ENVISAT Data Research Articles

Contribution of automatically generated radar altimetry water levels from unsupervised classification to study hydrological connectivity within Amazon floodplains

Study regionThe Curuaí floodplain in the low Amazon river in the Pará state of Brazil and Juruá basin, a major Solimões tributary. Study focusCharacterizing the hydrological dynamics of Amazon floodplains is essential to better understand and preserve these environments providing important resources to local populations. Radar altimetry is an effective remote sensing tool for monitoring water levels of continental hydrosystems, including floodplains. An unsupervised classification approach on radar echoes to determine hydrological regimes has recently been tested and showed a strong potential on the Congo River basin. This method is adapted to Envisat and Saral satellite radar altimetry data on two study areas in the Amazon Basin. The aim is to improve inland water detection along altimeter tracks to automatically generate water level time series (WLTS) over rivers, lakes, and poorly monitored floodplains and wetlands. New hydrological insightsResults show a good agreement with land cover maps obtained with optical imagery over selected Amazonian wetlands (70–80% accuracies with Envisat data and 50–60% with Saral data). Automatically generated WLTS are strongly correlated to the manually generated WLTS (R² ≈ 0.9; RMSE < 1 m). Compared to the manual method, the automatic method is faster, more efficient and replicable. Densifying the WL network in the floodplains bring crucial information on the connectivity dynamic between lakes and rivers.

Nearly Three Centuries of Lava Flow Subsidence at Timanfaya, Lanzarote

AbstractThe 1730–1736 eruption on Lanzarote was one of the most significant volcanic eruptions to occur on the Canary Islands, with lavas covering over 200 km2. Globally, it is volumetrically the third largest known subaerial basaltic fissure eruption in the past 1,100 years. Here we use Sentinel‐1 and ENVISAT interferograms on both ascending and descending orbits to construct a time series of line‐of‐sight surface displacements and calculate linear vertical deformation rates. We resolve a constant subsidence rate of about 6 mm/yr associated with an area of ∼20 km2 within the central and western portion of the Timanfaya lava flows relative to the rest of the island. This is consistent over the 28‐year period (1992–2020) covered by the Sentinel‐1 and ENVISAT data when combined with the previously published European Remote‐Sensing Satellite data. Time series constructed using Sentinel‐1 short interval interferograms have previously been shown to suffer systematic biases and we find that by making longer period interferograms these biases can be mitigated (when compared against an averaged stack of 1‐year interferograms). Cooling‐driven contraction of an intrusion would require improbably large sill thickness to achieve the observed subsidence rates. Our observations are consistent with the cooling of lavas on the order of one hundred meters, twice as thick as previous estimates, which suggests overall lava volume for this eruption may have been underestimated. This is also evidence of the longest duration of lava flow subsidence ever imaged which indicates that these cumulative thick flows can continue to deform significantly even three centuries after emplacement.

Structural lineament mapping of Central-Eastern high atlas, Morocco, using ASAR/Envisat and SAR/sentinel 1B data

The Central-Eastern part of the High Atlas is dominated by carbonate of Mesozoic age which is affected by the Alpine Orogeny. The deformation manifest in area by different geological structures. The analysis of these later lead to their classification in different category for understanding the geodynamic of the area. This study focuses to map structural lineaments in the Central-Eastern High Atlas using two types of Radar data: Synthetic Aperture Radar (SAR)/Sentinel 1B with polarization (VV + VH) and Advanced Synthetic Aperture Radar (ASAR)/Envisat with polarization (VV + HH). This research aims to demonstrate the utility of Radar data for extracting structural lineaments in carbonate deposits. In this work, two techniques of processing data are used: First, the automatic extraction technique, we are employing the Algorithm Line Module of PCI Geomatica program, after the enhancement of images by applying the mean Co-occurrence filter. Second, the manual extraction technique, it was accomplished by applying directional filters with four directions (N00°, N45°, N90° and N135°) in order to highlight linear structures, then trace the detected lineaments. The synthetic maps of structural lineaments are developed by the two techniques. They are validated by using the lithologic maps extracted from Landsat Operational Land Imager (OLI), the previous researches in the study area, shaded relief extracted from ASTER Global Digital Elevation Model (GDEM), and field investigation data. The results present a good correlation between the direction of structural lineaments extracted from the satellite images and the field measurements. Therefore, the directions of lineaments extracted are N-S and E-W, NE-SW and NW-SE, especially the abundance of the direction N-S. This last one is perpendicular with the major faults. The density of structural lineaments in the study area is controlled particularly by the lithological nature and dynamic evolution, where the concentration is high in the Liassic carbonates. The geostatistical and spatial distribution of the structural lineaments led us to conclude that different tectonic factors are responsible for the distribution of lineaments in the surface of the study area. The comparison of two types of radar data shows that Envisat data is more efficient in the manual extraction than Sentinel 1B data. However, Sentinel 1B data is more efficient in the automatic extraction than Envisat data. This work identifies several families of structural lineaments which can be determined the tectonic phases of the Alpine orogeny affected the intracontinental Atlas basin.

