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

Izeboud, Maaike; Lhermitte, Stef; Tricht, Kristof Van; Lenaerts, Jan T. M.; Lipzig, Nicole Van; Wever, Nander

doi:10.1029/2020gl087315

Cited by 16 publications

(16 citation statements)

References 24 publications

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“…The AWSs measure temperature, relative humidity, wind speed and direction, air pressure, and the full radiation balance, i.e., incoming and reflected shortwave radiation, and incoming and outgoing longwave radiation. Data from these stations are presented in Reijmer 2002and Jakobs et al (2020) and have been previously used to evaluate remote sensing retrievals (Trusel et al, 2013), ice core paleoclimate records (Medley et al, 2018), and climate models (van Wessem et al, 2018). According to our analysis and consistent with the findings of Lenaerts et al (2017) and Gossart et al (2019), MERRA-2 captures observed 2 m air temperature, relative humidity, and wind speed well but significantly underestimates both ISWR and ILWR.…”

Section: Snowpack Atmospheric Forcingsupporting

confidence: 81%

Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density

et al. 2021

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Abstract. Estimates of snow and firn density are required for satellite-altimetry-based retrievals of ice sheet mass balance that rely on volume-to-mass conversions. Therefore, biases and errors in presently used density models confound assessments of ice sheet mass balance and by extension ice sheet contribution to sea level rise. Despite this importance, most contemporary firn densification models rely on simplified semi-empirical methods, which are partially reflected by significant modeled density errors when compared to observations. In this study, we present a new drifting-snow compaction scheme that we have implemented into SNOWPACK, a physics-based land surface snow model. We show that our new scheme improves existing versions of SNOWPACK by increasing simulated near-surface (defined as the top 10 m) density to be more in line with observations (near-surface bias reduction from −44.9 to −5.4 kg m−3). Furthermore, we demonstrate high-quality simulation of near-surface Antarctic snow and firn density at 122 observed density profiles across the Antarctic ice sheet, as indicated by reduced model biases throughout most of the near-surface firn column when compared to two semi-empirical firn densification models (SNOWPACK mean bias=-9.7 kg m−3, IMAU-FDM mean bias=-32.5 kg m−3, GSFC-FDM mean bias=15.5 kg m−3). Notably, our analysis is restricted to the near surface where firn density is most variable due to accumulation and compaction variability driven by synoptic weather and seasonal climate variability. Additionally, the GSFC-FDM exhibits lower mean density bias from 7–10 m (SNOWPACK bias=-22.5 kg m−3, GSFC-FDM bias=10.6 kg m−3) and throughout the entire near surface at high-accumulation sites (SNOWPACK bias=-31.4 kg m−3, GSFC-FDM bias=-4.7 kg m−3). However, we found that the performance of SNOWPACK did not degrade when applied to sites that were not included in the calibration of semi-empirical models. This suggests that SNOWPACK may possibly better represent firn properties in locations without extensive observations and under future climate scenarios, when firn properties are expected to diverge from their present state.

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Section: Snowpack Atmospheric Forcingsupporting

confidence: 81%

Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density

et al. 2021

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“…In locations of high surface albedo, such as northern Greenland and the highelevation accumulation zone, the SEB is resilient to changes in incoming shortwave radiation and, rather, longwave cloudradiative effects dominate (Wang B. et al, 2018Lenaerts et al, 2019 and references therein). In locations of lower surface albedo, such as southern Greenland and the lowelevation ablation zone, there is a greater sensitivity to changes in incoming shortwave radiation and, consequently, shortwave cloud-radiative effects dominate (Wang W. et al, 2018Lenaerts et al, 2019 and references therein;Izeboud et al, 2020). This physical framework explains the seemingly disparate observational results showing that suppressed cloud cover over southern Greenland during frequent blocking events drives GrIS mass loss (Hofer et al, 2017) while also pointing to the critical role of moisture transport and the presence of lowlevel clouds in generating surface melt at high elevations during extensive melt events (Nghiem et al, 2012;Bennartz et al, 2013;Neff et al, 2014;Van Tricht et al, 2016;Gallagher et al, 2018;Tedesco and Fettweis, 2020).…”

