Altimeter Data Research Articles

Extraction of ocean tidal information based on global equal-area grid and satellite altimeter data

Extraction of ocean tidal information based on global equal-area grid and satellite altimeter data

Characteristics and dynamics of mesoscale eddies in the eastern Arabian sea

Present study investigates the characteristics and dynamics of mesoscale eddies in the eastern Arabian Sea (EAS), which is relatively less explored and quantified compared to the western Arabian Sea (WAS), using 26-year long altimeter data and numerical simulations. Our study shows that the continental slopes of the northern and southern parts of the EAS are the hotspots of the eddy generation. The EAS eddies propagate westward with speeds in the range of 10–30 cm/s and most of them dissipate before crossing central Arabian Sea (AS). In EAS, more number of eddies are formed in the winter season (44.2%) followed by spring (40.9%) and summer (10.5%) whereas in the WAS, summer season accounts for about 36.4% of eddies, followed by winter (30%) and spring (24%). While the eddy generation in the WAS is mainly associated with the instability caused by strong monsoon winds, our analysis shows that large positive baroclinic instability during winter associated with the propagation of intraseasonal, coastally-trapped Kelvin Waves from the equatorial Indian Ocean and subsequent Rossby wave radiation play an important role in the generation of eddies in the EAS. Our results confirm that remote forcing in the EAS plays a significant role in setting up instabilities compared to the local wind forcing. Estimation of eddy-induced transport shows that mesoscale eddies account for around 22% (8%) of the westward transport of heat (salt) in the upper 100 m in the EAS, especially in the southern part during winter when the low-saline water from the Bay of Bengal (BoB) intrudes into the AS.

An improved altimeter-derived gravity anomaly from shipborne gravity based on the mean sea surface height constraint factors method

Coastal marine gravity modeling faces challenges due to the degradation of the quality and poor coverage of altimeter data in coastal regions. The effective fusion of shipborne gravity data and altimeter-derived marine gravity data can make shipborne gravity data more useful for the accurate estimation of altimeter-derived coastal marine gravity. A mean sea surface height constraint factor (MSSHCF) method based on the ordinary kriging method and the remove-restore technique is proposed to fuse altimeter-derived gravity model with shipborne gravity data. In this method, all data are standardized during the interpolation process to reduce the error and mean sea surface as a vertical variable is added to the semi-variance function in ordinary kriging to obtain the residual shipborne gravity as corrected data source. The coastal marine gravity models V2.1 and V3.1 which fused altimeter-derived gravity data with shipborne gravity data and V1.1 without shipborne gravity data at a spatial resolution of 1′×1′ can be obtained. Validation experiments show that the accuracy of the gravity model V3.1 obtained by the MSSHCF method more closely agrees with the validated gravity model DTU17 and SS V31 than the model V2.1 obtained by the ordinary kriging interpolation method and the V1.1 model. Our results were validated against shipborne gravity data; the accuracy of model V3.1 was 4.95 % higher than the model V1.1 in South China Sea area A and 2.48 % higher in South China Sea area B. Meanwhile, the accuracy of model V3.1 was 2.07 % higher than model V2.1 in South China Sea area A and 2.42 % higher in South China Sea area B. The effects of distance from the coast and sea depth on the marine gravity model were also evaluated. The results show that the gravity model V3.1 has higher accuracy with the change in ocean distance and depth than the V2.1 and V1.1 gravity models. Thus, our study shows that the MSSHCF method effectively refines coastal altimeter-derived gravity using shipborne gravity data.

Accuracy of numerical wave model results: application to the Atlantic coasts of Europe

Abstract. Numerical wave models are generally less accurate in the coastal ocean than offshore. It is generally suspected that a number of factors specific to coastal environments can be blamed for these larger model errors: complex shoreline and topography, relatively short fetches, combination of remote swells and local wind seas, less accurate wind fields, presence of strong currents, bottom friction, etc. These factors generally have strong local variations, making it all the more difficult to adapt a particular model setup from one area to another. Here we investigate a wide range of modeling choices including forcing fields, spectral resolution, and parameterizations of physical processes in a regional model that covers most of the Atlantic and North Sea coasts. The effects of these choices on the model results are analyzed with buoy spectral data and wave parameter time series. Additionally, satellite altimeter data are employed to provide a more complete performance assessment of the modeled wave heights as a function of the distance to the coast and to identify areas where wave propagation is influenced by bottom friction. We show that the accurate propagation of waves from offshore is probably the most important factor on exposed shorelines, while other specific effects can be important locally, including winds, currents, and bottom friction.

