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Understanding the structure of Earth's polar ice sheets is important for modeling how global warming will impact polar ice and, in turn, the Earth's climate. Ground-penetrating radar is able to collect observations of the internal structure of snow and ice, but the process of manually labeling these observations is slow and laborious. Recent work has developed automatic techniques for finding the boundaries between the ice and the bedrock, but finding internal layers - the subtle boundaries that indicate where one year's ice accumulation ended and the next began - is much more challenging because the number of layers varies and the boundaries often merge and split. In this paper, we propose a novel deep neural network for solving a general class of tiered segmentation problems. We then apply it to detecting internal layers in polar ice, evaluating on a large-scale dataset of polar ice radar data with human-labeled annotations as ground truth., Comment: ICME version

Increasing atmospheric temperatures over ice cover affect surface processes, including melt, snowfall, and snow density. Here, we present the Surface Mass Balance and Snow on Sea Ice Working Group (SUMup) dataset, a standardized dataset of Arctic and Antarctic observations of surface mass balance components. The July 2018 SUMup dataset consists of three subdatasets, snow/firn density (https://doi.org/10.18739/A2JH3D23R), at least near-annually resolved snow accumulation on land ice (https://doi.org/10.18739/A2DR2P790), and snow depth on sea ice (https://doi.org/10.18739/A2WS8HK6X), to monitor change and improve estimates of surface mass balance. The measurements in this dataset were compiled from field notes, papers, technical reports, and digital files. SUMup is a compiled, community-based dataset that can be and has been used to evaluate modeling efforts and remote sensing retrievals. Active submission of new or past measurements is encouraged. Analysis of the dataset shows that Greenland Ice Sheet density measurements in the top 1m do not show a strong relationship with annual temperature. At Summit Station, Greenland, accumulation and surface density measurements vary seasonally with lower values during summer months. The SUMup dataset is a dynamic, living dataset that will be updated and expanded for community use as new measurements are taken and new processes are discovered and quantified.

We apply the magnetic resonance sounding (MRS) method to investigate a firn aquifer in the south-east region of the Greenland ice sheet. Our study aims to delineate and estimate the volume of the recently discovered water stored within the firn (compacted snow) that remains liquid throughout the year. We develop and test successfully amethodology for joint use of MRS and ground-penetrating radar (GPR). This noninvasive geophysical approach is particularly well-adapted to glacier conditions and has a promising future for in situ investigation of water distribution in glaciers. At our field site, MRS showed an aquifer located at variable depths between 20 and 30 m beneath the ice-sheet surface. At the monitoring site, both MRS and GPR show an increase in the water volume stored between April 2015 and July 2016. MRS estimates suggest that the volume increased by approximately 28%.

Contemporary climate warming over the Arctic is accelerating mass loss from the Greenland Ice Sheet through increasing surface melt, emphasizing the need to closely monitor its surface mass balance in order to improve sea-level rise predictions. Snow accumulation is the largest component of the ice sheet's surface mass balance, but in situ observations thereof are inherently sparse and models are difficult to evaluate at large scales. Here, we quantify recent Greenland accumulation rates using ultra-wideband (2-6.5 gigahertz) airborne snow radar data collected as part of NASA's Operation IceBridge between 2009 and 2012. We use a semi-automated method to trace the observed radiostratigraphy and then derive annual net accumulation rates for 2009-2012. The uncertainty in these radar-derived accumulation rates is on average 14 percent. A comparison of the radarderived accumulation rates and contemporaneous ice cores shows that snow radar captures both the annual and longterm mean accumulation rate accurately. A comparison with outputs from a regional climate model (MAR - Modele Atmospherique Regional for Greenland and vicinity) shows that this model matches radar-derived accumulation rates in the ice sheet interior but produces higher values over southeastern Greenland. Our results demonstrate that snow radar can efficiently and accurately map patterns of snow accumulation across an ice sheet and that it is valuable for evaluating the accuracy of surface mass balance models.

This presentation discusses current efforts to develop a Wideband Instrument for Snow Measurements (WISM). The objective of the effort are as follows: to advance the utility of a wideband active and passive instrument (8-40 gigahertz) to support the snow science community; improve snow measurements through advanced calibration and expanded frequency of active and passive sensors; demonstrate science utility through airborne retrievals of snow water equivalent (SWE); and advance the technology readiness of broadband current sheet array (CSA) antenna technology for spaceflight applications.

