Completely updated and revised to reflect new filtering techniques and major updating of the instrumentation used to collect and analyze data
Co-authored by scientists from academe and industry, both of whom have more than 30 years of experience in oceanographic research and field work
Significant revision of sections covering spectral, wavelet, and harmonic analysis techniques
Examples address typical data analysis problems yet provide the reader with formulaic 'recipes" for working with their own data
Significant expansion to 350 figures, illustrations, diagrams and photos
Autorentext
Richard E. Thomson is a researcher in coastal and deep-sea physical oceanography within the Ocean Sciences Division. Coastal oceanographic processes on the continental shelf and slope including coastally trapped waves, upwelling and baroclinic instability; hydrothermal venting and the physics of buoyant plumes; linkage between circulation and zooplankton biomass aggregations at hydrothermal venting sites; analysis and modelling of landslide generated tsunamis; paleoclimate using tree ring records and sediment cores from coastal inlets and basins.William (Bill) Emery worked as a professor in Aerospace Engineering Sciences at the University of Colorado from 1987, prior to which he worked in the University of British Columbia where he created a Satellite Oceanography education/research program. He has authored over 220-refereed publications and 4 textbooks in addition to having given 200 conference papers. He is a fellow of: the IEEE (2002), the American Meteorological Society (2010), the American Astronautical Society (2011) and the American Geophysical Union (2012). He was recently elected to the IEEE TAB Hall of Honor (2020). In 2022 he received the GRSS Fawaz Ulaby Distinguised Achievement Award.
Klappentext
Data Analysis Methods in Physical Oceanography, Third Edition is a practical reference to established and modern data analysis techniques in earth and ocean sciences. Its five major sections address data acquisition and recording, data processing and presentation, statistical methods and error handling, analysis of spatial data fields, and time series analysis methods. The revised Third Edition updates the instrumentation used to collect and analyze physical oceanic data and adds new techniques including Kalman Filtering. Additionally, the sections covering spectral, wavelet, and harmonic analysis techniques are completely revised since these techniques have attracted significant attention over the past decade as more accurate and efficient data gathering and analysis methods.
- Completely updated and revised to reflect new filtering techniques and major updating of the instrumentation used to collect and analyze data
- Co-authored by scientists from academe and industry, both of whom have more than 30 years of experience in oceanographic research and field work
- Significant revision of sections covering spectral, wavelet, and harmonic analysis techniques
- Examples address typical data analysis problems yet provide the reader with formulaic "recipes for working with their own data
- Significant expansion to 350 figures, illustrations, diagrams and photos
Leseprobe
1.2. Basic Sampling Requirements
A primary concern in most observational work is the accuracy of the measurement device, a common performance statistic for the instrument. Absolute accuracy requires frequent instrument calibration to detect and correct for any shifts in behavior. The inconvenience of frequent calibration often causes the scientist to substitute instrument precision as the measurement capability of an instrument. Unlike absolute accuracy, precision is a relative term and simply represents the ability of the instrument to repeat the observation without deviation. Absolute accuracy further requires that the observation be consistent in magnitude with some universally accepted reference standard. In most cases, the user must be satisfied with having good precision and repeatability of the measurement rather than having absolute measurement accuracy. Any instrument that fails to maintain its precision, fails to provide data that can be handled in any meaningful statistical fashion. The best instruments are those that provide both high precision and defensible absolute accuracy. It is sometimes advantageous to measure simultaneously the same variable with more than one reliable instrument. However, if the instruments have the same precision but not the same absolute accuracy, we are reminded of the saying that a man with two watches does not know the time . Digital instrument resolution is measured in bits, where a resolution of N bits means that the full range of the sensor is partitioned into 2N equal segments (N = 1, 2 ). For example, eight-bit resolution means that the specified full-scale range of the sensor, say V = 10 V, is divided into 28 = 256 increments, with a bit resolution of V/256 = 0.039 V. Whether the instrument can actually measure to a resolution or accuracy of V/2N units is another matter. The sensor range can always be divided into an increasing number of smaller increments but eventually one reaches a point where the value of each bit is buried in the noise level of the sensor and is no longer significant. 1.2.1. Sampling Interval
Assuming the instrument selected can produce reliable and useful data, the next highest priority sampling requirement is that the measurements be collected often enough in space and time to resolve the phenomena of interest. For example, in the days when oceanographers were only interested in the mean stratification of the world ocean, water property profiles from discrete-level hydrographic (bottle) casts were adequate to resolve the general vertical density structure. On the other hand, these same discrete-level profiles failed to resolve the detailed structure associated with interleaving and mixing processes, including those associated with thermohaline staircases (salt fingering and diffusive convection), that now are resolved by the rapid vertical sampling provided by modern conductivity-temperature-depth (CTD) probes. The need for higher resolution assumes that the oceanographer has some prior knowledge of the process of interest. Often this prior knowledge has been collected with instruments incapable of resolving the true variability and may, therefore, only be suggested by highly aliased (distorted) data collected using earlier techniques. In addition, laboratory and theoretical studies may provide information on the scales that must be resolved by the measurement system. For discrete digital data x(ti) measured at times t
Inhalt
1. Data Acquisition and Recording 2. Data Processing and Presentation 3. Statistical Methods and Error Handling 4. The Spatial Analyses of Data Fields 5. Time-series Analysis Methods 6. Digital Filters
Appendix A: Units in physical oceanography Appendix B: Glossary of statistical terminology Appendix C: Means, variance…