Seasonal variability of eddy kinetic energy in the north Indian Ocean

The seasonality of eddy kinetic energy (EKE) is analyzed in the north Indian Ocean by adopting high-resolution ocean reanalysis data. Significant eddy energy can be mainly spotted in six regions, including the Somali Current (SC) region, the Gulf of Aden, the Laccadive Sea, the east of Sri Lanka, the East Indian Coastal Current (EICC) region, and the northwest of Sumatra. As the most energetic region, the EKE averaged above 200 m could exceed 0.15 m2·s-2 in the SC region, whereas the mean EKE above 200 m is less than 0.04 m2·s-2 in the other regions. The barotropic and baroclinic instabilities are vital to eddy energy, and the contribution of each term in the barotropic/baroclinic equations varies with season and region. In the SC region and EICC region, EKE is primarily generated by barotropic conversion due to the sharp velocity shear caused by the strong SC during the summer monsoon and the EICC from March to June. For the other regions, the leading source of EKE is the eddy potential energy (EPE), which is extracted from available potential energy of mean flow via baroclinic conversion, and then the EPE is converted into EKE through vertical density flux. Once generated, EKE will be redistributed by pressure work and advection via eddy energy flux, which varies in sync with the monthly variation of total EKE, transporting EKE to the adjacent region or deeper layer. From the vertical aspect, eddy energy conversions are more prominent above 200 m. The maximal EKE and barotropic conversion mostly occur at the surface, whereas the EPE and baroclinic conversion may have two peaks, which lie at the surface and in the thermocline. Using the satellite altimeter data and wind data, we further investigate the impact of geostrophic eddy wind work, which reveals a slightly dampening effect to EKE in the north Indian Ocean.

Modeling the thermal environment of Mercury’s north pole using MLA. Implications for locations of water ice

Radar observations made by the Arecibo Observatory have revealed radar-bright deposits in the north polar region of Mercury which are consistent with water ice. These deposits are generally associated with floors of deep craters in permanent shadow. In this paper, we revisit topographic data, illumination, and associated thermal conditions of the north polar region of Mercury to investigate these radar-bright deposits. We used Mercury Laser Altimeter (MLA) data from the MESSENGER mission to derive a dedicated, adjusted high-resolution Digital Terrain Model (DTM) of the north polar region at 250 m/pixel. Based on this DTM, illumination conditions and temperature were derived for the first time on the fully available MLA dataset. Generally, craters equatorward of 86 ∘N are found to be too hot to contain surface water ice due to effective self-heating. For those warm craters that do contain radar-bright deposits, temperatures within the upper 10–20 cm of regolith are cold enough for water ice to be stable. Using our improved DTM, we confirm previously MLA-modeled illumination conditions in Prokofiev crater and argue that radar-bright patches outside the PSR in the area may be explained by icy deposits in cold and shallow (within 5 cm) sub-surface layers. In the radar observations we find a strong, unphysical correlation between radar-bright pixels and the number of radar observations per pixel. Consequently, several PSRs which were classified as free of radar-bright material (mainly at longitudes 120–340 ∘E) are most likely subject to a bias in the averaging process in deriving the composite radar image and might contain water ice after all.

Investigation of Waves Generated by Tropical Cyclone Kyarr in the Arabian Sea: An Application of ERA5 Reanalysis Wind Data

In this study, the wave conditions in the Arabian Sea induced by tropical cyclone Kyarr (2019) have been simulated by employing the 3rd generation wave model MIKE 21 SW. The model was run from 24 October to 1 November 2019, a total of 8 days. The MIKE 21 SW model was forced by reanalyzed ERA5 wind data from the European Centre for Medium-Range Weather Forecasts (ECMWF). The results are compared with buoy data from the Indian National Centre for Ocean Information Services (INCOIS), which is located at 67.44° E, 18.50° N. In addition, the satellite altimeter data (CryoSat-2, SARAL and Jason-3 satellite altimeter data) was utilized for validation. Three wave parameters are considered for the validation: the significant wave height; the peak wave period; and the mean wave direction. The validation results showed that the significant wave height, the peak wave period, and the mean wave direction could be reasonably predicted by the model with reanalysis wind data as input. The maximum significant wave height reached to 10.7 m (with an associated peak wave period of 12.5 s) on 28 October 2019 at 23:00:00 in the middle of the Arabian Sea. For coastal areas, the significant wave height along the Iran and Pakistan (north Arabian Sea) coasts increased to a range of 1.4–2.8 m when tropical cyclone Kyarr moved northward. This wave height along with elevated sea level may cause severe coastal erosion and nearshore inland flooding. Impacts of cyclones on coastal zones critical facilities and infrastructure can be reduced by timely and suitable action before the event, so coastal managers should understand the effect of cyclones and their destructive consequences. The validated model developed in this study may be utilized as input data of evaluating the risk to life and infrastructure in this area.

