PhD, University of Cincinnati, 2019, Arts and Sciences: Geography

Thermokarst lakes are the most conspicuous features in the Arctic coastal regions that cover roughly 15% - 40 % percent of the area. Those lakes play as a critical niche in the local environment system and provide habitats for a great number of species. In the context of global warming, lakes are experiencing dramatic changes in recent decades. The lake water level and the snow cover atop the ice in the winter are two sensitive indicators of the local and global climate change. Monitoring the variations in lake water level and snow accumulation in Arctic regions could provide more insights of the global climate change and facilitate our understanding of their influences on local hydrological and ecological systems. However, there are very rare in situ observations of lake water levels and lake snow accumulations for the Arctic regions due to the remote locations and also the harsh environmental conditions. Satellite radar and laser altimetry measures elevation profiles of Earth's surface at the global scale and offers an alternative to achieve the purpose. Most previous studies have focused on the application of satellite radar and laser altimetry on lakes at low or middle latitudes, with few of them discussing the applicability of these data to high-latitude lakes. In this research, I explored the capability of satellite radar and laser altimetry missions to monitor lake water levels and snow accumulation on frozen lakes in the Arctic coastal regions. The performances of Sentinel-3, the most recent satellite radar altimetry, on the retrieval of lake water levels were assessed particularly for high-latitude ice-covered lakes. The results showed that lake ice can greatly reduce the accuracy of Sentinel-3 observations. I developed a new empirical retracking algorithm that significantly improves the measurements and provide more reliable and consistent water level estimates for the ice-covered lakes. I examined the performances of ICESat/GLAS, the first and until now (open full item for complete abstract)

Committee: Hongxing Liu Ph.D. (Committee Chair); Richard Beck Ph.D. (Committee Member); Kenneth Hinkel Ph.D. (Committee Member); Emily Kang Ph.D. (Committee Member); Tomasz Stepinski Ph.D. (Committee Member) Subjects: Geography

Doctor of Philosophy, The Ohio State University, 2024, Geodetic Science

Present-day sea-level change under an increasingly warmer Earth is a significant and consequential problem adversely impacting humankind in our generation and beyond. In 2020, an estimated 896 million people, or 11% of the global population, reside in the world's coastal regions, which are already at risk of land losses from rapid sea-level rise. By 2050, over a billion people will be exposed to risks from coastal climate hazards (Glavovic et al., 2022). With the advent of satellite altimetry, continuous global sea-level measurements have been available since 1991. However, the measurements remain too short to accurately determine rapid sea-level rise in light of the detecting oceanic signals with periodicities up to decadal or longer. For estimating longer-term, global spatiotemporal sea-level change at regional scales, empirical sea-level reconstruction is known to be such a methodology. By combining shorter-term (30 years) satellite altimetry sea-level and sparsely distributed but long-term (>50 years) tide gauges records, the reconstruction method is aimed at modeling adequate long-period signals globally and at regional scales. However, contemporary reconstruction methods plausibly have considerable temporal mismatches between the satellite altimetry and the tide gauge sea-level records, resulting in errors in separation and quantification of climate episode patterns at multi-decadal or longer time scales, and rapid sea-level rise (trends and potential accelerated sea-level rise) regionally over the global oceans. Our scientific objective is to quantify the respective roles of identified climate episode patterns induced present-day sea-level changes towards understanding the internal oceanic variability forcing mechanisms under an increasingly warmer Earth. First, we processed global tide gauge sea-level records using statistical methods to minimize the impact of time series data gaps. This resulted in 263 out of 287 selected long-term tide gauge reco (open full item for complete abstract)

Committee: C. K. Shum (Advisor); Demián Gómez (Committee Member); Michael Durand (Committee Member); Michael Bevis (Committee Member) Subjects: Climate Change; Earth; Geophysics; Physical Oceanography

