It is well established that anthropogenic chlorine-containing chemicals contribute to ozone layer depletion. The successful implementation of the Montreal Protocol has led to reductions in the ...atmospheric concentration of many ozone-depleting gases, such as chlorofluorocarbons. As a consequence, stratospheric chlorine levels are declining and ozone is projected to return to levels observed pre-1980 later this century. However, recent observations show the atmospheric concentration of dichloromethane-an ozone-depleting gas not controlled by the Montreal Protocol-is increasing rapidly. Using atmospheric model simulations, we show that although currently modest, the impact of dichloromethane on ozone has increased markedly in recent years and if these increases continue into the future, the return of Antarctic ozone to pre-1980 levels could be substantially delayed. Sustained growth in dichloromethane would therefore offset some of the gains achieved by the Montreal Protocol, further delaying recovery of Earth's ozone layer.
Antarctic supraglacial lakes (SGLs) have been linked to ice shelf collapse and the subsequent acceleration of inland ice flow, but observations of SGLs remain relatively scarce and their interannual ...variability is largely unknown. This makes it difficult to assess whether some ice shelves are close to thresholds of stability under climate warming. Here, we present the first observations of SGLs across the entire East Antarctic Ice Sheet over multiple melt seasons (2014-2020). Interannual variability in SGL volume is >200% on some ice shelves, but patterns are highly asynchronous. More extensive, deeper SGLs correlate with higher summer (December-January-February) air temperatures, but comparisons with modelled melt and runoff are complex. However, we find that modelled January melt and the ratio of November firn air content to summer melt are important predictors of SGL volume on some potentially vulnerable ice shelves, suggesting large increases in SGLs should be expected under future atmospheric warming.
Supraglacial lakes are known to influence ice melt and ice flow on the Greenland ice sheet and potentially cause ice shelf disintegration on the Antarctic Peninsula. In East Antarctica, however, our ...understanding of their behavior and impact is more limited. Using >150 optical satellite images and meteorological records from 2000 to 2013, we provide the first multiyear analysis of lake evolution on Langhovde Glacier, Dronning Maud Land (69°11′S, 39°32′E). We mapped 7990 lakes and 855 surface channels up to 18.1 km inland (~670 m above sea level) from the grounding line and document three pathways of lake demise: (i) refreezing, (ii) drainage to the englacial/subglacial environment (on the floating ice), and (iii) overflow into surface channels (on both the floating and grounded ice). The parallels between these mechanisms, and those observed on Greenland and the Antarctic Peninsula, suggest that lakes may similarly affect rates and patterns of ice melt, ice flow, and ice shelf disintegration in East Antarctica.
Key Points
SGLs are present 670 m asl on the grounded ice of an East Antarctic outlet glacier
SGLs on the floating ice tongue disappear during peak surface air temperatures
SGLs on the grounded ice drain into surface channels which reroute water across the glacier surface
The weakening and/or removal of floating ice shelves in Antarctica can induce inland ice flow acceleration. Numerical modelling suggests these processes will play an important role in Antarctica's ...future sea-level contribution, but our understanding of the mechanisms that lead to ice tongue/shelf collapse is incomplete and largely based on observations from the Antarctic Peninsula and West Antarctica. Here, we use remote sensing of structural glaciology and ice velocity from 2001 to 2020 and analyse potential ocean-climate forcings to identify mechanisms that triggered the rapid disintegration of ~2445 km2 of ice mélange and part of the Voyeykov Ice Shelf in Wilkes Land, East Antarctica between 27 March and 28 May 2007. Results show disaggregation was pre-conditioned by weakening of the ice tongue's structural integrity and was triggered by mélange removal driven by a regional atmospheric circulation anomaly and a less extensive latent-heat polynya. Disaggregation did not induce inland ice flow acceleration, but our observations highlight an important mechanism through which floating termini can be removed, whereby the break-out of mélange and multiyear landfast sea ice triggers disaggregation of a structurally-weak ice shelf. These observations highlight the need for numerical ice-sheet models to account for interactions between sea-ice, mélange and ice shelves.
