Search Results (87)

Ubiquitous and accelerating mass loss from the Greenland Ice Sheet (GrIS) has been widely reported in recent scientific studies, implying rapid changes in the Arctic cryosphere. However, while numerous studies provide accounts of glacial mass loss and consequent sea level change, a qualitative assessment of the implications is conspicuously absent. This scoping review addresses that gap by synthesizing the recent scientific literature related to cryospheric change in Greenland and its implications for key species and ecological processes; and highlights the necessity of understanding the bigger picture of how multiple ecological processes, abiotic-biotic assemblages, and cryosphere-human interactions with the environment are rapidly changing and pushing the Arctic into a possible no-analog scenario in recent geological times. It is also argued that this situation presents a novel challenge for planetary sustainability and warrants the identification of new research priorities that can generate a holistic understanding of the complexity of the Arctic cryosphere, interactions between biotic and abiotic components, and local lifeworlds—all of which are related to the well-being of the Earth itself. Full article

As global temperatures rise, the Greenland ice sheet (GrIS) is undergoing accelerating mass loss, with significant implications for sea level rise and climate systems. Using GRACE and GRACE Follow-On (GRACE-FO) RL06 data from April 2002 to May 2023, alongside MARv3.14 regional climate model outputs (ice melting, runoff, rainfall, snowfall, and land surface temperature (LST)), we investigated the drivers of GrIS mass changes. Continuous wavelet transform analysis revealed significant annual signals in all variables except snowfall, with wavelet decomposition showing the largest annual amplitudes for ice melting (58.8 Gt/month) and runoff (44.5 Gt/month), surpassing those of GRACE/GRACE-FO (31.1 Gt/month). Cross-correlation analysis identified ice melting, runoff, rainfall, snowfall, and LST as significantly correlated with GrIS mass changes, with ice melting, runoff, and LST emerging as primary drivers, while snowfall and runoff exerted secondary influences. Temporal lags of 3, 4, 4, 7, and 4 months were observed for ice melting, runoff, rainfall, snowfall, and LST, respectively. These findings highlight the complex interplay of climatic and hydrological processes driving GrIS mass loss. Full article

Supraglacial melt-lakes form and evolve along the western edge of the Greenland Ice Sheet and have proven to play a significant role in ice sheet surface hydrology and mass balance. Prior methods to quantify melt-lake volume have relied upon Landsat-8 optical imagery, available at 30 m spatial resolution but with temporal resolution limited by satellite overpass times and cloud cover. We propose two novel methods to quantify the volume of meltwater stored in these lakes, including a high-resolution surface DEM (ArcticDEM) and an ablation model using daily averaged automated weather station data. We compare our methods to the depth-reflectance method for five supraglacial melt-lakes during the 2021 summer melt season. We find agreement between the depth-reflectance and DEM lake infilling methods, within +/−15% for most cases, but our ablation model underproduces by 0.5–2 orders of magnitude the volumetric melt needed to match our other methods, and with a significant lag in meltwater onset for routing into the lake basin. Further information regarding energy balance parameters, including insolation and liquid precipitation amounts, is needed for adequate ablation modelling. Despite the differences in melt-lake volume estimates, our approach in combining remote sensing and meteorological methods provides a framework for analysis of seasonal melt-lake evolution at significantly higher spatial and temporal scales, to understand the drivers of meltwater production and its influence on the spatial distribution and extent of meltwater volume stored on the ice sheet surface. Full article

The work presented here marks a further advance in expert uncertainty quantification. In a recent probabilistic evaluation of ice sheet process contributions to sea level rise, tail dependence was elicited and propagated through an uncertainty analysis for the first time. The elicited correlations and tail dependencies concerned pairings of three processes: Accumulation, Discharge and Run-off, which operate on major ice sheets in the West and East Antarctic and in Greenland. The elicitation enumerated dependencies between these processes under selected global temperature change scenarios over different future time horizons. These expert judgments allowed us to populate a Paired Copula Bayesian network model to obtain the estimated contributions of these ice sheets for future sea level rise. Including positive central tendency dependence and tail dependence increases the fatness of the upper tails of projected sea level rise distributions, an amplification important for designing and evaluating possible mitigation strategies. Detailing and jointly computing distributional dependencies and tail dependencies can be crucial components of good practice for assessing the influence of uncertainties on extreme values when modelling stochastic multifactorial processes. Full article

