Search

Abstract Accurate estimate of active layer thickness (ALT) is crucial for understanding permafrost and ecosystem responses to climate change. Interferometric Synthetic Aperture SAR (InSAR) technology can detect active layer freeze-thaw induced surface deformation with high accuracy, facilitating more accurate ALT estimation at the regional scale. Previous studies revealed a positive relationship between ALT and seasonal deformation in poorly drained Arctic soils. However, whether such relationship still holds in arid permafrost regions such as the Qinghai-Tibet Plateau (QTP) remains uncertain. Through synthesizing extensive field observations and remote sensing data, we find an overall negative correlation (r = -0.53, p

The effect of ultrasound and plasma pretreatment on freeze-dried kiwifruit crisps was investigated in this study. Using unpretreated kiwifruit as a control group (CG), the effects of ultrasound (US), plasma-activated water (PAW), ultrasound combined with plasma-activated water (UPAW), plasma-jet (PJ), and ultrasound combined with plasma-jet (UPJ) on the quality of vacuum freeze-dried kiwifruit were investigated. The results showed that all the pretreatments could change the microstructure of the crisps. The microstructure of dried kiwifruit after pretreatment showed more porous structures with different number and size compared to the CG group. The largest pore structure was observed in the UPAW group which had the highest crispness. The activity of water (Aw) of all pretreatment samples was significantly lower than the CG group (P

Located at the easternmost sector of the Last Ice Area (LIA) with the oldest and thickest sea ice, the north of Greenland has witnessed some unprecedented polynyas since 2018, receiving considerable attention. Sea ice concentration (SIC) derived from passive microwave data can provide near daily observations of these polynyas. However, these SIC products are limited by the coarse spatial resolution of passive microwave data, with mixed pixels and large uncertainties at the ice–water divide. It is especially difficult in the case of newly formed polynyas in the form of leads with narrow openings, preventing accurate estimation of the regional energy budget and heat fluxes as well as the hindering causal analysis of the polynyas. In this paper, a novel state-of-the-art deep-learning-based super-resolution (SR) method is adopted, and passive microwave SR images, with spatial resolutions of up to 4 times the original, are generated and employed to derive super-resolved SIC (SR-SIC). Experimental results confirm the benefits of SR-SIC for finer monitoring of sea ice at both the polynya and lead scale compared to the original lower-resolution SIC, with an average 7.55% improvement in F1-Score for polynya extent and 31.17% for lead width. Using the SR-SIC, more accurate quantitative parameters of polynyas and leads are extracted to present more detailed spatial distributions at their different development stages. For example, SR-SIC with reduced mixed pixels can distinguish more SIC values below 40%, advantageous for detecting open water pixels within polynya areas and improving the accuracy of heat fluxes estimation and ice production calculation. Moreover, SR-SIC has the capability to identify leads with openings less than 3 km and to locate the finer boundaries of the polynyas. Finally, it is found that the lead development along the 2018 winter polynya is associated with regional wind, air temperature, and ice drift. The prominent summer polynya events in 2018, 2020, and 2021 may be in part caused by the thinning sea ice in the north of Greenland.

ABSTRACTIt is critical to understand the mechanisms and impacts of global climate change in cryosphere and polar environment. Here we describe the design and progress of the remote sensing products we have developed to monitor these changes. We obtain datasets by combining multi-sensor remote sensing systems with field validation systems, and then develop a methodological system that combines multiple sources and calibration technologies to address the challenges of data heterogeneity in dynamically monitoring key parameters. This global change and response special project supported by the National Key Research and Development Program of China, named ‘observation and inversion of critical parameters of changes in the cryosphere and polar environment’, providing comprehensive records of essential elements of the cryosphere through long-term satellite records. The multi-team is completing the project and collecting data from multi-sensor to create remote sensing data products that include records of changes in the cryosphere, such as permafrost, glaciers, ice sheet mass balance, seasonal snow accumulation, sea ice, and albedo changes. Finally, the existing ground- and space-based observing system can be improved to provide dynamic monitoring of key parameters in the cryosphere and changes in the polar environment.