Integrating satellite altimeter data and geomorphic in‐stream flow tool to assess reach average hydraulic habitat of the Ganga River dolphin

AbstractThe Ganga River ecosystem is under severe anthropogenic stress. Flow regulations through structural barriers alter the geomorphic and hydraulic geometry of riverine habitats. Determining the ecological health of river habitats under the contemporary modification is detrimental to its restoration and management. This study evaluates reach averaged hydraulic habitat of the endangered Ganga River dolphin (Platanista gangetica) in a stretch between Bijnor and Narora barrages. We consider an optimal minimum flow depth as the determining factor of habitat suitability. Field measurement of the hydraulic geometry and flow characteristics show that the optimal flow depth is available in the study reach during the monsoon period, while in the pre‐monsoon, the minimum depth is present only in the reach upstream to Narora barrage. We use a geomorphic instream flow tool (GIFT) and satellite altimeter water level data to simulate reach averaged hydraulic habitat in varying flow conditions in area upstream of Narora barrage. We observe that to maintain the minimum flow depth which supports the dolphin habitat in the study reach, an optimal discharge of about is essential. Furthermore, we develop a water‐level (altimeter) and discharge (simulated from GIFT) rating curve for the study reach. It can be used to get a first‐order estimate of discharge for a given water level or vice versa. This study indicates that the altimetry datasets are good precursors for estimating averaged hydraulic habitat of rivers in the data‐scarce regions. The application of altimeter data can be a boon in the effective management of river habitat health over a reach scale.

Changes in Deep Ocean Contribute to a “See‐Sawing” Gulf Stream Path

AbstractThis study demonstrates that a decrease of the water‐mass density below 1,000 m has led to a pattern of see‐saw shift in the Gulf Stream (GS) position between 74 and 50°W in longitude during 1993–2017, with the New England Seamounts as the pivot point. The GS moved northward in the upstream region and shifted southward in the downstream. Our empirical orthogonal function analyses of satellite altimeter data demonstrate that the second mode (EOF2) represents changes in the GS strength and therefore can be used as an index for the Atlantic Meridional Overturning Circulation. Decreasing water density below 1,000 m is also the principal mechanism driving the weakening of the GS.

Coastal bathymetry inversion using SAR-based altimetric gravity data: A case study over the South Sandwich Island

The global bathymetry models are usually of low accuracy over the coastline of polar areas due to the harsh climatic environment and the complex topography. Satellite altimetric gravity data can be a supplement and plays a key role in bathymetry modeling over these regions. The Synthetic Aperture Radar (SAR) altimeters in the missions like CryoSat-2 and Sentinel-3A/3B can relieve waveform contamination that existed in conventional altimeters and provide data with improved accuracy and spatial resolution. In this study, we investigate the potential application of SAR altimetric gravity data in enhancing coastal bathymetry, where the effects on local bathymetry modeling introduced from SAR altimetry data are quantified and evaluated. Furthermore, we study the effects on bathymetry modeling by using different scale factor calculation approaches, where a partition-wise scheme is implemented. The numerical experiment over the South Sandwich Islands near Antarctica suggests that using SAR-based altimetric gravity data improves local coastal bathymetry modeling, compared with the model calculated without SAR altimetry data by a magnitude of 3.55 m within 10 km of offshore areas. Moreover, by using the partition-wise scheme for scale factor calculation, the quality of the coastal bathymetry model is improved by 7.34 m compared with the result derived from the traditional method. These results indicate the superiority of using SAR altimetry data in coastal bathymetry inversion.