Interpretation of the Spatiotemporal Evolution Characteristics of Land Deformation in Beijing during 2003–2020 Using Sentinel, ENVISAT, and Landsat Data

Since the 1930s, due to the rapid development of the city and the increase of population, the demand from Beijing residents for water resources has gradually increased. Land deformation in the Beijing Plain is a serious issue. In order to warn of, and mitigate, disasters, it is urgently necessary to obtain the latest rate, extent, and temporal evolution of land subsidence in Beijing. Firstly, the temporal and spatial distribution characteristics of land deformation in Beijing during 2003–2020 were unveiled using the time-series interferometric synthetic aperture radar (InSAR) technique and two different satellite datasets, sentinel-1a/1b and ENVISAT ASAR. By means of combining calibration of InSAR results with the global positioning system (GPS), we studied the evolutionary process of long-term land subsidence in Beijing. The precision of our InSAR annual subsidence results is less than 10 mm. Land subsidence in Beijing is unevenly distributed, and so five main land subsidence zones were monitored. The time-series results showed that the rate of land subsidence rate continued to increase from 2003 to 2015, but has gradually shown a slowing trend from 2015 to 2020. Further, we used the quadratic polynomial fitting method to interpolate the time-series deformation results from 2010 to 2015, and compared these with GPS. The results demonstrated that although the InSAR observation method is not strictly registered with GPS in time, its deformation trend is consistent. In addition, the calibrated long time-series was consistent with the three deformation stages of land subsidence evolution in Beijing. Finally, we analyzed the deformation information obtained by InSAR technology in combination with land use type data, precipitation and groundwater data. The results demonstrated that the central area is mostly stable, and land deformation in the northeast is obvious and uneven. In addition, land use type and precipitation have little influence on land subsidence. Changes in land subsidence were closely related to changes in groundwater level, and seasonal variations in deformation correlated with precipitation.

The 2011 Cordón Caulle eruption triggered by slip on the Liquiñe-Ofqui fault system

Determining the mechanisms that promote large silicic eruptions is one of the biggest challenges in volcanic hazard assessment. The 2011-2012 Cordón-Caulle eruption in Chile was one of the largest silicic eruptions of the 21st century and was characterized by a rapid change from explosive to effusive behavior. This eruption was preceded by inflation from 2007 to 2009, followed by two years of barely any ground deformation. Despite intensive monitoring by geodetic and seismological data, its trigger remains undetermined. Here, we benefit from SAR imagery over the Puyehue Cordón-Caulle Volcanic Complex acquired by ALOS-1, ENVISAT and SENTINEL-1 data, to analyze the temporal and spatial behavior of ground displacements before, during and after the eruption. First, we find that a similar prolate spheroidal source explains the ground deformation for the pre-eruptive and post-eruptive periods. Then, we use 3D numerical elasto-plastic models to assess the failure conditions resulting from the pre-eruptive magma injection. Our results show that such a magma injection was too small to trigger the eruption. Therefore we explore other eruption triggers. Analytical elastic inversion models show that the ground displacements observed during the explosive phase may have been produced by slip motion along a NNW-striking dextral-strike slip, double-branch fault of the north-trending Liquiñe-Ofqui Fault System (LOFS), or along a single southern branch fault of the LOFS and collapse of the caldera. When investigating the elasto-plastic deformation pattern resulting from dextral slip along this branch-fault system, we obtain a sub-vertical dilatational plastic zone that connects the reservoir wall to the surface in a location that coincides with that of the 2011 eruption. Hence, we propose that this LOFS branch-fault eventually destabilized (perhaps weakened by the 2007-2009 episode of magma injection), and then slipped in a way that opened channels for fluid migration from the magma reservoir up to the surface.

