The Boundary Layer and its Response to External Forcing at Summit Station Greenland

2020 ◽  
Author(s):  
William Neff ◽  
Christopher Cox ◽  
Mathew Shupe
Keyword(s):  
Boundary Layer ◽  
Heat Waves ◽  
Chemical Exchange ◽  
Layer Structure ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Back Trajectory ◽  
Data Set ◽  
Thermodynamic Structure ◽  
Typical Sequence

<p>The ICECAPS field program (Integrated Characterization of Energy, Clouds, Atmospheric State and Precipitation at Summit) has operated at Summit Station (over 3000 m ASL) since the spring of 2010 with a broad range of instruments to study the role of clouds and precipitation over the Greenland Ice Sheet (GIS).  In addition, a high-resolution minisodar has been operated nearby since 2008 (initially as part of an ice-atmosphere chemical exchange study).  The sodar provides detailed views of the thermodynamic structure of the boundary layer from 2 to 160 m above the surface. Several other collaborating programs support additional boundary-layer measurements such as broadband radiation and turbulent flux measurements. The sodar has proven useful in the interpretation of chemical interactions with the snow surface and underlying firn as well as comparisons of boundary layer depth estimators (Van Dam et al, 2013, 2015).  In addition it has documented the response of the boundary layer to changing cloud forcing (Shupe et al. 2013).  In addition, it has been used to study the wintertime boundary layer with super-cooled fog layers present (Cox et al, 2019).  Additional observations have added to an already rich data set, such as those of stable water vapor isotopes (e.g. Berkelhammer et al. 2016). </p><p>As in the 2012 melt episode that encompassed nearly the entire ice sheet, atmospheric rivers (ARs) bring moisture from the south along the coasts of Greenland and have been increasing (Mattingly et al., 2018; Neff 2018).  We will present a climatology from 2000 to 2012 of ARs some of which are associated with increased transport of moisture from the subtropics at times in concert with hurricanes and tropical storms that follow the same path.  This climatology reveals a distinct low-high pressure pattern spanning from NE Canada to the central Atlantic: the boundary between these systems provides the pathway for moisture to flow from the subtropics.  In this presentation will describe the characteristic cloud/clear skies sequence and accompanying boundary layer structure at Summit Station during these events.  A typical sequence is one of ARs trapped along the west coast and then spreading moisture over the GIS in subsequent days.</p><p>To understand the origin of the moisture arriving at Summit Station we also carried out back trajectory analyses that show connections to both ARs and extratropical remnants of hurricanes that follow the same path to Greenland.  Of particular interest will be the boundary layer behavior during the dramatic melt episodes of June and then July 2019 that had their origins in heat waves off of Africa and over Europe. </p><p> </p>

Faster multi-defect detection system in shield tunnel using combination of FCN and faster RCNN

2019 ◽  
Vol 22 (13) ◽  
pp. 2907-2921 ◽  
Author(s):  
Xinwen Gao ◽  
Ming Jian ◽  
Min Hu ◽  
Mohan Tanniru ◽  
Shuaiqing Li
Keyword(s):  
Boundary Layer ◽  
Defect Detection ◽  
Detection Rate ◽  
Layer Structure ◽  
Detection System ◽  
Identification Accuracy ◽  
Shield Tunnel ◽  
False Detection Rate ◽  
False Detection ◽  
Data Set

With the large-scale construction of urban subways, the detection of tunnel defects becomes particularly important. Due to the complexity of tunnel environment, it is difficult for traditional tunnel defect detection algorithms to detect such defects quickly and accurately. This article presents a deep learning FCN-RCNN model that can detect multiple tunnel defects quickly and accurately. The algorithm uses a Faster RCNN algorithm, Adaptive Border ROI boundary layer and a three-layer structure of the FCN algorithm. The Adaptive Border ROI boundary layer is used to reduce data set redundancy and difficulties in identifying interference during data set creation. The algorithm is compared with single FCN algorithm with no Adaptive Border ROI for different defect types. The results show that our defect detection algorithm not only addresses interference due to segment patching, pipeline smears and obstruction but also the false detection rate decreases from 0.371, 0.285, 0.307 to 0.0502, respectively. Finally, corrected by cylindrical projection model, the false detection rate is further reduced from 0.0502 to 0.0190 and the identification accuracy of water leakage defects is improved.

scholarly journals A daily, 1 km resolution data set of downscaled Greenland ice sheet surface mass balance (1958–2015)

2016 ◽  
Vol 10 (5) ◽  
pp. 2361-2377 ◽  
Author(s):  
Brice Noël ◽  
Willem Jan van de Berg ◽  
Horst Machguth ◽  
Stef Lhermitte ◽  
Ian Howat ◽  
...  
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Surface Mass Balance ◽  
Data Set ◽  
Surface Mass ◽  
Ice Caps ◽  
Elevation Model

