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Abstract The exceptional atmospheric conditions that have accelerated Greenland Ice Sheet mass loss in recent decades have been repeatedly recognized as a possible dynamical response to Arctic amplification. Here, we present evidence of two potentially synergistic mechanisms linking high-latitude warming to the observed increase in Greenland blocking. Consistent with a prominent hypothesis associating Arctic amplification and persistent weather extremes, we show that the summer atmospheric circulation over the North Atlantic has become wavier and link this wavier flow to more prevalent Greenland blocking. While a concomitant decline in terrestrial snow cover has likely contributed to this mechanism by further amplifying warming at high latitudes, we also show that there is a direct stationary Rossby wave response to low spring North American snow cover that enforces an anomalous anticyclone over Greenland, thus helping to anchor the ridge over Greenland in this wavier atmospheric state. 

Abstract. The Greenland Ice Sheet has become the largest single frozen source of global sea level rise following a pronounced increase in meltwater runoff in recent decades. The pivotal role of anomalous anticyclonic circulation patterns in facilitating this increase has been widely documented; however, this change in atmospheric circulation has coincided with a rapidly warming Arctic. While amplified warming at high latitudes has undoubtedly contributed to trends in Greenland's mass loss, the contribution of this shift in background conditions relative to changes in regional circulation patterns has yet to be quantified. Here, we apply the pseudo-global warming method of dynamical downscaling to estimate the contribution of the change in the thermodynamic background state under global warming to observed Greenland Ice Sheet surface mass loss since the turn of the century. Our analysis demonstrates that, had the recent atmospheric dynamical forcing of the Greenland Ice Sheet occurred under a preindustrial setting, anomalous surface mass loss would have been reduced by over 62 % relative to observations. We show that the change in the thermodynamic environment under amplified Arctic warming has augmented melt of the ice sheet via longwave radiative effects accompanying an increase in atmospheric water vapor content. Furthermore, the thermodynamic contribution to surface mass loss over the exceptional melt years of 2012 and 2019 was less than half that of the long-term average, demonstrating a reduced influence during periods of strong synoptic-scale atmospheric forcing. 

This dataset contains output from a prescribed model experiment conducted to investigate the impact of snow cover loss over North America on summer atmospheric circulation. We utilized the National Center for Atmospheric Research’s Community Earth System Model version 2.2 to complete a 10-year control simulation. We then modified the land-surface restart files for May 1st of each year of the control period by reducing the snow cover over North America to zero. Using these modified files, we then completed a reduced snow simulation by rerunning three-month simulations from May through July for each of the ten years. This dataset contains both the 10-year control simulation as well as the May–July “no-snow” simulations for each year. More details about the experimental setup and example output can be found in the following publication: Preece, J.R., Mote, T.L., Cohen, J. et al. Summer atmospheric circulation over Greenland in response to Arctic amplification and diminished spring snow cover. Nat Commun 14, 3759 (2023). https://doi.org/10.1038/s41467-023-39466-6 

{"Abstract":["### Access\n\nData files can be accessed via: https://arcticdata.io/data/10.18739/A2TT4FV6W/\n\n### Overview\n\nThe Modèle Atmosphérique Régional (MAR) regional climate model is fully coupled to the Soil Ice Snow Vegetation Atmosphere Transfer (SISVAT) one-dimensional surface-atmosphere energy and mass transfer scheme (Fettweis et al., 2005, 2020; Lefebre et al., 2005). SISVAT simulates meltwater production, percolation, refreeze, and the impact of snow metamorphism on albedo via a multilayered snowpack model, CROCUS (Brun et al., 1989; Brun et al., 1992). Through extensive verification, MAR has proved to be well-suited for analyses of Greenland Ice Sheet (GrIS) surface mass balance (SMB) (Fettweis et al., 2011; Fettweis et al., 2020; Lefebre et al. 2005; Mattingly et al. 2020). This dataset contains the results of a model experiment that utilized the pseudo-global warming method of dynamical downscaling in MAR version 3.12. It includes a control run, in which MARv3.12 was forced with European Centre for Medium-Range Weather Forecasts Reanalysis v5 (ERA5) global reanalysis to simulate the historical GrIS SMB from 2000 to 2019, and two pseudo-global warming simulations: PGW1, in which we estimate the impact of the change in the thermodynamic background state under anthropogenic warming to GrIS surface mass loss and PGW2 in which we isolate the influence of changing sea-surface conditions.The naming convention for each file is explained using the example below:\n\nFile name format: ICE_experiment_year_month_start day_end day of month.nc\n\nExample: ICE_b03_2009_09_01_30.nc\n\nexperiment: specifies one of the following labels for each of the model experiments: "a02" indicates output from the PGW1 run, "b03" indicates PGW2 output, "c01" marks the 2000-2019 control run, and "c02" contains control data for a 1980-1989 reference period when the mass balance of the Greenland Ice Sheet was relatively stable.\n\nyear: indicates the model year\n\nmonth: indicates the model month\n\nstart day and end day: indicate the first and last days of the model month"]} 

Abstract. Understanding the role of atmospheric circulation anomalies on the surfacemass balance of the Greenland ice sheet (GrIS) is fundamental for improvingestimates of its current and future contributions to sea level rise. Here,we show, using a combination of remote sensing observations, regionalclimate model outputs, reanalysis data, and artificial neural networks, thatunprecedented atmospheric conditions (1948–2019) occurring in the summerof 2019 over Greenland promoted new record or close-to-record values ofsurfacemass balance (SMB), runoff, and snowfall. Specifically, runoff in 2019 ranked second withinthe 1948–2019 period (after 2012) and first in terms of surface massbalance negative anomaly for the hydrological year 1 September 2018–31 August 2019. The summer of 2019 was characterized by an exceptionalpersistence of anticyclonic conditions that, in conjunction with low albedoassociated with reduced snowfall in summer, enhanced the melt–albedofeedback by promoting the absorption of solar radiation and favoredadvection of warm, moist air along the western portion of the ice sheettowards the north, where the surface melt has been the highest since 1948.The analysis of the frequency of daily 500 hPa geopotential heights obtainedfrom artificial neural networks shows that the total number of days with thefive most frequent atmospheric patterns that characterized the summer of2019 was 5 standard deviations above the 1981–2010 mean, confirming theexceptional nature of the 2019 season over Greenland.