Retrieval of Ocean Surface Currents and Winds Using Satellite SAR backscatter and Doppler frequency shift
Doctoral thesis, 2020
Ocean surface winds and currents play an important role for weather, climate, marine life, ship navigation, oil spill drift and search and rescue. In-situ observations of the ocean are sparse and costly. Satellites provide a useful complement to these observations. Synthetic aperture radar (SAR) is particularly attractive due to its high spatial resolution and its capability to extract both sea surface winds and currents day and night and almost independent of weather.
The work in this thesis involves processing of along-track interferometric SAR (ATI-SAR) data, analysis of the backscatter and Doppler frequency shift, and development of wind and current retrieval algorithms. Analysis of the Doppler frequency shift showed a systematic bias. A calibration method was proposed and implemented to correct for this bias. Doppler analysis also showed that the wave contribution to the SAR Doppler centroid often dominates over the current contribution. This wave contribution is estimated using existing theoretical and empirical Doppler models. For wind and current retrieval, two methods were developed and implemented.
The first method, called the direct method, consists of retrieval of the wind speed from SAR backscatter using an empirical backscatter model. In order to retrieve the radial current, the retrieved wind speed is used to correct for the wave contribution. The current retrieval was assessed using two different (theoretical and empirical) Doppler models and wind inputs (model and SAR-derived). It was found that the results obtained by combining the Doppler empirical model with the SAR-derived wind speed were more consistent with ocean models.
The second method, called Bayesian method, consists of blending the SAR observables (backscatter and Doppler shift) with an atmospheric and an oceanic model to retrieve the total wind and current vector fields. It was shown that this method yields more accurate estimates, i.e. reduces the models biases against in-situ measurements. Moreover, the method introduces small scale features, e.g. fronts and meandering, which are weakly resolved by the models.
The correlation between the surface wind vectors and the SAR Doppler shift was demonstrated empirically using the Doppler shift estimated from over 300 TanDEM-X interferograms and ECMWF reanalysis wind vectors. Analysis of polarimetric data showed that theoretical models such as Bragg and composite surface models over-estimate the backscatter polarization ratio and Doppler shift polarization difference. A combination of a theoretical Doppler model and an empirical modulation transfer function was proposed. It was found that this model is more consistent with the analyzed data than the pure theoretical models.
The results of this thesis will be useful for integrating SAR retrievals in ocean current products and assimilating SAR observables in the atmospheric, oceanic or coupled models. The results are also relevant for preparation studies of future satellite missions.
The work in this thesis involves processing of along-track interferometric SAR (ATI-SAR) data, analysis of the backscatter and Doppler frequency shift, and development of wind and current retrieval algorithms. Analysis of the Doppler frequency shift showed a systematic bias. A calibration method was proposed and implemented to correct for this bias. Doppler analysis also showed that the wave contribution to the SAR Doppler centroid often dominates over the current contribution. This wave contribution is estimated using existing theoretical and empirical Doppler models. For wind and current retrieval, two methods were developed and implemented.
The first method, called the direct method, consists of retrieval of the wind speed from SAR backscatter using an empirical backscatter model. In order to retrieve the radial current, the retrieved wind speed is used to correct for the wave contribution. The current retrieval was assessed using two different (theoretical and empirical) Doppler models and wind inputs (model and SAR-derived). It was found that the results obtained by combining the Doppler empirical model with the SAR-derived wind speed were more consistent with ocean models.
The second method, called Bayesian method, consists of blending the SAR observables (backscatter and Doppler shift) with an atmospheric and an oceanic model to retrieve the total wind and current vector fields. It was shown that this method yields more accurate estimates, i.e. reduces the models biases against in-situ measurements. Moreover, the method introduces small scale features, e.g. fronts and meandering, which are weakly resolved by the models.
The correlation between the surface wind vectors and the SAR Doppler shift was demonstrated empirically using the Doppler shift estimated from over 300 TanDEM-X interferograms and ECMWF reanalysis wind vectors. Analysis of polarimetric data showed that theoretical models such as Bragg and composite surface models over-estimate the backscatter polarization ratio and Doppler shift polarization difference. A combination of a theoretical Doppler model and an empirical modulation transfer function was proposed. It was found that this model is more consistent with the analyzed data than the pure theoretical models.
The results of this thesis will be useful for integrating SAR retrievals in ocean current products and assimilating SAR observables in the atmospheric, oceanic or coupled models. The results are also relevant for preparation studies of future satellite missions.