Space-based microwave sensors have been available for several decades, and with time more frequencies have been offered. Observations made at frequencies between 7 and 183 GHz were often used for monitoring cryospheric properties (e.g. sea ice concentration, snow accumulation, snow melt extent and duration). Since 2009, satellite observations are available at the low frequency of 1.4 GHz. Such observations are collected by the Soil Moisture and Ocean Salinity (SMOS) mission, and the AquariusSAC-D mission. Even though these missions have been designed for the monitoring of soil moisture and sea surface salinity, new applications are being developed to study the cryosphere. For instance, L-band observations can be used to monitor soil freezethaw (e.g. Rautiainen et al., 2012), and thin sea ice thickness (e.g. Kaleschke et al., 2010, Huntemann et al., 2013). Moreover, with the development of satellite missions comes the need for calibration and validation sites. These sites must have stable characteristics, such as the Antarctic Plateau (Drinkwater et al., 2004, Macelloni et al., 2013). Therefore, studying the cryosphere with 1.4 GHz observations is relevant for both science applications, and remote sensing applications.

Passive and active observations at L band (frequency (is) approximately 1.4 GHz) from the Aquarius/SAC-D mission offer new capabilities to study the polar regions. Due to the lack of polar-gridded products, however, applications over the cryosphere have been limited. We present three weekly polar-gridded products of Aquarius data to improve our understanding of L-band observations of ice sheets, sea ice, permafrost, and the polar oceans. Additionally, these products intend to facilitate access to L-band data, and can be used to assist in algorithm developments. Aquarius data at latitudes higher than 50 degrees are averaged and gridded into weekly products of brightness temperature (TB), normalized radar cross section (NRCS), and sea surface salinity (SSS). Each grid cell also contains sea ice fraction, the standard deviation of TB, NRCS, and SSS, and the number of footprint observations collected during the seven-day cycle. The largest 3 dB footprint dimensions are 97 km×156 km and 74 km×122 km (along × across track) for the radiometers and scatterometer, respectively. The data is gridded to the Equal-Area Scalable Earth version 2.0 (EASE2.0) grid, with a grid cell resolution of 36 km. The data sets start in August 2011, with the first Aquarius observations and will be updated on a monthly basis following the release schedule of the Aquarius Level 2 data sets. The weekly gridded products are distributed by the US National Snow and Ice Data Center at http://nsidc.org/data/aquarius/index.html

Snow accumulation over an ice sheet is the sole mass input, making it a primary measurement for understanding the past, present, and future mass balance. Near-surface frequency-modulated continuous-wave (FMCW) radars image isochronous firn layers recording accumulation histories. The Semiautomated Multilayer Picking Algorithm (SAMPA) was designed and developed to trace annual accumulation layers in polar firn from both airborne and ground-based radars. The SAMPA algorithm is based on the Radon transform (RT) computed by blocks and angular orientations over a radar echogram. For each echogram's block, the RT maps firn segmented-layer features into peaks, which are picked using amplitude and width threshold parameters of peaks. A backward RT is then computed for each corresponding block, mapping the peaks back into picked segmented-layers. The segmented layers are then connected and smoothed to achieve a final layer pick across the echogram. Once input parameters are trained, SAMPA operates autonomously and can process hundreds of kilometers of radar data picking more than 40 layers. SAMPA final pick results and layer numbering still require a cursory manual adjustment to correct noncontinuous picks, which are likely not annual, and to correct for inconsistency in layer numbering. Despite the manual effort to train and check SAMPA results, it is an efficient tool for picking multiple accumulation layers in polar firn, reducing time over manual digitizing efforts. The trackability of good detected layers is greater than 90%.

A perennial storage of water in a firn aquifer was discovered in southeast Greenland in 2011. We present the first in situ measurements of the aquifer, including densities and temperatures. Water was present at depths between approx. 12 and 37m and amounted to 18.7 +/- 0.9 kg in the extracted core. The water filled the firn to capacity at approx. 35m. Measurements show the aquifer temperature remained at the melting point, representing a large heat reservoir within the firn. Using model results of liquid water extent and aquifer surface depth from radar measurements, we extend our in situ measurements to the Greenland ice sheet. The estimated water volume is 140 +/- 20 Gt, representing approx. 0.4mm of sea level rise (SLR). It is unknown if the aquifer temporary buffers SLR or contributes to SLR through drainage and/or ice dynamics.

