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dc.contributor.advisorGraßl, Hartmut (Prof. Dr.)
dc.contributor.authorLi, Xiao-Ming
dc.date.accessioned2020-10-19T12:45:36Z-
dc.date.available2020-10-19T12:45:36Z-
dc.date.issued2010
dc.identifier.urihttps://ediss.sub.uni-hamburg.de/handle/ediss/3626-
dc.description.abstractOver the ocean, the SAR and ASAR instruments onboard ESA’s ERS and ENVISAT satellites are operated in wave mode whenever no other operation is requested. In wave mode, SAR collects data to form small images of 10 km x 5 km size every 200 or 100 km along the satellite’s orbit. Ocean wave parameters can be retrieved from these SAR/ASAR wave mode data over the global ocean with high quality. The wave parameters can be used for validation of numerical wave model forecasts and hindcasts, assimilation of models, observations and forecast of extreme ocean weather, as well as for global wave climate analysis. The main focus of the thesis is ocean wave information retrieval from SAR and ASAR wave mode data. This includes validation of published schemes for retrieving two-dimensional ocean wave spectra and development of the new empirical algorithm CWAVE_ENV for the retrieval of integral wave parameters directly from ASAR wave mode data without using other input as the first guess. Three months of ASAR wave mode data acquired globally from December 2006 to February 2007 are used to validate the algorithms of the nonlinear PARSA (Partition Rescaling and Shift Algorithm) and the quasi-linear WVW (used by ESA for Level 2 ASAR Wave Mode Wave Spectra) by comparing them to collocated in situ buoy measurements and numerical wave model results. The PARSA algorithm needs the SAR look cross spectra and first guess spectra from numerical wave model as input. The algorithm can yield the full two-dimensional ocean wave spectrum and the retrieved integral wave parameters agree with buoy measurements with a bias of only 0.09 m and a scatter index of 21%. The comparison with the forecast wave model of DWD is even better with a bias of -0.01 m and a scatter index of 16%. The quasi-linear ESA algorithm WVW has the advantage of not needing any priori. However, the retrieved wave spectra are limited to the domain of long wavelengths, mainly swell. Therefore the significant wave height (SWH) integrated from the WVW spectra has a higher bias of -0.19 m and a larger scatter index of 36% when compared to in situ buoy measurements. Furthermore, the underestimation of SWH increases with sea state. Around 25% ASAR wave mode cross spectra cannot be converted successfully by using the algorithm, probably because of the low signal to noise ratio. Based on the empirical algorithm CWAVE_ERS developed for reprocessed ERS-2 SAR wave mode data, the CWAVE_ENV algorithm is proposed in this thesis and implemented for the ASAR wave mode data. Using the same three months ASAR wave mode data and the collocated dataset, the empirical algorithm is validated. Validation, particularly compared to independent datasets, i.e., in situ buoy measurements and radar altimeters, proves that reliable and accurate sea state measurements can be achieved. The bias is only 0.06 m and the scatter index 24%, compared to the buoy measurements over deep water. The respective bias is -0.11 m and -0.13 m and the scatter index 13% and 17% when compared to the crossover measurements of the spaceborne radar altimeters on GFO and JASON, respectively. For a full year dataset, from June 2006 to May 2007, ASAR wave mode data were processed using the CWAVE_ENV algorithm leading to a global sea state analysis. Global 10-year returned extreme SWH is estimated to be 23.4 m using a lognormal probability density function (pdf) as the best fit for high sea state. Seasonal and annual maps for SWH, mean wave period, and wave steepness are compiled. In the winter season, the fetch-limit effects of the North Atlantic lead to high wave build up continuously from west to east, causing the gradual growth of swell. Compared to the results of reanalyzed wave model ERA-40 during 1971 - 2000, the annual mean wave height derived from ASAR wave mode data shows a similar pattern of high waves in the North Pacific, North Atlantic and the Southern Hemisphere. However, in the Northwestern Indian, a much stronger monsoon signal is observed in the ASAR results than the model results. With respect to the mean wave period, extreme swell is observed in the open sea south of Australia, which is around 1 s higher than the model results for the mean value. The SAR wave mode data are useful for global wave studies, while in the coastal regions, SAR data with higher resolution as well as larger coverage are required for investigating spatial changes of sea state. Wave refraction and diffraction around the Terceira island (located in the North Atlantic) is analyzed using the new high resolution TerraSAR-X data. Variations of wave height, peak wavelength and wave direction in the coastal wave processes are identified using the two-dimensional SAR image spectra.en
dc.language.isoenen
dc.publisherStaats- und Universitätsbibliothek Hamburg Carl von Ossietzky
dc.relation.isbasedonLi, Xiao-Ming; Lehner, Susanne; He, Ming-Xia (2008): Ocean wave measurements based on satellite synthetic aperture radar (SAR) and numerical wave model (WAM) data - extreme sea state and cross sea analysis. International Journal of Remote Sensing, 29 (21), pp. 6403 - 6416, DOI: 10.1080/01431160802175546
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subjectSeegangsmessungende
dc.subjectSARde
dc.subjectWave Mode-Datende
dc.subjectsea state measurementen
dc.subjectSARen
dc.subjectWave Mode dataen
dc.subject.ddc550 Geowissenschaften
dc.titleOcean Surface Wave Measurement Using SAR Wave Mode Dataen
dc.title.alternativeÜber die Bestimmung der Eigenschaften von Ozean-Oberflächen Wellen mittels SAR Wave-Mode Datende
dc.typedoctoralThesis
dcterms.dateAccepted2010-01-22
dc.rights.ccNo license
dc.rights.rshttp://rightsstatements.org/vocab/InC/1.0/
dc.subject.bcl38.03 Methoden und Techniken der Geowissenschaften
dc.type.casraiDissertation-
dc.type.dinidoctoralThesis-
dc.type.driverdoctoralThesis-
dc.type.statusinfo:eu-repo/semantics/publishedVersion
dc.type.thesisdoctoralThesis
tuhh.opus.id4492
tuhh.opus.datecreation2010-03-09
tuhh.type.opusDissertation-
thesis.grantor.departmentGeowissenschaften
thesis.grantor.placeHamburg
thesis.grantor.universityOrInstitutionUniversität Hamburg
dcterms.DCMITypeText-
tuhh.gvk.ppn631108165
dc.identifier.urnurn:nbn:de:gbv:18-44926
item.languageiso639-1other-
item.creatorOrcidLi, Xiao-Ming-
item.grantfulltextopen-
item.creatorGNDLi, Xiao-Ming-
item.advisorGNDGraßl, Hartmut (Prof. Dr.)-
item.fulltextWith Fulltext-
Enthalten in den Sammlungen:Elektronische Dissertationen und Habilitationen
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