Melting and calving of glaciers and ice caps in Antarctica and Greenland could potentially contribute significantly to global sea level rise. Updates to existing outlines that provide critical glacier baseline information in both regions could help in the analysis of particular changes in glacier parameters such as area and volume from time-series inventories. Here we synthesize previously established techniques and apply new multi-source datasets to update glacier outlines in selected test areas of Antarctica and Greenland, as well as to reduce uncertainties and errors during the mapping process. The workflow includes mapping glacier boundaries, subdividing glaciers by watersheds and assigning glacier attributes. Complicated glacier scenarios and updating challenges in polar regions are discussed and demonstrated by representative case studies. For the first time in Antarctica, we analyze the effect of terminus types on mapped glacier areas, and in Greenland we compare the differences with glacier mapping results using Landsat OLI and ETM+. With new data sources, the methods described in this study might help to create glacier outlines on a larger scale in Antarctica and Greenland. Although data sources can be substituted, the enormous amount of manual labor required to update glacier inventories remains a significant challenge.

Abstract Wilkes Land and Totten Glacier (TG) in East Antarctica (EA) have been losing ice mass significantly since 1989. There is a lack of knowledge of long-term mass balance in the region which hinders the estimation of its contribution to global sea level rise. Here we show that this acceleration trend in TG has occurred since the 1960s. We reconstruct ice flow velocity fields of 1963–1989 in TG from the first-generation satellite images of ARGON and Landsat-1&4, and build a five decade-long record of ice dynamics. We find a persistent long-term ice discharge rate of 68 ± 1 Gt/y and an acceleration of 0.17 ± 0.02 Gt/y2 from 1963 to 2018, making TG the greatest contributor to global sea level rise in EA. We attribute the long-term acceleration near grounding line from 1963 to 2018 to basal melting likely induced by warm modified Circumpolar Deep Water. The speed up in shelf front during 1973–1989 was caused by a large calving front retreat. As the current trend continues, intensified monitoring in the TG region is recommended in the next decades.

Accurate ice flow velocity data are essential for studying the mass balance of the Antarctic ice sheet. However, there is a lack of ice velocity maps of 1960s–80s in basin-wide regions or the entire ice sheet. In this study, an enhanced hierarchical network densification approach is developed for basin-wide Antarctic velocity mapping using historical ARGON and Landsat images. The produced multiple historical velocity maps from 1963 to 1989 in the region of the Fimbul and Jelbart ice shelves, East Antarctica, achieved an accuracy better than 29 m a−1. They revealed that the ice flow velocity had no significant changes over the period. Combining the surface mass balance estimate with the ice discharge estimated from our historical velocity maps and recently published velocity maps, we estimated a positive mass balance of 8.6 ± 3.9 Gt a−1 in the study area from 1963 and 2015. Our results indicate that the region's positive mass balance, as estimated in recently published studies, has been maintained since the 1960s. It is also in concordance with the low level of mass balance from 1992 to 2017 in East Antarctica. This suggests that the study area has been stable since the 1960s.

Passive microwave data is an important data source for the continuous monitoring of Arctic-wide sea ice concentration (SIC). However, its coarse spatial resolution leads to blurring effects at the ice-water divides, resulting in the great challenges of fine-scale and accurate SIC estimation, especially for regions with low SIC. Besides, the SIC derived by operational algorithms using high-frequency passive microwave observations has great uncertainties in open water or marginal ice zones due to atmospheric effects. In this article, a novel framework is proposed to achieve accurately SIC estimation with improved spatial details from original low-resolution Advanced Microwave Scanning Radiometer 2 (AMSR2) images, with joint the super-resolution (SR) and SIC estimation network. Based on the SR network, the spatial resolution of original AMSR2 images can be improved by four times, benefiting to construct AMSR2 SR features with more high-frequency information for SIC estimation. The SIC network with an encoder–decoder structure and atrous convolution, is employed to accurately perform the SIC retrieval by considering the characteristics of passive microwave images in the Arctic sea ice region. Experimental results show that the proposed SR-Aided SIC estimation approach can generate accurate SIC with more detailed sea ice textures and much sharper sea ice edges. With respect to MODIS SIC products distributed in Arctic scale, the proposed model achieves a root-mean-square error (RMSE) of 5.94% and mean absolute error (MAE) of 3.04%, whereas the Arctic Radiation and Turbulence Interaction Study (ARTIST) Sea Ice (ASI) SIC results have three and two times greater values of RMSE and MAE.

