Direct Measurements of Meltwater Runoff on the Greenland Ice Sheet Surface

Meltwater runoff from the Greenland Ice Sheet surface influences surface mass balance (SMB), ice dynamics and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-hour trial for a 63.1 square kilometer moulin-terminating internally drained catchment (IDC) on Greenland's mid-elevation (1207-1381 meters above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6.1 (Modele Atmospherique Regionale 3.6.1), RACMO2.3 (Regional Atmospheric Climate Model 2.3), MERRA-2 (Modern Era Retrospective-analysis for Research and Applications-2) and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins, but are improved using synthetic unit hydrograph theory (SUH). Retroactive SUH applications to two older field studies reproduces their findings, signifying that remotely sensed IDC area, shape, and river-length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6.1, RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment models overestimated runoff by plus 21 percent to plus 58 percent, linked to overestimated ablation and possible meltwater retention in bare, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of surface mass balance with ice dynamics and subglacial systems

Direct measurements of meltwater runoff on the Greenland ice sheet surface

Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2 moulin-terminating internally drained catchment (IDC) on Greenland?s midelevation (1,207?1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systemspublishersversionPeer reviewe

Cancer risk in hospitalised asthma patients

Asthma is an increasingly common disorder, affecting 5–10% of the population. It involves a dysregulated immune function, which may predispose to subsequent cancer. We examined cancer risk among Swedish subjects who had hospital admission once or multiple times for asthma. An asthma research database was created by identifying asthma patients from the Swedish Hospital Discharge Register and by linking them with the Cancer Registry. A total of 140 425 patients were hospitalised for asthma during 1965–2004, of whom 7421 patients developed cancer, giving an overall standardised incidence ratio (SIR) of 1.36. A significant increase was noted for most sites, with the exception of breast and ovarian cancers and non-Hodgkin's lymphoma and myeloma. Patients with multiple hospital admissions showed a high risk, particularly for stomach (SIR 1.70) and colon (SIR 1.99) cancers. A significant decrease was noted for endometrial cancer and skin melanoma. Oesophageal and lung cancers showed high risks throughout the study period, whereas stomach cancer increased towards the end of the period. The relatively stable temporal trends suggest that the asthmatic condition rather than its medication is responsible for the observed associations

Eosinophils in glioblastoma biology

Glioblastoma multiforme (GBM) is the most common primary brain tumor in adults. The development of this malignant glial lesion involves a multi-faceted process that results in a loss of genetic or epigenetic gene control, un-regulated cell growth, and immune tolerance. Of interest, atopic diseases are characterized by a lack of immune tolerance and are inversely associated with glioma risk. One cell type that is an established effector cell in the pathobiology of atopic disease is the eosinophil. In response to various stimuli, the eosinophil is able to produce cytotoxic granules, neuromediators, and pro-inflammatory cytokines as well as pro-fibrotic and angiogenic factors involved in pathogen clearance and tissue remodeling and repair. These various biological properties reveal that the eosinophil is a key immunoregulatory cell capable of influencing the activity of both innate and adaptive immune responses. Of central importance to this report is the observation that eosinophil migration to the brain occurs in response to traumatic brain injury and following certain immunotherapeutic treatments for GBM. Although eosinophils have been identified in various central nervous system pathologies, and are known to operate in wound/repair and tumorstatic models, the potential roles of eosinophils in GBM development and the tumor immunological response are only beginning to be recognized and are therefore the subject of the present review

Hydrologic dynamics of the Greenland Ice Sheet from remote sensing and field measurements

The current need for forecasting Greenland Ice Sheet contributions to global sea level rise is complicated by the lack of understanding of ice sheet hydrology. The proportion of meltwater contributing to sea level rise, as well as the pathways transporting meltwater on, through, and out of the ice sheet, are not well understood. Remote sensing of hydrologic dynamics in combination with small-scale fieldwork allows examination of broad spatial and temporal trends in the Greenland hydrologic system responding to a changing climate. This dissertation reviews the current state of knowledge on Greenland Ice Sheet hydrology, and examines three components of the Greenland hydrologic system: (1) fjord sediment plumes as an indicator of meltwater output, (2) supraglacial streamflow as an indicator of meltwater input to the ice sheet, and (3) moulin distribution and formation as a mechanism diverting meltwater from the surface of the ice sheet to the bed. Buoyant sediment plumes that develop in fjords downstream of outlet glaciers are controlled by numerous factors, including meltwater runoff. MODIS retrievals of sediment plume concentration show a strong regional and seasonal response to meltwater production on the ice sheet surface, despite limitations in fjords with rapidly calving glaciers, providing a tool for tracking meltwater release to the ocean. Summertime field observations and high-resolution satellite imagery reveal extensive supraglacial river networks across the southwestern ablation zone transporting large volumes of meltwater to moulins, yet these features remain poorly mapped and their discharges unquantified. A GIS modeling framework is developed to spatially adapt Manning’s equation for use with high-resolution WorldView-2 imagery to map supraglacial river discharge. Moulins represent connections between surface meltwater on the Greenland ice sheet and subglacial drainage networks, where increased meltwater can enhance ice sliding dynamics. A new high-resolution moulin dataset in western Greenland created from WorldView-1/2 imagery in the 2012 record melt year is used to assess moulin distribution and formation. Moulin locations show a significantly different distribution compared to geospatial variables in the entire study area, with moulins forming in areas of thinner ice, higher velocity and extensional strain rate, as well as lower surface elevation and slope, and higher bed elevation and slope

Learning Adjustable Reduced Downsampling Network for Small Object Detection in Urban Environments

Detecting small objects (e.g., manhole covers, license plates, and roadside milestones) in urban images is a long-standing challenge mainly due to the scale of small object and background clutter. Although convolution neural network (CNN)-based methods have made significant progress and achieved impressive results in generic object detection, the problem of small object detection remains unsolved. To address this challenge, in this study we developed an end-to-end network architecture that has three significant characteristics compared to previous works. First, we designed a backbone network module, namely Reduced Downsampling Network (RD-Net), to extract informative feature representations with high spatial resolutions and preserve local information for small objects. Second, we introduced an Adjustable Sample Selection (ADSS) module which frees the Intersection-over-Union (IoU) threshold hyperparameters and defines positive and negative training samples based on statistical characteristics between generated anchors and ground reference bounding boxes. Third, we incorporated the generalized Intersection-over-Union (GIoU) loss for bounding box regression, which efficiently bridges the gap between distance-based optimization loss and area-based evaluation metrics. We demonstrated the effectiveness of our method by performing extensive experiments on the public Urban Element Detection (UED) dataset acquired by Mobile Mapping Systems (MMS). The Average Precision (AP) of the proposed method was 81.71%, representing an improvement of 1.2% compared with the popular detection framework Faster R-CNN