Contribution of Sentinel-3A Radar Altimetry Data to the Study of the Water Level Variations in Lake Buyo (West of Côte d’Ivoire)

The artificial Lake Buyo is an important water reservoir that ensures the availability of water for multiple purposes: drinking water supply, fishing, and energy. In the last five years, this lake has experienced extreme variations in its surface area and water levels, including very significant declines, which has impacted the supply of electricity. This study aimed to assess temporal variations in the water levels of Lake Buyo using radar altimetry. Altimetric data from the Sentinel-3A satellite on Lake Buyo (tracks 16 (orbit 8) and 743 (orbit 372)) were selected over the period from 31 May 2016 to 12 June 2021 and compared to the in situ measurements provided by the Direction de la Production de l’Electricité de Côte d’Ivoire (DPE-CI). The extraction of the time series of the Sentinel-3A altimetric water levels and their corrections (geophysical and environmental corrections) were carried out with the ALTiS software. The results showed an overall agreement between the altimetric water levels and the in situ measurements, with a correlation coefficient (R2) ranging from 0.98 to 0.99 obtained, as well as a Nash–Sutcliffe Efficiency (NSE) coefficient also between 0.98 and 0.99. Further, the bias (0.12 m and 0.13 m) and root mean square error (RMSE) (0.38 and 0.67 m) values showed that the results were acceptable. The analysis of the water levels time series allowed for the identification of two main periods: March to October and November to February. The first period corresponded to a high level period, recording a maximum level of 200.06 m. The second period, from November to March, was characterized by a drop in the water level, recording a minimum level of 187.42 m. The water levels time series provided by Sentinel-3 allowed us to appreciate the respective influences of seasonal and interannual variations on rainfall and the contributions of the Sassandra River tributaries to the water levels of Lake Buyo.

Deep-Learning-Based Feature Extraction Approach for Significant Wave Height Prediction in SAR Mode Altimeter Data

Predicting sea wave parameters such as significant wave height (SWH) has recently been identified as a critical requirement for maritime security and economy. Earth observation satellite missions have resulted in a massive rise in marine data volume and dimensionality. Deep learning technologies have proven their capabilities to process large amounts of data, draw useful insights, and assist in environmental decision making. In this study, a new deep-learning-based hybrid feature selection approach is proposed for SWH prediction using satellite Synthetic Aperture Radar (SAR) mode altimeter data. The introduced approach integrates the power of autoencoder deep neural networks in mapping input features into representative latent-space features with the feature selection power of the principal component analysis (PCA) algorithm to create significant features from altimeter observations. Several hybrid feature sets were generated using the proposed approach and utilized for modeling SWH using Gaussian Process Regression (GPR) and Neural Network Regression (NNR). SAR mode altimeter data from the Sentinel-3A mission calibrated by in situ buoy data was used for training and evaluating the SWH models. The significance of the autoencoder-based feature sets in improving the prediction performance of SWH models is investigated against original, traditionally selected, and hybrid features. The autoencoder–PCA hybrid feature set generated by the proposed approach recorded the lowest average RMSE values of 0.11069 for GPR models, which outperforms the state-of-the-art results. The findings of this study reveal the superiority of the autoencoder deep learning network in generating latent features that aid in improving the prediction performance of SWH models over traditional feature extraction methods.

Simulated Signatures of Greenland Melting in the North Atlantic: A Model Comparison With Argo Floats, Satellite Observations, and Ocean Reanalysis

AbstractIncreased Greenland ice sheet melting has an impact on global mean and regional sea level rise and the ocean circulation. In this study, we explore whether Greenland melting signatures found in ocean model simulations are visible in observations from radar altimetry, satellite gravimetry and Argo floats. We have included Greenland freshwater flux (GF) in the global Finite‐Element‐Sea ice‐Ocean Model (FESOM) for the years 1993–2016. The reference run is computed by excluding Greenland freshwater input. These experiments are performed on a low resolution (ca. 24 km) and a high resolution (ca. 6 km) eddy‐permitting mesh. For comparison with the model experiments, we use different observational data, such as Argo floats, satellite observations, and reanalyses. We find that surface GF maps into signatures in temperature and salinity down to about 100 m in the surroundings of Greenland. The simulated melting signatures are particularly visible in steric heights in Baffin Bay and Davis Strait. Here, we find an improvement of the mean square error of up to 30% when including GF. For the Nordic part of the Nordic Seas, however, we find no improvement when including GF. We compare steric heights with reanalysis data and a new setup of the inversion method from gravimetric and altimetric satellite data. We cannot confirm that the GF signatures on variables such as temperature and salinity are visible in the observations on the time scales considered. However, we find that increased model resolution often causes larger improvements than occur due to including the simulated melting effect.