Study region: the source region of the Yangtze River (SRYR) Study focus: Precipitation uncertainties significantly impact water resource management, while the uncertainties of various precipitation products are not fully investigated due to the lack of observations, especially in high-altitudinal permafrost areas. In this study, we selected nine products representing three types of precipitation, including gauge-based, satellite-based and merged products, and conducted a comprehensive evaluation using regional water balance method and hydrological model simulations. New hydrological insights for the region: Our results indicate most precipitation products can replicate the observed precipitation decreasing trend with increasing elevation below 4500 m, but trends vary at higher elevations. The gauge-based precipitation products with bias correction outperform others, while most satellite-based products underestimate precipitation. The water-balance based evaluation shows a merged product (TPHiPr), and two gauge-based products perform best, followed by a satellite-based product (MSWEP). Process-based model simulations driven by selected precipitation products can reproduce daily runoff processes well in the entire SRYR (NSE = 0.68–0.86), but the performance degraded in the high-altitudinal Tuotuohe subbasin (NSE = 0.08–0.76). The runoff coefficients comparisons in these two regions also indicate the possible deficiencies of precipitation products in the high-altitudinal regions. Our results highlight the challenges of current precipitation products in characterizing the spatial and temporal precipitation changes in the high-altitudinal permafrost regions, and call for more accurate products in these areas.

CryoSat-2 repeatedly collects dense radar altimetry footprints covering high latitudes of the polar ice sheets for over ten years. The Baseline-D height product of CryoSat-2 was recently upgraded and released in 2019. Based on the internal or locally external evaluation of CryoSat-2 Baseline-D ice heights, we extended the validation both heterogeneously and spatially to accomplish a comprehensive assessment. First, reliable ice surface global navigation satellite system point solutions along the 36th Chinese National Antarctic Research Expedition traverse functioned as a height reference for comparison with the CryoSat-2 SAR synthetic aperture radar interferometric mode (SIN) data. Secondly, the Land Ice Along-Track Height product over Lambert–Amery system (LAS) from ice, cloud, and land elevation satellite 2 (ICESat-2), was also applied to validate CryoSat-2 SIN and low-resolution mode (LRM) data. As the results indicate, the SIN height accuracy is evaluated to be −1.68 m ± 2.35 m (slope < 0.65°) along the traverse and −0.96 ± 1.95 m (slope < 0.95° and roughness < 3 m) over the margin of LAS. The LRM height accuracy is evaluated to be −0.13 ± 0.46 m (slope < 0.1° & roughness < 1 m) over the interior of LAS. The standard deviation of the height differences degrades linearly against the limited growth of the terrain slope/roughness at the confidence level of 99%. It is worth noting that the spatially heterogeneous pattern of height differences is correlated with surface topography variations. This article should imply the potential to improve the estimation of mass balance and its uncertainty of polar ice sheets based on radar altimetry data.

Soil moisture (SM) is one of the key measures to understand the land-atmosphere interaction and permafrost dynamics in the Qinghai–Tibet Plateau (QTP). ERA5-Land is a new reanalysis product with high spatial resolution (9 km), which can provide long-term SM data with a large spatial coverage as well as at multilayer soil depths. However, preliminary comparisons with in-situ data show that the ERA5-Land SM product generally underestimates the seasonal variability and demonstrate a positive bias on the QTP. In this article, we proposed to utilize the mode decomposition method to correct such bias. Specifically, through using the variational mode decomposition, we decomposed the long time-series of ERA5-Land SM data into a series of intrinsic mode functions, and found that the SM seasonal variation can be well represented by the low-frequency modes, which were then selected to feed a regression model for the bias correction. The single-site bias correction results show that our method significantly improves the accuracy of ERA5-Land SM product with bias reduced by 0.22 m3/m3, 0.3 m3/m3, and 0.15 m3/m3 for alpine meadow, alpine steppe, and alpine desert sites, respectively. Together with the slightly reduced accuracy but still acceptable results for the cross-site bias correction, we successfully demonstrate the potential of the mode decomposition method for the bias correction of the ERA5-Land SM product at regional scale. Our method is of great use to study climate impact on regional ecohydrological processes and the permafrost changes in the QTP region.

