Sea surface topography retrieved from GNSS reflectometry phase data of the GEOHALO flight mission

Semmling, A. M.; Beckheinrich, Jamila; Wickert, Jens; Beyerle, G.; Schön, Steffen; Fabra, Fran; Pflug, Hartmut; He, Kaifei; Schwabe, Joachim; Scheinert, Mirko

doi:10.1002/2013gl058725

Cited by 56 publications

(52 citation statements)

References 19 publications

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“…Those measurements, however, differ particularly from conventional altimetric measurements and are insufficiently studied so far. Airborne experiments proved GNSS-R based SSH retrievals also at large incidence angles (Semmling et al 2014). However, dependent on the incidence angle the retrievals are affected by sea surface roughness.…”

Section: Experiments Setupmentioning

confidence: 85%

“…To account for possible limitations of the space-borne GNSS-R measurements ,e.g., due to sea surface roughness (Semmling et al 2014), some of the SHIFTASSIM have been repeated (c.f., Sec. 3) by using only observations with reflection incidence angles φ ≤ 40 • (where φ = 0 • is perpendicular to the sea surface, i.e., zenith incidence).…”

Section: Results and Conclusionmentioning

confidence: 99%

“…Different altimetric retrievals have been described for airborne GNSS-R experiments. In the following we distinguish between code delay observations (Lowe et al 2002;Rius et al 2010;CarrenoLuengo et al 2013) and carrier phase observations (Semmling et al 2014). In general, the code delay has a coarser precision compared to the carrier phase.…”

Section: Precision Of Reflection Eventsmentioning

confidence: 99%

“…The simulation uses an altimetric precisionδ code of 20 cm based on code delay retrieval as given by Cardellach and Rius (2008). This precision is anticipated for the GEROS-ISS mission and a rather conservative assumption compared to precisions reported for recent airborne experiments (Carreno-Luengo et al 2013;Semmling et al 2014). Therefore, a precisionδ phase of 3 cm for carrier phase retrieval, based on observations described in Semmling et al (2014) is used in addition.…”

Section: Precision Of Reflection Eventsmentioning

confidence: 99%

“…GNSS-R estimates SSH by comparing the transittimes between GPS-satellite signals on the direct path and on the ocean reflected path. SSH measurements have already been reported for airborne experiments (Lowe et al 2002;Ruffini et al 2004;Rius et al 2010;Semmling et al 2014). A respective space-borne GNSS-R setup is expected to increase the global temporal and spatial resolution of ocean observations (Martin-Neira 1993;Wickert et al 2009) as GNSS guarantees at least four simultaneous direct links between the GPS-satellites and the receiver.…”

Section: Introductionmentioning

confidence: 99%

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Potential of space-borne GNSS reflectometry to constrain simulations of the ocean circulation

et al. 2015

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The Agulhas current system transports warm and salty water masses from the Indian Ocean into the Southern Ocean and into the Atlantic. The transports impact past, present and future climate on local and global scales. The size and variability, however, of the respective transports are still much debated. In this study, an idealized model based twin experiment is used to study whether sea surface height (SSH) anomalies estimated from reflected signals of the Global Navigation Satellite System (GNSS-R) can be used to determine the internal water mass properties and transports of the Agulhas region. A space-borne GNSS-R detector on the International Space Station (ISS) is assumed and simulated. The detector is able to observe daily SSH fields with a spatial resolution of 1-5 • . Depending on reflection geometry, the precision of a single SSH observation is estimated to reach 3 cm (20 cm) when the carrier phase (code delay) information of the reflected GNSS signal is used. The average precision over the Agulhas region is 7 cm (42 cm). The proposed GNSS-R measurements surpass the radar-based satellite altimetry missions in temporal and spatial resolution but are less precise. Using the estimated GNSS-R characteristics, measurements of SSH are generated by sampling a regional nested general circulation model of the South African oceans. The artificial observations are subsequently assimilated with a 4DVAR adjoint data assimilation method into the same ocean model but with a different initial state and forcing. The assimilated and the original, i.e., the sampled model state are compared to systematically identify improvements and degradations in the model variables that arise due to the assimilation of GNSS-R based SSH observations. We show that SSH and the independent, i.e., not assimilated model variables velocity, temperature and salinity improve by the assimilation of GNSS-R based SSH observations. After the assimilation of 90 days of SSH observations, improvements in the independent variables cover the whole water column. Locally, up to 39 % of the original model state are recovered. Shorter assimilation windows result in enhanced reproduction of the observed and assimilated SSH but are accompanied by an insufficient or wrong recovery of sub-surface water properties. The assimilation of real GNSS-R observations, when available, and consequently the estimation of Agulhas water mass properties and the leakage of heat and salt into the Atlantic will benefit from this model based study.