Accuracy Evaluation of Altimeter-Derived Gravity Field Models in Offshore and Coastal Regions of China

Satellite radar altimetry has made unique contributions to global and coastal gravity field recovery. This paper starts with a general introduction followed by the progress of satellite radar altimetry technology. Then, the methods of marine gravity field recovery and dominating gravity models are described briefly. Finally, typical gravity models are compared with shipboard gravity measurements to evaluate their accuracies in offshore and coastal regions of China. The root mean squares of deviations between gravity models and shipboard gravity are all more than 7 mGal in offshore regions and within the range of 9.5–10.2 mGal in coastal regions. Further analysis in coastal regions indicates that the new gravity models with new satellite missions including Jason-2, SARAL/Altika, and Envisat data have relatively higher accuracy, especially SARAL/Altika data, significantly improving the coastal gravity field. Accuracies are low in areas with strong currents, showing that tide correction is very important for altimetry-derived marine gravity recovery as well as shipboard measurements in coastal gravity field determination. Moreover, as an external check, shipboard gravity data need more operations to improve their precision, such as higher instrument accuracy and finer data processing.

Decades of Ground Deformation in the Weihe Graben, Shaanxi Province, China, in Response to Various Land Processes, Observed by Radar Interferometry and Levelling

Ground deformation is usually used as direct evidence for early warning of geological hazards. The Weihe Graben, located in the southern margin of the Ordos Plateau, is surrounded by many active faults. Earthquakes (e.g., the 1556 Huaxian M 8 earthquake), mine accidents and ground fissures are the major hazards that pose great threats to this densely populated region. In order to characterise both tectonic and anthropogenic activities in the Weihe Graben, we use Envisat data from 2003 to 2010 and Sentinel-1 data from 2014 to 2021, combined with levelling data from 1970 to 2014, to investigate the long-term ground deformation. We generate four InSAR rate maps using the small-baseline subset (SBAS) algorithm. The uncertainties of the InSAR rates are 1–2 mm/year by calculating the differences between the InSAR and levelling measurements. From the deformation time series, we found that most of the faults surrounding the Weihe Graben move at a relatively slow rate (&lt;3 mm/year). Elastic dislocation modelling based on the InSAR and levelling data yields a slip rate of 2.3 ± 0.3 mm/year for the Huashan Fault, the seismogenic fault for the 1556 Huaxian earthquake. Anthropogenic deformation is much stronger than the tectonic deformation. We identified localised subsidence of 12 mines with a deformation rate ranging from 5 to 17 mm/year. The cities of Xi’an and Xianyang also show evident subsidence, which is likely to be caused by groundwater extraction. Land subsidence in Xi’an has slowed down from an average rate of 10–20 mm/year between 2003 and 2010 to about 5–10 mm/year between 2017 and 2020, but in Xianyang, subsidence has increased dramatically in the past five years from 1 mm/year to 7 mm/year. This is because new industrial and urban development centres have gradually moved from Xi’an to Xianyang. We identified a region bounded by the Kouzhen-Guanshan and Fufeng-Liquan Faults with strong subsidence, as a result of excessive extraction of groundwater. To quantify the effects of crustal groundwater unloading on faults, we calculated the static Coulomb stress changes on the two faults and found that Coulomb stress changes are localised in the upper 5 km with a magnitude of 0.01–0.02 bar/year. The Coulomb stress changes might be large enough (0.1 bar) to affect local seismicity if such excessive extraction of groundwater continued for 10 years.

