Thesis (Sc.D.)--Massachusetts Institute of Technology, Dept. of Meteorology, 1980. / Microfiche copy available in Archives and Science. / Bibliography: leaves 152-159. / by Long Sang Chiu. / Sc.D.

Thesis (Ph. D.)--Joint Program in Applied Ocean Physics and Engineering (Massachusetts Institute of Technology, Dept. of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2007. / Includes bibliographical references (p. 124-126). / This thesis introduces an algorithm for inverting for the geoacoustic properties of the seafloor in shallow water. The input data required by the algorithm are estimates of the amplitudes of the normal modes excited by a low-frequency pure-tone sound source, and estimates of the water column sound speed profiles at the source and receiver positions. The algorithm makes use of perturbation results, and computes the small correction to an estimated background profile that is necessary to reproduce the measured mode amplitudes. Range-dependent waveguide properties can be inverted for so long as they vary slowly enough in range that the adiabatic approximation is valid. The thesis also presents an estimator which can be used to obtain the input data for the inversion algorithm from pressure measurements made on a vertical line array (VLA). The estimator is an Extended Kalman Filter (EKF), which treats the mode amplitudes and eigenvalues as state variables. Numerous synthetic and real-data examples of both the inversion algorithm and the EKF estimator are provided. The inversion algorithm is similar to eigenvalue perturbation methods, and the thesis also presents a combination mode amplitude/eigenvalue inversion algorithm, which combines the advantages of the two techniques. / by Travis L. Poole. / Ph.D.

Thesis: S.M., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2013. / Includes bibliographical references (pages 133-141). / Between 2002 and 2011 a single mooring was maintained in the core of the Pacific Water boundary current in the Alaskan Beaufort Sea near 152° W. Using velocity and hydrographic data from six year-long deployments during this time period, we examine the interannual variability of the current. It is found that the volume, heat, and freshwater transport have all decreased drastically over the decade, by more than 80%. The most striking changes have occurred during the summer months. Using a combination of weather station data, atmospheric reanalysis fields, and concurrent shipboard and mooring data from the Chukchi Sea, we investigate the physical drivers responsible for these changes. It is demonstrated that an increase in summertime easterly winds along the Beaufort slope is the primary reason for the drop in transport. The intensification of the local winds has in turn been driven by a strengthening of the summer Beaufort High in conjunction with a deepening of the summer Aleutian Low. Since the fluxes of mass, heat, and freshwater through Bering Strait have increased over the same time period, this raises the question as to the fate of the Pacific water during recent years and its impacts. We present evidence that more heat has been fluxed directly into the interior basin from Barrow Canyon rather than entering the Beaufort shelfbreak jet, and this is responsible for a significant portion of the increased ice melt in the Pacific sector of the Arctic Ocean. / by Eric T. Brugler. / S.M.

Thesis: S.M., Joint Program in Applied Ocean Science and Engineering (Massachusetts Institute of Technology, Department of Mechanical Engineering; and the Woods Hole Oceanographic Institution), 2014. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 79-81). / The ocean is a complex, constantly changing, highly dynamical system. Prediction capabilities are constantly being improved in order to better understand and forecast ocean properties for applications in science, industry, and maritime interests. Our overarching goal is to better predict the ocean environment in regions of complex topography with a continental shelf, shelfbreak, canyons and steep slopes using the MIT Multidisciplinary Simulation, Estimation and Assimilation Systems (MSEAS) primitive-equation ocean model. We did this by focusing on the complex region surrounding Taiwan, and the period of time immediately following the passage of Typhoon Morakot. This area and period were studied extensively as part of the intense observation period during August - September 2009 of the joint U.S. - Taiwan program Quantifying, Predicting, and Exploiting Uncertainty Department Research Initiative (QPE DRI). Typhoon Morakot brought an unprecedented amount of rainfall within a very short time period and in this research, we model and study the effects of this rainfall on Taiwan's coastal oceans as a result of river discharge. We do this through the use of a river discharge model and a bulk river-ocean mixing model. We complete a sensitivity study of the primitive-equation ocean model simulations to the different parameters of these models. By varying the shape, size, and depth of the bulk mixing model footprint, and examining the resulting impacts on ocean salinity forecasts, we are able to determine an optimal combination of salinity relaxation factors for highest accuracy. / by Jennifer Jacobs Landry. / S.M.