As the follow-on study to the assessment of ICESat-2 ice surface elevations, we assessed how they are influenced by the surface slopes, which are derived from the ICESat-2 elevations of the received photons and available in the land-ice surface heights product (ATL06), by using coordinated GNSS observations along a 520 km long traverse of the 36th CHINese Antarctic Research Expedition (CHINARE) route in East Antarctica. We further analyzed the impact of the slopes on the ICESat-2 elevation accuracy, which is important for the studies of the local ice flow dynamics, mass balance, and Antarctic contribution to sea level rise. We found that the along-track surface slopes in the ICESat-2 ATL06 data have a high overall agreement of 0.18° ± 0.16° (1σ) and a correlation of 0.66 (R2) with the GNSS slopes. Furthermore, two waveform related corrections, first-photon, and transmit-pulse shape bias corrections, were able to adjust on average a combined elevation bias of ∼1.0 cm. Finally, we found a high linear dependency of elevation errors on slopes, i.e., ∼6.2 cm per 1° slope (R2 = 0.57, slope

The Antarctic Peninsula has undergone dramatic changes in recent decades, including ice-shelf melting, disintegration, and retreat of the grounding line. The Larsen B ice shelf is of particular concern due to the unprecedented ice-shelf collapse in 2002. Since few observations on the Antarctic Peninsula were available before the 1970s, long-term investigation of the surface elevation change in the Larsen B region could not be pursued. In 1995, the United States administration declassified a collection of archived intelligence satellite photographs from the 1960s to the 1970s, including analogue satellite images from the ARGON program covering parts of the Larsen B region. We chose overlapping ARGON photos captured in the Larsen B region in 1963. These photos were all subjected to a tailored photogrammetric stereo-matching process, which overcomes those specific challenges related to the use of historical satellite images, such as poor image quality, low resolution, and a lack of high-precision validation data. We discovered that between 1963 and 2001, the surface elevations of the main tributary glaciers in the Larsen B embayment have undergone little change before the ice shelf collapse from 1963 to 2001 by comparing the reconstructed ARGON-derived digital elevation model (DEM) (1963) and ASTER-derived DEM (2001). In addition, the results demonstrated that the hierarchical image matching method can be modified and applied to reconstruct a historical Antarctic DEM using satellite images acquired ∼60 years ago through an innovative and rigorous ground control point selection procedure that guarantees no changes occurred at these points over the period. The new ARGON-derived DEM derived from ARGON (1963) can be used to build a long-term spatiotemporal record of observations for extended analyses of ice-surface dynamics and mass balance in the Larsen B region.

Considered as the most popular pathogen worldwide, Helicobacter pylori is intensively associated with diverse gastric diseases, including gastric ulcers, chronic progressive gastritis, and gastric cancer. Aside from its pathogenic effect on gastric diseases, growing evidences reveal that H. pylori may be related to numerous extragastric diseases. In this article, we reviewed recent studies and systematically elucidated that H. pylori may interfere with many biological processes outside the stomach and influence the occurrence of various extragastric diseases. Many epidemiological studies have indicated that H. pylori plays a pathogenic role in COVID-19, atherosclerosis, hyperemesis gravidarum and several other extragastric diseases, while the effect of H. pylori is currently under investigation in gastroesophageal reflux disease, asthma, and inflammatory bowel disease. Moreover, we also summarized the possible pathogenic mechanisms of H. pylori that may be related to chronic systemic inflammation and molecular mimicker. Taken together, this review provides a new perspective on the role of H. pylori in extragastric diseases and explores the possible mechanisms, which may help guide clinical treatment.

Permafrost in Qinghai–Tibet Plateau (QTP) has been suffering from global warming in recent years, characterized by the deepening of the permafrost active layer. Seasonal changes in permafrost are usually reflected as ground surface deformation, which can be monitored by multi-temporal interferometric synthetic aperture radar (MT-InSAR) technology. Owing to the extreme environment in the QTP, there are few ground-based deformational observation data available, and records of permafrost monitoring by MT-InSAR with ground validation are limited. Here we present a study of surface deformation monitoring for permafrost with MT-InSAR technology validated by a large number of in-situ observations compared with the previous published results. In this study, a small baseline subset (SBAS) method was used with ENVISAT ASAR data in WuDaoLiang, QTP, to acquire the surface deformation and to analyze the corresponding characteristics. The results were first validated with 24 GNSS leveling observation points along the Qinghai–Tibet Railway, including numeric validation (e.g., statistics and KS test) between the InSAR derived deformation and the time-interpolated GNSS leveling values, and the variation trend of the two deformation sequences during a permafrost deformation period, at each observation point. Considering both the differences in magnitudes and trends, the deformation at 22 out of 24 points detected by InSAR corresponded well to the GNSS observation series over one year, which indicates the reliability of MT-InSAR for permafrost monitoring. After validation, the amplitudes and linear velocity of the InSAR deformation in this region were calculated and analyzed, together with selected points in different types of terrain. Generally, in the deformation map, most pixels show a trend of periodic and seasonal displacement, uplift in winter and subsidence in summer, with amplitudes of 3–10 mm in most regions. The deformation in mountain areas is less than that of flat lands in amplitude, and shows more randomness in periodic characteristics. Meanwhile, some points with obvious settlement have been detected, probably corresponding with permafrost degradation.