Glacierized change in the Himalayas affects river-discharge, hydro-energy and agricultural production, and Glacial Lake Outburst Flood potential, but its quantification and extent of impacts remains highly uncertain. Here we present conservative, comprehensive and quantitative predictions for glacier area and meltwater flux changes in Bhutan, monsoonal Himalayas. In particular, we quantify the uncertainties associated with the glacier area and meltwater flux changes due to uncertainty in climate data, a critical problem for much of High Asia. Based on a suite of gridded climate data and a robust glacier melt model, our results show that glacier area and meltwater change projections can vary by an order of magnitude for different climate datasets. However, the most conservative results indicate that, even if climate were to remain at the present-day mean values, almost 10% of Bhutan s glacierized area would vanish and the meltwater flux would drop by as much as 30%. Under the conservative scenario of an additional 1 C regional warming, glacier retreat is going to continue until about 25% of Bhutan s glacierized area will have disappeared and the annual meltwater flux, after an initial spike, would drop by as much as 65%. Citation

Surface mass balance (SMB) over ice sheets and snow on sea ice (SOSI) are important components of the cryosphere. Large knowledge gaps remain in scientists' abilities to monitor SMB and SOSI, including insufficient measurements and difficulties with satellite retrievals. On ice sheets, snow accumulation is the sole mass gain to SMB, and meltwater runoff can be the dominant single loss factor in extremely warm years such as 2012. SOSI affects the growth and melt cycle of the Earth's polar sea ice cover. The summer of 2012 saw the largest satellite-recorded melt area over the Greenland ice sheet and the smallest satellite-recorded Arctic sea ice extent, making this meeting both timely and relevant.

The accelerating loss of mass from the Greenland ice sheet is a major contribution to current sea level rise. Increased melt water runoff is responsible for half of Greenlands mass loss increase. Surface melt has been increasing in extent and intensity, setting a record for surface area melt and runoff in 2012. The mechanisms and timescales involved in allowing surface melt water to reach the ocean where it can contribute to sea level rise are poorly understood. The potential capacity to store this water in liquid or frozen form in the firn (multi-year snow layer) is significant, and could delay its sea-level contribution. Here we describe direct observation of water within a perennial firn aquifer persisting throughout the winter in the southern ice sheet,where snow accumulation and melt rates are high. This represents a previously unknown storagemode for water within the ice sheet. Ice cores, groundairborne radar and a regional climatemodel are used to estimate aquifer area (70 plue or minus 10 x 10(exp 3) square kilometers ) and water table depth (5-50 m). The perennial firn aquifer represents a new glacier facies to be considered 29 in future ice sheet mass 30 and energy budget calculations.

Enhanced melting along with surface-temperature increases measured using infrared satellite data, have been documented for the Greenland Ice Sheet. Recently we developed a climate-quality data record of ice-surface temperature (IST) of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) 1ST product -- http://modis-snow-ice.gsfc.nasa.gov. Using daily and mean monthly MODIS 1ST maps from the data record we show maximum extent of melt for the ice sheet and its six major drainage basins for a 12-year period extending from March of 2000 through December of 2011. The duration of the melt season on the ice sheet varies in different drainage basins with some basins melting progressively earlier over the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. The short time of the study period (approximately 12 years) precludes an evaluation of statistically-significant trends. However the dataset provides valuable information on natural variability of IST, and on the ability of the MODIS instrument to capture changes in IST and melt conditions indifferent drainage basins of the ice sheet.

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid. This record will be elevated in status to a CDR when at least nine more years of data become available either from MODIS Terra or Aqua, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Our ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the VIIRS era. Differences in the APP and MODIS cloud masks have so far precluded the current 1ST records from spanning both the APP and MODIS time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The complete MODIS 1ST daily and monthly data record is available online.

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR.

We have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) Terra ice-surface temperature (1ST) algorithm. A climate-data record (CDR) is a time series of measurements of sufficient length, consistency, and continuity to determine climate variability and change. We present daily and monthly Terra MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 at 6.25-km spatial resolution on a polar stereographic grid within +/-3 hours of 17:00Z or 2:00 PM Local Solar Time. Preliminary validation of the ISTs at Summit Camp, Greenland, during the 2008-09 winter, shows that there is a cold bias using the MODIS IST which underestimates the measured surface temperature by approximately 3 C when temperatures range from approximately -50 C to approximately -35 C. The ultimate goal is to develop a CDR that starts in 1981 with the Advanced Very High Resolution (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present. Differences in the APP and MODIS cloud masks have so far precluded the current IST records from spanning both the APP and MODIS IST time series in a seamless manner though this will be revisited when the APP dataset has been reprocessed. The Greenland IST climate-quality data record is suitable for continuation using future Visible Infrared Imager Radiometer Suite (VIIRS) data and will be elevated in status to a CDR when at least 9 more years of climate-quality data become available either from MODIS Terra or Aqua, or from the VIIRS. The complete MODIS IST data record will be available online in the summer of 2011.