The Earth has cooled since the early Pliocene, which was punctuated by accelerated cooling indicative of thresholds. I posit that the cooling was initiated when the Neogene uplift of the Tibetan highland caused it to ice over, augmenting the albedo. I formulate a minimal warm/cold/Arctic box model to test this hypothesis and prognose the Pliocene climate. In particular, based on model physics, I discern three thermal thresholds as Pliocene cools: (1) when the Arctic temperature falls below the marking temperature of the ice front, the East Greenland ice sheet would descend to the sea level and calve into the Nordic Seas; (2) when the Arctic temperature cools to the freezing point, the ice sheet would form and expand over circum-Arctic lowlands to cause a massive deposition of ice-rafted debris marking Northern Hemisphere glaciation (NHG); (3) when glacial state persists through low eccentricity, it would cause a transition from obliquity- to eccentricity-dominated glacial cycles. Aligning these thresholds with the observed ones around 3.5, 2.7, and 1 million years ago, the model produces a temporal evolution of the Pliocene temperature as well as its driving albedo change. Since the latter can be accommodated by the observed one, it supports the Neogene uplift as the tectonic origin of NHG. Full article

The occurrence of Supraglacial Lakes (SGLs) may influence the signals acquired with microwave radiometers, which may result in a degree of uncertainty when employing microwave radiometer data for the detection of surface melt. Accurate monitoring of surface melting requires a reasonable assessment of this uncertainty. However, there is a scarcity of research in this field. Therefore, in this study, we computed surface melt in the vicinity of Automatic Weather Stations (AWSs) by employing Defense Meteorological Satellite Program (DMSP) Ka-band data and Soil Moisture and Ocean Salinity (SMOS) satellite L-band data and extracted SGL pixels by utilizing Sentinel-2 data. A comparison between surface melt results derived from AWS air temperature estimates and those obtained with remote sensing inversion in the two different bands was conducted for sites below the mean snowline elevation during the summers of 2016 to 2020. Compared with sites with no SGLs, the commission error (CO) of DMSP morning and evening data at sites where these water bodies were present increased by 36% and 30%, respectively, and the number of days with CO increased by 12 and 3 days, respectively. The omission error (OM) of SMOS morning and evening data increased by 33% and 32%, respectively, and the number of days with OM increased by 17 and 21 days, respectively. Identifying the source of error is a prerequisite for the improvement of surface melt algorithms, for which this study provides a basis. Full article

The melting of the Greenland ice sheet (GrIS) in summer has rapidly and significantly increased in recent decades, especially for the northern GrIS. Circulation related to GrIS melting is important for understanding the contribution of the GrIS to the global sea level. In this paper, we used the SOM method to obtain three spatial patterns of GrIS melting based on model output data: overall melting, northern melting, and southern melting patterns. We also examined their linkages to the observed atmospheric circulation. GrIS melting is primarily related to Greenland blocking (GB), while different types of GB are responsible for different melting patterns. The overall and northern melting patterns are both associated with high-latitude GB, which is associated with the decay and westward movement of mid-latitude and high-latitude European blocking (EB), respectively. It is found that the generation of mid-latitude and high-latitude EBs are related to mid-latitude eastern North Atlantic warming and Greenland–Norskehavet–North Sea warming, respectively, while the movement of EB is related t upstream weakened zonal wind anomalies. Furthermore, the southern melting pattern is linked to mid-latitude GB, which is associated with the wave train from the East Pacific to Southern Greenland through North America and further related to the mid-latitude of East Pacific warming. Full article

Change of supraglacial lakes (SGLs) is an important hydrological activity on the Greenland ice sheet (GrIS), and storage and drainage of SGLs occur throughout the year. However, current studies tend to split SGL changes into melt/non-melt seasons, ignoring the effect of buried lakes in the exploration of drainage, and the existing threshold-based approach to SGL extraction in a synthetic aperture radar (SAR) is influenced by the choice of the study area mask. In this study, a new method (Otsu–Canny–Otsu (OCO)), which accesses the features of SGLs on optical and SAR images objectively, is proposed for full-year SGL extraction with Google Earth Engine (GEE). The SGLs on the Petermann Glacier were monitored well by OCO throughout 2021, including buried lakes and more detailed rapid drainage events. Some SGLs’ extent varied minimally in a year (area varying by 10–25%) while some had very rapid drainage (a rapid drainage event from July 26 to 30). The SGL extraction results were influenced by factors such as the mode of polarization, the surface environment, and the depth of the lake. The OCO method can provide a more comprehensive analysis for SGL changes throughout the year. Full article

