the subpolar North Atlantic. Journal of Geophysical Research-Oceans, 124(5), (2019): 3333-3360, doi:10.1029/2018JC014686

WORLD OCEAN ATLAS 2023. Volume 3: Dissolved Oxygen, Apparent Oxygen Utilization, Dissolved Oxygen Saturation, and 30-year Climate Normal

The World Ocean Atlas (WOA23) of dissolved oxygen (O2), Apparent Oxygen Utilization (AOU), and O2 percent saturation (OS) is the most comprehensive observation-based and quality-controlled global ocean mean climatologies for the 1965 to 2022 (WOA23F) and 1971-2000 (WOA23N; 30-year “climate normal” time periods. We describe data sources, quality control (QC), statistics, and objective analysis (OA) used to estimate mean annual, seasonal, monthly fields at 102 standard depths levels (0-5500m depth) on a one-degree latitude-longitude grid resolution. WOA23F uses O2 measurements from chemical (Winkler titrations) and sensor-based [CTD as well as PFL (delayed-mode Argo, deep Argo, as well as BGC-Argo)] totaling ~27.4 million measurements (~1 million profiles) from the World Ocean Database 2023 (WOD23). A O2 solubility adjustment rate as a function of depth (0-1500 m) and time (1965-2022) was calculated using yearly in situ temperature anomalies and applied to all O2 measurements to minimize the effect of ocean warming on O2 solubility between sampling years. The global mean difference between Winkler and CTD O2 profiles geographically and temporally matched profile pairs deeper than 1000 m depth is ± 0.24 ìmol.kg-1 . Delayed mode PFL O2 profiles matched to the Winkler/CTD profile pairs show a negative mean depth offset of about -1.694± 5.15 ìmol.kg-1 . For internal consistency with the Winkler/CTD data pairs, a 1.694 ìmol.kg-1 adjustment was added to all of the PFL data irrespective of depth and location. The global mean difference between the statistical and objectively analyzed annual mean values is ~ 0.20 ± 0.28 ìmol.kg-1 for O2, -0.46 ± 0.93 ìmol.kg-1 for AOU, and 0.12 ± 0.21 % for O2 saturation (OS). The global climatological mean ocean O2 and AOU inventories are ~238.31 ± 5.26 and ~210.88 ± 4.65 Pmol, respectively. The hemispheric seasonal OI and AOUI range (0-1500 m depth) is quantified. The WOA23F global ocean mean O2 content (ìmol.kg-1) difference from WOA18 (-0.93 ± 0.93), WOA23N (-0.93 ± 0.68), GLODAP (-0.30 ± 0.42), and RB23 (-0.54 ± 0.30) for the 0-5500 m depth. For the 0-2000 m depth layer, WOA23F is higher by ~2.87 ± 1.10 ìmol.kg-1 than GOBAI. A 30-year (1971-2000) Climate Normal (WOA23N) of O2, AOU, and O2 saturation is presented using Winkler and CTD sensor-based O2 measurements. The WOA23N annual mean O2 and AOU inventories are ~239.12 ± 5.28 and 209.63 ± 4.63 Pmol, respectively. The number of Winkler shipboard measurements have declined significantly after about year 2000 in comparison to the 1965-2000 time period

Development of the CSOMIO coupled ocean-oil-sediment biology model

The fate and dispersal of oil in the ocean is dependent upon ocean dynamics, as well as transformations resulting from the interaction with the microbial community and suspended particles. These interaction processes are parameterized in many models limiting their ability to accurately simulate the fate and dispersal of oil for subsurface oil spill events. This paper presents a coupled ocean-oil-biology-sediment modelling system developed by the Consortium for Simulation of Oil-Microbial Interactions in the Ocean (CSOMIO) project. A key objective of the CSOMIO project was to develop and evaluate a modeling framework for simulating oil in the marine environment, including its interaction with microbial food webs and sediments. The modeling system developed is based on the Coupled Ocean-Atmosphere-Wave-Sediment Transport model (COAWST). Central to CSOMIO’s coupled modeling system is an oil plume model coupled to the hydrodynamic model (Regional Ocean Modeling System, ROMS). The oil plume model is based on a Lagrangian approach that describes the oil plume dynamics including advection and diffusion of individual Lagrangian elements, each representing a cluster of oil droplets. The chemical composition of oil is described in terms of three classes of compounds: saturates, aromatics, and heavy oil (resins and asphaltenes). The oil plume model simulates the rise of oil droplets based on ambient ocean flow and density fields, as well as the density and size of the oil droplets. The oil model also includes surface evaporation and surface wind drift. A novel component of the CSOMIO model is two-way Lagrangian-Eulerian mapping of the oil characteristics. This mapping is necessary for implementing interactions between the ocean-oil module and the Eulerian sediment and biogeochemical modules. The sediment module is a modification of the Community Sediment Transport Modeling System. The module simulates formation of oil-particle aggregates in the water column. The biogeochemical module simulates microbial communities adapted to the local environment and to elevated concentrations of oil components in the water column. The sediment and biogeochemical modules both reduce water column oil components. This paper provides an overview of the CSOMIO coupled modeling system components and demonstrates the capabilities of the modeling system in the test experiments

Remotely Sensed Winds and Wind Stresses for Marine Forecasting and Ocean Modeling

Strengths and weakness of remotely sensed winds are discussed, along with the current capabilities for remotely sensing winds and stress. Future missions are briefly mentioned. The observational needs for a wide range of wind and stress applications are provided. These needs strongly support a short list of desired capabilities of future missions and constellations

Remotely sensed winds and wind stresses for marine forecasting and ocean modeling

Strengths and weakness of remotely sensed winds are discussed, along with the current capabilities for remotely sensing winds and stress. Future missions are briefly mentioned. The observational needs for a wide range of wind and stress applications are provided. These needs strongly support a short list of desired capabilities of future missions and constellations

Sea Ice Modelling

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