ALBERT

Description: Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 1995

Description: Inverse modeling activities in oceanography have recently been intensified, aided by the oncoming observational data stream of WOCE and the advance of computer power. However, interpretations of inverse model results from climatological hydrographic data are far from simple. This thesis examines the behavior of an inverse model in the WOCE CME (Community Modeling Effort) results where the physics and the parameter values are known. The ultimate hypotheses to be tested are whether the inferred circulations from a climatological hydrographic data set (where limited time means and spatial smoothing are usually used) represent the climatological ocean general circulations, and what the inferred "diffusion" coefficients really are. The inverse model is first tested in a non-eddy resolving numerical GCM ocean. Numerical/scale analyses are used to test whether the inverse model properly represents the GCM ocean. Experiments show how biased answers could result from an incorrect model, and how a correct model must produce the right answers. When the inverse model is applied to the time-mean hydrographic data of an eddy-resolving GCM ocean in the fine grid resolution of the GCM, the estimated horizontal circulation is statistically consistent with the EGCM time means in both patterns and values. Although the flow patterns are similar, the uncertainties for the GCM time means and the inverse model estimates are different. The former are very large, such that the GCM time-mean circulation has no significance in the deep ocean. The latter are much smaller, and with them the estimated circulations are well defined. This is consistent with the concept that ocean motions are very energetic, while variations of tracers (temperature, salinity) are low frequency. The inverse model succeeded in extracting the ocean general circulation from the "climatological" hydrographic data. The estimated vertical velocities are also statistically indistinguishable from the GCM time means. However, significant differences between the estimated "diffusion" coefficients and the EGCM eddy diffusion coefficients are found at certain locations. These discrepancies are attributed to the differences in physics of the inverse model and the EGCM ocean. The "diffusion" coefficients from the inversion parameterize not only the eddy fluxes, but also (part of) the temporal variation and biharmonic terms which are not explicitly included in the inverse model. Given the essentially red spectrum of the ocean, it makes sense to look for smooth solutions. Aliasing due to subsampling on a coarse grid and the effects of spatial smoothing are addressed in the last part of this thesis. It is shown that this aliasing could be greatly reduced by spatial smoothing. The estimated horizontal circulation from the spatially smoothed time-mean EGCM hydrographic data with a coarse grid resolution (2.4° longitude by 2.0° latitude) is generally consistent with the spatially smoothed EGCM time means. Significant differences only occur at some grid points at great depths, where the GCM circulations are very weak. The conclusions of this study are different from some previous studies. These discrepancies are explained in the concluding chapter. Finally, it should be pointed out that the issue of properly representing a GCM ocean by an inverse model is not identical to the issue of represent ing the real ocean by the same inverse model, since the GCM ocean is not identical to the real ocean. Numerical calculations show that both the non-eddy resolving and the eddy-resolving GCM oceans used in this work are evolving towards a statistical equilibrium. In the real ocean, the importance of temporal variation terms in the property conservation equations should also be analyzed when a steady mverse model is applied to a limited time-mean (the climatological) data set.

Description: This research was carried out under National Science Foundation grant OCE- 90-04396.

Description: Submitted in partial fulfillment of the requirements for the degree of Master of Science at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution September 1991

Description: Based on the Levitus atlas, we find that the application of the Montgomery streamfunction to the isopycnal surfaces induces an error which can not be ignored in some regions in the ocean. The error arises from the sloping effect of the specific volume anomaly along isopycnal surfaces. By including the major part of this effect, new streamfunctions, namely the pressure anomaly and main pressure streamfunctions, are suggested for the use in potential density coordinates. By using the newly proposed streamfunction and by including the variations of specific volume anomaly along isopycnal surfaces, the inverse model proposed by Hogg (1987) is modified for increasing accuracy and applied to the Brazil Basin to study the circulation, diffusion and water mass balances. The equations in the model, i.e. the dynamic equation, continuity equation, integrated vorticity equation, and conservation equations for heat, salt and oxygen (in which a consumption sink term is allowed), are written in centered finite difference form with lateral steps of 2 degree latitude and longitude and 8 levels in the vertical. This system of equations with constraints of positive diffusivities and oxygen consumption rates is solved by the inverse method. The results indicate that the circulation in the upper oceans is consistent with previous works, but that in the deep ocean is quite different. In the NADW region, we find a coincidence of the flows with the tongues of water properties. The diffusivities and diapycnal velocities seem stronger in the region near the equator than in the south, with reasonable values. Diffusion plays an important role in the water mass balance. Examples show that similar property fields may results from different processes.

Description: Author Posting. © American Meteorological Society, 2021. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 102(8), (2021): S143–S198, https://doi.org/10.1175/BAMS-D-21-0083.1.

Description: This chapter details 2020 global patterns in select observed oceanic physical, chemical, and biological variables relative to long-term climatologies, their differences between 2020 and 2019, and puts 2020 observations in the context of the historical record. In this overview we address a few of the highlights, first in haiku, then paragraph form: La Niña arrives, shifts winds, rain, heat, salt, carbon: Pacific—beyond. Global ocean conditions in 2020 reflected a transition from an El Niño in 2018–19 to a La Niña in late 2020. Pacific trade winds strengthened in 2020 relative to 2019, driving anomalously westward Pacific equatorial surface currents. Sea surface temperatures (SSTs), upper ocean heat content, and sea surface height all fell in the eastern tropical Pacific and rose in the western tropical Pacific. Efflux of carbon dioxide from ocean to atmosphere was larger than average across much of the equatorial Pacific, and both chlorophyll-a and phytoplankton carbon concentrations were elevated across the tropical Pacific. Less rain fell and more water evaporated in the western equatorial Pacific, consonant with increased sea surface salinity (SSS) there. SSS may also have increased as a result of anomalously westward surface currents advecting salty water from the east. El Niño–Southern Oscillation conditions have global ramifications that reverberate throughout the report.

Description: Argo data used in the chapter were collected and made freely available by the International Argo Program and the national programs that contribute to it. (https://argo.ucsd.edu, https://www.ocean-ops. org). The Argo Program is part of the Global Ocean Observing System. Many authors of the chapter are supported by NOAA Research, the NOAA Global Ocean Monitoring and Observing Program, or the NOAA Ocean Acidification Program. • L. Cheng is supported by National Natural Science Foundation of China (42076202) and Strategic Priority Research Program of the Chinese Academy of Sciences (XDB42040402. • R. E. Killick is supported by the Met Office Hadley Centre Climate Programme funded by BEIS and Defra. PMEL contribution numbers 5214, 5215, 5216, 5217, and 5247.