Surface Roughness Variation Across Polar Ice Deposit Boundaries on Mercury

AbstractWe analyze the surface roughness of five north polar craters on Mercury using 125 m/pixel Mercury Laser Altimeter data. Each crater hosts a polar deposit (PD) with a low‐reflectance surface. The PDs have distinct geologic contacts, enabling an analysis of roughness across deposit boundaries onto ice‐free portions of the host craters' floors. The low‐reflectance surfaces in Angelou, Despréz, and Ensor collocate with radar‐bright signatures consistent with the presence of several‐meters‐thick water‐ice deposits beneath their low‐reflectance surfaces. Subdued roughness in these three craters is consistent with the superposition of several meters of ice. The difference between roughness on and off their low‐reflectance surfaces is within one standard deviation (SD) of the results, but is found to be statistically significant, as indicated by K‐S and Mann‐U Whitney tests, and meaningful, as indicated by Cohen's d tests. There is no meaningful difference in Jiménez and Josetsu, two craters that lack strong radar‐bright signatures, consistent with the hypothesis that they do not host substantial water ice beneath their low‐reflectance surfaces and thus not all of Mercury's available cold traps are occupied by water ice. Analyzing the roughness of polar craters may provide insight into the presence/absence of thick volatile deposits, but higher‐resolution topography would be helpful given the high SD associated with roughness. Finally, we identify subdued roughness along three PDs that may be related to thick lag deposit margins or enhanced diffusive mixing along deposit edges. Roughness may provide new insight into surface characteristics of the ices and inform surface evolution models.

SDUST2021GRA: global marine gravity anomaly model recovered from Ka-band and Ku-band satellite altimeter data

Abstract. With the launch of altimetry satellites with different observation frequencies and different survey missions, it is necessary to integrate multi-satellites altimeter data to establish a new global marine gravity anomaly model. Based on Ka-band sea surface heights (SSHs) from SARAL/AltiKA and Ku-band SSHs from other satellites (including HY-2A) in geodetic missions and exact repeat missions, the global marine gravity anomaly model of SDUST2021GRA on a 1′ × 1′ grid is derived. Gridded deflections of vertical (DOV) are determined from along-track geoid gradients by the least squares collocation method, in which the noise variances of along-track geoid gradients are obtained by the iteration method for Ka-band geodetic mission and by the SSH crossover discrepancies for other altimetry missions. SDUST2021GRA is recovered from the gridded DOVs by the inverse Vening Meinesz formula, and analyzed by comparing with the recognized marine gravity anomaly models of DTU17 and SIO V30.1. Finally, the accuracy of SDUST2021GRA, DTU17, and SIO V30.1 is assessed by preprocessed shipborne gravity anomalies. In conclusion, the differences between SDUST2021GRA and recognized models are small, indicating the reliability of SDUST2021GRA. The differences are mainly concentrated between −5 and 5 mGal, which accounts for more than 95 % of the total number. Assessed by shipborne gravity, the accuracy of SDUST2021GRA is 2.37 mGal globally, which is higher than that of DTU17 (2.74 mGal) and SIO V30.1 (2.69 mGal). The precision advantage of SDUST2021GRA is mainly concentrated in offshore areas. HY-2A-measured altimeter data have an important role on gravity anomaly recovery in areas with complex coastlines and many islands. SDUST2021GRA is concluded to reach an international advanced level for the altimeter-derived marine gravity model, especially in the offshore area. The SDUST2021GRA model data are freely available at https://doi.org/10.5281/zenodo.6668159 (Zhu et al., 2022).

Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods

Abstract. The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping the general circulation is yet unknown. In the following paper, we use an unsupervised neural network clustering method to analyze the long-term variability of the different mesoscale structures. We decompose 26 years of altimetric data into clusters reflecting different circulation patterns of weak and strong flows with either strain or vortex-dominated velocities. The vortex-dominated cluster is more persistent in the western part of the basin, which is more active than the eastern part due to the strong flow along the coast, interacting with the extended bathymetry and engendering continuous instabilities. The cluster that reflects a weak flow dominated the middle of the basin, including the Mid-Mediterranean Jet (MMJ) pathway. However, the temporal analysis shows a frequent and intermittent occurrence of a strong flow in the middle of the basin, which could explain the previous contradictory assessment of MMJ existence using in-situ observations. Moreover, we prove that the Levantine Sea is becoming more and more energetic as the activity of the main mesoscale features is showing a positive trend.