Arctic Sea Ice Freeboard Retrieval from Envisat Altimetry Data

Arctic sea ice variations are sensitive to Arctic environmental changes and global changes. Freeboard and thickness are two important parameters in sea ice change research. Satellite altimetry can provide long-time and large-scale sea ice monitoring. We estimated the Arctic sea ice freeboard and its variations for the period from 2002 to 2012 from Envisat satellite altimetry data. To remove geoid undulations, we reprocessed the Envisat data using a newly developed mean sea surface (MSS) model, named DTU18. Residuals in the static geoid were removed by using the moving average technique. We then determined the local sea surface height and sea ice freeboard from the Envisat elevation profiles. We validated our freeboard estimates using two radar freeboard products from the European Space Agency (ESA) Climate Change Initiative (CCI) and the Alfred Wegener Institute (AWI), as well as the Operation IceBridge (OIB) sea ice freeboard product. The overall differences between our estimates and the CCI and AWI data were 0.11 ± 0.14 m and 0.12 ± 0.14 m, respectively. Our estimates show good agreement with the three products for areas of freeboard larger than 0.2 m and smaller than 0.3 m. For areas of freeboard larger than 0.3 m, our estimates correlate better with OIB freeboard than with CCI and AWI. The variations in the Arctic sea ice thickness are discussed. The ice freeboard reached its minimum in 2008 during the research period. Sharp decreases were found in the winters of 2005 and 2007.

Ground deformation at the Cerro Blanco caldera: A case of subsidence at the Central Andes BackArc

Cerro Blanco Volcanic Complex (CBVC) is one of the youngest caldera complexes in the Southern Central Andes. Subsidence registered at CBVC has shown a slowdown in deformation velocity since 1992 (2.6 cm/yr) to 2010 (0.87 cm/yr). We update the deformation state of this caldera system by processing DInSAR data between 2003 and 2020 and GPS as a complementary tool. Results showed a circular deformation pattern of about 12 km diameter related to subsidence centered at CBVC throughout the entire period under analysis. Deformation rate decreased from 1 cm/yr for 2003–2009 period (Envisat data) to 0.7 cm for the 2012–2020 period (COSMO-SkyMed and Sentinel-1 data). Rate values were confirmed with GPS measurements during 2004 and 2013–2015. Analytical inverse modelling was used to infer the main characteristic of the source responsible for the measured displacement. Best-fitting solution corresponded to a spherical source located between 9 and 14 km from the surface with a volume decrease of about −0.013 km3/yr for the entire period. We propose that a combination of magmatic and geothermal dynamic as the origin of the continuous and slow subsidence observed in the CBVC as a consequence of the last eruption that occurred ca. 4 ka ago.

Estimation of multiple inflows and effective channel by assimilation of multi-satellite hydraulic signatures: The ungauged anabranching Negro river

With the upcoming SWOT satellite mission, which should provide spatially dense river surface elevation, width and slope observations globally, comes the opportunity to assimilate such data into hydrodynamic models, from the reach scale to the hydrographic network scale. Based on the HiVDI (Hierarchical Variational Discharge Inversion) modeling strategy (Larnier et al. (2020)), this study tackles the forward and inverse modeling capabilities of distributed channel parameters and multiple inflows (in the 1D Saint–Venant model) from multisatellite observations of river surface. It is shown on synthetic cases that the estimation of both inflows and distributed channel parameters (bathymetry-friction) is achievable with a minimum spatial observability between inflows as long as their hydraulic signature is sampled. Next, a real case is studied: 871km of the Negro river (Amazon basin) including complex multichannel reaches, 21 tributaries and backwater controls from major confluences. An effective modeling approach is proposed using (i) WS elevations from ENVISAT data and dense in situ GPS flow lines (Moreira (2016)), (ii) average river top widths from optical imagery (Pekel et al. (2016)), (iii) upstream and lateral flows from the MGB large-scale hydrological model (Paiva et al. (2013a)). The calibrated effective hydraulic model closely fits satellite altimetry observations and presents real-like spatial variabilities; flood wave propagation and water surface observation frequential features are analyzed with identifiability maps following (Brisset et al. (2018)). Synthetic SWOT observations are generated from the simulated flowlines and allow to infer model parameters (436 effective bathymetry points, 17 friction patches and 22 upstream and lateral hydrographs) given hydraulically coherent prior parameter values. Inferences of channel parameters carried out on this fine hydraulic model applied at a large scale give satisfying results using noisy SWOT-like data at reach scale. Inferences of spatially distributed temporal parameters (lateral inflows) give satisfying results as well, with even relatively small scale hydrograph variations being inferred accurately on this long reach. This study brings insights in: (i) the hydraulic visibility of the signatures of multiple inflow hydrographs at a large scale with SWOT; (ii) the simultaneous identifiability of spatially distributed channel parameters and inflows by assimilation of satellite altimetry data; (iii) the need for prior information; (iv) the need to further tailor and scale network hydrodynamic models and assimilation methods to improve the fusion of multisource information and potential information feedback to hydrological modules in integrated chains.

