Temporal Detail Research Articles

The ecology of chronic wasting disease in wildlife.

Prions are misfolded infectious proteins responsible for a group of fatal neurodegenerative diseases termed transmissible spongiform encephalopathy or prion diseases. Chronic Wasting Disease (CWD) is the prion disease with the highest spillover potential, affecting at least seven Cervidae (deer) species. The zoonotic potential of CWD is inconclusive and cannot be ruled out. A risk of infection for other domestic and wildlife species is also plausible. Here, we review the current status of the knowledge with respect to CWD ecology in wildlife. Our current understanding of the geographic distribution of CWD lacks spatial and temporal detail, does not consider the biogeography of infectious diseases, and is largely biased by sampling based on hunters' cooperation and funding available for each region. Limitations of the methods used for data collection suggest that the extent and prevalence of CWD in wildlife is underestimated. If the zoonotic potential of CWD is confirmed in the short term, as suggested by recent results obtained in experimental animal models, there will be limited accurate epidemiological data to inform public health. Research gaps in CWD prion ecology include the need to identify specific biological characteristics of potential CWD reservoir species that better explain susceptibility to spillover, landscape and climate configurations that are suitable for CWD transmission, and the magnitude of sampling bias in our current understanding of CWD distribution and risk. Addressing these research gaps will help anticipate novel areas and species where CWD spillover is expected, which will inform control strategies. From an ecological perspective, control strategies could include assessing restoration of natural predators of CWD reservoirs, ultrasensitive CWD detection in biotic and abiotic reservoirs, and deer density and landscape modification to reduce CWD spread and prevalence.

Improving consistency among models of overlapping scope in multi-sector studies: The case of electricity capacity expansion scenarios

Multi-decadal scenarios produced by modeling studies are used to study the evolution of key infrastructure that cuts across energy, water, and land systems. Scenarios produced by different models contain inconsistencies due to disparate model structures and assumptions. Although inconsistencies can characterize structural uncertainties, they could have important consequences in various contexts such as multi-sector energy-water-land studies that couple multiple models. In such studies, it is important for models with overlapping scope (models having different sectoral, regional, temporal, and process details but producing scenarios for some common output variable(s)) to produce consistent scenarios of common output variable(s) to minimize propagation of inconsistent information. Using the example of baseline electricity capacity expansion scenarios produced by two models with overlapping scope, we explore cross-model scenario consistency (extent to which projections for a common scenario variable(s) diverge). We define a quantitative metric of consistency and examine the sensitivity of consistency of the models’ electricity generation by technology outputs to changes in harmonization of assumptions surrounding the representations of key capacity expansion drivers such as fuel prices, renewable resources, demand, and retirements. Our study establishes a framework to systematically examine scenario consistency. In addition, our study utilizes complementary features of well-established models to produce consistent baseline electricity capacity expansion scenarios which can then be used in multi-sector studies.

Spatial text processing: are estimates of time and distance influenced by the age of characters and readers?

It is widely accepted that, while hearing or reading a story, people continuously form and update mental representations of the characters, places and events being described, based on plausible spatial, temporal or intentional details. According to the embodied cognition approach, the mental representations that accompany text reading are grounded in each reader's own sensorimotor experiences. Two experiments were conducted to examine whether readers' estimates of time and distance are influenced by age, their own and that of the character being described. In Experiment 1, 182 young adults read the description of a route in a town being covered by a young or an elderly character. In Experiment 2, the same descriptions as in Experiment 1 were read by 121 young adults and 53 older people. To avoid a possible confound, a follow-up to Experiment 1 (Experiment 1a) repeated the study by removing from texts the adverbs describing the walking speed of characters. In all experiments, participants were asked to estimate: (a) the time the characters took to reach their destinations (time estimation task); and (b) the distance they covered (distance estimation task). The results showed that both characters' and readers' ages influenced the time estimated, whereas no effects were found on estimates of distance: the elderly character was estimated to take longer than the young character (Experiments 1, 1a and 2), and older readers estimated longer times than younger readers (Experiment 2). This prompts the conclusion that personal features of both the readers and the characters they read about were used to infer the temporal dimension of situations described in the narratives. The theoretical implications of the findings are discussed.