Doctor of Philosophy, The Ohio State University, 2022, Geodetic Science

Satellite altimetry has been the de facto technique for estimating barotropic tides over the global oceans, with solutions either assimilated or directly employed to develop of hydrodynamic and empirical barotropic ocean tide models. However, solutions remain poorly estimated over the marginal seas owing to their semi-enclosed geometric configuration featuring abrupt changes in bathymetry and proximity to land masses. These regions are also largely influenced by non-tidal variability changes due to ocean circulation processes with periods ranging from days to several years. High-frequency motions arising from these processes are difficult to observe due to the inherent sub-optimal sampling from satellite altimeters, resulting in spatio-temporal aliasing errors. Conversely, low-frequency motions, though observable from satellite altimeters, can add significant noise to their observations. This dissertation introduces a case study in the Gulf of Mexico (GoM). In this region, the non-tidal variability can attain satellite altimetry sea surface height anomaly (SSHA) root mean square (RMS) values exceeding 30 cm in highly energetic areas. Furthermore, a global barotropic ocean tide model intercomparison suggests that these effects have been neglected even in the best performing models, thus resulting in poorly estimated barotropic tides. Consequently, this dissertation aims to identify and remove quasi-periodic non-tidal signals contaminating altimetry observations to further improve the estimation of barotropic tides over the marginal seas. This study proposes an experimental non-tidal variability correction for altimetry data based on a combination of numerical solutions from an ocean circulation model and a model of oceanic sea-level anomalies. The empirical orthogonal function (EOF) analysis method is employed to identify and correct altimetry observations for quasiperiodic non-tidal variability signals. After correcting the altimetry observati (open full item for complete abstract)

Committee: C.K. Shum (Advisor); Michael Durand (Committee Member); Demián Gómez (Committee Member); Michael Bevis (Committee Member) Subjects: Earth; Environmental Science; Geophysics; Oceanography; Remote Sensing

Doctor of Philosophy, The Ohio State University, 2020, Geodetic Science

Satellite nadir altimetry uses a space-based sensor to repeatedly measure the height, allowing geodesists and other Earth scientists to monitor temporal changes in surface height on a global or regional basis. Satellite altimetry was originally designed for observing and monitoring global ocean surface topography, but innovative methodologies have been developed and demonstrated for sensing non-ocean surfaces. In this study, two non-ocean altimetry applications have been explored and examined: lake ice thickness retrieval in the Laurentian Great Lakes, and land subsidence rate derivation at San Joaquin Valley. For lake ice thickness study, because there is not yet an operational satellite-based observing system in the Great Lakes, we explore the feasibility of lake ice thickness retrieval using satellite radar and laser altimetry. Cryosat-2 Low Resolution Mode and one-year long ICESat-2 Inland Water Surface Height data product are used to estimate lake ice thickness during the winter 2011 through winter 2019 using the ice freeboard method, which has been extensively used for polar sea ice thickness retrieval but has not yet been applied for lake ice thickness change studies. The Cryosat-2 radar altimeter estimated ice thickness is compared with in-situ data, the difference is 0.2 m., indicating excellent agreements. The Cryosat-2 solution is further compared with ice cover and air temperature data, the correlation coefficients are larger than 70% in Lake Superior, Erie and Ontario, implying the validity of the altimeter-derived interannual variability of lake ice changes. We also discover that Cryosat-2 ice thickness and ice cover data have strong linear relationship. The one-year long ICESat-2 dataset is used, for the first time, to quantify the ice thickness in Great Lakes region in the winter 2019. Comparison between Cryosat-2 and ICESat-2 derived ice thickness, the Cryosat-2 observable shows higher estimates due to problem of penetration in snow layer (open full item for complete abstract)

Committee: C. K. Shum (Advisor); Michael Bevis (Committee Member); Philip Chu (Committee Member); Demián Gómez (Committee Member); Michael Durand (Committee Member) Subjects: Geography

Doctor of Philosophy, The Ohio State University, 2019, Earth Sciences

Tide gauges record relative sea level (RSL), i.e. the vertical position of the sea surface relative to the adjacent land mass or relative to the seafloor under the gauge. A tide gauge cannot distinguish between a rise in sea level or subsidence of the land or seawall or pier that supports the gauge. Absolute sea level (ASL) refers to the level or height of the sea surface stated in some standard geodetic reference frame, e.g. ITRF2008. Since satellite altimeters make a geometrical measurement of sea level, this constitutes a determination of ASL. Satellite altimeters suffer from instrumental drift and thus need to be calibrated using tide gauges. This requires us to estimate the rate of RSL change at each tide gauge and convert this into an estimate of the rate of ASL change. This is done using a GPS station located at or near the tide gauge, since it can measure the vertical velocity of the lithosphere – often referred to as vertical land motion, VLM – which allows us to exploit the relationship ASL = RSL + VLM. This goal has motivated geodesists to build dozens of continuous GPS (or CGPS) stations near tide gauges – an agenda sometimes referred to as the CGPS@TG agenda. Unfortunately, a significant fraction of all long-lived tide gauges – especially those in the Pacific - have also recorded non-steady land motion caused by earthquakes. Rather than simply delete such datasets from the agenda, this thesis explores a new analytical method, based on the concept of a geodetic station trajectory model, that allows us to compute RSL and ASL rates even at tide gauges affected by regional earthquakes. We illustrate this method using two tide gauges (PAGO and UPOL) and three GPS stations (ASPA, SAMO and FALE) located in the Samoan islands of the Southwest Pacific. In addition to managing the impact of large regional earthquakes, we also seek new approaches to reducing noise in RSL rate estimates by suppressing the higher frequency sea level changes associated with ocean (open full item for complete abstract)