Modelling groundwater rebound in recently abandoned coalfields using DInSAR

Advances in differential interferometric synthetic aperture radar (DInSAR) processing algorithms, such as the Intermittent Small Baseline Subset (ISBAS), and increased data availability from SAR systems, such as Sentinel-1, provide the opportunity to increase the spatial and temporal density of ground deformation measurements. Such measurements, when combined with modelling, have the potential to make a significant cost-effective contribution to the progressive abandonment strategy of recently closed coalfields. Applications of DInSAR over coalfields have observed heave in coal measures rocks and temporal correlations between the rise of mine water and deformation time-series. The cessation of systematic dewatering can have a variety of detrimental impacts and knowledge of the time-scales (i.e. the rate of rebound) and structure of the mine system are crucial to the remediation strategy. Although mine plans and borehole measurements provide vital information in this regard, mine plans are often incomplete or inaccurate, whereas monitoring boreholes are spatially sparse. Consequently, groundwater can flow in unanticipated directions via goaf, mine shafts and roadways, making it difficult to determine where the impacts of rebound are likely to occur. In this study, ground deformation data obtained using ISBAS DInSAR on ENVISAT (2002–2009) and Sentinel-1 (2015–2019) data are used to develop a simple method to model groundwater rebound in abandoned coalfields. A forward analytical model based upon the principle of effective stress and mine water ponds is first implemented to estimate surface heave in response to changes in groundwater levels measured in monitoring boreholes. The forward model is then calibrated and validated using the ground deformation data. The DInSAR data were subsequently inverted to map the change in groundwater levels in greater detail across the coalfield and forecast surface discharges in order to support mitigation strategies.

Extreme subsidence in a populated city (Mashhad) detected by PSInSAR considering groundwater withdrawal and geotechnical properties

Ground deformation can cause serious environmental issues such as infrastructure damage, ground compaction, and reducing the ground capacity to store water. Mashhad, as one of the largest and most populated cities in the Middle East, has been suffering from extreme subsidence. In the last decade, some researchers have been interested in measuring land subsidence rates in the Mashhad valley by InSAR techniques. However, most of those studies were based on inaccurate measurements introducing uncertainties in the resulting subsidence rates. These researches used a small number of EnviSat data with long perpendicular and inhomogeneous temporal baseline. This paper seeks to determine the subsidence rate in urban areas of Mashhad in recent years, the threat that was neglected by the city managers and decision-makers. For this purpose, the Persistent Scatterer InSAR technique was applied in the study area using two time-series of descending and ascending Sentinel-1A acquisitions between 2014 and 2017. The results demonstrated the maximum line-of-sight deformation rate of 14.6 cm/year and maximum vertical deformation (subsidence) rate about 19.1 cm/year which could have irreversible consequences. The results were assessed and validated using piezometric data, GPS stations, and geotechnical properties. This assessment confirms that the main reason for subsidence in the interested area is groundwater over-extraction. Also, investigation of geotechnical properties shows that thick fine-grained layers in the northwest of the city could strongly affect the results. At the end of this paper, a new simplified method was proposed to estimate specific storage in special cases to predict the subsidence rate.