Siting strategy of new tidal stations in the Bohai Sea using adjoint method

The optimal siting selection strategy for new tidal stations in the Bohai Sea is investigated using a two-dimensional tidal model with the adjoint method. Harmonic constants (HCs) of the M2 constituent at all computing grids are estimated in the Bohai Sea by assimilating observations from existing tidal stations and altimeter data processed by X-Track software. Several grid points on the coastline are selected as new tidal station sites, and different combinations of selected points are regarded as different siting strategies. The HCs at these new tidal stations are served as “simulated observations” (SOs) which are assimilated into the tidal model to re-estimate the HCs in the Bohai Sea. Through comparisons between the re-estimated HCs and SOs, we can evaluate the effects of different siting strategies. Divide the Bohai Sea into different subdomains, numerical experiments are constructed to investigate the effects of different strategies in different subdomains, while the effects of schemes including inversion variables and different tidal constituents on siting selection are experimented. By analyzing the root-mean-square (RMS) difference between re-estimated HCs and SOs on the coastline in different subdomains, the optimum strategy for siting of new tidal stations in the Bohai Sea is obtained.

Assessment of the use of scatterometer wind data to force wave models in the North Atlantic Ocean

The present work uses for the first time scatterometer wind fields to force a wave model and compares the accuracy of the resulting wave conditions with the ones obtained when using two different sources of hindcast wind fields forcing the same wave spectral model in the Atlantic Ocean. For this purpose, a 5-year hindcast (2010–2014) is performed with the wave spectral model SWAN for the Madeira and Azores archipelagos. The model uses as input the bathymetry from GEBCO, the wave boundary conditions from the WAVEWATCH III wave model provided by Ifremer and winds from the ERA-Interim and ERA5 databases, and remotely sensed winds from scatterometers. A quantitative analysis of the results is performed, and the numerical results are validated against altimeter data and buoy measurements. Globally, ERA-Interim, ERA5 and scatterometer wind data provided similar accuracy of the generated wave fields, as expressed in the error statistics, which are very close to each other, but in the case of extreme events, the scatterometer data reveals more intense winds and consequently lead to sea states with higher significant wave height. This is more visible in the Azores area than in Madeira. The results demonstrate that, in general, the significant wave height is well reproduced by SWAN.

Biases Analysis and Calibration of ICESat-2/ATLAS Data Based on Crossover Adjustment Method

The new-generation photon-counting laser altimeter aboard the Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) has acquired unprecedented high-density laser data on the global surface. The continuous analysis and calibration of potential systematic biases in laser data are important for generating highly accurate data products. Current studies mainly calibrate the absolute systematic bias of laser altimeters based on external reference data. There are few studies that focus on the analysis and calibration of relative systematic biases in long-term laser data. This paper explores a method for systematic biases analysis and calibration of ICESat-2 laser data based on track crossovers for the first time. In the experiment, the simulated data and ICESat-2 data were used to verify the algorithm. The results show that, during the three-year period in orbit, the standard deviation (STD) and bias of the crossover differences of the ICESat-2 terrain data were 0.82 m and −0.03 m, respectively. The simulation validation well demonstrate that the crossover adjustment can calibrate the relative bias between different beams. For ICESat-2 data, the STD of the estimated systematic bias after crossover adjustment was 0.09 m, and the mean absolute error (MAE) was 0.07 m. Compared with airborne lidar data, the bias and root mean square error (RMSE) of the ICESat-2 data remained basically unchanged after adjustment, i.e., −0.04 m and 0.38 m, respectively. This shows that the current ICESat-2 data products possess excellent internal and external accuracy. This study shows the potential of crossover for evaluating and calibrating the accuracy of spaceborne photon-counting laser altimeter data products, in terms of providing a technical approach to generate global/regional high-accuracy point cloud data with consistent accuracy.

Do Eddies Connect the Tropical Atlantic Ocean and the Gulf of Mexico?

AbstractConsistent with satellite‐tracked trajectories of drogued drifters, but at odds with Eulerian assessment of satellite‐altimetry measurements of sea‐surface height, we show that North Brazil Currents Rings (NBCRs) are incapable of bypassing the Lesser Antilles as structures that coherently transport material. We arrive at this conclusion by applying geodesic eddy detection on the altimetric data set over nearly its entire extent. While we detect northwestward translating NBCRs that can be classified as coherent Lagrangian eddies, they typically experience strong filamentation and complete loss of coherence prior to reaching the Lesser Antilles. Moreover, the filamented material hardly penetrates into the Caribbean Sea, let alone the Gulf of Mexico, and not without substantively mixing with the ambient fluid east of the archipelago. The nature of the inability of the de‐facto oceanographic Eulerian, streamline‐based eddy detection technique to produce a correct assessment of the connectivity between the tropical Atlantic and the Gulf of Mexico is rooted in its lack of objectivity.