Committee: Michael Bevis (Committee Chair); C.K. Shum (Committee Member); Loren Babcock (Committee Member); Michael Barton (Committee Member) Subjects: Earth; Geological; Geophysical; Geophysics; Geotechnology; Ocean Engineering; Oceanography

Doctor of Philosophy, The Ohio State University, 2017, Electrical and Computer Engineering

While various techniques including satellite remote sensing have been used to monitor Earth's surface and atmosphere, the increasing recent interest in the use of Global Navigation Satellite Signal Reflectometry (GNSS-R), which uses reflected GNSS signals from the Earth's surface for remote sensing applications, motivates studies of GNSS-R for retrieving geophysical parameters including sea surface height, wind speed and direction, and land surface properties. This method provides exceptional global coverage and shorter revisit times compared to conventional satellite missions. Also, it is stable, accurate, and cost effective. This dissertation examines how GNSS-R datasets can be exploited for retrievals of sea surface height (SSH) (including consideration of the electromagnetic (EM) bias error source,) wind direction, sea ice coverage, and land surface properties. Because the CYGNSS (Cyclone Global Navigation Satellite System) constellation provides extensive coverage in time and space, studies of the temporal behaviors of oceanic winds are also reported. A "Full DDM" (Delay-Doppler Map) retrieval method is introduced for sea surface height retrievals. Various conditions for retrieval simulations are demonstrated, including fixed geometry, varying geometries with a nature run wind field dataset, and TDS-1 (TechDemosat-1) satellite measurements. The utility of additional spatial and temporal averaging to further beat down retrieval errors is also discussed. Also, the electromagnetic (EM) bias, which is one of error sources in ocean altimetry due to the asymmetric properties of sea waves, is studied for GNSS-R. It is shown that the EM bias varies approximately as the cosine of the specular angle, and the contributions of sea waves on the order of the electromagnetic wavelength or larger are also illustrated through the Monte Carlo simulations performed. Furthermore, the dissertation investigates the influence of wind direction on both purely specular bistatic scat (open full item for complete abstract)

Committee: Joel T. Johnson (Advisor); C. K. Shum (Committee Member); Graeme Smith (Committee Member) Subjects: Electrical Engineering; Electromagnetics; Remote Sensing

Doctor of Philosophy (PhD), Ohio University, 2017, Electrical Engineering & Computer Science (Engineering and Technology)

This dissertation investigates the feasibility of completing an aircraft precision approach using two GNSS satellites in combination with a Stable Frequency Reference (SFR) and various altimeters. Two different sensor combinations are implemented for altimetry. The first combination uses both barometric and radar altimeters to provide height estimates, which are integrated with Global Navigation Satellite Systems (GNSS) satellites from different constellations with a SFR for positioning. Before the start of the approach, a full GNSS solution is used to calibrate the SFR and the vertical solution relative to the aircraft touchdown point (ATP). The theoretical clock and position error covariance is derived as a function of measurement error, satellite geometry, SFR stability, barometric height and radar altimeter performance. Detailed error models for each of the navigation sensors are developed for a covariance analysis. This is followed by both simulations and evaluations using flight test data to verify the positioning accuracy and the feasibility of completing an aircraft precision approach with only two satellites from different constellations. With respect to Category I precision approach requirements of 16 m (95%) horizontal and 4 m (95%) vertical, the horizontal radial 2-σ positioning performance is approximately 6 m, while the vertical 2-σ positioning performance is approximately 4 m. The second sensor combination uses GPS reflection measurements from a software defined receiver (SDR) for aircraft passive bistatic altimetry, and a SFR to continue navigation when only two GPS satellites are available. The scenario for this combination is focused on flights over water, which provides strong reflected signals while alternate terrestrial radio navigation signals are generally not available. Theoretical clock and position error covariance are derived as a function of measurement error, satellite geometry, SFR stability, and GPS bistatic altimetry performance. T (open full item for complete abstract)