A New Method of De-Aliasing Large-Scale High-Frequency Barotropic Signals in the Mediterranean Sea

With the development of satellite observation technology, higher resolution and shorter return cycle have also placed higher demands on satellite data processing. The non-tide high-frequency barotropic oscillation in the marginal sea produces large aliasing errors in satellite altimeter observations. In previous studies, the satellite altimeter aliasing correction generally relied on a few bottom pressure data or the model data. Here, we employed the high-frequency tide gauge data to extract the altimeter non-tide aliasing correction in the west Mediterranean Sea. The spatial average method and EOF analysis method were adopted to track the high-frequency oscillation signals from 15 tide gauge records (TGs), and then were used to correct the aliasing errors in the Jason-1 and Envisat observations. The results showed that the EOF analysis method is better than the spatial average method in the altimeter data correction. After EOF correction, 90% of correlation (COR) between TG and sea level of Jason-1 has increased ~5%, and ~3% increase for the Envisat sea level; for the spatial average correction method, only ~70% of Jason-1 and Envisat data at the TGs location has about 2% increase in correlation. The EOF correction reduced the average percentage of error variance (PEL) by ~30%, while the spatial average correction increased the average percentage of PEL by ~20%. After correction by the EOF method, the altimeter observations are more consistent with the distribution of strong currents and eddies in the west Mediterranean Sea. The results prove that the proposed EOF method is more effective and accurate for the non-tide aliasing correction.

A Kalman Filter Time Series Analysis Method for InSAR

AbstractEarth orbiting satellites, such as Sentinel 1A‐B, build up an ever‐growing set of synthetic aperture radar images of the ground. This conceptually allows for real‐time monitoring of ground displacements using Interferometric Synthetic Aperture Radar (InSAR), notably in tectonically active regions such as fault zones or over volcanoes. We propose a Kalman filter for InSAR time series analysis (KFTS), an efficient method to rapidly update preexisting time series of displacement with data as they are made available, with limited computational cost. KFTS solves together for the evolution of phase change with time and for a parametrized model of ground deformation. Synthetic tests of the KFTS reveal exact agreement with the equivalent weighted least squares solution and a convergence of descriptive model parameter after the assimilation of about 1 year of data. We include the impact of sudden deformation events such as earthquakes or slow slip events on the time series of displacement. First tests of the KFTS on ENVISAT data over Mt. Etna (Sicily) and Sentinel 1 data around the Chaman fault (Afghanistan, Pakistan) show precise (±0.05 mm) retrieval of phase change when data are sufficient. Otherwise, the optimized parametrized model is used to forecast phase change. Good agreement is found with classic time series analysis solution and GPS‐derived time series. Accurate estimates are conditioned to the proper parametrization of errors so that models and observations can be combined with their respective uncertainties. This new tool is freely available to process ongoing InSAR time series.

Land subsidence from interferometric SAR and groundwater patterns in the Qazvin plain, Iran

ABSTRACTQazvin plain as one of the important plains in northwest Iran in terms of industrial and agricultural activities, reveals evidence of land subsidence in the last decade. We used a descending ENVISAT dataset during 2003–2006 and two ascending and descending Sentinel-1 tracks acquired during 2014–2016 to study the subsidence in the area. Our time-series analysis of the ENVISAT data reveals that the area is subsiding at an average rate of 40 mm yr−1 with a maximum value of 50 mm yr−1 in the line of sight direction. Moreover, our result for the Sentinel-1 ascending and descending tracks shows that the average subsidence rate reaches 65 mm yr−1 in the line of sight direction. Comparing the obtained mean velocity maps of the two datasets indicates the growing subsidence pattern in the northwest-southeast direction inside the plain. The investigation of the water source reveals that the overexploitation of aquifers caused an approximately 17 m decline in the groundwater level from 2001 to 2011. This drastic drop in the groundwater level has resulted in progressive subsidence over time. The comparison between the extent of subsidence from the image processing and the water level depletion contour map in the Qazvin plain depicts that subsidence is occurring in areas with a high decrease in underground water level. This study suggests that, besides decreasing the number of deep wells as well as their outflow water, the types of agricultural production related to water consumption and irrigation methods in an area such as Iran can play an important role in decreasing the stress on aquifers.