Towards A Taxonomy of Uncertainties: Analysing Sources of Spatio-Temporal Uncertainty on the Example of Non-Standard German Corpora

Different types of uncertainties occur in almost all datasets and are an inherent property of data across different academic disciplines, including digital humanities (DH). In this paper, we address, demonstrate and analyse spatio-temporal uncertainties in a non-standard German legacy dataset in a DH context. Although the data collection is primarily a linguistic resource, it contains a wealth of additional, comprehensive information, such as location and temporal detail. The addressed uncertainties have manifested because of a variety of reasons, and partly also because of decades of data transformation processes. We here propose our own taxonomy for capturing and classifying the various uncertainties, and show with numerous examples how the remedying but also re-introduction of uncertainties affects DH practices.

The current weather and climate of Mars: 12 years of atmospheric monitoring by the Planetary Fourier Spectrometer on Mars Express

We used thermal-infrared spectra returned by the Mars Express Planetary Fourier Spectrometer (PFS/MEx) to retrieve atmospheric temperature profiles, surface temperatures, and column-integrated optical depths of dust and water ice. More than 2,500,000 spectra were processed to build this new atmospheric dataset, covering the full range of season, latitude, longitude, and local time. The data presented here span more than six Martian Years (from MY 26, Ls = 331°, 10 January 2004 to MY 33, Ls = 78°, 6 December 2015). We present an overview of the seasonal and latitudinal dependence of the above atmospheric quantities for the relevant period, as well as an assessment of the interannual variability in the current Martian climate. The general effect of suspended dust on atmospheric temperatures observed during the global dust storm of MY 28 is also presented. Atmospheric temperatures and aerosol opacity were successfully retrieved over cold surface areas and in the polar regions, including the polar nights. Rather than the aphelion cloud belt, the most prominent feature one can observe in the climatology of the Martian water ice clouds is the seasonal extent, pattern and thickness of the North polar hoods (NPH), where most of the thickest clouds are observed. The NPH also shows peculiar features, observed in detail here for the first time, with characteristic spatial and seasonal patterns that repeat very similarly every Martian year. By exploiting PFS/MEx capability to perform observations at different local times (LT), this dataset allowed the characterization of how dust and ice cloud optical depths vary throughout the day on Mars. We present observations of the dust daily cycle during non-dusty seasons; the daily variation of water ice opacity in the aphelion cloud belt; and the diurnal variation of the North and South polar hoods. With unprecedented spatial and temporal coverage and details revealed, this dataset offers new challenges to the Martian global circulation models and, at the same time, a new reference for the MYs complementary to those observed by previous orbiters.

A new dense 18-year time series of surface water fraction estimates from MODIS for the Mediterranean region

Abstract. Detailed knowledge on surface water distribution and its changes is of high importance for water management and biodiversity conservation. Landsat-based assessments of surface water, such as the Global Surface Water (GSW) dataset developed by the European Commission Joint Research Centre (JRC), may not capture important changes in surface water during months with considerable cloud cover. This results in large temporal gaps in the Landsat record that prevent the accurate assessment of surface water dynamics. Here we show that the frequent global acquisitions by the Moderate Resolution Imaging Spectrometer (MODIS) sensors can compensate for this shortcoming, and in addition allow for the examination of surface water changes at fine temporal resolution. To account for water bodies smaller than a MODIS cell, we developed a global rule-based regression model for estimating the surface water fraction from a 500 m nadir reflectance product from MODIS (MCD43A4). The model was trained and evaluated with the GSW monthly water history dataset. A high estimation accuracy (R2=0.91, RMSE =11.41 %, and MAE =6.39 %) was achieved. We then applied the algorithm to 18 years of MODIS data (2000–2017) to generate a time series of surface water fraction maps at an 8 d interval for the Mediterranean. From these maps we derived metrics including the mean annual maximum, the standard deviation, and the seasonality of surface water. The dynamic surface water extent estimates from MODIS were compared with the results from GSW and water level data measured in situ or by satellite altimetry, yielding similar temporal patterns. Our dataset complements surface water products at a fine spatial resolution by adding more temporal detail, which permits the effective monitoring and assessment of the seasonal, inter-annual, and long-term variability of water resources, inclusive of small water bodies.