Committee: Frank van Graas (Advisor); Maarten Uijt de Haag (Advisor); Michael Braasch (Committee Member); Douglas Lawrence (Committee Member) Subjects: Electrical Engineering

Doctor of Philosophy, The Ohio State University, 2015, Geodetic Science and Surveying

Knowledge of mass variations of continental ice sheets including both Greenland ice sheet (GrIS) and Antarctic ice sheet (AIS) is important for quantifying their contribution to present-day sea level rise. Previous estimates for the respective trend of mass variations over both ice sheets using the Gravity Recovery and Climate Experiment (GRACE) data differ widely, primarily contaminated by large uncertainties of glacial isostatic adjustment (GIA) models over Antarctica, inter-annual or longer variations due to the relatively short data span, and also limited by the coarse spatial resolution (~333 km) of GRACE data. Satellite radar altimetry, i.e., the Environmental satellite (Envisat) altimetry, measures ice sheet elevation change with much better spatial resolution (~25 km) especially over polar regions but requires the density of ice/snow associated with measured elevation change to infer mass change. In this study, GRACE-derived mass variations and Envisat-observed elevation changes are investigated primarily at the inter-annual scale, with the focus on estimating nominal density of ice/snow associated with measured inter-annual mass and elevation changes. To process Envisat data, the along-track repeat analysis is modified separately, with surface gradient corrected by the use of digital elevation model (DEM) and collinear method. By comparing the root mean square (RMS), the trends of elevation changes generated from both methods, and the corresponding uncertainties of trends, the modified collinear method is demonstrated to be more effective for surface gradient correction. Moreover, elevation change retrieved by the ice-1 and ice-2 waveform retracking algorithms are compared in three cases over the AIS, with results confirming that for the ice-2 algorithm, empirical corrections from changes in backscatter and waveform shape parameters are needed. The trend of elevation change retrieved by the ice-1 algorithm with only backscatter analysis is consistent with (open full item for complete abstract)

Committee: C.K. Shum (Advisor); Christopher Jekeli (Committee Member); Ian Howat (Committee Member); Kenneth Jezek (Committee Member); Michael Bevis (Committee Member) Subjects: Climate Change; Geographic Information Science; Geophysics

Doctor of Philosophy, The Ohio State University, 2013, Geodetic Science and Surveying

Fresh water resources are critical for daily human consumption. Therefore, a continuous monitoring effort over their quantity and quality is instrumental. One important model for water quantity monitoring is the rainfall-runoff model, which represents the response of a watershed to the variability of precipitation, thus estimating the discharge of a channel (Bedient and Huber, 2002, Beven, 2012). Remote sensing and satellite geodetic observations are capable to provide critical hydrological parameters, which can be used to support hydrologic modeling. For the case of satellite radar altimetry, limited temporal resolutions (e.g., satellite revisit period) prohibit the use of this method for a short (less than weekly) interval monitoring of water level or discharge. On the other hand, the current satellite radar altimeter footprints limit the water level measurement for rivers wider than 1 km (Birkett, 1998, Birkett et al., 2002). Some studies indeed reported successful retrieval of water level for small-size rivers as narrow as 80 m (Kuo and Kao, 2011, Michailovsky et al., 2012); however, the processing of current satellite altimetry signals for small water bodies to retrieve accurate water levels, remains challenging. To address this scientific challenge, this study poses two main objectives: (1) to monitor small (40-200 m width) and medium-sized (200-800 m width) rivers and lakes using satellite altimetry through identification and choice of the over-water radar waveforms corresponding to the appropriately waveform-retracked water level; and (2) to develop a rainfall-runoff hydrological model to represent the response of mesoscale watershed to the variability of precipitation. Both studies address the humid tropics of Southeast Asia, specifically in Indonesia, where similar studies do not yet exist. This study uses the Level 2 radar altimeter measurements generated by European Space Agency's (ESA's) Envisat (Environmental Satellite) mission. The first study proves (open full item for complete abstract)

Committee: C.K. Shum (Advisor); Christopher Jekeli (Committee Member); Michael Durand (Committee Member) Subjects: Civil Engineering; Hydrology; Physical Geography; Remote Sensing; Water Resource Management

Doctor of Philosophy, The Ohio State University, 2012, Geodetic Science and Surveying