Subglacial water bodies are critical components in analyzing the instability of the Antarctic ice sheet. Their detection and identification normally rely on geophysical and remote sensing methods such as airborne radar echo sounding (RES), ground seismic, and satellite/airborne altimetry and gravity surveys. In particular, RES surveys are able to detect basal terrain with a relatively high accuracy that can assist with the mapping of subglacial hydrology systems. Traditional RES processing methods for the identification of subglacial water bodies mostly rely on their brightness in radargrams and hydraulic flatness. In this study, we propose an automatic method with the main objective to differentiate the basal materials by quantitatively evaluating the shape of the A-scope waveform near the basal interface in RES radargrams, which has been seldom investigated. We develop an automatic algorithm mainly based on the traditional short-time Fourier transform (STFT) to quantify the shape of the A-scope waveform in radargrams. Specifically, with an appropriate window width applied on the main peak of each A-scope waveform in the RES radargram, STFT shows distinct and contrasting frequency responses at the ice-water interface and ice-rock interface, which is largely dependent upon their different reflection characteristics at the basal interface. We apply this method on 882 RES radargrams collected in the Antarctic’s Gamburtsev Province (AGAP) in East Antarctica. There are 8822 identified A-scopes with the calculated detection value larger than the set threshold, out of the overall 1,515,065 valid A-scopes in these 882 RES radargrams. Although these identified A-scopes only takes 0.58% of the overall A-scope population, they show exceptionally continuous distribution to represent the subglacial water bodies. Through a comprehensive comparison with existing inventories of subglacial lakes, we successfully verify the validity and advantages of our method in identifying subglacial water bodies using the detection probability for other basal materials of theoretically the highest along-track resolution. The frequency signature obtained by the proposed joint time–frequency analysis provides a new corridor of investigation that can be further expanded to multivariable deep learning approaches for subglacial and englacial material characterization, as well as subglacial hydrology mapping.

Pine Island Glacier (PIG) is one of the largest contributors to sea level rise in Antarctica. Continuous thinning and frequent calving imply significant destabilization of Pine Island Glacier Ice Shelf (PIGIS). To understand the mechanism of its accelerated disintegration and its future development, we conducted a long-term monitoring and comprehensive analysis of PIGIS, including ice flow velocity, ice shelf fronts, ocean water temperature, rifts, and surface strain rates, based on multi-source satellite observations during 1973–2020. The results reveal that: (1) ice flow velocities of PIGIS increased from 2.3 km/yr in 1973 to 4.5 km/yr in 2020, with two rapid acceleration periods of 1995–2009 and 2017–2020, and its change was highly correlated to the ocean water temperature variation. (2) At least 13 calving events occurred during 1973–2020, with four unprecedented successive retreats in 2015, 2017, 2018, and 2020. (3) The acceleration of ice shelf rifting and calving may correlate to the destruction of shear margins, while this damage was likely a response to the warming of bottom seawater. The weakening southern shear margin may continue to recede, indicating that the instability of PIGIS will continue.

We present results of a regional comparative study of surface mass changes from 2004 to 2008 based on Gravity Recovery and Climate Experiment (GRACE), The Ice, Cloud and Land Elevation Satellite (ICESat) and CHINARE observations over the Lambert Glacier/Amery Ice Shelf system (LAS). Estimation of the ICESat mass change rates benefitted from the density measurements along the CHINARE traverse and a spatial density adjustment method for reducing the effect of spatial density variations. In the high-elevation inland region, a positive trend was estimated from both ICESat and GRACE data, which is in line with the CHINARE accumulation measurements. In the coastal region, there were areas with high level accumulations in both ICESat and GRACE trend maps. In many high flow-speed glacier areas, negative mass change rates may be caused by dynamic ice flow discharges that have surpassed the snow accumulation. Overall, the mass change rate estimate in the LAS of 2004–2008 from the GRACE, ICESat and CHINARE data is 5.41 ± 4.59 Gt a−1, indicating a balanced to slightly positive mass trend. Along with other published results, this suggests that a longer-term positive mass trend in the LAS may have slowed in recent years.