Supraglacial lakes are important to ice sheet mass balance because their development and drainage has been linked to changes in ice flow velocity and ice shelf disintegration. However, little is ...known about their distribution on the world's largest ice sheet in East Antarctica. Here, we use ~5 million km
of high-resolution satellite imagery to identify >65,000 lakes (>1,300 km
) that formed around the peak of the melt season in January 2017. Lakes occur in most marginal areas where they typically develop at low elevations (<100 m) and on low surface slopes (<1°), but they can exist 500 km inland and at elevations >1500 m. We find that lakes often cluster a few kilometres down-ice from grounding lines and ~60% (>80% by area) develop on ice shelves, including some potentially vulnerable to collapse driven by lake-induced hydro-fracturing. This suggests that parts of the ice sheet may be highly sensitive to climate warming.
As surface melt is increasing on the Greenland Ice Sheet (GrIS), quantifying
the retention capacity of the firn layer is critical to linking meltwater
production to meltwater runoff. ...Firn-densification models have so far relied
on empirical approaches to account for the percolation–refreezing process,
and more physically based representations of liquid water flow might bring
improvements to model performance. Here we implement three types of water
percolation schemes into the Community Firn Model: the bucket approach, the
Richards equation in a single domain and the Richards equation in a
dual domain, which accounts for partitioning between matrix and fast
preferential flow. We investigate their impact on firn densification at four
locations on the GrIS and compare model results with observations. We find
that for all of the flow schemes, significant discrepancies remain with
respect to observed firn density, particularly the density variability in
depth, and that inter-model differences are large (porosity of the upper 15 m firn varies by up to 47 %). The simple bucket scheme is as efficient in
replicating observed density profiles as the single-domain Richards equation,
and the most physically detailed dual-domain scheme does not necessarily
reach best agreement with observed data. However, we find that the
implementation of preferential flow simulates ice-layer formation more
reliably and allows for deeper percolation. We also find that the firn model
is more sensitive to the choice of densification scheme than to the choice
of water percolation scheme. The disagreements with observations and the
spread in model results demonstrate that progress towards an accurate
description of water flow in firn is necessary. The numerous uncertainties
about firn structure (e.g. grain size and shape, presence of ice layers) and
about its hydraulic properties, as well as the one-dimensionality of firn
models, render the implementation of physically based percolation schemes
difficult. Additionally, the performance of firn models is still affected by
the various effects affecting the densification process such as
microstructural effects, wet snow metamorphism and temperature sensitivity
when meltwater is present.
Supraglacial lakes (SGLs) are now known to be widespread in Antarctica, where they represent an important component of ice sheet mass balance. This paper reviews how recent progress in satellite ...remote sensing has substantially advanced our understanding of SGLs in Antarctica, including their characteristics, geographic distribution and impacts on ice sheet dynamics. Important advances include: (a) the capability to resolve lakes at sub-metre resolution at weekly timescales; (b) the measurement of lake depth and volume changes at seasonal timescales, including sporadic observations of lake drainage events and (c) the integration of multiple optical satellite datasets to obtain continent-wide observations of lake distributions. Despite recent progress, however, there remain important gaps in our understanding, most notably: (a) the relationship between seasonal variability in SGL development and near-surface climate; (b) the prevalence and impact of SGL drainage events on both grounded and floating ice and (c) the sensitivity of individual ice shelves to lake-induced hydrofracture. Given that surface melting and SGL development is predicted to play an increasingly important role in the surface mass balance of Antarctica, bridging these gaps will help constrain predictions of future rapid ice loss from Antarctica.
Supraglacial lakes (SGLs) enhance surface melting and can flex and
fracture ice shelves when they grow and subsequently drain, potentially
leading to ice shelf disintegration. However, the seasonal ...evolution of SGLs
and their influence on ice shelf stability in East Antarctica remains poorly
understood, despite some potentially vulnerable ice shelves having high
densities of SGLs. Using optical satellite imagery, air temperature data
from climate reanalysis products and surface melt predicted by a regional
climate model, we present the first long-term record (2000–2020) of seasonal
SGL evolution on Shackleton Ice Shelf, which is Antarctica's northernmost
remaining ice shelf and buttresses Denman Glacier, a major outlet of the
East Antarctic Ice Sheet. In a typical melt season, we find hundreds of SGLs
with a mean area of 0.02 km2, a mean depth of 0.96 m and a mean total
meltwater volume of 7.45×106 m3. At their most extensive, SGLs
cover a cumulative area of 50.7 km2 and are clustered near to the
grounding line, where densities approach 0.27 km2 km−2. Here,
SGL development is linked to an albedo-lowering feedback associated with
katabatic winds, together with the presence of blue ice and exposed rock.