In this study, we demonstrate three environmental-related applications employing altimetry and remote sensing satellites, and exemplify the prospective usage underlying the current progressivity in mechanical and data analyzing technologies. Our discussion starts from the improved waveform retracking techniques in need for altimetry measurements over coastal and inland water regions. We developed two novel auxiliary procedures, namely the Subwaveform Filtering (SF) method and the Track Offset Correction (TOC), for waveform retracking algorithms to operationally detect altimetry waveform anomalies and further reduce possible errors in determination of the track offset. After that, we present two demonstrative studies related to the ionospheric and tropospheric compositions, respectively, as their variations are the important error sources for satellite electromagnetic signals. We firstly compare the total electron content (TEC) measured by multiple altimetry and GNSS sensors. We conclude that the ionosphere delay measured by Jason-2 is about 6–10 mm shorter than the GPS models. On the other hand, we use several atmospheric variables to study the climate change over high elevation areas. Five types of satellite data and reanalysis models were used to study climate change indicators. We conclude that the spatial distribution of temperature trend among data products is quite different, which is probably due to the choice of various time spans. Following discussions about the measuring techniques and relative bias between data products, we applied our improved altimetry techniques to three environmental science applications with helps of remote sensing imagery. We first manifest the detectability of hydrological events by satellite altimetry and radiometry. The characterization of one-dimensional (along-track) water boundary using former Backscattering Coefficient (BC) method is assisted by the two-dimensional (horizontal) estimate of water extent using the Moderate Res (open full item for complete abstract)

Committee: C.K. Shum (Advisor); Michael Durand (Committee Member); Christopher Jekeli (Committee Member); Jiyoung Lee (Committee Member); Song Liang (Committee Member) Subjects: Environmental Science

Doctor of Philosophy, The Ohio State University, 2009, Civil Engineering

Present day numerical models of water bodies are being called upon to make increasinglyfrequent predictions with elevated accuracy standards and requirements. Such a hydrodynamic prediction system is applied in Lake Erie and its ability to accurately model the Lake water elevations is examined in great detail during the 1999-2000 period to decide whether it complies with the currently acceptable standards set for water elevation forecasting and datum establishment purposes. The core model of the prediction system is the Princeton Coastal Ocean Model (POM) that is applied in both its 3D and 2D versions to test whether: a) the 3D calculations predict better the near shore surge amplitudes and b) the 2D calculations provide the accuracy level required by datum determination studies. The model is evaluated at the near-shore lake regions using observed data acquired from 14 land stationed water elevation gages and at the off-shore lake regions using observed data acquired from the Topex/Poseidon water level observation system. Because calculations of water elevations from altimetry data are still impeded by the need for a reliable geoid model, water elevations generated by the POM are pre-processed to provide water surface anomalies to be compared against water surface anomalies provided by the altimetric water level observation system. Upon the complete evaluation of the prediction system initial set up, the following questions are also addressed: a) what is the best method for accounting for the hydrological variations in the lake water levels; b) how does the meteorological data frequency of observation, the consistency of all the meteorological data parameters, and the meteorological station density and distribution over the lake affect the system predictive ability; and c) what is the best interpolation method for gridding the observed meteorological data. The results showed an improvement of the overall model's predictive ability and a better performance especially (open full item for complete abstract)

Committee: Keith Bedford W. (Advisor); Carolyn Merry J. (Committee Member); Rongxing Li (Committee Member) Subjects: Civil Engineering; Oceanography

Doctor of Philosophy, The Ohio State University, 2005, Geodetic Science and Surveying

Accurate knowledge about sea level and its change is essential to humanity because a large proportion of the Earth's population lives in coastal regions. This study discusses the existing techniques for sea level measurements, including the use of different types of gauges (e.g., water level gauge or tide gauge, and bottom pressure gauge), as well as GPS and satellite altimetry. The GPS water level measurements from a buoy or a vessel are presented and utilized in this study along with other techniques to collect ellipsoidal, geocentric sea surface height measurements for various studies that help improve our knowledge about sea level and its change. An operational technique of using GPS water level measurement is proposed in this study. The limitation and an upper bound accuracy of the kinematic (epoch-by-epoch) positioning in terms of baseline length are discussed. A set of GPS data in Lake Erie, including buoy data as well as a local GPS network on land, are used to provide the numerical results. Three main applications of using the GPS water level measurements are presented in this study. They are integration of various data sources in the coastal, satellite radar calibration, and GPS hydrology. The objective of these applications is to demonstrate the potential of the GPS technique in collecting water level measurements. The use of GPS measurements is also highlighted in connection with the improvement that they may bring to various techniques such as the use of coastal water level gauge and bottom pressure gauge, and satellite altimetry. This study discusses three applications of using GPS water level measurements. They have shown the capabilities of the GPS technique on buoys or vessels to interact with other techniques for making accurate water level measurements. With the water impacts humanity, such measurements have proven to be valuable for better understanding for the coastal environment.

