Controls on rapid supraglacial lake drainage in West Greenland: An Exploratory Data Analysis approach

ABSTRACTThe controls on rapid surface lake drainage on the Greenland ice sheet (GrIS) remain uncertain, making it challenging to incorporate lake drainage into models of GrIS hydrology, and so to determine the ice-dynamic impact of meltwater reaching the ice-sheet bed. Here, we first use a lake area and volume tracking algorithm to identify rapidly draining lakes within West Greenland during summer 2014. Second, we derive hydrological, morphological, glaciological and surface-mass-balance data for various factors that may influence rapid lake drainage. Third, these factors are used within Exploratory Data Analysis to examine existing hypotheses for rapid lake drainage. This involves testing for statistical differences between the rapidly and non-rapidly draining lake types, as well as examining associations between lake size and the potential controlling factors. This study shows that the two lake types are statistically indistinguishable for almost all factors investigated, except lake area. Thus, we are unable to recommend an empirically supported, deterministic alternative to the fracture area threshold parameter for modelling rapid lake drainage within existing surface-hydrology models of the GrIS. However, if improved remotely sensed datasets (e.g. ice-velocity maps, climate model outputs) were included in future research, it may be possible to detect the causes of rapid drainage.</jats:p

Dual-satellite (Sentinel-2 and Landsat 8) remote sensing of supraglacial lakes in Greenland

© 2018 All rights reserved. Remote sensing is commonly used to monitor supraglacial lakes on the Greenland Ice Sheet (GrIS); however, most satellite records must trade off higher spatial resolution for higher temporal resolution (e.g. MODIS) or vice versa (e.g. Landsat). Here, we overcome this issue by developing and applying a dual-sensor method that can monitor changes to lake areas and volumes at high spatial resolution (10-30&thinsp;m) with a frequent revisit time ( ~ 3 days). We achieve this by mosaicking imagery from the Landsat 8 Operational Land Imager (OLI) with imagery from the recently launched Sentinel-2 Multispectral Instrument (MSI) for a ~ 12 000 km2area of West Greenland in the 2016 melt season. First, we validate a physically based method for calculating lake depths with Sentinel-2 by comparing measurements against those derived from the available contemporaneous Landsat 8 imagery; we find close correspondence between the two sets of values (R2Combining double low line 0.841; RMSE Combining double low line 0.555 m). This provides us with the methodological basis for automatically calculating lake areas, depths, and volumes from all available Landsat 8 and Sentinel-2 images. These automatic methods are incorporated into an algorithm for Fully Automated Supraglacial lake Tracking at Enhanced Resolution (FASTER). The FASTER algorithm produces time series showing lake evolution during the 2016 melt season, including automated rapid ( ≤ 4 day) lake-drainage identification. With the dual Sentinel-2-Landsat 8 record, we identify 184 rapidly draining lakes, many more than identified with either imagery collection alone (93 with Sentinel-2; 66 with Landsat 8), due to their inferior temporal resolution, or would be possible with MODIS, due to its omission of small lakes &lt; 0.125 km2. Finally, we estimate the water volumes drained into the GrIS during rapid-lake-drainage events and, by analysing downscaled regional climate-model (RACMO2.3p2) run-off data, the water quantity that enters the GrIS via the moulins opened by such events. We find that during the lake-drainage events alone, the water drained by small lakes ( &lt; 0.125 km2) is only 5.1 % of the total water volume drained by all lakes. However, considering the total water volume entering the GrIS after lake drainage, the moulins opened by small lakes deliver 61.5 % of the total water volume delivered via the moulins opened by large and small lakes; this is because there are more small lakes, allowing more moulins to open, and because small lakes are found at lower elevations than large lakes, where run-off is higher. These findings suggest that small lakes should be included in future remote-sensing and modelling work.NER

Adaptive Refinements in BEM

Accuracy estimates and adaptive refinements is nowadays one of the main research topics in finite element computations [6,7,8, 9,11].Its extension to Boundary Elements has been tried as a means to better understand its capabilities as well as to impro ve its efficiency and its obvious advantages. The possibility of implementing adaptive techniques was shown [1,2] for h-conver gence and p-convergence respectively. Some posterior works [3,4 5,10] have shown the promising results that can be expected from those techniques. The main difficulty is associated to the reasonable establishment of “estimation” and “indication” factors related to the global and local errors in each refinement. Although some global measures have been used it is clear that the reduction in dimension intrinsic to boundary elements (3D→2D: 2D→1D) could allow a direct comparison among residuals using the graphic possibilities of modern computers and allowing a point-to-point comparison in place of the classical global approaches. Nevertheless an indicator generalizing the well known Peano’s one has been produced

Skyrmion Multi-Walls

Skyrmion walls are topologically-nontrivial solutions of the Skyrme system which are periodic in two spatial directions. We report numerical investigations which show that solutions representing parallel multi-walls exist. The most stable configuration is that of the square $N$-wall, which in the $N\to\infty$ limit becomes the cubically-symmetric Skyrme crystal. There is also a solution resembling parallel hexagonal walls, but this is less stable.Comment: 7 pages, 1 figur

A Fully Automated Supraglacial lake area and volume Tracking (“FAST”) algorithm: Development and application using MODIS imagery of West Greenland