The offshore transport of Greenland coastal waters influenced by freshwater input from ice sheet melting during summer plays an important role in ocean circulation and biological processes in the Labrador Sea. Many previous studies over the last decade have investigated shelfbreak transport processes in the region, primarily using ocean model simulations. Here, we use 27 years of surface geostrophic velocity observations from satellite altimetry, modified to include Ekman dynamics based on atmospheric reanalysis, and virtual particle releases to investigate seasonal and interannual variability in transport of coastal water in the Labrador Sea. Two sets of tracking experiments were pursued, one using geostrophic velocities only, and another using total velocities including the wind effect. Our analysis revealed substantial seasonal variability, even when only geostrophic velocities were considered. Water from coastal southwest Greenland is generally transported northward into Baffin Bay, although westward transport off the west Greenland shelf increases in fall and winter due to winds. Westward offshore transport is increased for water from southeast Greenland so that, in some years, water originating near the east Greenland coast during summer can be transported into the central Labrador Sea and the convection region. When wind forcing is considered, long-term trends suggest decreasing transport of Greenland coastal water during the melting season toward Baffin Bay, and increasing transport into the interior of the Labrador Sea for water originating from southeast Greenland during summer, where it could potentially influence water column stability. Future studies using higher-resolution velocity observations are needed to capture the role of submesoscale variability in transport pathways in the Labrador Sea. Full article

We present an attempt to estimate the long-term changes in Relative Sea Level (RSL), in addition to the different factors contributing to such trends on a local and regional scale, using a statistical linear model. The time series analysis corresponded to 17 tide-gauges, grouped in three different areas: the northern and western Atlantic coasts of the Iberian Peninsula, the Canary Islands, and the southern and eastern coasts of the Iberian Peninsula and Balearic Islands. The analysis was performed for two periods: 1948–2019, using tide-gauge data; and 1993–2019, using both tide-gauge and altimetry data for comparison. The trends for the period 1948–2019 ranged between 1.09 ± 0.14 (Canary Islands) and 2.05 ± 0.21 mm/yr for the northern and western Atlantic Iberian Peninsula. Altimetry data during the period 1993–2019 yielded quite homogeneous results for all the locations and regions, ranging between 2.7 ± 0.4 and 3.0 ± 0.3 mm/yr. In contrast, the results obtained from tide-gauge data for this recent period showed a large dispersion, very likely due to local effects, or perhaps even to levelling or instrumental errors. Nevertheless, when the results were averaged for each area, the observed trends were comparable to the altimetry results, with values of 2.3 ± 0.8, 2.7 ± 0.5, and 2.8 ± 0.8 mm/yr for the three regions of study. A stepwise forward linear regression was used to relate the observed RSL variability to the atmospheric forcing and the thermosteric and halosteric components of the sea level. Surprisingly, the thermosteric and halosteric contributions were not significantly correlated to the observed RSL in many cases; consequently, the steric, the total addition of mass, the mass of salt, and the freshwater contributions to the observed sea level trends could not be reliably estimated. This result seems to have been the consequence of the scarcity of temperature and salinity data; this hypothesis was confirmed, with the exception of the tide-gauge data for L’Estartit. This location is close to a well sampled region. In this case, the atmospheric variables and the thermosteric and halosteric terms accounted for 80% of the observed RSL variance, and the contributions of these terms could be estimated. The freshwater contribution for this location was between 1.3 and 1.4 mm/yr, consistent with recent estimations of the contributions of glaciers and Greenland and Antarctica Ice Sheets. These results highlight the importance of monitoring programs and routine sampling for the determination of the different factors contributing to the sea level variability. Full article

Geothermal heat flow is key to unraveling several large-scale geophysical systems, including the inner workings of the Greenlandic ice sheet, and by extension, the possibility of understanding the past and prior global climate. Similarly, it could provide insight into the paleo-trace of the Icelandic mantle plume, which in turn is integral in answering long-standing questions on the origin of mountains in western and eastern Greenland and in Norway. This study documents the results from an intra-scientific field approach, which combines geological, petrophysical, and satellite magnetic field data in a nonlinear probabilistic inversion. These results include Curie depths with associated uncertainties and Geothermal Heat Flux estimates. While baselines remain challenging to evaluate due to the strong nonlinearity of the problem posed, stress testing reveals a high robustness of the predicted spatial variations, which largely disagree with the classic straightforward northwest–southeast or east–west plume trace across Greenland. Instead, our results indicate a complex heat flux pattern, including a localized region with anomalously heightened heat flux near the origin of the Northeast Greenland Ice Stream. Full article

