Recent Precipitation Decrease Across the Western Greenland Ice Sheet Percolation Zone

Lewis, Gabriel; Osterberg, E. C.; Hawley, Robert G.; Marshall, Hans Peter; Meehan, Tate; Graeter, K.; McCarthy, F.; Overly, T. B.; Thundercloud, Zayta; Ferris, D. G.

doi:10.5194/tc-2019-103

Cited by 9 publications

(17 citation statements)

References 49 publications

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“…Finally, the annual accumulation rates from ice cores are dispersed into a monthly temporal resolution by weighting the monthly (based on the 1960-2012 RACMO2.1 data) fraction of the annual total for each grid cell in the domain. The accumulation reconstruction has been evaluated by Lewis et al (2017Lewis et al ( , 2019.…”

Section: Box13 (Calibrated Rcm -5km)mentioning

confidence: 99%

GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice sheet

Fettweis¹

2020

Preprint

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The Greenland Ice Sheet (GrIS) mass loss has been accelerating at a rate of about 20 +/- 10 Gt/yr2 since the end of the 1990's, with around 60% of this mass loss directly attributed to enhanced surface meltwater runoff. However, in the climate and glaciology communities, different approaches exist on how to model the different surface mass balance (SMB) components using: (1) complex physically-based climate models which are computationally expensive; (2) intermediate complexity energy balance models; (3) simple and fast positive degree day models which base their inferences on statistical principles and are computationally highly efficient. Additionally, many of these models compute the SMB components based on different spatial and temporal resolutions, with different forcing fields as well as different ice sheet topographies and extents, making inter-comparison difficult. In the GrIS SMB model intercomparison project (GrSMBMIP) we address these issues by forcing each model with the same data (i.e., the ERA-Interim reanalysis) except for two global models for which this forcing is limited to the oceanic conditions, and at the same time by interpolating all modelled results onto a common ice sheet mask at 1 km horizontal resolution for the common period 1980-2012. The SMB outputs from 13 models are then compared over the GrIS to (1) SMB estimates using a combination of gravimetric remote sensing data from GRACE and measured ice discharge, (2) ice cores, snow pits, in-situ SMB observations, and (3) remotely sensed bare ice extent from MODerate-resolution Imaging Spectroradiometer (MODIS). Our results reveal that the mean GrIS SMB of all 13 models has been positive between 1980 and 2012 with an average of 340 +/- 112 Gt/yr, but has decreased at an average rate of -7.3 Gt/yr2 (with a significance of 96%), mainly driven by an increase of 8.0 Gt/yr2 (with a significance of 98%) in meltwater runoff. Spatially, the largest spread among models can be found around the margins of the ice sheet, highlighting the need for accurate representation of the GrIS ablation zone extent and processes driving the surface melt. In addition, a higher density of in-situ SMB observations is required, especially in the south-east accumulation zone, where the model spread can reach 2 mWE/yr due to large discrepancies in modelled snowfall accumulation. Overall, polar regional climate models (RCMs) perform the best compared to observations, in particular for simulating precipitation patterns. However, other simpler and faster models have biases of same order than RCMs with observations and remain then useful tools for long-term simulations. It is also interesting to note that the ensemble mean of the 13 models produces the best estimate of the present day SMB relative to observations, suggesting that biases are not systematic among models. Finally, results from MAR forced by ERA5 will be added in this intercomparison to evaluate the added value of using this new reanalysis as forcing vs the former ERA-Interim reanalysis (used in SMBMIP).&#160;

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Section: Box13 (Calibrated Rcm -5km)mentioning

confidence: 99%

GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice sheet

Fettweis¹

2020

Preprint

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“…Recent GrIS SMB decrease is driven by enhanced surface melting and runoff (van den Broeke et al, 2016;Trusel et al, 2018), caused by increasing atmospheric temperatures (Van Angelen et al, 2014;Fettweis et al, 2013a) and persistent anomalously high large-scale atmo-spheric blocking over the GrIS (Fettweis et al, 2013b;Belleflamme et al, 2015). In contrast, climate modeling and airborne radar observations indicate that GrIS precipitation has remained relatively constant (van den Broeke et al, 2016;Montgomery et al, 2020;Fettweis et al, 2020), with only an increase over parts of the interior (Csatho et al, 2014;Lewis et al, 2019). Throughout the remainder of the 21st century, sustained atmospheric warming is expected to cause continued GrIS mass loss (Pattyn et al, 2018), but the potential role of increasing precipitation on mitigating that GrIS mass loss is highly uncertain.…”