Calibration and verification of century based wave climate data record along the Turkish coasts using satellite altimeter data

In order to produce consistent reanalysis of the climate system, ECMWF (The European Centre for Medium-Range Weather Forecasts) has produced firstly an uncoupled atmospheric reanalysis ERA-20C, and then a coupled climate reanalysis, called CERA-20C, which covers the period January 1900 to December 2010. Both data sets are available at 3-hour time increments. Such a century long data can be an alternative to calculate the extreme waves corresponding to low probability of occurrences without extrapolation of extreme value statistics’ results which may contribute to the error in the estimation of design waves in case of small number of wave data. In this study, main purpose is to calibrate and verify the century-based wave data in order to derive the longest and the consistent wave data along the Turkish coasts as a first time to be used in the extreme wave analysis. For this purpose, first of all, significant wave height data of ERA-20C and CERA-20C are compared by using ENVISAT data over the whole Black Sea for 2007–2008 as a pilot study. Comparison results show that both datasets give similar results but CERA-20C seems to be better in terms of statistical error measures. Then CERA-20C significant wave height data are calibrated using satellite Radar Altimeter data set. Jason family of satellites (TOPEX, Jason-1 and 2) and Envisat family of satellites (ERS-2 and Envisat) are inter-calibrated to get the consistent satellite data sets with a total duration of 18 years (1995–2012) for Envisat family and 26 years (1992–2017) for Jason family in order to be used in calibration of CERA-20C wave height. The mean wave period is also estimated from RA backscatter coefficients (Ku and C bands) and the significant wave height by using Artificial Neural Network Method. Then the estimated mean wave periods are used for the calibration of CERA-20C wave period. Calibrated CERA-20C data are compared with in-situ measurements for the verification purposes. Results of verification study show that the calibrated CERA-20C wave data agree well with the in-situ measurements in terms of Quantile-Quantile analysis with lower deviations from y = x line and capture the largest sea states. In fact, CERA-20C, century-based wave data become appropriate to determine the extreme waves to be used in the design of coastal structures along the Turkish coasts.

Precision and Bias Comparison Between Laser and Radar Altimetry Data in the Amundsen Sea Embayment and the Lambert-Amery System of Antarctica

This article focuses on the precision and bias of laser altimetry data [Ice, Cloud, and Land Elevation Satellite (ICESat)] and radar altimetry data (Envisat) L2 products during the contemporary period from 2003 to 2008 in the Amundsen Sea Embayment (ASE) in West Antarctica (an ice loss region) and the Lambert-Amery System (LAS) in East Antarctica (an ice gain region). We used the crossover method to obtain the elevation differences between ICESat tracks, Envisat tracks, and between ICESat and Envisat tracks. The crossover points were generated and the difference of each crossover pair was calculated as raw data. The standard deviations were then computed from the raw data in a grid cell for both ICESat and Envisat. The precision of both satellites varied as a function of the surface slope in the abovementioned two regions, from 6.6 to 16.6 cm for the ICESat data and from 0.11 to 0.35 m for the Envisat data. The crossover points from ICESat-Envisat showed a mean bias of 0.55 ± 4.00 m for the ASE and 0.45 ± 0.99 m for the LAS, in accordance with the penetration depth of the radar altimetry. The relationship between the precision of the satellite measurements with the slope of the ice sheet and the ice velocity in the study area showed that the regions with gentle slopes and low velocity obtained a better precision of altimetry data.

Assessing the Impact of Lead and Floe Sampling on Arctic Sea Ice Thickness Estimates from Envisat and CryoSat‐2

AbstractMultidecadal observations of sea ice thickness, in addition to those available for extent, are key to understanding long‐term variations and trends in the amount of Arctic sea ice. The European Space Agency's Envisat (2002–2010) and CryoSat‐2 (2010–present) satellite radar altimeter missions provide a continuous 17‐year dataset with the potential to estimate sea ice thickness. However, the satellite footprints are not equal in area and so different distributions of floes and leads are sampled by each mission. Here, we compare lead and floe sampling from Envisat and CryoSat‐2 to investigate the impact of geometric sampling differences on Arctic sea ice thickness estimates. We find that Envisat preferentially samples wider, thicker sea ice floes, and that floes in less consolidated ice regions are effectively thickened by off‐nadir ranging to leads. Consequently, Envisat sea ice thicknesses that are an average of 80 cm higher than CryoSat‐2 over first‐year ice and 23 cm higher over multiyear ice. By considering the along‐track distances between lead and floe measurements, we are able to develop a sea ice thickness correction that is based on Envisat's inability to resolve discrete surfaces relative to CryoSat‐2. This is a novel, physically based approach to addressing the bias between the satellites and reduces the average thickness difference to negligible values over first‐year and multiyear ice. Finally, we evaluate our new bias‐corrected Envisat sea ice thickness product using independent airborne, moored‐buoy and submarine data. The European Space Agency's Envisat and CryoSat‐2 satellites have the potential to produce a continuous record of Arctic sea ice thickness since 2002, but this is complicated by the fact that the satellites do not sample the sea ice surface in the same way. We find that Envisat is only able to sample larger, thicker sea ice relative to CryoSat‐2, because of its poorer resolution. In this paper we account for these differences in sampling to combine Arctic sea ice thickness estimates from two the satellite missions. Applying a sea ice thickness bias correction to Envisat data reduces the ice thickness difference between Envisat and CryoSat‐2 from an average of 53.0 to 0.5 cm