Doppler centroid analysis
Bayesian inversion
ocean surface winds
Ocean surface currents
synthetic aperture radar
along-track InSAR
Chalmers - online; Password: 900262
Opponent: Johnny A. Johannessen, Nansen Environmental and Remote Sensing Center (NERSC), Bergen, Norway
Author
Anis Elyouncha
Chalmers, Space, Earth and Environment, Microwave and Optical Remote Sensing
Measurements of Sea Surface Currents in the Baltic Sea Region Using Spaceborne Along-Track InSAR
IEEE Transactions on Geoscience and Remote Sensing,;Vol. 57(2019)p. 8584-8599
Journal article
Empirical Relationship Between the Doppler Centroid Derived From X-Band Spaceborne InSAR Data and Wind Vectors
IEEE Transactions on Geoscience and Remote Sensing,;Vol. 60(2022)
Journal article
Joint retrieval of ocean surface wind and current vectors from satellite SAR data using a Bayesian inversion method
Remote Sensing of Environment,;Vol. 260(2021)
Journal article
Using Sentinel-1 Ocean Data for Mapping Sea Surface Currents Along the Southern Norwegian Coast
International Geoscience and Remote Sensing Symposium (IGARSS),;(2019)p. 8058-8061
Paper in proceeding
Wind direction ambiguity removal using along-track InSAR: A case study
International Geoscience and Remote Sensing Symposium (IGARSS),;Vol. Volume 2018-July(2018)p. 3262-3265
Paper in proceeding
Vind och strömmar vid havsytan spelar en viktig roll, t.ex. för väder, klimat, liv i havet, fartygsnavigation, spridning av olja och plast samt sök- och räddningsinsatser. Haven täcker en stor del av jordens yta dock är det ont om lokala observationer. Dessutom är utrustning för lokala observationer ofta dyr att installera och underhålla. Med satelliter kan man samla in observationer från hela jorden. Radarsystem är särskilt attraktiva eftersom de kan samla in information om vind och strömmar vid havsytan under både dag och natt och oberoende av väder. Satelliter med radar är därför ett bra komplement till lokala observationer.
Satellitradar sänder elektromagnetiska vågor mot havsytan och registrerar signalen som reflekteras tillbaka till radarsystemet. Den mottagna signalen innehåller information om havsytans ojämnhet och rörelse. Genom att analysera den mottagna signalen med avancerad signalbehandling kan vi få fram information om vind och havsströmmar nära ytan. Styrkan på den mottagna signalen är kopplad till ytans ojämnhet, dvs om det inte blåser är ytan jämn och blank och den reflekterade signalen är svag, medan stark vind ger en ojämn yta som ger en stark reflekterad signal. Därför kan vi beräkna vindhastigheten nära havsytan genom att mäta styrkan på den reflekterade radarsignalen. Den reflekterade radarsignalen är också känslig för ytans rörelser. Om havsströmmar gör att ytan rör sig så ändras frekvensen hos den reflekterade radarsignalen, dvs frekvensen ökar om ytan rör sig mot radarsystemet och minskar om ytan rör sig bort från radarsystemet. Detta kallas Dopplereffekten. Genom att mäta förändringar i den reflekterade radarsignalens frekvens kan vi därför beräkna strömmarna vid havsytan.
Den här avhandlingen presenterar metoder för att behandla och analysera styrkan hos den reflekterade radarsignalen och förändringar i frekvensen, p.g.a. Dopplereffekten, samt algoritmer för att omvandla dessa signaler till information om vind och havsströmmar. Resultaten som presenteras i avhandlingen kan användas för att integrera information från radar i produkter som ger vind och havsströmmar samt i havsmodeller och atmosfärsmodeller. Målet är att hjälpa oceanografer att få en bättre förståelse för havens dynamik och förbättra modellernas prognoser.
Satellitradar sänder elektromagnetiska vågor mot havsytan och registrerar signalen som reflekteras tillbaka till radarsystemet. Den mottagna signalen innehåller information om havsytans ojämnhet och rörelse. Genom att analysera den mottagna signalen med avancerad signalbehandling kan vi få fram information om vind och havsströmmar nära ytan. Styrkan på den mottagna signalen är kopplad till ytans ojämnhet, dvs om det inte blåser är ytan jämn och blank och den reflekterade signalen är svag, medan stark vind ger en ojämn yta som ger en stark reflekterad signal. Därför kan vi beräkna vindhastigheten nära havsytan genom att mäta styrkan på den reflekterade radarsignalen. Den reflekterade radarsignalen är också känslig för ytans rörelser. Om havsströmmar gör att ytan rör sig så ändras frekvensen hos den reflekterade radarsignalen, dvs frekvensen ökar om ytan rör sig mot radarsystemet och minskar om ytan rör sig bort från radarsystemet. Detta kallas Dopplereffekten. Genom att mäta förändringar i den reflekterade radarsignalens frekvens kan vi därför beräkna strömmarna vid havsytan.
