scholarly journals Temporal Characteristics of Cloud Radiative Effects on the Greenland Ice Sheet: Discoveries From Multiyear Automatic Weather Station Measurements

2018 ◽  
Vol 123 (20) ◽  
pp. 11,348-11,361 ◽  
Author(s):  
Wenshan Wang ◽  
Charles S. Zender ◽  
Dirk van As
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Radiative Effects ◽  
Temporal Characteristics ◽  
Cloud Radiative Effects

scholarly journals PROMICE automatic weather station data

2021 ◽  
Author(s):  
Robert S. Fausto ◽  
Dirk van As ◽  
Kenneth D. Mankoff ◽  
Baptiste Vandecrux ◽  
Michele Citterio ◽  
...  
Keyword(s):  
Surface Energy Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Atmospheric Conditions ◽  
Production Chain ◽  
Near Surface ◽  
Surface Mass ◽  
Future Assessment

Abstract. The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheetproperties since 2007. Currently the PROMICE automatic weather station network includes 25 instrumented sites in Greenland.Accurate measurements of the surface and near-surface atmospheric conditions in a changing climate is important for reliablepresent and future assessment of changes to the Greenland ice sheet. Here we present the PROMICE vision, methodology,and each link in the production chain for obtaining and sharing quality-checked data. In this paper we mainly focus on thecritical components for calculating the surface energy balance and surface mass balance. A user-contributable dynamic webbaseddatabase of known data quality issues is associated with the data products at (https://github.com/GEUS-PROMICE/PROMICE-AWS-data-issues/). As part of the living data option, the datasets presented and described here are available atDOI: 10.22008/promice/data/aws, https://doi.org/10.22008/promice/data/aws (Fausto and van As, 2019).

scholarly journals Assessing the accuracy of Greenland ice sheet ice ablation measurements by pressure transducer

2012 ◽  
Vol 58 (212) ◽  
pp. 1144-1150 ◽  
Author(s):  
Robert S. Fausto ◽  
Dirk Van As ◽  
Andreas P. Ahlstrøm ◽  
Michele Citterio
Keyword(s):  
Time Series ◽  
Pressure Transducer ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ablation Rate ◽  
Absolute Pressure ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Vertical Column ◽  
Physically Based

AbstractWe present a method of measuring ice ablation using an absolute pressure transducer as part of an automatic weather station (AWS) system, which we have installed in 17 locations on the Greenland ice sheet. The pressure transducer assembly is drilled into the ice, enclosed in a hose filled with antifreeze liquid. The pressure signal registered by the transducer is that of the vertical column of liquid over the sensor, which can be translated to depth, and ice ablation rate, knowing the density of the liquid. Measuring at sub-daily timescales, this assembly is well suited to monitoring ice ablation in remote regions, with clear advantages over other, well-established methods. The pressure transducer system has the potential to monitor ice ablation for several years without re-drilling, and the system is suitable for high-ablation areas (>5ma-1). A routine to transform raw measurements into ablation values is presented, including a physically based method to remove air-pressure variability from the signal. The pressure transducer time series is compared to that recorded by a sonic ranger for the climatically hostile setting on the Greenland ice sheet.

scholarly journals Greenland bare-ice albedo from PROMICE automatic weather station measurements and Sentinel-3 satellite observations

2021 ◽  
Vol 47 ◽  
Author(s):  
Adrien Wehrlé ◽  
Jason E. Box ◽  
Masashi Niwano ◽  
Alexandre M. Anesio ◽  
Robert S. Fausto
Keyword(s):  
Time Series ◽  
Snow Cover ◽  
Satellite Imagery ◽  
Spatial Dependence ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Satellite Observations ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Weather Stations

The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) provides surface meteorological and glaciological measurements from widespread on-ice automatic weather stations since mid-2007. In this study, we use 105 PROMICE ice-ablation time series to identify the timing of seasonal bare-ice onset preceded by snow cover conditions. From this collection, we find a bare-ice albedo at ice-ablation onset (here called bare-ice-onset albedo) of 0.565 ± 0.109 that has no apparent spatial dependence among 20 sites across Greenland. We then apply this snow-to-ice albedo transition value to measure the variations in daily Greenland bare-ice area in Sentinel-3 optical satellite imagery covering the extremely low and high respective melt years of 2018 and 2019. Daily Greenland bare-ice area peaked at 153 489 km² in 2019, 1.9 times larger than in 2018 (80 220 km²), equating to 9.0% (in 2019) and 4.7% (in 2018) of the ice sheet area.