Supraglacial lakes (SGLs) on the Greenland Ice Sheet (GrIS) influence ice dynamics if they drain rapidly by hydrofracture. MODIS data are often used to investigate SGLs, including calculating SGL area changes through time, but no existing work presents a method that tracks changes to individual (and total) SGL volume in MODIS imagery over a melt season. Here, we develop such a method by first testing three automated approaches to derive SGL areas from MODIS images from the MOD09 level-2 surface-reflectance product, by comparing calculated areas for the Paakitsoq and Store Glacier regions in West Greenland with areas derived from Landsat-8 (LS8) images. Second, we apply a physically-based depth-calculation algorithm to the pixels within the SGL boundaries from the best performing area-derivation method, and compare the resultant depths with those calculated using the same method applied to LS8 imagery. Our results indicate that SGL areas are most accurately generated using dynamic thresholding of MODIS band 1 (red) MOD09 data with a 0.640 threshold value; calculated values from MODIS are closely comparable to those derived from LS8. Third, we incorporate the best performing area- and depth-detection methods into a Fully Automated SGL Tracking (“FAST”) algorithm that tracks individual SGLs between successive MODIS images. Finally, we apply the FAST algorithm to the two study regions, where it identifies 43 (Paakitsoq) and 19 (Store Glacier) rapidly draining SGLs during 2014, representing 21% and 15% of the respective total SGL populations, including some clusters of rapidly draining SGLs. The FAST algorithm improves upon existing automatic SGL tracking methods through its calculation of both SGL areas and volumes over large regions of the GrIS on a fully automatic basis. It therefore has the potential to be used for investigating statistical relationships between SGL areas, volumes and drainage events over the whole of the GrIS, and over multiple seasons, which might provide further insights into the factors that trigger rapid SGL drainage.This research was funded by a UK Natural Environment Research Council PhD studentship awarded to A.G.W. through the Cambridge Earth System Science Doctoral Training Partnership (grant number: NE/L002507/1). A.F.B. acknowledges the support of a Bowring Junior Research Fellowship (St Catharine's College, University of Cambridge) and a Leverhulme/Newton Trust Early Career Fellowship

Studies on the Toxicity and Efficacy of a New Amino Acid Solution in Pediatric Parenteral Nutrition

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142223/1/jpen0368.pd

Impact of the June 2018 Saddleworth Moor wildfires on air quality in northern England

The June 2018 Saddleworth Moor fires were some of the largest UK wildfires on record and lasted for approximately three weeks. They emitted large quantities of smoke, trace gases and aerosols which were transported downwind over the highly populated regions of Manchester and Liverpool. Surface observations of PM2.5 indicate that concentrations were 4–5.5 times higher than the recent seasonal average. State-of-the-art satellite measurements of total column carbon monoxide (TCCO) from the TROPOMI instrument on the Sentinel 5—Precursor (S5P) platform, coupled with measurements from a flight of the UK BAe-146–301 research aircraft, are used to quantify the substantial enhancement in emitted trace gases. The aircraft measured plume enhancements with near-fire CO and PM2.5 concentrations >1500 ppbv and >125 μg m−3 (compared to ~100 ppbv and ~5 μg m−3 background concentrations). Downwind fire-plume ozone (O3) values were larger than the near-fire location, indicating O3 production with distance from source. The near-fire O3:CO ratio was (ΔO3/ΔCO) 0.001 ppbv/ppbv, increasing downwind to 0.060–0.105 ppbv/ppbv, suggestive of O3 production enhancement downwind of the fires. Emission rates of CO and CO2 ranged between 1.07 (0.07–4.69) kg s−1 and 13.7 (1.73–50.1) kg s−1, respectively, similar to values expected from a medium sized power station

ImmunoCluster provides a computational framework for the non-specialist to profile high- dimensional cytometry data

High dimensional cytometry is an innovative tool for immune monitoring in health and disease, it has provided novel insight into the underlying biology as well as biomarkers for a variety of diseases. However, the analysis of large multiparametric datasets usually requires specialist computational knowledge. Here we describe ImmunoCluster (https://github.com/kordastilab/ImmunoCluster) an R package for immune profiling cellular heterogeneity in high dimensional liquid and imaging mass cytometry, and flow cytometry data, designed to facilitate computational analysis by a non-specialist. The analysis framework implemented within ImmunoCluster is readily scalable to millions of cells and provides a variety of visualization and analytical approaches, as well as a rich array of plotting tools that can be tailored to users' needs. The protocol consists of three core computational stages: 1, data import and quality control; 2, dimensionality reduction and unsupervised clustering; and 3, annotation and differential testing, all contained within an R-based open-source framework

Identification and characterization of a novel non-structural protein of bluetongue virus

Bluetongue virus (BTV) is the causative agent of a major disease of livestock (bluetongue). For over two decades, it has been widely accepted that the 10 segments of the dsRNA genome of BTV encode for 7 structural and 3 non-structural proteins. The non-structural proteins (NS1, NS2, NS3/NS3a) play different key roles during the viral replication cycle. In this study we show that BTV expresses a fourth non-structural protein (that we designated NS4) encoded by an open reading frame in segment 9 overlapping the open reading frame encoding VP6. NS4 is 77–79 amino acid residues in length and highly conserved among several BTV serotypes/strains. NS4 was expressed early post-infection and localized in the nucleoli of BTV infected cells. By reverse genetics, we showed that NS4 is dispensable for BTV replication in vitro, both in mammalian and insect cells, and does not affect viral virulence in murine models of bluetongue infection. Interestingly, NS4 conferred a replication advantage to BTV-8, but not to BTV-1, in cells in an interferon (IFN)-induced antiviral state. However, the BTV-1 NS4 conferred a replication advantage both to a BTV-8 reassortant containing the entire segment 9 of BTV-1 and to a BTV-8 mutant with the NS4 identical to the homologous BTV-1 protein. Collectively, this study suggests that NS4 plays an important role in virus-host interaction and is one of the mechanisms played, at least by BTV-8, to counteract the antiviral response of the host. In addition, the distinct nucleolar localization of NS4, being expressed by a virus that replicates exclusively in the cytoplasm, offers new avenues to investigate the multiple roles played by the nucleolus in the biology of the cell