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Section: Experiments Setupmentioning

confidence: 85%

Section: Results and Conclusionmentioning

confidence: 99%

Section: Precision Of Reflection Eventsmentioning

confidence: 99%

Section: Precision Of Reflection Eventsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Potential of space-borne GNSS reflectometry to constrain simulations of the ocean circulation

et al. 2015

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First spaceborne phase altimetry over sea ice using TechDemoSat‐1 GNSS‐R signals

Cardellach

Fabra

et al. 2017

Geophysical Research Letters

165

127

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A track of sea ice reflected Global Navigation Satellite System (GNSS) signal collected by the TechDemoSat‐1 mission is processed to perform phase altimetry over sea ice. High‐precision carrier phase measurements are extracted from coherent GNSS reflections at a high angle of elevation (>57°). The altimetric results show good consistency with a mean sea surface (MSS) model, and the root‐mean‐square difference is 4.7 cm with an along‐track sampling distance of ∼140 m and a spatial resolution of ∼400 m. The difference observed between the altimetric results and the MSS shows good correlation with the colocated sea ice thickness data from Soil Moisture and Ocean Salinity. This is consistent with the reflecting surface aligned with the bottom of the ice‐water interface, due to the penetration of the GNSS signal into the sea ice. Therefore, these high‐precision altimetric results have potential to be used for determination of sea ice thickness.

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Airborne Gravimetry of GEOHALO Mission: Data Processing and Gravity Field Modeling

Barthelmes

Förste

et al. 2017

JGR Solid Earth

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Airborne gravimetry is a crucial method to improve our knowledge about the Earth gravity field, especially in hard‐to‐access regions. Generally, the accuracy of airborne gravimetry is several milligals, which is suitable for filling the so‐called polar gaps in satellite‐derived global gravity field models. Here some investigations based on airborne gravity measurements from the GEOHALO mission over Italy are presented. To subtract the vertical accelerations from the values measured by the gravimeter, four different versions of kinematic accelerations were derived from Global Navigation Satellite Systems (GNSS) recordings. To remove the high‐frequency noise, a low‐pass filter with a cutoff wavelength of 200 s was applied to both Chekan‐AM measurements and kinematic accelerations from GNSS. To investigate how future airborne gravity campaigns could be designed, a dedicated flight track was repeated two times showing that the equipment worked well also at higher altitude and speed. From the final best results follows an RMS of gravity differences at crossover points of 1.4 mGal, which, according to the law of error propagation, implies the accuracy of a single measurement to be 1.4/2≈1 mGal. To demonstrate how a satellite‐only gravity field model can be improved by airborne measurements, a gravity field model for the GEOHALO region has been computed. To compute also an improved regional geoid model, the point mass modeling (PMM) and the remove‐compute‐restore (RCR) technique, using a recent satellite‐only model and residual terrain modeling (RTM), were applied. Finally, GNSS/leveling points have been used to check the quality of the regional point mass model.

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Sea surface topography retrieved from GNSS reflectometry phase data of the GEOHALO flight mission

Cited by 56 publications

References 19 publications

Potential of space-borne GNSS reflectometry to constrain simulations of the ocean circulation

Potential of space-borne GNSS reflectometry to constrain simulations of the ocean circulation

First spaceborne phase altimetry over sea ice using TechDemoSat‐1 GNSS‐R signals

Airborne Gravimetry of GEOHALO Mission: Data Processing and Gravity Field Modeling

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