Filling the gap between plot and landscape scale – eight years of soil erosion monitoring in 14 adjacent watersheds under soil conservation at Scheyern, Southern Germany

Abstract. Watershed studies are essential for erosion research because they embed real agricultural practices, heterogeneity along the flow path, and realistic field sizes and layouts. An extensive literature review covering publications from 1970 to 2018 identified a prominent lack of studies, which (i) observed watersheds that are small enough to address runoff and soil delivery of individual land uses, (ii) were considerably smaller than erosive rain cells (<400 ha), (iii) accounted for the episodic nature of erosive rainfall and soil conditions by sufficiently long monitoring time series, (iv) accounted for the topographic, pedological, agricultural and meteorological variability by measuring at high spatial and temporal resolution, (v) combined many watersheds to allow comparisons, and (vi) were made available. Here we provide such a dataset comprising 8 years of comprehensive soil erosion monitoring (e.g. agricultural management, rainfall, runoff, sediment delivery). The dataset covers 14 adjoining and partly nested watersheds (sizes 0.8 to 13.7 ha), which were cultivated following integrated (four crops) and organic farming (seven crops and grassland) practices. Drivers of soil loss and runoff in all watersheds were determined with high spatial and temporal detail (e.g., soil properties are available for 156 m2 blocks, rain data with 1 min resolution, agricultural practices and soil cover with daily resolution). The long-term runoff and especially the sediment delivery data underline the dynamic and episodic nature of associated processes, controlled by highly dynamic spatial and temporal field conditions (soil properties, management, vegetation cover). On average, the largest 10 % of events lead to 85.4 % sediment delivery for all monitored watersheds. The analysis of the Scheyern dataset clearly demonstrates the distinct need for long-term monitoring in runoff and erosion studies.

Distinct Patterns of Hippocampal and Neocortical Evolution in Primates

Because of the central role of the hippocampus in representing spatial and temporal details of experience, comparative studies of its volume and structure are relevant to understanding the evolution of representational memory across species. The hippocampal formation, however, is organized into separate anatomical subregions with distinct functions, and little is known about the evolutionary diversification of these subregions. We investigate relative volumetric changes in hippocampal subregions across a large sample of primate species. We then compare the evolution of the hippocampal formation to the neocortex. Results across hippocampal subregions indicate that, compared to strepsirrhines, the anthropoid lineage displays a decrease in relative CA3, fascia dentata, subiculum, and rhinal cortex volume in tandem with an increase in relative neocortical volume. These findings indicate that hippocampal function in anthropoids might be substantially augmented by the executive decision-making functions of the neocortex. Humans are found to have a unique cerebral organization combining increased relative CA3, subiculum, and rhinal cortex with increased relative neocortical volumes, suggesting that these regions may play a role in behaviors that are uniquely specialized in humans.

A climatological assessment of balancing effects and shortfall risks of photovoltaics and wind energy in Germany and Europe

Abstract. With an increased share of solar and wind energy e.g. in the German and European energy systems it is becoming increasingly important to analyze the impact of weather variability on the reliability of the energy production. In this study, we calculate solar PV and wind power capacity factors using two recently developed climatological datasets that provide information with high spatial and temporal details on the continental (European) scale and are of sufficient length for assessments at climatological time scales: Surface radiation derived from meteorological satellites (SARAH-2) and wind speed from a high-resolution regional reanalysis (COSMO-REA6). Balancing effects are analysed: On average, the seasonal cycles of PV and wind power production complement each other in Germany as well as in Europe. The frequency of events with a risk of low electricity generation is analyzed under different assumptions. When using wind energy over German land areas as a reference case, the results illustrate that the number of low production events is reduced when Germany's Exclusive Economic Zone is included into the analysis, or when a combined system of PV and wind energy is considered. A European-wide analysis also leads to a distinct reduction of such events.

The irregular breathing effect on target volume and coverage for lung stereotactic body radiotherapy.

The major challenge in treating a mobile target is obtaining the temporal and spatial information imaging and treatment details. This phantom study quantitatively evaluates the geometric and dosimetric effects of various treatment techniques under different respiratory patterns. The regular motion model was a sinusoidal waveform with a longitudinal range of ±1.5 cm and a period of 4 sec, while irregular motion models were generated by extracting signals from clinical cases. Helical CT for a static target and 4D CT with retrospective sorting were acquired. Phase bin, maximum, and average intensity projection (MIP and AIP) CT datasets were reconstructed. RapidArc and IMRT plans were generated on static and moving target CT datasets with different motion patterns using the phase‐based gating and nongating treatment. Dose measurements were performed using EBT3 films. Dose profile and gamma analysis (±3%/1 mm criteria) were used for dose comparisons. For the irregular motions, internal target volume variations between AIP and MIP datasets (AIP/MIP) had slight differences (−6.2% to −7.7%) for gated plans, and larger differences (−12.3% to −15.2%) for nongated plans. Dosimetric measurements showed a high gamma passing rate (>98.5%) for the static plan in the target region, while the AIP and MIP gated plans had average passing rates of 92.2% ± 5.7% and 85.8% ± 9.5%, respectively. Nongated plans had significantly lower and deviated passing rates, while the AIP and MIP plans had passing rates of 43.6% ± 22.2% and 66.7% ± 28.2%, respectively (p < 0.05). Lung stereotactic body radiotherapy treatment delivered with the gated technique did not compromise the gross tumor volumes coverage, and was insensitive to the breathing irregularities and plan techniques. Adequate margins should be accounted to cover the mis‐gating effect when using the phase‐based gating under irregular motion.