Abstract. This study presents a data set of daily, 1 km resolution Greenland ice sheet (GrIS) surface mass balance (SMB) covering the period 1958–2015. Applying corrections for elevation, bare ice albedo and accumulation bias, the high-resolution product is statistically downscaled from the native daily output of the polar regional climate model RACMO2.3 at 11 km. The data set includes all individual SMB components projected to a down-sampled version of the Greenland Ice Mapping Project (GIMP) digital elevation model and ice mask. The 1 km mask better resolves narrow ablation zones, valley glaciers, fjords and disconnected ice caps. Relative to the 11 km product, the more detailed representation of isolated glaciated areas leads to increased precipitation over the southeastern GrIS. In addition, the downscaled product shows a significant increase in runoff owing to better resolved low-lying marginal glaciated regions. The combined corrections for elevation and bare ice albedo markedly improve model agreement with a newly compiled data set of ablation measurements.

scholarly journals Multi-modal albedo distributions in the ablation area of the southwestern Greenland Ice Sheet

2015 ◽  
Vol 9 (3) ◽  
pp. 905-923 ◽  
Author(s):  
S. E. Moustafa ◽  
A. K. Rennermalm ◽  
L. C. Smith ◽  
M. A. Miller ◽  
J. R. Mioduszewski ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Arctic Region ◽  
Bimodal Distribution ◽  
The Arctic ◽  
Remotely Sensed Data ◽  
Data Set ◽  
Ablation Area

Abstract. Surface albedo is a key variable controlling solar radiation absorbed at the Greenland Ice Sheet (GrIS) surface and, thus, meltwater production. Recent decline in surface albedo over the GrIS has been linked to enhanced snow grain metamorphic rates, earlier snowmelt, and amplified melt–albedo feedback from atmospheric warming. However, the importance of distinct surface types on ablation area albedo and meltwater production is still relatively unknown. In this study, we analyze albedo and ablation rates using in situ and remotely sensed data. Observations include (1) a new high-quality in situ spectral albedo data set collected with an Analytical Spectral Devices Inc. spectroradiometer measuring at 325–1075 nm along a 1.25 km transect during 3 days in June 2013; (2) broadband albedo at two automatic weather stations; and (3) daily MODerate Resolution Imaging Spectroradiometer (MODIS) albedo (MOD10A1) between 31 May and 30 August 2012 and 2013. We find that seasonal ablation area albedos in 2013 have a bimodal distribution, with snow and ice facies characterizing the two peaks. Our results show that a shift from a distribution dominated by high to low albedos corresponds to an observed melt rate increase of 51.5% (between 10–14 July and 20–24 July 2013). In contrast, melt rate variability caused by albedo changes before and after this shift was much lower and varied between ~10 and 30% in the melting season. Ablation area albedos in 2012 exhibited a more complex multimodal distribution, reflecting a transition from light to dark-dominated surface, as well as sensitivity to the so called "dark-band" region in southwest Greenland. In addition to a darkening surface from ice crystal growth, our findings demonstrate that seasonal changes in GrIS ablation area albedos are controlled by changes in the fractional coverage of snow, bare ice, and impurity-rich surface types. Thus, seasonal variability in ablation area albedos appears to be regulated primarily as a function of bare ice expansion at the expense of snow, surface meltwater ponding, and melting of outcropped ice layers enriched with mineral materials, enabling dust and impurities to accumulate. As climate change continues in the Arctic region, understanding the seasonal evolution of ice sheet surface types in Greenland's ablation area is critical to improve projections of mass loss contributions to sea level rise.

scholarly journals Accumulation rates (2009–2017) in Southeast Greenland derived from airborne snow radar and comparison with regional climate models

2020 ◽  
Vol 61 (81) ◽  
pp. 225-233 ◽  
Author(s):  
Lynn Montgomery ◽  
Lora Koenig ◽  
Jan T. M. Lenaerts ◽  
Peter Kuipers Munneke
Keyword(s):  
Spatial Data ◽  
Climate Models ◽  
Layer Structure ◽  
Accumulation Rate ◽  
Regional Climate ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Regional Climate Models ◽  
Internal Layers ◽  
Accumulation Rates

AbstractSince the year 2000, Greenland ice sheet mass loss has been dominated by a decrease in surface mass balance rather than an increase in solid ice discharge. Southeast Greenland is an important region to understand how high accumulation rates can offset increasing Greenland ice sheet meltwater runoff. To that end, we derive a new 9-year long dataset (2009–17) of accumulation rates in Southeast Greenland using NASA Operation IceBridge snow radar. Our accumulation dataset derived from internal layers focuses on high elevations (1500–3000 m) because at lower elevations meltwater percolation obscured internal layer structure. The uncertainty of the radar-derived accumulation rates is 11% [using Firn Densification Model (FDM) density profiles] and the average accumulation rate ranges from 0.5 to 1.2 m w.e. With our observations spanning almost a decade, we find large inter-annual variability, but no significant trend. Accumulation rates are compared with output from two regional climate models (RCMs), MAR and RACMO2. This comparison shows that the models are underestimating accumulation in Southeast Greenland and the models misrepresent spatial heterogeneity due to an orographically forced bias in snowfall near the coast. Our dataset is useful to fill in temporal and spatial data gaps, and to evaluate RCMs where few in situ measurements are available.

