Ocean surface wave measurements using SAR wave mode data

Over 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 c...

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Bibliographic Details
Main Author: Li, Xiao-Ming
Format: Thesis
Language:English
Published: 2010
Subjects:
Online Access:https://elib.dlr.de/65886/
https://elib.dlr.de/65886/1/version_submit_high.pdf
http://www2.sub.uni-hamburg.de/opus/volltexte/2010/4492/
id ftdlr:oai:elib.dlr.de:65886
record_format openpolar
institution Open Polar
collection German Aerospace Center: elib - DLR electronic library
op_collection_id ftdlr
language English
topic Gewässerfernerkundung
spellingShingle Gewässerfernerkundung
Li, Xiao-Ming
Ocean surface wave measurements using SAR wave mode data
topic_facet Gewässerfernerkundung
description Over 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.
format Thesis
author Li, Xiao-Ming
author_facet Li, Xiao-Ming
author_sort Li, Xiao-Ming
title Ocean surface wave measurements using SAR wave mode data
title_short Ocean surface wave measurements using SAR wave mode data
title_full Ocean surface wave measurements using SAR wave mode data
title_fullStr Ocean surface wave measurements using SAR wave mode data
title_full_unstemmed Ocean surface wave measurements using SAR wave mode data
title_sort ocean surface wave measurements using sar wave mode data
publishDate 2010
url https://elib.dlr.de/65886/
https://elib.dlr.de/65886/1/version_submit_high.pdf
http://www2.sub.uni-hamburg.de/opus/volltexte/2010/4492/
long_lat ENVELOPE(134.033,134.033,68.667,68.667)
geographic Pacific
Indian
Asar
geographic_facet Pacific
Indian
Asar
genre North Atlantic
genre_facet North Atlantic
op_relation https://elib.dlr.de/65886/1/version_submit_high.pdf
Li, Xiao-Ming (2010) Ocean surface wave measurements using SAR wave mode data. Dissertation, University of Hamburg.
_version_ 1766133130808262656
spelling ftdlr:oai:elib.dlr.de:65886 2023-05-15T17:34:20+02:00 Ocean surface wave measurements using SAR wave mode data Li, Xiao-Ming 2010-03-09 application/pdf https://elib.dlr.de/65886/ https://elib.dlr.de/65886/1/version_submit_high.pdf http://www2.sub.uni-hamburg.de/opus/volltexte/2010/4492/ en eng https://elib.dlr.de/65886/1/version_submit_high.pdf Li, Xiao-Ming (2010) Ocean surface wave measurements using SAR wave mode data. Dissertation, University of Hamburg. Gewässerfernerkundung Hochschulschrift NonPeerReviewed 2010 ftdlr 2019-08-04T22:55:15Z Over 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. Thesis North Atlantic German Aerospace Center: elib - DLR electronic library Pacific Indian Asar ENVELOPE(134.033,134.033,68.667,68.667)