Increase the frame rate of a camera via temporal ghost imaging

Computational temporal ghost imaging (CTGI) allows the reconstruction of a fast signal from a two dimensional (2D) detection with no temporal resolution. High speed spatial modulation is implemented to encode temporal detail of the signal into the 2D detection. By calculating the correlation between the modulation and the rendered image, the temporal information can be retrieved. CTGI indicates a way to detect high speed non-reproducible signal from a slow detector. Based on CTGI, we propose an innovative scheme that can increase the frame rate of a camera by resolving the temporal detail of every camera image. To achieve this, CTGI is conducted parallelly to different areas of the scene. High speed spatial multiplexed modulation is performed, constraining the continuous scene into a series of short-time-scale frames. All the modulated frames are accumulated into one image that is eventually used in the correlation retrieval process. By performing CTGI reconstruction on each area independently, the temporal detail of the whole scene can be obtained. This method can have a strong application in ultrafast imaging.

Correcting Bias in Crowdsourced Data to Map Bicycle Ridership of All Bicyclists

Traditional methods of counting bicyclists are resource-intensive and generate data with sparse spatial and temporal detail. Previous research suggests big data from crowdsourced fitness apps offer a new source of bicycling data with high spatial and temporal resolution. However, crowdsourced bicycling data are biased as they oversample recreational riders. Our goals are to quantify geographical variables, which can help in correcting bias in crowdsourced, data and to develop a generalized method to correct bias in big crowdsourced data on bicycle ridership in different settings in order to generate maps for cities representative of all bicyclists at a street-level spatial resolution. We used street-level ridership data for 2016 from a crowdsourced fitness app (Strava), geographical covariate data, and official counts from 44 locations across Maricopa County, Arizona, USA (training data); and 60 locations from the city of Tempe, within Maricopa (test data). First, we quantified the relationship between Strava and official ridership data volumes. Second, we used a multi-step approach with variable selection using LASSO followed by Poisson regression to integrate geographical covariates, Strava, and training data to correct bias. Finally, we predicted bias-corrected average annual daily bicyclist counts for Tempe and evaluated the model’s accuracy using the test data. We found a correlation between the annual ridership data from Strava and official counts (R2 = 0.76) in Maricopa County for 2016. The significant variables for correcting bias were: The proportion of white population, median household income, traffic speed, distance to residential areas, and distance to green spaces. The model could correct bias in crowdsourced data from Strava in Tempe with 86% of road segments being predicted within a margin of ±100 average annual bicyclists. Our results indicate that it is possible to map ridership for cities at the street-level by correcting bias in crowdsourced bicycle ridership data, with access to adequate data from official count programs and geographical covariates at a comparable spatial and temporal resolution.

HIGH-FREQUENCY 3D GEOMORPHIC OBSERVATION USING HOURLY TERRESTRIAL LASER SCANNING DATA OF A SANDY BEACH

Abstract. Geomorphic processes occur spatially variable and at varying magnitudes, frequencies and velocities, which poses a great challenge to current methods of topographic change analysis. For the quantification of surface change, permanent terrestrial laser scanning (TLS) can generate time series of 3D point clouds at high temporal and spatial resolution. We investigate how the temporal interval influences volume change observed on a sandy beach regarding the temporal detail of the change process and the total volume budget, on which accretion and erosion counteract. We use an hourly time series of TLS point clouds acquired over six weeks in Kijkduin, the Netherlands. A raster-based approach of elevation differencing provides the volume change over time per square meter. We compare the hourly analysis to results of a three- and six-week observation period. For the larger period, a volume increase of 0.3 m3/ m2 is missed on a forming sand bar before it disappears, which corresponds to half its volume. Generally, a strong relationship is shown between observation interval and observed volume change. An increase from weekly to daily observations leads to a five times larger volume change quantified in total. Another important finding is a temporally variable measurement uncertainty in the 3D time series, which follows the daily course of air temperature. Further experiments are required to fully understand the effect of atmospheric conditions on high-frequency TLS acquisition in beach environments. Continued research of 4D geospatial analysis methods will enable automatic identification of dynamic change and improve the understanding of geomorphic processes.