scholarly journals Mass balance of the Greenland ice sheet – a study of ICESat data, surface density and firn compaction modelling

2010 ◽  
Vol 4 (4) ◽  
pp. 2103-2141 ◽  
Author(s):  
L. S. Sørensen ◽  
S. B. Simonsen ◽  
K. Nielsen ◽  
P. Lucas-Picher ◽  
G. Spada ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Mass Loss ◽  
Mass Balance ◽  
Volume Change ◽  
Surface Density ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Altimetry Data ◽  
Data Set ◽  
Elevation Changes

Abstract. ICESat has provided surface elevation measurements of the ice sheets since the launch in January 2003, resulting in a unique data set for monitoring the changes of the cryosphere. Here we present a novel method for determining the mass balance of the Greenland ice sheet derived from ICESat altimetry data. Four different methods for deriving the elevation changes from the ICESat altimetry data set are used. This multi method approach gives an understanding of the complexity associated with deriving elevation changes from the ICESat altimetry data set. The altimetry can not stand alone in estimating the mass balance of the Greenland ice sheet. We find firn dynamics and surface densities to be important factors in deriving the mass loss from remote sensing altimetry. The volume change derived from ICESat data is corrected for firn compaction, vertical bedrock movement and an intercampaign elevation bias in the ICESat data. Subsequently, the corrected volume change is converted into mass change by surface density modelling. The firn compaction and density models are driven by a dynamically downscaled simulation of the HIRHAM5 regional climate model using ERA-Interim reanalysis lateral boundary conditions. We find an annual mass loss of the Greenland ice sheet of 210 ± 21 Gt yr−1 in the period from October 2003 to March 2008. This result is in good agreement with other studies of the Greenland ice sheet mass balance, based on different remote sensing techniques.

scholarly journals Vital role of daily temperature variability in surface mass balance parameterizations of the Greenland Ice Sheet

2014 ◽  
Vol 8 (2) ◽  
pp. 575-585 ◽  
Author(s):  
I. Rogozhina ◽  
D. Rau
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Temperature Variability ◽  
Daily Temperature ◽  
Surface Mass Balance ◽  
Data Set ◽  
Surface Mass ◽  
Continental Scale ◽  
Degree Day

Abstract. This study aims to demonstrate that the spatial and seasonal effects of daily temperature variability in positive degree-day (PDD) models play a decisive role in shaping the modeled surface mass balance (SMB) of continental-scale ice masses. Here we derive monthly fields of daily temperature standard deviation (SD) across Greenland from the ERA-40 (European Centre for Medium-Range Weather Forecasts 40 yr Reanalysis) reanalysis spanning from 1958 to 2001 and apply these fields to model recent surface responses of the Greenland Ice Sheet (GIS). Neither the climate data set analyzed nor in situ measurements taken in Greenland support the range of commonly used spatially and temporally uniform SD values (~ 5 °C). In this region, the SD distribution is highly inhomogeneous and characterized by low values during summer months (~ 1 to 2.5 °C) in areas where most surface melting occurs. As a result, existing SMB parameterizations using uniform, high SD values fail to capture both the spatial pattern and amplitude of the observed surface responses of the GIS. Using realistic SD values enables significant improvements in the modeled regional and total SMB with respect to existing estimates from recent satellite observations and the results of a high-resolution regional model. In addition, this resolves large uncertainties associated with other major parameters of a PDD model, namely degree-day factors. The model appears to be nearly insensitive to the choice of degree-day factors after adopting the realistic SD distribution.

scholarly journals On elevation models as input for mass-balance calculations of the Greenland ice sheet

1996 ◽  
Vol 23 ◽  
pp. 181-186 ◽  
Author(s):  
R. S. W. van de Wal ◽  
S. Ekholm
Keyword(s):  
Marginal Zone ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Balance Model ◽  
Data Sets ◽  
Differential Gps ◽  
Data Set ◽  
Radio Echo Sounding ◽  
The Difference ◽  
Elevation Model

In this paper the elevation model for the Greenland ice sheet based upon radio-echo-sounding flights of the Technical University of Denmark (TUD) (Letréguilly and others, 1991) are compared with the satellite-altimetry model (Tscherning and others, 1993) improved with airborne-laser and radar altimetry (IA model). Although the general hypsometry of both data sets is rather similar, differences seem to be large at individual points along the ice margin. Over the entire ice sheet, the difference between the IA model and the TUD model is 33 m with a root-mean-square error of 112 m. Differential GPS measurements collected in the ice-marginal zone near Søndre Strømfjord show that the IA model is more accurate than the TUD model. The latter data set underestimates the elevation by approximately 150 m in the ice-marginal zone near Søndre Strømfjord.Calculation of the ablation with an energy-balance model and with a degree-day model points to a 20% decrease in the ablation if the IA model is used. Not only does this show the sensitivity of ablation calculations to the orographic input but it also indicates that the ablation calculated by the models used nowadays is relatively overestimated.

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