Regional Greenland Accumulation Variability from Operation IceBridge Airborne Accumulation Radar

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

doi:10.5194/tc-2016-248

Cited by 11 publications

(31 citation statements)

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“…Comparisons between CloudSat and modeled accumulation rates with the airborne accumulation radar dataset of Lewis et al (). Each point represents a decadal (2006–2016) average in m w.e./a.…”

Section: Resultscontrasting

confidence: 65%

Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet

Ryan

Smith

et al. 2020

JGR Atmospheres

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The Greenland Ice Sheet is now the single largest cryospheric contributor to global sea‐level rise yet uncertainty remains about its future contribution due to complex interactions between increasing snowfall and surface melt. Reducing uncertainty in future snowfall predictions requires sophisticated, physically based climate models evaluated with present‐day observations. The accuracy of modeled snowfall rates, however, has yet to be systematically assessed because observations are sparse. Here, we produce high spatial resolution (15 km) snowfall climatologies (2006–2016) derived from CloudSat's 2C‐SNOW‐PROFILE product to evaluate climate model simulations of snowfall across the Greenland Ice Sheet. In comparison to accumulation datasets acquired from ice cores and airborne accumulation radar, we find that our CloudSat climatologies capture broad spatial patterns of snowfall in both the accumulation and ablation zones. By comparing our CloudSat snowfall climatologies with the Regional Atmospheric Climate Model Version 2.3p2 (RACMO2.3p2), Modèle Atmosphérique Régional 3.9 (MAR3.9), ERA5, and Community Earth System Model version 1 (CESM1), we demonstrate that climate models likely overestimate snowfall rates at the margins of the ice sheet, particularly in South, Southeast, and Northwest Greenland during autumn and winter. Despite this overestimation, there are few areas of the ice sheet where the models and CloudSat substantially disagree about the spatial pattern and seasonality of snowfall rates. We conclude that a combination of CloudSat snowfall observations and the latest generation of climate models has the potential to improve understanding of how snowfall rates respond to increasing air temperatures, thereby constraining one of the largest sources of uncertainty in Greenland's future contribution to global sea levels.

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Section: Resultscontrasting

confidence: 65%

Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet

Ryan

Smith

et al. 2020

JGR Atmospheres

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“…Arguably, VR-CESM28 now performs on-par with RCMs in these regions (Lewis et al, 2016). In transient simulations, the improved distribution of snowfall may prove pivotal as it modulates the timing and strength of the snow-albedo feedback (Picard et al, 2012) and ice advection.…”

Section: Discussionmentioning

confidence: 99%

Regional Grid Refinement in an Earth System Model: Impacts on the Simulated Greenland Surface Mass Balance

Lenaerts¹,

Kampenhout²,

Rhoades³

et al. 2018

Preprint

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In this study, the resolution dependence of the simulated Greenland Ice Sheet surface mass balance in the variableresolution Community Earth System Model (VR-CESM) is investigated. Coupled atmosphere-land simulations are performed on three regionally refined grids over Greenland at 1°(∼111 km), 0.5°(∼55 km), and 0.25°(∼28 km), maintaining a quasiuniform resolution of 1°(∼111 km) over the rest of the globe. The SMB in the accumulation zone is significantly improved compared to airborne radar and in-situ observations, with a general wetting at the margins and a drying in the interior GrIS. 5Total precipitation decreases with resolution, which is in line with best-available regional climate model results. In the ablation zone, VR-CESM starts developing a positive SMB bias in some locations. Potential driving mechanisms are proposed, amongst which are diversions in large scale circulation, changes in cloud cover, and changes in summer snowfall. Overall, our results demonstrate that VR-CESM is a viable new tool in the cryospheric sciences and can be used to dynamically downscale future scenarios and/or be interactively coupled to dynamical ice sheet models.

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“…In addition, variability in total precipitation (snow plus rain) is regulated by regional patterns of naturally occurring internal variability, such as the phase of the Greenland Blocking Index (GBI; Hanna et al, ), the Atlantic Multidecadal Oscillation (Chylek et al, ; Lewis et al, ), as well as the North Atlantic Oscillation (NAO) (Hurrel, ), and episodic Rossby wave‐breaking events on the flanks of the North Atlantic jet stream (Liu & Barnes, ). Greenland winter precipitation is moderately anticorrelated with the phase of the NAO (Bromwich et al, ; Hurrel, ; Hurrell & Van Loon, ).…”

Section: Ice Sheets As Components Of the Coupled Earth Systemmentioning

confidence: 99%

An Overview of Interactions and Feedbacks Between Ice Sheets and the Earth System

Fyke

Sergienko

Löfverström

et al. 2018

Reviews of Geophysics

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Ice sheet response to forced changes-such as that from anthropogenic climate forcing-is closely regulated by two-way interactions with other components of the Earth system. These interactions encompass the ice sheet response to Earth system forcing, the Earth system response to ice sheet change, and feedbacks resulting from coupled ice sheet/Earth system evolution. Motivated by the impact of Antarctic and Greenland ice sheet change on future sea level rise, here we review the state of knowledge of ice sheet/Earth system interactions and feedbacks. We also describe emerging observation and model-based methods that can improve understanding of ice sheet/Earth system interactions and feedbacks. We particularly focus on the development of Earth system models that incorporate current understanding of Earth system processes, ice dynamics, and ice sheet/Earth system couplings. Such models will be critical tools for projecting future sea level rise from anthropogenically forced ice sheet mass loss. Plain Language Summary Sea level rise from ice sheets depends closely on interactions betweenice sheets and the surrounding Earth system. These interactions determine how forcings to the climate system (such as from anthropogenic climate influences) translate to ice sheet change, which in turn impact the surrounding environment. This set of two-way interactions between ice sheets and the Earth system forms the basis for important, yet poorly understood feedback loops. This review article describes the current state of knowledge of ice sheet/Earth system interactions and feedbacks and describes promising observational techniques for better understanding their behavior. It also highlights challenges and opportunities in modeling these interactions and feedbacks using coupled ice sheet/Earth system models, which will ultimately be used to predict future sea level rise caused by ice sheet loss.

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Regional Greenland Accumulation Variability from Operation IceBridge Airborne Accumulation Radar

Cited by 11 publications

References 0 publications

Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet

Evaluation of CloudSat's Cloud‐Profiling Radar for Mapping Snowfall Rates Across the Greenland Ice Sheet

Regional Grid Refinement in an Earth System Model: Impacts on the Simulated Greenland Surface Mass Balance

An Overview of Interactions and Feedbacks Between Ice Sheets and the Earth System

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