The Data Management System for the Global Temperature and Salinity Profile Programme

Sun, Chang‐Guk

doi:10.5270/oceanobs09.cwp.86

Cited by 63 publications

(59 citation statements)

References 7 publications

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“…Optimal spectral decomposition was required to process the raw dataset into a research-usable gridded format, as described below. (Sun et al 2009). …”

Section: Establishment Of Global Synoptic Ocean Temperature Datasetmentioning

confidence: 99%

Climate Change: Anticipated Effects on High-Energy Laser Weapon Systems in Maritime Environments

Fiorino

Randall

Bartell

et al. 2011

Journal of Applied Meteorology and Climatology

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This study quantifies the potential impacts on ship-defense high-energy-laser (HEL) performance due to atmospheric effects in the marine boundary layer driven by recent observations and analysis of worldwide sea surface temperatures (SSTs). The atmospheric effects are defined using the worldwide probabilistic climatic database available in the High Energy Laser End-to-End Operational Simulation (HELEEOS) model, which includes an SST database for the period 1854-1997. A more recent worldwide sea surface temperature database was provided by the Naval Postgraduate School for the period 1990-2008. Mean differences and trends between the two SST databases are used to deduce possible climate change impacts on simulated maritime HEL engagements. The anticipated effects on HEL propagation performance are assessed at an operating wavelength of 1.0642 mm across the world's oceans and mapped onto a 18 3 18 grid. The scenario evaluated is near surface and nearly horizontal over a range of 5000 m in which anticipated clear-air maritime aerosols occur. Summer and winter scenarios are considered. In addition to realistic vertical profiles of molecular and aerosol absorption and scattering, correlated optical turbulence profiles in probabilistic (percentile) format are used.

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“…Optimal spectral decomposition was required to process the raw dataset into a research-usable gridded format, as described below. (Sun et al 2009). …”

Section: Establishment Of Global Synoptic Ocean Temperature Datasetmentioning

confidence: 99%

Climate Change: Anticipated Effects on High-Energy Laser Weapon Systems in Maritime Environments

Fiorino

Randall

Bartell

et al. 2011

Journal of Applied Meteorology and Climatology

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“…However, accurate salinity, density, or sound speed measurements can also be used as input to the same front tracking algorithms when they are frontal indicators. Ocean Database (WODB) [131], the Global Temperature and Salinity Profile Programme (GTSPP) [132] and pseudo profiles to bolster the shelfbreak front. e synoptic data were melded with the World Ocean Atlas (WOA) [133,134] climatology modified to match the 2006 slope conditions.…”

Section: Latitude Depth Time)mentioning

confidence: 99%

Autonomous and adaptive oceanographic feature tracking on board autonomous underwater vehicles