This paper presents an integrated approach to landslide research based on remote sensing and sensor networks. This approach is composed of three important parts: (i) landslide susceptibility mapping using remote-sensing techniques for susceptible determination of landslide spots; (ii) scaled-down landslide simulation experiments for validation of sensor network for landslide monitoring, and (iii) in situ sensor network deployment for intensified landslide monitoring. The study site is the Taziping landslide located in Hongkou Town (Sichuan, China). The landslide features generated by landslides triggered by the 2008 Wenchuan Earthquake were first extracted by means of object-oriented methods from the remote-sensing images before and after the landslides events. On the basis of correlations derived between spatial distribution of landslides and control factors, the landslide susceptibility mapping was carried out using the Artificial Neural Network (ANN) technique. Then the Taziping landslide, located in the above mentioned study area, was taken as an example to design and implement a scaled-down landslide simulation platform in Tongji University (Shanghai, China). The landslide monitoring sensors were carefully investigated and deployed for rainfall induced landslide simulation experiments. Finally, outcomes from the simulation experiments were adopted and employed to design the future in situ sensor network in Taziping landslide site where the sensor deployment is being implemented.

Early detection and early warning are of great importance in giant landslide monitoring because of the unexpectedness and concealed nature of large-scale landslides. In China, the western mountainous areas are prone to landslides and feature many giant complex landslides, especially following the Wenchuan Earthquake in 2008. This work concentrates on a new technique, known as the “hybrid-SAR technique”, that combines both phase-based and amplitude-based methods to detect and monitor large-scale landslides in Li County, Sichuan Province, southwestern China. This work aims to develop a robust methodological approach to promptly identify diverse landslides with different deformation magnitudes, sliding modes and slope geometries, even when the available satellite data are limited. The phase-based and amplitude-based techniques are used to obtain the landslide displacements from six TerraSAR-X Stripmap descending scenes acquired from November 2014 to March 2015. Furthermore, the application circumstances and influence factors of hybrid-SAR are evaluated according to four aspects: (1) quality of terrain visibility to the radar sensor; (2) landslide deformation magnitude and different sliding mode; (3) impact of dense vegetation cover; and (4) sliding direction sensitivity. The results achieved from hybrid-SAR are consistent with in situ measurements. This new hybrid-SAR technique for complex giant landslide research successfully identified representative movement areas, e.g., an extremely slow earthflow and a creeping region with a displacement rate of 1 cm per month and a typical rotational slide with a displacement rate of 2–3 cm per month downwards and towards the riverbank. Hybrid-SAR allows for a comprehensive and preliminary identification of areas with significant movement and provides reliable data support for the forecasting and monitoring of landslides.

There is a need to accurately link the water level to the shoreline vertical datum for various applications including coastal management, lake/river/estuary/wetland hydrological or storm surge modeling/forecasting. Coastal topography is historically surveyed and referenced to the predetermined vertical datum in terms of orthometric heights, or the heights above the geoid, which is poorly known in terms of accuracy and lack of adequate spatial resolution for coastal applications such as estuary or storm surge modeling. We demonstrate an accurate linking of the lake surface to a shoreline datum using satellite techniques, including GPS buoy and satellite altimetry, water level gauges, and local geoid and lake circulation models. The possible error sources are analyzed and an error budget is reported in this study. An innovated method to estimate geoid height near the water level gauge using a GPS buoy is proposed. It is found that at a 95% confidence interval, the method is consistent with the National Geodetic Survey GEOID03 geoid model. The lake surface represented using a lake circulation model provided by the Great Lakes Forecasting Systems is also verified with kriging based on the data (1999 - 2001) from the water level gauge, and TOPEX/POSEIDON altimeter. Mean discrepancies of 2.7 and 7.2 cm are found with the data from the gauges around Lake Erie, and from the combination of the gauges and the altimeter, respectively. It reveals that the current dominant limitation of more accurate linking of water surface to shoreline is the insufficient knowledge of geoid in the current models. Further improvement is feasible through more accurate and higher resolution modeling of the lake geoid.