Global data and tools for local forest cover loss and REDD+ performance assessment: Accuracy, uncertainty, complementarity and impact

Assessing the performance of efforts to reduce emissions from deforestation and forest degradation (REDD+) requires data on forest cover change. Innovations in remote sensing and forest monitoring provide ever-increasing levels of coverage, spatial and temporal detail, and accuracy. More global products and advanced open-source algorithms are becoming available. Still, these datasets and tools are not always consistent or complementary, and their suitability for local REDD+ performance assessments remains unclear. These assessments should, ideally, be free of any confounding factors, but performance estimates are affected by data uncertainties in unknown ways. Here, we analyse (1) differences in accuracy between datasets of forest cover change; (2) if and how combinations of datasets can increase accuracy; and we demonstrate (3) the effect of (not) doing accuracy assessments for REDD+ performance measurements.Our study covers five local REDD+ initiatives in four countries across the tropics. We compared accuracies of a readily available global forest cover change dataset and a locally modifiable open-source break detection algorithm. We applied human interpretation validation tools using Landsat Time Series data and high-resolution optical imagery. Next, we assessed whether and how combining different datasets can increase accuracies using several combination strategies. Finally, we demonstrated the consequences of using the input datasets for REDD+ performance assessments with and without considering their accuracies and uncertainties.Estimating the amount of deforestation using validation samples could substantially reduce uncertainty in REDD+ performance assessments. We found that the accuracies of the various data sources differ at site level, although on average neither one of the input products consistently excelled in accuracy. Using a combination of both products as stratification for area estimation and validated with a sample of high-resolution data seems promising. In these combined products, the expected trade-offs in accuracies across change classes (before, after, no change) and across accuracy types (user’s and producer’s accuracy) were negligible, so their use is advantageous over single-source datasets. More locally calibrated wall-to-wall products should be developed to make them more useful and applicable for REDD+ purposes. The direction and degree of REDD+ performance remained statistically uncertain, as CIs were overlapping in most cases for the deforestation estimates before and after the start of the REDD+ interventions. Given these uncertainties and inaccuracies and to increase the credibility of REDD+ it is advised to (1) be conservative in REDD+ accounting, and (2) not to rely on results from single currently available global data sources or tools without sample-based validation if results-based payments are intended to be made on this basis.

Effects of negative emotion on neural correlates of item and source memory during encoding and retrieval

The enhancing effect of emotion on item memory is well-established, but emotion’s influence on source memory has proven more elusive. Previous studies recording event-related potentials (ERPs) associated with memory encoding (Dms) and retrieval (old/new effects) showed an emotional enhancement of ERPs related to item memory, whereas ERPs related to source memory yielded contradictory results in the presence of emotion. The present study examined the influence of item emotionality on the neural correlates of memory encoding and retrieval for items and temporal source details. Participants studied negative and neutral pictures in two temporally distinct blocks and, 24 h later, were asked to recognize the studied pictures and the blocks in which they appeared. Our results showed that negative items were more often remembered, with or without source information, than neutral images. This finding of an overall memory advantage for negative images was confirmed by the Dm effects, which demonstrated significant and indistinguishable Dms for negative images remembered with or without source. Overall, Dm effects were greater for negative as compared to neutral images. In contrast to the behavioral and Dm results, an emotional enhancement of the source-related old/new effect was seen over the left hemisphere, suggesting that only negative (and not neutral) images retrieved with correct source were accompanied by memory for additional details. These results suggest that retrieval of temporal source information is not enhanced for negative images but that item emotionality could lead to an enhancement for the retrieval of additional details, contingent on retrieval of temporal source information.

Les données de téléphonie mobile peuvent-elles améliorer la mesure du tourisme international en France ?

Since July 2015, the Banque de France and the French Ministry for the Economy and Finance have been experimenting with the use of mobile phone data to estimate the number and overnight stays of foreign visitors in France. The purpose of the experiment is to assess the ability of such data to eventually replace, in part or in whole, the traffic data by mode of transport currently used to establish the representativeness of foreign visitor surveys (Enquete aupres des visiteurs venant de l’etrangers or EVE). Mobile phone data have yet to be incorporated into the method used to count tourists. However, estimates based on mobile phone data have a number of benefits in terms of the time required to obtain data, the level of temporal and geographical detail and short-term trend monitoring. This ongoing trial illustrates the difficulty of exploiting original Big Data and demonstrates the importance of drawing on traditional survey data to improve the quality of estimates.