scholarly journals The Spatiotemporal Variability of Cloud Radiative Effects on the Greenland Ice Sheet Surface Mass Balance

2020 ◽  
Vol 47 (12) ◽  
Author(s):  
M. Izeboud ◽  
S. Lhermitte ◽  
K. Van Tricht ◽  
J. T. M. Lenaerts ◽  
N. P. M. Van Lipzig ◽  
...  
Keyword(s):  
Mass Balance ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Spatiotemporal Variability ◽  
Surface Mass Balance ◽  
Radiative Effects ◽  
Surface Mass ◽  
Sheet Surface ◽  
Cloud Radiative Effects

scholarly journals Climatology and ablation at the South Greenland ice sheet margin from automatic weather station observations

2009 ◽  
Vol 3 (1) ◽  
pp. 117-158 ◽  
Author(s):  
D. van As ◽  
C. E. Bøggild ◽  
S. Nielsen ◽  
A. P. Ahlstrøm ◽  
R. S. Fausto ◽  
...  
Keyword(s):  
Surface Albedo ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Katabatic Wind ◽  
Weather Station ◽  
Automatic Weather Station ◽  
The South ◽  
Near Surface ◽  
Highly Sensitive ◽  
Wind Events

Abstract. We describe the climatology from a meteorological dataset acquired from automatic weather station observations done in the ablation zone of the Greenland Ice Sheet between 2001 and 2007. Stations were placed in three regions below the polar circle: on the southern tip of the ice sheet, on a calving glacier in the Nuuk fjord, and on the south-eastern ice margin near Tasiilaq. The yearly cycles in temperature, relative humidity and wind speed reveal the largest variability in wintertime, causing annual values to depend largely on winter values. Adding to wintertime variability are extremely strong and cold katabatic wind events in the southeast ("piteraqs"). During summer no pronounced daily cycle in near-surface atmospheric parameters is recorded in the three regions, in spite of a large cycle in solar radiation, dominantly regulating surface melt. Net ablation is largest at the southernmost station due to low surface albedo, and can be up to six metres per year, but is highly sensitive to the timing of the start of the ice ablation season. Illustrative of this is that similar ablation amounts are found in the Nuuk fjord region where little or no snow accumulates in winter.

scholarly journals Programme for Monitoring of the Greenland Ice Sheet (PROMICE) automatic weather station data

2021 ◽  
Vol 13 (8) ◽  
pp. 3819-3845
Author(s):  
Robert S. Fausto ◽  
Dirk van As ◽  
Kenneth D. Mankoff ◽  
Baptiste Vandecrux ◽  
Michele Citterio ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Atmospheric Conditions ◽  
Production Chain ◽  
Near Surface ◽  
Surface Mass ◽  
Future Assessment ◽  
Critical Components

Abstract. The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) has been measuring climate and ice sheet properties since 2007. Currently, the PROMICE automatic weather station network includes 25 instrumented sites in Greenland. Accurate measurements of the surface and near-surface atmospheric conditions in a changing climate are important for reliable present and future assessment of changes in the Greenland Ice Sheet. Here, we present the PROMICE vision, methodology, and each link in the production chain for obtaining and sharing quality-checked data. In this paper, we mainly focus on the critical components for calculating the surface energy balance and surface mass balance. A user-contributable dynamic web-based database of known data quality issues is associated with the data products at https://github.com/GEUS-Glaciology-and-Climate/PROMICE-AWS-data-issues/ (last access: 7 April 2021). As part of the living data option, the datasets presented and described here are available at https://doi.org/10.22008/promice/data/aws (Fausto et al., 2019).

scholarly journals Snow surface height variations on the Antarctic ice sheet in Princess Elizabeth Land, Antarctica: 1 year of data from an automatic weather station

2004 ◽  
Vol 39 ◽  
pp. 181-187 ◽  
Author(s):  
Qin Dahe ◽  
Xiao Cunde ◽  
Ian Allison ◽  
Bian Lingen ◽  
Rod Stephenson ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Cloud Amount ◽  
Snow Accumulation ◽  
Strong Wind ◽  
Weather Station ◽  
Automatic Weather Station ◽  
Antarctic Ice Sheet ◽  
Total Cloud Amount ◽  
Surface Snow ◽  
The Antarctic