Den här avhandlingen presenterar metoder för att behandla och analysera styrkan hos den reflekterade radarsignalen och förändringar i frekvensen, p.g.a. Dopplereffekten, samt algoritmer för att omvandla dessa signaler till information om vind och havsströmmar. Resultaten som presenteras i avhandlingen kan användas för att integrera information från radar i produkter som ger vind och havsströmmar samt i havsmodeller och atmosfärsmodeller. Målet är att hjälpa oceanografer att få en bättre förståelse för havens dynamik och förbättra modellernas prognoser.
Ocean surface winds and currents play an important role for weather, climate, marine life, ship navigation, oil spill and plastic spreading, search and rescue, etc. But the ocean is big and local observations in the ocean are sparse and costly. Satellites provide global observations. Radar is particularly attractive due to its all weather and day-and-night capability to extract both sea surface wind and currents. The combination of satellite and radar gives a good complement to local measurements.
Satellite radar transmits electromagnetic waves toward the sea surface and records the signal reflected back to the radar. The received signal carries information about the sea surface roughness and motion. By analysing the received signal using advanced processing techniques, we can extract information about the near surface wind and currents. The amplitude of the reflected signal is related to the sea surface roughness, i.e. if the surface is calm (no wind) the reflected signal is weak and if the surface is roughened by the wind the reflected signal is strong. Thus by measuring the amplitude of the reflected signal from the sea surface, we can calculate the wind speed near the surface. The reflected signal is also sensitive to the surface motion. If the surface is moving due to an ocean current the frequency of the returned signal changes according to the sea surface motion, i.e. it increases if the surface is moving toward the radar and decreases if the surface is moving away from the radar. This is called the Doppler effect. Thus by measuring the change in frequency of the reflected signal we can calculate the ocean surface currents.
The work in this thesis presents methods for the processing and analysis of the backscatter and Doppler frequency shift, and wind and current retrieval algorithms. The results of this thesis are useful for integrating radar retrievals in ocean wind and current products and assimilating radar observables in the atmospheric, oceanic models. The goal is to help oceanographers to better understand the ocean dynamics and improve the models predictions.
Satellite radar transmits electromagnetic waves toward the sea surface and records the signal reflected back to the radar. The received signal carries information about the sea surface roughness and motion. By analysing the received signal using advanced processing techniques, we can extract information about the near surface wind and currents. The amplitude of the reflected signal is related to the sea surface roughness, i.e. if the surface is calm (no wind) the reflected signal is weak and if the surface is roughened by the wind the reflected signal is strong. Thus by measuring the amplitude of the reflected signal from the sea surface, we can calculate the wind speed near the surface. The reflected signal is also sensitive to the surface motion. If the surface is moving due to an ocean current the frequency of the returned signal changes according to the sea surface motion, i.e. it increases if the surface is moving toward the radar and decreases if the surface is moving away from the radar. This is called the Doppler effect. Thus by measuring the change in frequency of the reflected signal we can calculate the ocean surface currents.
The work in this thesis presents methods for the processing and analysis of the backscatter and Doppler frequency shift, and wind and current retrieval algorithms. The results of this thesis are useful for integrating radar retrievals in ocean wind and current products and assimilating radar observables in the atmospheric, oceanic models. The goal is to help oceanographers to better understand the ocean dynamics and improve the models predictions.
Satellite observations of submesoscale ocean surface dynamics
Swedish National Space Board (214/19), 2020-01-01 -- 2023-12-31.
Understanding ocean surface dynamics with satelite data
Swedish National Space Board (167/14), 2015-01-01 -- 2019-03-31.
Subject Categories
Remote Sensing
Geophysics
Oceanography, Hydrology, Water Resources
ISBN
978-91-7905-390-1
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4857
Publisher
Chalmers
Chalmers - online; Password: 900262
Opponent: Johnny A. Johannessen, Nansen Environmental and Remote Sensing Center (NERSC), Bergen, Norway