Section: Greenland Blocking: Impacts On Ice Sheet Surface Mass Balance and Relationships With Moisture Transportmentioning

confidence: 99%

Local and Remote Atmospheric Circulation Drivers of Arctic Change: A Review

et al. 2021

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Arctic Amplification is a fundamental feature of past, present, and modelled future climate. However, the causes of this “amplification” within Earth’s climate system are not fully understood. To date, warming in the Arctic has been most pronounced in autumn and winter seasons, with this trend predicted to continue based on model projections of future climate. Nevertheless, the mechanisms by which this will take place are numerous, interconnected. and complex. Will future Arctic Amplification be primarily driven by local, within-Arctic processes, or will external forces play a greater role in contributing to changing climate in this region? Motivated by this uncertainty in future Arctic climate, this review seeks to evaluate several of the key atmospheric circulation processes important to the ongoing discussion of Arctic amplification, focusing primarily on processes in the troposphere. Both local and remote drivers of Arctic amplification are considered, with specific focus given to high-latitude atmospheric blocking, poleward moisture transport, and tropical-high latitude subseasonal teleconnections. Impacts of circulation variability and moisture transport on sea ice, ice sheet surface mass balance, snow cover, and other surface cryospheric variables are reviewed and discussed. The future evolution of Arctic amplification is discussed in terms of projected future trends in atmospheric blocking and moisture transport and their coupling with the cryosphere. As high-latitude atmospheric circulation is strongly influenced by lower-latitude processes, the future state of tropical-to-Arctic teleconnections is also considered.

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“…Melt events longer than 10 d, unprecedented in the recent past, accounted for 18 % of the present day melt events. Obviously, these trends follow from global warming (Johannessen et al, 2004), characterized by a pronounced warming in the Arctic (e.g., Serreze and Barry, 2011), and large-scale melt events are expected to cover the entire ice sheet in the near future (Box et al, 2012). However, it is interesting to briefly discuss the importance of climate warming as compared to circulation-induced warming for the occurrence and spatial extent of melt events.…”

Section: Large-scale Greenland Melt Eventsmentioning

confidence: 99%

A Lagrangian analysis of the dynamical and thermodynamic drivers of large-scale Greenland melt events during 1979–2017

Hermann¹,

Papritz²,

Wernli³

2020

Weather Clim. Dynam.

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Abstract. In this study, we systematically investigate the dynamical and thermodynamic processes that lead to 77 large-scale melt events affecting high-elevation regions of the Greenland Ice Sheet (GrIS) in June–August (JJA) 1979–2017. For that purpose, we compute 8 d kinematic backward trajectories from the lowermost ∼500 m above the GrIS during these events. The key synoptic feature accompanying the melt events is an upper-tropospheric ridge southeast of the GrIS associated with a surface high-pressure system. This circulation pattern is favorable to induce rapid poleward transport (up to 40∘ latitude) of warm (∼15 K warmer than climatological air masses arriving on the GrIS) and moist air masses from the lower troposphere to the western GrIS and subsequently to distribute them in the anticyclonic flow over north and east Greenland. During transport to the GrIS, the melt event air masses cool by ∼15 K due to ascent and radiation, which keeps them just above the critical threshold to induce melting. The thermodynamic analyses reveal that the final warm anomaly of the air masses is primarily owed to anomalous horizontal transport from a climatologically warm region of origin. However, before being transported to the GrIS, i.e., in their region of origin, these air masses were not anomalously warm. Latent heating from condensation of water vapor, occurring as the airstreams are forced to ascend orographically or dynamically, is of secondary importance. These characteristics were particularly pronounced during the most extensive melt event in early July 2012, where, importantly, the warm anomaly was not preserved from anomalously warm source regions such as North America experiencing a record heat wave. The mechanisms identified here are in contrast to melt events in the low-elevation high Arctic and to midlatitude heat waves, where adiabatic warming by large-scale subsidence is essential. Considering the impact of moisture on the surface energy balance, we find that radiative effects are closely linked to the air mass trajectories and enhance melt over the entire GrIS accumulation zone due to (i) enhanced downward longwave radiation related to poleward moisture transport and a shift in the cloud phase from ice to liquid primarily west of the ice divide and (ii) increased shortwave radiation in clear-sky regions east of the ice divide. Given the ongoing increase in the frequency and the melt extent of large-scale melt events, the understanding of upper-tropospheric ridges over the North Atlantic, i.e., also Greenland blocking, and its representation in climate models is crucial in determining future GrIS accumulation zone melt and thus global sea level rise.

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

Cited by 16 publications

References 24 publications

Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density

Physics-based SNOWPACK model improves representation of near-surface Antarctic snow and firn density

Local and Remote Atmospheric Circulation Drivers of Arctic Change: A Review

A Lagrangian analysis of the dynamical and thermodynamic drivers of large-scale Greenland melt events during 1979–2017

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