Accurate monitoring of surface temperature and melting on the Greenland Ice Sheet (GrIS) is important for tracking the ice sheet’s mass balance as well as global and Arctic climate change. Using a moderate-resolution-imaging-spectroradiometer (MODIS)-derived land-surface-temperature (LST) data product with a resolution of 1 km from 2000 to 2020, the temporal and spatial variations of annual and seasonal ‘clear-sky’ surface temperature were evaluated. We also monitored summer surface melting and studied the relationship between the mass balance of the ice sheet and changes in surface temperature and melting. The results show that the mean annual LST during the study period is −24.86 ± 5.46 °C, with the highest of −22.48 ± 5.61 °C in 2010 and the lowest temperature of −26.49 ± 5.30 °C in 2015. With the change of season, the spatial variation of the ice-sheet surface temperature changes greatly. 2012 and 2019 experienced the warmest summers (−5.92 ± 4.01 °C and −6.51 ± 3.93 °C), with extreme cumulative melting detected on the ice-sheet surface (89.9% and 89.7%, respectively), and 2002 also experienced a greater extent of melting. But short period of melt in 2002 and 2019 (30.6% and 31.4%, respectively), accounted for a larger proportion, with neither the duration nor intensity of the melt reaching that of 2012. There is a strong correlation between the GrIS surface temperature and its mass balance. By fitting the relationship between surface temperature and mass balance, it was found that 93.83% (6.17%) of the ice-sheet response to surface-temperature change was via surface-mass balance (discharge and basal-mass balance). Full article

Coastal waters off west Greenland are strongly influenced by the input of low salinity water from the Arctic and from meltwater from the Greenland Ice Sheet. Changes in freshwater content in the region can play an important role in stratification, circulation, and primary production; however, investigating salinity variability in the region is challenging because in situ observations are sparse. Here, we used satellite observations of sea surface salinity (SSS) from the Soil Moisture and Ocean Salinity mission produced by LOCEAN and by the Barcelona Expert Center (SMOS LOCEAN and SMOS BEC) and from the Soil Moisture Active Passive mission produced by the Jet Propulsion Laboratory (SMAP JPL) as well as by Remote Sensing Systems (SMAP RSS) to investigate how variability in a narrow coastal band off west Greenland is captured by these different products. Our analyses revealed that the various satellite SSS products capture the seasonal freshening off west Greenland from late spring to early fall. The magnitudes of the freshening and of coastal salinity gradients vary between the products however, being attenuated compared to historical in situ observations in most cases. The seasonal freshening off southwest Greenland is intensified in SMAP JPL and SMOS LOCEAN near the mouth of fjords characterized by large inputs of meltwater near the surface, which suggests an influence of meltwater from the Greenland Ice Sheet. Synoptic observations from 2012 following large ice sheet melting revealed good agreement with the spatial scale of freshening observed with in situ and SMOS LOCEAN data. Our analyses indicate that satellite SSS can capture the influence of meltwater input and associated freshwater plumes off coastal west Greenland, but those representations differ between products. Full article

In 1912, a Swiss expedition led by meteorologist Alfred de Quervain crossed the Greenland ice sheet on a route from Disko Bay to Tasiilaq. Based on that, in 2002, a series of geodetic expeditions carried out by W. Korth and later by T. Hitziger began along the same traverse as in 1912, with the last measurements taken in May 2021. The statically collected GPS/GNSS data provide very accurate elevation changes at 36 points along the almost 700 km long crossing over a period of 19 years. According to this, there is a maximum increase of 2.1 m in the central area and a decrease of up to 38.7 m towards the coasts (influence Ilulissat Isbræ). By using kinematic GNSS measurements, there is a very dense profile with a spacing of a few meters. The comparison of those measurements is performed using crossing points or minimum distances and gives equivalent results for both methods. It is shown that local ice topography is preserved, and thus gaps in data sets can be caught. Areas of accumulation and ablation on the ice sheet can be identified, showing the widespread influence of outlet glaciers up to 200 km. The data can be used for direct verification of altimetry data, such as IceSat. Both IceSat elevations and their changes can be compared. Full article

High spatial and temporal resolution products of near-surface air temperature (T2m) over the Greenland Ice Sheet (GrIS) are required as baseline information in a variety of research disciplines. Due to the sparse network of in situ data on the GrIS, remote sensing data and machine learning methods provide great advantages, due to their capacity and accessibility. The Land Surface Temperature (LST) at 780 m resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) and T2m observation from 25 Automatic Weather Stations (AWSs) are used to establish a relationship over the GrIS by comparing multiple machine learning approaches. Four machine learning methods—neural network (NN), gaussian process regression (GPR), support vector machine (SVM), and random forest (RF)—are used to reconstruct the T2m at daily and monthly scales. We develop a reliable T2m reconstruction model based on key meteorological parameters, such as albedo, wind speed, and specific humidity. The reconstructions daily and monthly products are generated on a 780 m × 780 m spatial grid spanning from 2007 to 2019. When compared with in situ observations, the NN method presents the highest accuracy, with R of 0.96, RMSE of 2.67 °C, and BIAS of −0.36 °C. Similar to the regional climate model (RACMO2.3p2), the reconstructed T2m can better reflect the spatial pattern in term of latitude, longitude, and altitude effects. Full article