Enhanced melting of the Greenland Ice Sheet has been documented in recent literature along with surface-temperature increases measured using infrared satellite data since 1981. Using a recently-developed climate-quality data record, 11- and 12-year trends in the clear-sky ice-surface temperature (IST) of the Greenland Ice Sheet have been studied using the Moderate-Resolution Imaging Spectroradiometer (MODIS) IST product. Daily and monthly MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are now available at 6.25-km spatial resolution on a polar stereographic grid as described in Hall et al. (submitted). This record will be elevated in status to a climate-data record (CDR) when more years of data become available either from the MODIS on the Terra or Aqua satellites, or from the Visible Infrared Imager Radiometer Suite (VIIRS) to be launched in October 2011. Maps showing the maximum extent of melt for the entire ice sheet and for the six major drainage basins have been developed from the MODIS IST dataset. Twelve-year trends of the duration of the melt season on the ice sheet vary in different drainage basins with some basins melting progressively earlier over the course of the study period. Some (but not all) of the basins also show a progressively-longer duration of melt. IST 12-year trends are compared with in-situ data, and climate data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) Reanalysis.

Surface temperatures on the Greenland Ice Sheet have been studied on the ground, using automatic weather station (AWS) data from the Greenland-Climate Network (GC-Net), and from analysis of satellite sensor data. Using Advanced Very High Frequency Radiometer (AVHRR) weekly surface temperature maps, warming of the surface of the Greenland Ice Sheet has been documented since 1981. We extended and refined this record using higher-resolution Moderate-Resolution Imaging Spectroradiometer (MODIS) data from March 2000 to the present. We developed a daily and monthly climate-data record (CDR) of the "clear-sky" surface temperature of the Greenland Ice Sheet using an ice-surface temperature (1ST) algorithm developed for use with MODIS data. Validation of this CDR is ongoing. MODIS Terra swath data are projected onto a polar stereographic grid at 6.25-km resolution to develop binary, gridded daily and mean-monthly 1ST maps. Each monthly map also has a color-coded image map that is available to download. Also included with the monthly maps is an accompanying map showing number of days in the month that were used to calculate the mean-monthly 1ST. This is important because no 1ST decision is made by the algorithm for cells that are considered cloudy by the internal cloud mask, so a sufficient number of days must be available to produce a mean 1ST for each grid cell. Validation of the CDR consists of several facets: 1) comparisons between ISTs and in-situ measurements; 2) comparisons between ISTs and AWS data; and 3) comparisons of ISTs with surface temperatures derived from other satellite instruments such as the Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+). Previous work shows that Terra MODIS ISTs are about 3 C lower than in-situ temperatures measured at Summit Camp, during the winter of 2008-09 under clear skies. In this work we begin to compare surface temperatures derived from AWS data with ISTs from the MODIS CDR. The Greenland Ice Sheet 1ST CDR will be useful for monitoring surface-temperature trends and can be used as input or for validation of climate models. The CDR can be extended into the future using MODIS Terra, Aqua and NPOESS Preparatory Project Visible Infrared Imager Radiometer Suite (VII RS) data.

Current trends show rise in Arctic surface and air temperatures, including over the Greenland ice sheet where rising temperatures will contribute to increased sea-level rise through increased melt. We aim to establish the uncertainties in using satellite-derived surface temperature for measuring Arctic surface temperature, as satellite data are increasingly being used to assess temperature trends. To accomplish this, satellite-derived surface temperature, or land-surface temperature (LST), must be validated and limitations of the satellite data must he assessed quantitatively. During the 2008/09 boreal winter at Summit, Greenland, we employed data from standard US National Oceanic and Atmospheric Administration (NOAA) air-temperature instruments, button-sized temperature sensors called thermochrons and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument to (1) assess the accuracy and utility of thermochrons in an ice-sheet environment and (2) compare MODIS-derived LSTs with thermochron-derived surface and air temperatures. The thermochron-derived air temperatures were very accurate, within 0.1+/-0.3 C of the NOAA-derived air temperature, but thermochron-derived surface temperatures were approx. 3 C higher than MODIS-derived LSTs. Though the surface temperature is largely determined by air temperature, these variables can differ significantly. Furthermore, we show that the winter-time mean air temperature, adjusted to surface temperature was approx. 11 C higher than the winter-time mean MODIS-derived LST. This marked difference occurs largely because of satellite-derived LSTs cannot be measured through cloud cover, so caution must be exercised in using time series of satellite LST data to study seasonal temperature trends.

An earlier issue presents the first half of the author's experience living and working at the National Science Foundation's (NSF) Greenland Summit Camp. The author is a remote-sensing glaciologist at NASA s Goddard Space Flight Center. She took measurements that will be used to validate data collected by NASA s Aqua, Terra, and Ice, Clouds, and land Elevation Satellite (ICESat) satellites with ground-truth measurements of the Greenland Ice Sheet she made at Summit Camp from November 2008-February 2009. This article presents excerpts from the second half of her stay and work at the Greenland Summit.