Estimer la population résidente à partir de données de téléphonie mobile, une première exploration

Many studies are focused on using data derived from mobile phones to construct statistical indicators. Mobile phone data have the advantage of providing information with both high spatial resolution and at high frequency, allowing applications such as measurements of the spatial or temporal details of population presence. Nonetheless, using mobile phone data to construct statistical indicators raises difficulties : data from a single operator are not representative of the whole population and they often lack socio-demographic detail, which limits their quality for many applications. This article is based on a database of mobile phone records from subscribers collected by a large French operator. It aims to offer a view on the potential, but also the problems posed by mobile phone data, specifically by illustrating how indicators of residential populations can or can not be estimated from them.

Influences of forested and grassland vegetation on late Quaternary ecosystem development as recorded in lacustrine sediments

AbstractGeosphere-biosphere interactions are ubiquitous features of the Earth surface, yet the development of interactions between newly exposed lithologic surfaces and colonizing plants during primary succession after glaciation are lacking temporal detail. To assess the nature, rate, and magnitude of vegetation influence on parent material and sediment delivery, we analyzed ecosystem and geochemical proxies from lacustrine sediment cores at a grassland site and a forested site in the northern United States. Over time, terrigenous inputs declined at both sites, with increasing amounts of organic inputs toward present. The similarities between sites were striking given that the grassland sequence began in the Early Holocene, and the forested sequence began after the last glacial maximum. Multiple mechanisms of chemical weathering, hydrologic transport, and changes in source material potentially contribute to this pattern. Although there were strong links between vegetation composition and nitrogen cycling at each site, it appears that changes in forest type, or from oak woodland to grassland, did not exert a large influence on elemental (K, Ti, Si, Ca, Fe, Mn, and S) abundance in the sedimentary sequences. Rather, other factors in the catchment-lake system determined the temporal sequence of elemental abundance.

Examination of the ecohydrological separation hypothesis in a humid subtropical area: Comparison of three methods

The ecohydrological separation between soil water sources for plant water uptake and groundwater recharge has been recently examined in various climate zones primarily based on isotopic composition of water. The existence of the ecohydrological separation has profound implications for mechanistic ecohydrological modeling and water resource management. However, it is still unclear when and where the ecohydrological separation occurs, especially in humid regions. In this study, high frequency sampling of precipitation, bulk soil water, groundwater and twig xylem water for hydrogen and oxygen isotope composition measurement was conducted in a humid subtropical site in the central southern China from March 2017 to April 2018. We examined evidence of the ecohydrological separation with three methods (dual-isotope space, line-conditioned excess (lc-excess), and the piecewise isotope balance (PIB) method). The results show that the isotopic composition of plant xylem and bulk soil water are not distinguishable from those of precipitation water on the dual-isotope space due to a weak evaporation effect at the study site, indicating that there is no evidence of the ecohydrological separation. However, the other two methods support the ecohydrological separation in this humid area, with the results from the PIB method revealing more temporal details. The present study suggests that the ecohydrological separation can happen in subtropical humid climate. It is more likely to occur in spring and winter at the study site when plant-accessible water pool has been replenished by antecedent precipitation, while ecohydrological connection seems to occur during winter snowmelt. With the limitations of three methods, the caution should be taken when only one method is applied in examining the ecohydrological separation in such an environment.

Resolving Seasonal Ice Velocity of 45 Greenlandic Glaciers With Very High Temporal Details

AbstractSeasonal glacier ice velocities are important for understanding controlling mechanisms of ice flow. For many Greenlandic glaciers, however, these measurements are limited by low temporal resolution. We present seasonal ice velocity changes, melt season onset and extent, and ice front positions for 45 Greenlandic glaciers using 2015–2017 Sentinel‐1 synthetic aperture radar data. Seasonal velocity fluctuations of roughly half of the glaciers appear to be primarily controlled by surface melt‐induced changes in the subglacial hydrology. This includes (1) glaciers that speed up with the onset of surface melt and (2) glaciers with comparable late winter and early melt season velocities that show significant slowdown during most of the melt season and speedup during winter. In contrast, less than a quarter of the study glaciers show strong correspondence between seasonal ice speed and terminus changes. Our results pinpoint seasonal variations across Greenland, highlighting the variable influence of meltwater on year‐round ice velocities.