Improving the quality of Sentinel-3A data with a hybrid mean sea surface model, and implications for Sentinel-3B and SWOT

Abstract In this paper we compute a new local mean sea surface (MSS) model along the Sentinel-3A ground track. This so-called hybrid mean profile (HMP) blends the content of an average of 18 months of Sentinel-3A data for wavelengths ranging from 15 to 100 km, and the CNES/CLS 2015 gridded MSS model for larger and shorter scales. The improvement observed on Sentinel-3A sea level anomalies (SLA) is significant: the residual error is 0.2 cm2, i.e. 17% of the SLA variance between 15 and 100 km, or 57% less than the gridded MSS model error. The highest error reduction is observed for wavelengths ranging from 20 to 80 km. From a geographical point of view, the improvement is mainly located along geodetic features that are not completely resolved in the gridded MSS models. It can locally be as high as 1 cm2, i.e. very large when compared to the variance of the small scale SLA. Similarly, in coastal regions where the gridded model is known to exhibit higher errors, the HMP exhibits a very stable behavior that is on average 4 times more accurate. To understand the implications for future datasets and mission, we also develop a simple prediction model for the leakage of noise and small scale SLA into the MSS model. The model was validated with Sentinel-3A and ENVISAT data. Using the HMP strategy on the 21-day phase of the SWOT mission would be attractive for two reasons: 1/this methodology would reduce the small scale error of gridded MSS models thanks to SWOT’s unprecedented 2D topography coverage and noise level, and 2/the gridded MSS models provides a more trustworthy reference for the larger temporal scales that cannot be not averaged out by SWOT alone. After 3 years of nominal mission, the residual SWOT HMP error should be less than 2% of the sea level anomaly variance. In contrast, the so-called fast-sampling (or 1-day repeat) phase of SWOT is slightly more challenging because of the temporal correlation of the SLA (1-day samples are not independent). Depending on the accuracy of the pre-launch gridded MSS (i.e. upper wavelength limit where SWOT data must be used), the decorrelation scales could range from 1 to 5 days. The resulting HMP error would ranges from 5 to 12% of the SLA variance at the end of the fast-sampling phase. These results emphasize the need to keep improving the smaller scales of gridded MSS models as they will remain a major altimetry asset, at least until 2023, when SWOT has collected enough 21-day samples to provide a very robust HMP model.

Pre-Collapse Space Geodetic Observations of Critical Infrastructure: The Morandi Bridge, Genoa, Italy

We present a methodology for the assessment of possible pre-failure bridge deformations, based on Synthetic Aperture Radar (SAR) observations. We apply this methodology to obtain a detailed 15-year survey of the Morandi bridge (Polcevera Viaduct) in the form of relative displacements across the structure prior to its collapse on August 14th 2018. We generated a displacement map for the structure from space-based SAR measurements acquired by the Italian constellation COSMO-SkyMed and the European constellation Sentinel-1A/B over the period 2009–2018. Historical satellite datasets include Envisat data spanning 2003–2011. The map reveals that the bridge was undergoing an increased magnitude of deformations over time prior to its collapse. This technique shows that the deck next to the collapsed pier was characterized since 2015 by increasing relative displacements. The COSMO-SkyMed dataset reveals the increased deformation magnitude over time of several points located near the strands of this deck between 12th March 2017 and August 2018.