Southeastern South America (SESA), a region encompassing Paraguay, Southern Brazil, Uruguay, and northern Argentina, experienced a 23% increase in austral summer precipitation from 1902-2022, one of the largest precipitation trends observed globally. There is little consensus on the drivers of the precipitation trend, but Atlantic multidecadal variability, stratospheric ozone depletion, and greenhouse gas emissions stand out as key contributing factors. The work presented in this dissertation addresses two main questions. First, what are the historical drivers of the SESA precipitation increase? To address this, I investigate simulations from the Coupled Model Intercomparison Project (CMIP) Phases 3, 5, and 6 and find that not only do fully-coupled climate models simulate positive SESA precipitation trends that are much weaker over the historical interval, but some models persistently simulate negative precipitation trends. The same is true of two atmospheric models forced with observed historical sea surface temperatures. While future 21st-century projections yield positive ensemble mean precipitation trends that grow with increasing greenhouse-gas emissions, the mean forced response never exceeds the observed historical trend. Finally, some pre-industrial control runs occasionally simulate centennial-scale trends that fall within the observational range, but most do not. The second question I address is why climate models struggle to simulate the observed SESA precipitation trend. In an attempt to understand the model bias, I investigate one driver of SESA precipitation variability: the South American low-level jet. By developing a jet index from low-level moisture fluxes into SESA, I find that increased moisture flux through the jet accounts for 20-45% of the observed SESA precipitation trend from 1951-2020 in two reanalysis datasets. While results vary among reanalyses, both point to increased humidity as a fundamental driver of increased moisture flux and precipitation. Increased humidity within the jet is consistent with warming sea surface temperatures driven by anthropogenic forcing, although additional natural climate variations also may have played a role. The jet’s velocity also increased, further enhancing precipitation, but without a clear connection to anthropogenic forcing. These findings indicate that the SESA precipitation trend is partly attributable to jet intensification arising from both natural variability and anthropogenic forcing. In my final research chapter, I explore whether CMIP6 models simulate a realistic relationship between SESA precipitation and the jet, as well as whether inaccuracies in the characterization of the jet could explain muted trends in simulated SESA precipitation. I find that the interannual variability in the simulated jet-precipitation relationship aligns well with results from observations from 1951-2014. Interannual precipitation variability across the models is primarily dominated by the jet’s velocity. The models simulate a forced increase in humidity within the jet, consistent with observations and theory, that contributes a positive trend to SESA precipitation. Given that the models generally simulate realistic jet-precipitation relationships, I conclude that model misrepresentation of the jet is not a likely explanation for the discrepancy between simulated and observed SESA precipitation trends. Despite remaining uncertainties, my work sheds new light on our understanding of SESA precipitation variability and trends. Future work is needed to better understand the large-scale drivers of SESA precipitation outside of the jet and why climate models largely underestimate or fail to reproduce the observed precipitation trend. While Atlantic multidecadal variability is often cited as an important contributor to the SESA precipitation trend, I find austral summer forcing from the Atlantic to be ambiguous with regard to SESA precipitation and requires further analysis. Additionally, I highlight the Pacific South American mode as another contributing factor that warrants further exploration.

Radiative Transfer Models (RTM) have many applications in the satellite microwave remote sensing field, such as the retrieval of oceanic and atmospheric environmental parameters, including surface wind vectors and sea surface temperatures, integrated water vapor, cloud liquid, and precipitation. A key component of the ocean RTM is the emissivity model used to determine the brightness temperature (Tb) at the ocean’s surface. A new wideband ocean emissivity RTM developed by the Central Florida Remote Sensing Laboratory (CFRSL) calculates ocean emissivity over a wide range of frequencies, incidence angles, sea surface temperatures (SST), and wind speed. This thesis presents the validation of this CFRSL model using independent WindSat Tb measurements collocated with Global Data Assimilation System (GDAS) Numerical weather model environmental parameters for frequencies between 6.8 to 37 GHz and wind speeds between 0 – 20 m/s over the July 2005 – June 2006 year. In addition, the CFRSL emissivity model is validated using WindSat derived ocean wind speeds and SST that are contained in the Environmental Data Record (EDR) and combined with the GDAS environmental parameters. Finally, the validation includes comparisons to the well-established XCAL ocean emissivity RTM. The focus of this validation and comparison is to assess performance of the emissivity model results with respect to a wide range of frequency and wind speeds but limited to a narrow range of incidence angles between approximately 50° - 55°

In this dissertation, I explore elements of the changing Arctic Ocean through the application of Stable Isotope, Noble Gas Isotopes, and sulfur hexafluoride (SF6) to better understand ice dynamics for freshwater balance, air/sea gas exchange and ocean circulation. For the tracer studies of stable isotope fractionation, our approach is to use sea ice core data to determine the stable oxygen isotope effective fractionation coefficient. The result is an average value close to 2.2 ‰, which is compared to literature values. For the tracer studies of air/sea gas exchange, we use Neon (Ne) and Helium (He) isotope data sets collected in the ‘Switchyard’ region of the Arctic Ocean between 2005 and 2013 and in the Greenland and Norwegian seas between 1994 and 1999. The Switchyard data show a distinct excess in Ne concentrations in the upper waters. We hypothesize that rejection of Ne during sea ice formation accounts for the Ne excess in the Switchyard area of the Arctic Ocean. Based on this hypothesis we estimate sea-ice formation rates by integrating the Ne excess from the surface to the Atlantic Water layer. The resulting amount of excess Ne corresponds to formation of a nearly 4 m thick sea ice layer. We compare the sea ice formation obtained from the Ne excess method with an independent estimate based on oxygen isotope ratio anomalies ?18O, which is nearly 6.07 m. The difference in the sea ice formation estimated by these two methods indicates loss of Ne through leads. We estimate that the gas exchange rate through the sea-ice cover is ca. 11.3 percent per year. The gas exchange rate through sea-ice covered water would be 0.015 meters per day. For the tracer studies of mean residence times, we analyzed tritium (3H), helium isotope (3He and 4He) and sulfur hexafluoride (SF6) samples collected in the ‘Switchyard’ region of the Arctic Ocean between 2008 and 2013. We calculated apparent tracer ages using the 3H/3He ratios and the partial pressure of SF6 and compare their values for the depth interval between the surface and the core of the Atlantic Water layer. The apparent tracer ages range from zero to about 30 years. Generally, the linear correlation between the 3H/3He and SF6 apparent ages was strong, with the coefficient of determination R2 of 0.94. We explore deviations from this linear trend and discuss them in the context of mixing, air-sea gas exchange, and the impact of sea ice formation on the helium and SF6 gas balances in the surface mixed layer.

