Accession Number : ADA306701
Title : Inhomogeneous and Nonstationary Feature Analysis: Melding of Oceanic Variability and Structure (INFEAMOVS).
Descriptive Note : Final rept. 1 Oct 90-30 Sep 95,
Corporate Author : MIAMI UNIV FL
Personal Author(s) : Mariano, Arthur J.
PDF Url : ADA306701
Report Date : 26 FEB 1996
Pagination or Media Count : 6
Abstract : The primary research goals were (1) the development of new data analysis and assimilation techniques; (2) application of these techniques, production of optimal estimates of oceanic fields and frontal locations for studying oceanic variability; (3) assimilation of satellite and in situ data sets into layered shallow-water models, such as the Miami Isopycnal Coordinate Ocean Model (MICOM) and the Navy's layered ocean model. The following techniques were developed: (1) Contour Analysis (e.g. Mariano and Chin, 1995), (2) Parameter Matrix Algorithm for Objective Analysis (OA) (Mariano and Brown, 1992), (3) Empirical Orthogonal Contours (EOC) (Mariano, 1996; Mariano and Chin, 1996). (4) Motion-compensated space-time interpolation algorithms (Chin and Mariano, 1995) (5) Nearly-optimal wavelet and Markov Random Field approximations to the Kalman filter/smoother (e.g. Chin et al., 1995; Chin and Mariano, 1995). These techniques were applied to the following data sets, that are available via anonymous ftp from playin.rsmas.miami: (1) The analysis of bio-physical variability during the BIOSYNOP/ Anatomy of a Meander experiment. (2) The analysis of oceanic frontal variability, e.g. Gulf Stream and Kuroshio paths, for determining the dominant patterns of spatial and temporal variability. (3) Global satellite-derived Sea Surface Temperature (SST). (4) Ship-drift based sea surface velocity estimates. (5) Hurricane Gilbert ocean response experiment. Some of the major results of our studies are: The parameter matrix algorithm can be used for efficient objective analysis of large satellite data sets and can be used for mapping fields in strong frontal regions. The use of contour positions for analyzing oceanographic data is a powerful approach.
Descriptors : *OCEANOGRAPHIC DATA, DATA BASES, DATA PROCESSING, OCEAN CURRENTS, OCEAN SURFACE, KALMAN FILTERING, TELEMETERING DATA, SURFACE TEMPERATURE, OCEAN MODELS, MARINE METEOROLOGY, GULF STREAM, FRONTS(OCEANOGRAPHY), OCEAN SURVEILLANCE, RECONNAISSANCE SATELLITES, HURRICANES.
Subject Categories : Physical and Dynamic Oceanography
Distribution Statement : APPROVED FOR PUBLIC RELEASE