Committee: Che Kwan Shum (Advisor) Subjects: Geodesy

Doctor of Philosophy, The Ohio State University, 2013, Geodetic Science and Surveying

Global sea-level rise has become one of the major social-economic hazards associated with the consequence of global warming. Geodetic sea-level change measurements, including tide gauge, radar altimetry and GRACE (Gravity Recovery And Climate Experiment), are contaminated by the ongoing glacial isostatic adjustment (GIA) process that is the viscoelastic response of the Earth to the loading of glaciation and deglaciation during a glacial cycle. Traditionally the GIA effect is removed from various geodetic sea-level observations by using a predicted correction from a GIA forward model. In this study, theoretical treatment of how the GIA effect should be specifically addressed for correcting various geodetic sea-level observations is described, and the results of an accuracy assessment study using an ensemble of 15 contemporary GIA models is conducted to estimate the effect of the current GIA model uncertainty on sea-level and ice-sheet mass balance studies. We find that large discrepancies exist in contemporary GIA models and some of the models are not internally consistent with regard to the two theoretically predicted relations. Using the elastic sea-level fingerprint method, recent change in Earth's dynamic oblateness (or J2), 2003–2012, resulting from present-day ice sheet and mountain glacier/ice cap mass losses is studied. Sensitivity test and result shows that the contribution of mass loss from regions such as the glaciers systems in the Canadian Arctic Archipelago and Alaska are not negligible, although the dominant contributor remains the Antarctic and Greenland ice-sheets. Combining different sea-level change observations (satellite altimetry, GRACE and Argo), published contemporary studies have claimed the ocean mass component of sea-level budget “closure”, meaning that the two independent data types (de-steric satellite altimetry sea-level change and GRACE ocean bottom pressure change) agree with each other during 2004–2012. We argue that the se (open full item for complete abstract)

Committee: C.K. Shum (Advisor); Michael Bevis (Committee Member); Christopher Jekeli (Committee Member) Subjects: Climate Change; Earth; Geophysics

Doctor of Philosophy, The Ohio State University, 2012, Geodetic Science and Surveying

Ocean tides, resulting mainly from the gravitational attractions of the Moon and the Sun, represent 80% of the ocean surface topography variability with a practical importance for commerce and science over hundreds of years. Tides have strong influence on modeling of coastal or continental shelf circulations, play a significant role in climate due to its complex interactions between ocean, atmosphere, and sea ice, dissipate their energy in the ocean and solid Earth, and decelerate the Moon's mean motion. Oceanographic studies and applications, including coastal or continental shelf ocean circulations, also require observations to be ‘de-tided' using ocean tidal forward prediction models before geophysical or oceanographic interpretation, particularly over coastal regions. Advances in satellite radar altimetry technology enabled a globally sampled record of sea surface height (SSH) and its changes over the past two decades, particularly after the launch of TOPEX/POSEIDON satellite. This geophysical record enables numerous scientific studies or discoveries, including improved global ocean tide modeling. Several contemporary ocean tide models have been determined either through the assimilation of satellite altimetry and coastal tide gauge data, often referred to as ‘assimilation models' (e.g. FES2004, NAO.99b and TPXO6.2/7.1/7.2), or via the use of altimetry observations in an ‘empirical modeling' approach to solve for tidal constituents based on a-priori tide models, including assimilated models (e.g. DTU10, EOT08a/10a/11a, GOT00.2/4.7). However, ocean tide model accuracy is still much worse, up to an order of magnitude, in the coastal regions or over partially or permanently sea-ice or ice-shelf covered polar ocean, than that of models in the deep ocean. Here purely observation-based (empirical) ocean tide models with 0.25-degree spatial resolution, the OSU12 models, has been determined using improved multi-satellite altimetry data from TOPEX, Jason-1/-2, Envisat (open full item for complete abstract)

Committee: C.K. Shum (Committee Chair); Christopher Jekeli (Committee Member); Burkhard Schaffrin (Committee Member); Philip Chu (Committee Member) Subjects: Oceanography