Section: Introductionmentioning

confidence: 99%

Present-day and future Greenland Ice Sheet precipitation frequency from CloudSat observations and the Community Earth System Model

et al. 2020

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Abstract. The dominant mass input component of the Greenland Ice Sheet (GrIS) is precipitation, whose amounts and phase are poorly constrained by observations. Here we use spaceborne radar observations from CloudSat to map the precipitation frequency and phase on the GrIS, and we use those observations, in combination with a satellite simulator to enable direct comparison between observations and model, to evaluate present-day precipitation frequency in the Community Earth System Model (CESM). The observations show that substantial variability of snowfall frequency over the GrIS exists, that snowfall occurs throughout the year, and that snowfall frequency peaks in spring and fall. Rainfall is rare over the GrIS and only occurs in regions under 2000 m elevation and in the peak summer season. Although CESM overestimates the rainfall frequency, it reproduces the spatial and seasonal variability of precipitation frequency reasonably well. Driven by the high-emission, worst-case Representative Concentration Pathway (RCP) 8.5 scenario, CESM indicates that rainfall frequency will increase considerably across the GrIS, and will occur at higher elevations, potentially exposing a much larger GrIS area to rain and associated meltwater refreezing, firn warming, and reduced storage capacity. This technique can be applied to evaluate precipitation frequency in other climate models and can aid in planning future satellite campaigns.

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“…2, green line). A smoothing length of 20 m has been used by other recent studies dealing with large-scale GPR transects as well (e.g., Lewis et al, 2019). We use the smoothed data for spatial extrapolation.…”

Section: Transect Data Analysismentioning

confidence: 99%

“…Within the last decade several studies have used radar systems to quantify accumulation variability in Greenland by tracking internal reflection horizons (IRHs; e.g., Dunse et al, 2008;Miège et al, 2013;Hawley et al, 2014;Karlsson et al, 2016;Koenig et al, 2016;Lewis et al, 2017Lewis et al, , 2019. While those studies aimed to track IRH variability using data from long ground transects of roughly 100 km (Miège et al, 2013) to more than 1000 km (Hawley et al, 2014) lengths or using airborne-radar data (Karlsson et al, 2016;Koenig et al, 2016;Lewis et al, 2017), only Dunse et al (2008) linked the point observations from snow pits and cores to the surrounding area.…”

Section: Introductionmentioning

confidence: 99%

Relating regional and point measurements of accumulation in southwest Greenland

Heilig

Eisen

Schneebeli³

et al. 2020

The Cryosphere

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Abstract. In recent decades, the Greenland ice sheet (GrIS) has frequently experienced record melt events, which have significantly affected surface mass balance (SMB) and estimates thereof. SMB data are derived from remote sensing, regional climate models (RCMs), firn cores and automatic weather stations (AWSs). While remote sensing and RCMs cover regional scales with extents ranging from 1 to 10 km, AWS data and firn cores are point observations. To link regional scales with point measurements, we investigate the spatial variability of snow accumulation (bs) within areas of approximately 1–4 km2 and its temporal changes within 2 years of measurements. At three different sites on the southwestern GrIS (Swiss Camp, KAN-U, DYE-2), we performed extensive ground-penetrating radar (GPR) transects and recorded multiple snow pits. If the density is known and the snowpack dry, radar-measured two-way travel time can be converted to snow depth and bs. We spatially filtered GPR transect data to remove small-scale noise related to surface characteristics. The combined uncertainty of bs from density variations and spatial filtering of radar transects is at 7 %–8 % per regional scale of 1–4 km2. Snow accumulation from a randomly selected snow pit is very likely representative of the regional scale of 1–4 km2 (with probability p=0.8 for a value within 10 % of the regional mean for KAN-U, and p>0.95 for Swiss Camp and DYE-2). However, to achieve such high representativeness of snow pits, it is required to determine the average snow depth within the vicinity of the pits. At DYE-2, the spatial pattern of snow accumulation was very similar for 2 consecutive years. Using target reflectors placed at respective end-of-summer-melt horizons, we additionally investigated the occurrences of lateral redistribution within one melt season. We found no evidence of lateral flow of meltwater in the current climate at DYE-2. Such studies of spatial representativeness and temporal changes in accumulation are necessary to assess uncertainties of the linkages of point measurements and regional-scale data, which are used for validation and calibration of remote-sensing data and RCM outputs.

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Recent Precipitation Decrease Across the Western Greenland Ice Sheet Percolation Zone

Cited by 9 publications

References 49 publications

GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice sheet

GrSMBMIP: Intercomparison of the modelled 1980-2012 surface mass balance over the Greenland Ice sheet

Present-day and future Greenland Ice Sheet precipitation frequency from CloudSat observations and the Community Earth System Model

Relating regional and point measurements of accumulation in southwest Greenland

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