No description available.

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Earth and Planetary Sciences, 1980. / Microfiche copy available in Archives and Science. / Vita. / Bibliography: leaves 156-158. / by Nancy Amanda Bray. / Ph.D.

The interaction between ocean and atmosphere sits at the heart of the climate system, and the empirical parameterizations of air-sea fluxes required to couple models of the two media together typically rest on the assumption that the upper ocean is homogenized by turbulent mixing. However, there are a number of globally relevant phenomena that modify the density structure of the surface ocean at vertical scales of just a few meters, affecting the coupling between the ocean and atmosphere. Because of their limited vertical scale and intermittent temporal occurrence, the effects of near-surface processes can be challenging to represent accurately in both fundamental physical theory and computational modeling, and must be accounted for when making in-situ and remote sensing measurements of the ocean surface. The four chapters presented herein address diverse near-surface phenomena – sea ice, precipitation, phytoplankton, and diurnal warming – through a consistent philosophy of using comprehensive observational datasets from above and below the air-sea interface to interrogate and improve upon our theoretical understanding of the processes at play. In each case, the comparison between observations and theoretical modeling reveals the strengths and limitations of the current models and motivates new modifications. Specifically, this work provides observation-based improvements to the accuracy of theoretical frameworks for the ocean-ice heat transfercoefficient, ocean skin temperature during precipitation, solar heating in the ocean’s upper meters in the presence of variable phytoplankton concentrations, and diurnal warm layer response to changes in wind forcing. Crucially, the proposed modifications avoid introducing unnecessary or prohibitive increases in complexity, so that, where appropriate, they may be readily implemented into the current generation of global climate models. In Chapter 1, we present oceanographic and atmospheric time series from a heavily instrumented “ice-tethered observatory” located on landfast ice above the river outflow channel in front of Kotzebue, Alaska. This observing station was deployed as part of the Ikaaġvik Sikukun (Iñupiaq for “Ice Bridges”) project, in which hypotheses and subsequent observational programs were co-produced in partnership with an Indigenous Elder advisory council in Kotzebue. The measurements allow us to quantify the heat budget of the ice above the outflow channel, and identify the ocean as the primary source of heat contributing to thinning of the ice, while also revealing a fundamental limitation of the current approach to calculating ocean-ice heat fluxes from bulk properties. In Chapter 2, we present radiometric observations of ocean skin temperature, near-surface (5cm) temperature from a towed thermistor, and bulk atmospheric and oceanic variables, for 69 rain events observed over the course of 4 months in the Indian Ocean as part of the DYNAMO project. We test a state-of-the-art prognostic model developed by Bellenger et al. (2017) to predict ocean skin temperature in the presence of rain, and demonstrate a physically motivated modification to the model that improves its performance with increasing rain rate. We also characterize the vertical skin-bulk temperature gradient induced by rain and find that it levels off at high rain rates, suggestive of a transition in skin-layer physics that has been previously hypothesized in the literature. In Chapter 3, we identify a need for a parameterization that is accurate in the upper meters and contains an explicitly spectral dependence on the concentration of biogenic material, while maintaining the computational simplicity of the parameterizations currently in use. To address this, we assemble simple, observationally-validated physical modeling tools for the key controls on ocean radiant heating, and simplify them into a parameterization that fulfills this need. We then use observations from 64 spectroradiometer depth casts across 6 cruises in diverse water bodies, 13 surface hyperspectral radiometer deployments, and 2 UAV flights to probe the accuracy and uncertainty associated with the new parameterization. We conclude with a novel case study using the parameterization to demonstrate the impact of chlorophyll concentration on the structure of diurnal warm layers. In Chapter 4, we present co-located measurements of vertical temperature and turbulence structures in large DWLs made from a lagrangian float featuring a robotic lead screw T/S profiler and pulse-to-pulse coherent ADCP, yielding particularly revealing observations of the DWL response to variability in wind and solar forcing at sub-hourly timescales. Comparison of these observations with several upper ocean models reveals the importance of the solar heating parameterization developed in Chapter 3, and suggests a modification to the critical bulk Richardson number currently employed in the K-Profile Parameterization. Comparison to a simple scaling for DWL evolution highlights both the scaling’s potential and its limitations, and a new extension to the scaling is developed to remedy its inaccuracy in cases of wind decrease.