Petillo

Schmidt

Lermusiaux

et al. 2015

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Abstracte capabilities of autonomous underwater vehicles (AUVs) and their ability to perform tasks both autonomously and adaptively are rapidly improving, and the desire to quickly and efficiently sample the ocean environment as Earth's climate changes and natural disasters occur has increased significantly in the last decade. As such, this thesis proposes to develop a method for single and multiple AUVs to collaborate autonomously underwater while autonomously adapting their motion to changes in their local environments, allowing them to sample and track various features of interest with greater efficiency and synopticity than previously possible with preplanned AUV or ship-based surveys. is concept is demonstrated to work in field testing on multiple occasions: with a single AUV autonomously and adaptively tracking the depth range of a thermocline or acousticline, and with two AUVs coordinating their motion to collect a data set in which internal waves could be detected. is research is then taken to the next level by exploring the problem of adaptively and autonomously tracking spatiotemporally dynamic underwater fronts and plumes using individual and autonomously collaborating AUVs. Stephanie entered the Massachusetts Institute of Technology/Woods Hole Oceanographic Institution Joint Graduate Program following college to study Oceanographic Engineering. Her Doctoral research, which comprises this thesis, has focused on using autonomous underwater vehicles (AUVs) to perform autonomous and environmentally adaptive sampling of the ocean environment, focusing on underwater feature detection and tracking for more efficient and synoptic data collection with AUVs. Stephanie has enjoyed being on and near the ocean, working with oceanographic vehicles and instrumentation, and seeing her complex underwater vehicle missions work out in the water, and she has had the great opportunity of participating in over a dozen research cruises since she first started working with underwater vehicles in college. roughout graduate school, Stephanie has continued her many hobbies and activities, adding hiking, farming, sailing, and woodworking to the list. I would also like to thank all the members of the LAMSS lab past and present: ank you Toby for fixing nearly any software problem we threw at you on cruise and in the office, and for completing our A-team for every cruise we were on together. ank you also for being my partner in crime on cruise, on travel, and in life. I could not have completed this research nearly as efficiently without you there to devise all sorts of work-arounds when I wanted extra features to make my virtual experiments easier to run. ank you to Erin and Sheida for being both great friends and lab mates and for teaching me that it is okay to not be the only woman in an engineering lab! anks Stephanie for always being excited about my research and hosting craft nights. om, thanks for being such a quick learner on cruise and generally a fun person to hang out with. AcknowledgmentsYou will be a good rep...

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“…Data assimilation is required for operational ocean studies and maneuvers (Sun 1999), and has contributed significantly to the success of ocean modeling and prediction. In a numerical ocean model, a single variable or all the model variables c (no matter two-or three-dimensional) can be ordered by grid point and by variable, forming a single vector of length NP with N as the total number of grid points and P as the number of variables.…”

Section: Introductionmentioning

confidence: 99%

“…With it, several new ocean phenomena have been identified from observational data, such as a bimodal structure of chlorophyll-a with winter/spring (February-March) and fall (September-October) blooms in the Black Sea (Chu et al 2005b), fall-winter recurrence of current reversal from westward to eastward on the TexasLouisiana continental shelf from the current meter, a near-surface drifting buoy (Chu et al 2005a), propagation of long Rossby waves at middepths (around 1000 m) in the tropical North Atlantic from the Argo float data (Chu et al 2007), and temporal and spatial variability of global upper-ocean heat content (Chu 2011) from the data of the Global Temperature and Salinity Profile Program (GTSPP; Sun et al 2009). However, the OSD method has not yet been used for ocean data assimilation.…”

Section: Introductionmentioning

confidence: 99%

Optimal Spectral Decomposition (OSD) for Ocean Data Assimilation

Chu

Tokmakian

Fan

et al. 2015

Journal of Atmospheric and Oceanic Technology

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Optimal spectral decomposition (OSD) is applied to ocean data assimilation with variable (temperature, salinity, or velocity) anomalies (relative to background or modeled values) decomposed into generalized Fourier series, such that any anomaly is represented by a linear combination of products of basis functions and corresponding spectral coefficients. It has three steps: 1) determination of the basis functions, 2) optimal mode truncation, and 3) update of the spectral coefficients from innovation (observational increment). The basis functions, depending only on the topography of the ocean basin, are the eigenvectors of the Laplacian operator with the same lateral boundary conditions as the assimilated variable anomalies. The Vapnik-Chervonkis dimension is used to determine the optimal mode truncation. After that, the model field updates due to innovation through solving a set of a linear algebraic equations of the spectral coefficients. The strength and weakness of the OSD method are demonstrated through a twin experiment using the Parallel Ocean Program (POP) model.

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The Data Management System for the Global Temperature and Salinity Profile Programme

Cited by 63 publications

References 7 publications

Climate Change: Anticipated Effects on High-Energy Laser Weapon Systems in Maritime Environments

Climate Change: Anticipated Effects on High-Energy Laser Weapon Systems in Maritime Environments

Autonomous and adaptive oceanographic feature tracking on board autonomous underwater vehicles

Optimal Spectral Decomposition (OSD) for Ocean Data Assimilation

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