AbstractThe net surface snow accumulation on the Antarctic ice sheet is determined by a combination of precipitation, sublimation and wind redistribution. We present a 1 year record of hourly snow-height measurements that shows its seasonal variability. The measurements were made with an ultrasonic sensor mounted on an automatic weather station (AWS) installed at LGB69, Princess Elizabeth Land, Antarctica (70.835˚S, 77.075˚E; 1850 ma.s.l.). The average accumulation at this site is approximately 0.70 m snow a–1. Throughout the winter, between April and September, there was little change in surface snow height. The strongest accumulation occurred during the period October–March, with four episodic increases occurring during 2002. These episodic events coincided with obvious humidity ‘pulses’ and decreases of incoming solar radiation as recorded by the AWS. Observations of the total cloud amount at Davis station, 160 km north-northeast of LGB69, showed good correlation with major accumulation events recorded at LGB69. There was an obvious anticorrelation between the lowest cloud height at Davis and the daily accumulation rate at LGB69. Although there was no correlation over the total year between wind speed and accumulation at LGB69, large individual accumulation events are associated with episodes of strong wind. Strong accumulation events at LGB69 are associated with major storms in the region and inland transport of moist air masses from the coast.

scholarly journals The firn meltwater Retention Model Intercomparison Project (RetMIP): Evaluation of nine firn models at four weather station sites on the Greenland ice sheet

2020 ◽  
Author(s):  
Baptiste Vandecrux ◽  
Ruth Mottram ◽  
Peter L. Langen ◽  
Robert S. Fausto ◽  
Martin Olesen ◽  
...  
Keyword(s):  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Weather Station ◽  
Model Intercomparison ◽  
Retention Model ◽  
Intercomparison Project ◽  
In Situ Observations ◽  
Over Time ◽  
Eulerian Models

Abstract. Perennial snow, or firn, covers 80 % of the Greenland ice sheet and has the capacity to retain part of the surface meltwater, buffering the ice sheet’s contribution to sea level. Multi-layer firn models are traditionally used to simulate the firn processes and estimate meltwater retention. We present the output from nine firn models, forced by weather-station-derived mass and energy fluxes at four sites representative of the dry snow, percolation, ice slab and firn aquifer areas. We compare the model outputs and evaluate them against in situ observations. Models that explicitly account for deep meltwater percolation overestimate percolation depth and consequently firn temperature at the percolation and ice slab sites although they accurately simulate the recharge of the firn aquifer. Models using Darcy's law and a bucket scheme compare favourably to observations at the percolation site but only the Darcy models accurately simulate firn temperature and thus meltwater percolation at the ice slab site. We find that Eulerian models, that transfer firn through fixed layers, smooth sharp gradients in firn temperature and density over time. From the model spread, we find that simulated densities (respectively temperature) have an uncertainty envelope of ±60 kg m−3 (resp. ±14 °C) in the dry snow area and up to ±280 kg m−3 (resp. ±15–18 °C) at warmer sites.

scholarly journals How Well Are Clouds Simulated over Greenland in Climate Models? Consequences for the Surface Cloud Radiative Effect over the Ice Sheet

2018 ◽  
Vol 31 (22) ◽  
pp. 9293-9312 ◽  
Author(s):  
A. Lacour ◽  
H. Chepfer ◽  
N. B. Miller ◽  
M. D. Shupe ◽  
V. Noel ◽  
...  
Keyword(s):  
Cloud Cover ◽  
Climate Models ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Ground Level ◽  
Radiative Effect ◽  
Cloud Properties ◽  
Cloud Radiative Effect ◽  
Primary Driver ◽  
Cloud Radiative Effects

Using lidar and radiative flux observations from space and ground, and a lidar simulator, we evaluate clouds simulated by climate models over the Greenland ice sheet, including predicted cloud cover, cloud fraction profile, cloud opacity, and surface cloud radiative effects. The representation of clouds over Greenland is a central concern for the models because clouds impact ice sheet surface melt. We find that over Greenland, most of the models have insufficient cloud cover during summer. In addition, all models create too few nonopaque, liquid-containing clouds optically thin enough to let direct solar radiation reach the surface (−1% to −3.5% at the ground level). Some models create too few opaque clouds. In most climate models, the cloud properties biases identified over all Greenland also apply at Summit, Greenland, proving the value of the ground observatory in model evaluation. At Summit, climate models underestimate cloud radiative effect (CRE) at the surface, especially in summer. The primary driver of the summer CRE biases compared to observations is the underestimation of the cloud cover in summer (−46% to −21%), which leads to an underestimated longwave radiative warming effect (CRELW = −35.7 to −13.6 W m−2 compared to the ground observations) and an underestimated shortwave cooling effect (CRESW = +1.5 to +10.5 W m−2 compared to the ground observations). Overall, the simulated clouds do not radiatively warm the surface as much as observed.

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