Optical detection systems have the potential to get around some limitations of acoustic detection systems, especially with increased fleet and port security in noisy littoral waters. Identification of environmental effects especially tropical storms on underwater optical detection is a key to the success. A typhoon-influenced area is chosen in the western North Pacific Ocean with high ocean transparency and low seasonal optical variability. Underwater inherent optical properties (IOPs) such as the beam attenuation coefficient for 470 nm light are measured in the selected region from the U.S. Naval Oceanographic Office sea gliders deployed after super typhoon Guchol’s (June 7 to 20, 2012) passage from June 25 to 30, 2012, and with no typhoon activity from January 9 to February 28, 2014. The observed two sets (with and without typhoon) of IOPs are taken as the input into the Navy’s electro-optical detection simulator. The simulation shows low detection after the super typhoon Guchol-2012’s passage and high detection without typhoon passage.
This paper is to answer the question “How can inter- and intra-annual variability in the ocean be leveraged by the submarine Force?” through quantifying inter- and intra-annual variability in (T, S) fields and in turn underwater acoustic characteristics such as transmission loss, signal excess, and range of detection. The Navy’s Generalized Digital Environmental Model (GDEM) is the climatological monthly mean data and represents mean annual variability. An optimal spectral decomposition method is used to produce a synoptic monthly gridded (SMG) (T, S) dataset for the world oceans with 1° ×1° horizontal resolution, 28 vertical levels (surface to 3,000 m depth), monthly time increment from January 1945 to December 2014 now available at the NOAA/NCEI website: http://data.nodc.noaa.gov/cgibin/iso?id=gov.noaa.nodc:0140938. The sound velocity decreases from 1945 to 1975 and increases afterwards due to global climate change. Effect of the inter- and intra-annual (T, S) variability on acoustic propagation in the Yellow Sea is investigated using a well-developed acoustic model (Bellhop) in frequencies from 3.5 kHz to 5 kHz with sound velocity profile (SVP) calculated from GDEM and SMG datasets, various bottom types (silty clay, fine sand, gravelly mud, sandy mud, and cobble or gravel) from the NAVOCEANO‘s High Frequency Environmental Algorithms (HFEVA), source and receiver depths. Acoustic propagation ranges are extended drastically due to the inter-annual variability in comparison with the climatological SVP (from GDEM). Submarines’ vulnerability of detection as its depth varies and avoidance of short acoustic range due to inter-annual variability are also discussed.
Optical communication/detection systems have potential to get around some limitations of current acoustic communications and detection systems especially increased fleet and port security in noisy littoral waters. Identification of environmental effects on underwater optical transmission is the key to the success of using optics for underwater communication and detection. This paper is to answer the question “What are the transfer and correlation functions that relate measurements of hydrographic to optical parameters?” Hydrographic and optical data have been collected from the Naval Oceanographic Office survey ships with the High Intake Defined Excitation (HIDEX) photometer and sea gliders with optical back scattering sensor in various Navy interested areas such as the Arabian Gulf, Gulf of Oman, east Asian marginal seas, and Adriatic Sea. The data include temperature, salinity, bioluminescence, chlorophyll-a fluorescence, transmissivity at two different wavelengths (TRed at 670 nm, TBlue at 490 nm), and back scattering coefficient (bRed at 700 nm, bBlue at 470 nm). Transfer and correlation functions between the hydrographic and optical parameters are obtained. Bioluminescence and fluorescence maxima, transmissivity minimum with their corresponding depths, red and blue laser beam peak attenuation coefficients are identified from the optical profiles. Evident correlations are found between the ocean mixed layer depth and the blue and red laser beam peak attenuation coefficients, bioluminescence and fluorescence maxima in the Adriatic Sea, Arabian Gulf, Gulf of Oman, and Philippine Sea. Based on the observational data, an effective algorithm is recommended for solving the radiative transfer equation (RTE) for predicting underwater laser radiance.
The monthly mean TOPEX/POSEIDON crossover data in the South China Sea are used to investigate the spatial and temporal variability of sea surface height anomaly (SSHA). Multi-time scale variability is found using the empirical orthogonal function (EOF) analysis. The seasonal variability dominates SSHA with two spatial patterns: basin-wide gyre and north-south double gyres. The intraseasonal variability of SSH has high spatial variability at the continental s helf such as west of Hainan Island and Borneo, and east-west double gyre structure in the deep basin. The interannual variability of SSHA has a north-south double gyre pattern. The scale interaction between seasonal interannual processes may be taken at the north-south double gyre pattern.
A global daily altimetry dataset was recently established at the Naval Research Laboratory on the base of Geosat Follow-On, TOPEX/POSEIDON, and ERS-2 data using the Modular Ocean Data Assimilation System (MODAS). After quality control such as tidal and orbit error removal, referencing to a consistent mean, it provides a global sea surface height (SSH) data with high temporal and spatial resolutions. We identify the first baroclinic Rossby waves wtih a phase speed around 3-5 cm/s in the northern South China Sea using 1994-2001 daily SSH data. We also find that there is no evident Rossby wave signal in the southern South China Sea.
A full spectral third-generation ocean wind-wave model, Wavewatch-III has been implemented in the South China Sea (SCS) for investigating the wind wave characteristics. This model was developed at the Ocean Modeling Branch of the National Centers for Environmental Prediction (NCEP). The NASA QuickScat data (0.25° resolution) two times daily were used to simulate the wind waves for the whole year in 2000. The significant wave heights from Wavewatch-III are compared to the TOPEX/POSEIDON (T/P) significant wave height data over the satellite crossover points in SCS. The model errors of significant wave height have Gaussian-type distribution with small mean value of 0.02 m (almost no bias). The model errors are comparable to the T/P altimeter accuracy (0.5 m) om the central SCS and smaller than the T/P altimeter accuracy in the northern and southern SCS, which indicates the capability of Wavewatch-III for SCS wave simulation.