Regional Greenland accumulation variability from Operation IceBridge airborne accumulation radar

Lewis, Gabriel; Osterberg, E. C.; Hawley, R. L.; Whitmore, B.; Marshall, Hans Peter; Box, Jason E.

doi:10.5194/tc-11-773-2017

“…A similarly important development is the observation of snow accumulation using radar operated from airplanes [55,63,80], strongly improving the coverage of observed SMB in the GrIS accumulation zone. This is especially important because of previously reported large discrepancies in absolute values of GrIS accumulation [2,9,40].…”

Section: Surface Mass Balance Observations For Model Evaluationmentioning

confidence: 99%

Greenland Ice Sheet Surface Mass Loss: Recent Developments in Observation and Modeling

Broeke

¹

,

Box

²

,

Fettweis

³

et al. 2017

Curr Clim Change Rep

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Surface processes currently dominate Greenland ice sheet (GrIS) mass loss. We review recent developments in the observation and modeling of GrIS surface mass balance (SMB), published after the July 2012 deadline for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). Since IPCC AR5, our understanding of GrIS SMB has further improved, but new observational and model studies have also revealed that temporal and spatial variability of many processes are still poorly quantified and understood, e.g., bio-albedo, the formation of ice lenses and their impact on lateral meltwater transport, heterogeneous vertical meltwater transport ('piping'), the impact of atmospheric-circulation changes and mixed-phase clouds on the surface energy balance, and the magnitude of turbulent heat exchange over rough ice surfaces. As a result, these processes are only schematically or not at all included in models that are currently used to assess and predict future GrIS surface mass loss.

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“…cloud physics (Van Tricht et al, 2016) and turbulent fluxes (Noël et al, 2015;Fausto et al, 2016). Therefore, considerable efforts have been dedicated to evaluating and improving polar RCM output in Greenland (Ettema et al, 2010b;Van Angelen et al, 2013b;Lucas-Picher et al, 2012;Fettweis et al, 2017;Noël et al, 2015;Langen et al, 2017), using in situ SMB observations (Bales et al, 2001(Bales et al, , 2009van de Wal et al, 2012;Machguth et al, 2016), airborne radar measurements of snow accumulation (Koenig et al, 2016;Overly et al, 2016;Lewis et al, 2017) and meteorological records (Ahlstrøm et al, 2008;Kuipers Munneke et al, 2018;Smeets et al, 2018), including radiative fluxes that are required to close the ice sheet surface energy balance (SEB) and hence quantify surface melt energy.…”

Section: Introductionmentioning

confidence: 99%

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016)

Noël

¹

,

Berg

²

,

Wessem

³

et al. 2018

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Abstract. We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 . The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of cloud condensate into precipitation have been tuned to correct inland snowfall underestimation: snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves the spatial patterns and temporal variability of SMB compared with the previous model version, notably in the north-east, south-east and along the K-transect in south-western Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS presentday climate and SMB, and will be used for projections of the GrIS climate and SMB in response to a future climate scenario in a forthcoming study.

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“…Therefore, considerable efforts have been dedicated to evaluate and improve polar RCM output in Greenland (Ettema et al, 2010b;Van Angelen et al, 2013b;Lucas-Picher et al, 2012;Fettweis et al, 2017;Noël et al, 2015;Langen et al, 2017), using in situ SMB observations (Bales et al, 35 2001(Bales et al, 35 , 2009Machguth et al, 2016), airborne radar measurements of snow accumulation (Koenig et al, 2016;Overly et al, 2016;Lewis et al, 2017) and meteorological records (Ahlstrøm et al, 2008;Kuipers Munneke et al, 2017;Smeets et al, 2017), including radiative fluxes that are required to close the ice sheet surface energy balance (SEB), and hence quantify surface melt energy.…”

Section: Introductionmentioning

confidence: 99%

Modelling the climate and surface mass balance of polar ice sheets using RACMO2, Part 1: Greenland (1958–2016)

Noël¹,

Berg²,

Wessem³

et al. 2017

Preprint

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Abstract.We evaluate modelled Greenland ice sheet (GrIS) near-surface climate, surface energy balance (SEB) and surface mass balance (SMB) from the updated regional climate model RACMO2 ). The new model version, referred to as RACMO2.3p2, incorporates updated glacier outlines, topography and ice albedo fields. Parameters in the cloud scheme governing the conversion of 5 cloud condensate into precipitation have been tuned to correct inland snowfall underestimation; snow properties are modified to reduce drifting snow and melt production in the ice sheet percolation zone. The ice albedo prescribed in the updated model is lower at the ice sheet margins, increasing ice melt locally. RACMO2.3p2 shows good agreement compared to in situ meteorological data and point SEB/SMB measurements, and better resolves SMB patterns than the previous model version, 10 notably in the northeast, southeast, and along the K-transect in southwestern Greenland. This new model version provides updated, high-resolution gridded fields of the GrIS present-day climate and SMB, and will be used for future climate scenario projections in a forthcoming study. 1The Cryosphere Discuss., https://doi.org/10. 5194/tc-2017-201 Manuscript under review for journal The Cryosphere Discussion started: 6 October 2017 c Author(s) 2017. CC BY 4.0 License. IntroductionPredicting future mass changes of the Greenland ice sheet (GrIS) using regional climate models 15 (RCMs) remains challenging (Rae et al., 2012). The reliability of projections depend on the ability of RCMs to reproduce the contemporary GrIS climate and surface mass balance (SMB), i.e. snowfall accumulation minus ablation from meltwater runoff, sublimation and drifting snow erosion (Van Angelen et al., 2013a;. In addition, model simulations are affected by the quality of the re-analysis used as lateral forcing (Fettweis et al., , 2017Bromwich et al., 2015) 20 and by the accuracy of the ice sheet mask and topography prescribed in models (Vernon et al., 2013).Besides direct RCM simulations, the contemporary SMB of the GrIS has been reconstructed using various other methods, e.g. Positive Degree Day (PDD) models forced by statistically downscaled reanalyses (Hanna et al., 2011; Wilton et al., 2016), mass balance models forced by the climatological output of an RCM (HIRHAM4) (Mernild et al., 2010(Mernild et al., , 2011, and data assimilation from an RCM Therefore, considerable efforts have been dedicated to evaluate and improve polar RCM output in Greenland (Ettema et al., 2010b;Van Angelen et al., 2013b;Lucas-Picher et al., 2012;Fettweis et al., 2017;Noël et al., 2015;Langen et al., 2017), using in situ SMB observations (Bales et al., For more than two decades, the polar version of the Regional Atmospheric Climate Model (RACMO2) has been developed to simulate the climate and SMB of the Antarctic and Greenland ice sheets. In previous versions, snowfall accumulation was systematically underestimated in the GrIS interior, while melt was generally overestimated in the percolation zone (Noël et al....

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Regional Greenland accumulation variability from Operation IceBridge airborne accumulation radar

Cited by 43 publications

References 52 publications

Greenland Ice Sheet Surface Mass Loss: Recent Developments in Observation and Modeling

Greenland Ice Sheet Surface Mass Loss: Recent Developments in Observation and Modeling

Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016)

Modelling the climate and surface mass balance of polar ice sheets using RACMO2, Part 1: Greenland (1958–2016)

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