Although below-average seasonal (December–January–February, DJF)
temperatures are associated with below-average peaks in total SGL area and
volume, warmer seasonal temperatures do not necessarily result in higher SGL
areas and volumes. Rather, peaks in total SGL area and volume show a much
closer correspondence with short-lived high-magnitude snowmelt events. We
therefore suggest seasonal lake evolution on this ice shelf is instead more
sensitive to snowmelt intensity associated with katabatic-wind-driven
melting. Our analysis provides important constraints on the boundary
conditions of supraglacial hydrology models and numerical simulations of ice
shelf stability.
The formation and rapid drainage of supraglacial lakes (SGL) influences the mass balance and dynamics of the Greenland Ice Sheet (GrIS). Although SGLs are expected to spread inland during the 21st ...century due to atmospheric warming, less is known about their future spatial distribution and volume. We use GrIS surface elevation model and regional climate model outputs to show that at the end of the 21st century (2070–2099) approximately 9.8 ± 3.9 km3 (+113% compared to 1980‐2009) and 12.6 ± 5 km3 (+174%) of meltwater could be stored in SGLs under moderate and high representative concentration pathways (RCP 4.5 and 8.5), respectively. The largest increase is expected in the northeastern sector of the GrIS (191% in RCP 4.5 and 320% in RCP 8.5), whereas in west Greenland, where the most SGLs are currently observed, the future increase will be relatively moderate (55% in RCP 4.5 and 68% in RCP 8.5).
Key Points
We present a comprehensive new data set of potential supraglacial lake locations on the Greenland Ice Sheet
Supraglacial lakes are predicted to become more prevalent on the ice sheet during the 21st century with an increase in volume of 113–174%
According to our results, by the end of the 21st century, the majority of supraglacial lakes will be found in northeastern Greenland
Clustering – the automated grouping of similar data – can
provide powerful and unique insight into large and complex data sets, in a
fast and computationally efficient manner. While clustering has ...been used in
a variety of fields (from medical image processing to economics), its
application within atmospheric science has been fairly limited to date, and
the potential benefits of the application of advanced clustering techniques
to climate data (both model output and observations) has yet to be fully
realised. In this paper, we explore the specific application of clustering to
a multi-model climate ensemble. We hypothesise that clustering techniques can
provide (a) a flexible, data-driven method of testing model–observation
agreement and (b) a mechanism with which to identify model development
priorities. We focus our analysis on chemistry–climate model (CCM) output of
tropospheric ozone – an important greenhouse gas – from the recent
Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP).
Tropospheric column ozone from the ACCMIP ensemble was clustered using the
Data Density based Clustering (DDC) algorithm. We find that a multi-model
mean (MMM) calculated using members of the most-populous cluster identified
at each location offers a reduction of up to ∼ 20 % in the global
absolute mean bias between the MMM and an observed satellite-based
tropospheric ozone climatology, with respect to a simple, all-model MMM. On a
spatial basis, the bias is reduced at ∼ 62 % of all locations, with
the largest bias reductions occurring in the Northern Hemisphere – where
ozone concentrations are relatively large. However, the bias is unchanged at
9 % of all locations and increases at 29 %, particularly in the
Southern Hemisphere. The latter demonstrates that although cluster-based
subsampling acts to remove outlier model data, such data may in fact be
closer to observed values in some locations. We further demonstrate that
clustering can provide a viable and useful framework in which to assess and
visualise model spread, offering insight into geographical areas of agreement
among models and a measure of diversity across an ensemble. Finally, we
discuss caveats of the clustering techniques and note that while we have
focused on tropospheric ozone, the principles underlying the cluster-based
MMMs are applicable to other prognostic variables from climate models.
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