DEGRADATION OF OCEAN SIGNALS IN SATELLITE ALTIMETRY DUE TO ORBIT ERROR REMOVAL PROCESSES

Authors
Citation
Ca. Wagner et Ck. Tai, DEGRADATION OF OCEAN SIGNALS IN SATELLITE ALTIMETRY DUE TO ORBIT ERROR REMOVAL PROCESSES, J GEO RES-O, 99(C8), 1994, pp. 16255-16267
Citations number
18
Categorie Soggetti
Oceanografhy
Journal title
JOURNAL OF GEOPHYSICAL RESEARCH-OCEANS
ISSN journal
21699275 → ACNP
Volume
99
Issue
C8
Year of publication
1994
Pages
16255 - 16267
Database
ISI
SICI code
2169-9275(1994)99:C8<16255:DOOSIS>2.0.ZU;2-0
Abstract
The accuracy of recovering sea level changes with a satellite altimete r depends critically on the error in the satellite's ephemeris and how it is removed from the height data. We examine two global ocean data sets of sea level changes:(1) climatologic monthly hydrographic variat ions and (2) a 1-year wind-driven general circulation model (GCM). We then assess their degradation after orbit error removal is applied to the two data sets. The simulations use along track data sampling for a bout a year of the Geosat exact repeat mission (ERM). The simulated or bit error removals are made from differences of overlapping (or collin ear) passes of the simulated sea heights. Radial orbit correction algo rithms include along-track polynomials of up to one half revolution in length and global sinusoids of from one half revolution to about 4 da ys long with a 1 cycle/revolution (cpr) fundamental period. Orbit erro r removal first degrades the ocean signal along track, usually in a mi ld way depending on the pass length and the seasonal differences betwe en the collinear data sets. However, the resulting distortion of yearl y time series at fixed locations is generally more severe, especially when the actual signal is weak and at higher latitudes. Average degrad ation of both climatologic and GCM time series at fixed locations is s ignificant in all cases and more severe with local pass polynomials th an with global sinusoids. Thus we find that in even the least destruct ive along-track error removal process, the global error of the derived climatologic time series (defined as rms simulated-orbit-error/rms si gnal) is greater than 0.30. However, the correlation of time series, d erived versus original, and their power ratios (rms derived/rms signal ) is generally high (greater than 0.78 globally) for all methods, thou gh certain locations result in negative correlation (reversal of phase ). Degradation of the more variable GCM changes (with mesoscale eddies ) is generally not as severe as in climatologic series. Thus the GCM t ime series error distortion with long arc 1-cpr sinusoid orbit error r emoval was found to be only 0.20, while with full pass bias and tilts the error was 0.53. The corresponding global errors found for climate time series were 0.31 and 0.54. Similar results should be expected for any satellite mission using collinear or crossover altimetry spanning appreciable oceanographic change.