One consequence of recent Arctic warming is an increased
occurrence and longer seasonality of above-freezing air temperature
episodes. There is significant disagreement in the literature concerning
potential physical connectivity between high-latitude open water duration
proximate to the Greenland Ice Sheet (GrIS) and late-season (i.e.,
end-of-summer and autumn) GrIS melt events. Here, a new date of sea ice
advance (DOA) product is used to determine the occurrence of Baffin Bay sea
ice growth along Greenland's west coast for the 2011–2015 period. Over the
2-month period preceding the DOA, northwest Atlantic Ocean and atmospheric
conditions are analyzed and linked to late-season melt events observed at a
series of on-ice automatic weather stations (AWSs) along the K-transect in
southwestern Greenland. Surrounding ice sheet, tundra, and coastal winds
from the Modèle Atmosphérique Régional (MAR) and Regional
Atmospheric Climate Model (RACMO) provide high-resolution spatial context to
AWS observations and are analyzed along with ERA-Interim reanalysis fields
to understand the meso-to-synoptic-scale (thermo)dynamic drivers of the melt
events. Results suggest that late-season melt events, which primarily occur
in the ablation area, are strongly affected by ridging atmospheric
circulation patterns that transport warm, moist air from the subpolar North Atlantic toward west Greenland. Increasing concentrations of North Atlantic
water vapor are shown to be necessary to produce melt conditions as autumn
progresses. While thermal conduction and advection off south Baffin Bay open waters impact coastal air temperatures, local marine air incursions are
obstructed by barrier flows and persistent katabatic winds along the western
GrIS margin.
Introduction
Substantial decline in Arctic sea ice extent and mass loss from the
Greenland Ice Sheet (GrIS) have been observed for the last four decades
(e.g., Serreze and Stroeve, 2015; Bamber et al., 2018). Under sustained
climate warming, sea and land ice are becoming increasingly sensitive to
changes in the frequency and duration of anomalous weather patterns (e.g.,
Overland and Wang, 2016; Hanna et al., 2014, 2018b). The overall mass balance
of the GrIS has contributed roughly 0.5 mm yr-1 to global mean sea-level rise since the early 1990s (van den Broeke et al., 2016), with about
60 % of the mass loss attributed to a decline in surface mass balance
(SMB) and 40 % associated with increased ice discharge (van den Broeke et
al., 2017). Observed warming of near-surface ocean waters west of Greenland
since at least the early 1990s is linked to accelerated submarine melt and
outlet glacier retreat (Holland et al., 2008; Straneo and Heimbach, 2013)
concurrent with more frequent summertime air temperature extremes along the
coast (Hanna et al., 2012; Mernild et al., 2014). These findings raise the
question of whether Baffin local ocean conditions are of importance in
governing the spatial extent and temporal variations in western GrIS melt.
Conflicting evidence has been presented in the literature over the past decade
regarding the importance of the warming of the nearby ocean on GrIS surface
melt. Regional climate model simulations have suggested that local sea
surface temperature (SST) impacts on GrIS climate and SMB are negligible due
to offshore flow arising from a prevailing katabatic wind regime (Hanna et
al., 2014; Noël et al., 2014). Using a statistical approach, Rennermalm
et al. (2009) found contemporaneous Baffin open water (<15 % sea
ice concentration, SIC) and western GrIS melt to be positively correlated
in late summer (1979–2007). The authors noted that the strongest,
statistically significant correlation (r=0.71) was observed in August near
the K-transect (Fig. 1) and was attributed, in part, to wind-driven onshore
transport of warm marine air. Hanna et al. (2009) evaluated lagged
correlations between July coastal air temperatures at Ilulissat and Nuuk
(∼200 km north and ∼300 km south of Kangerlussuaq, respectively) from Danish Meteorological Institute (DMI) weather stations and adjacent, offshore HadISST1 SST values in the preceding
and following 2 months. The authors noted a simultaneous, positive SST
relationship with Ilulissat temperatures (r=0.56), while Nuuk temperatures
were significantly correlated with offshore May–July SSTs (r>0.50) over the 1977–2006 record. Ballinger et al. (2018a) found significant
interannual correlations (r>0.40, p≤0.05) during 1979–2014
between Baffin freeze onset dates (from the Markus et al., 2009 product) and
September–December surface air temperatures (SAT) at most DMI stations
found along the west Greenland coastline. The authors found that
significant, positive correlations between Baffin and Labrador SST and
coastal SAT often persist through December after the onset of freeze.
Applying a similar approach and melt/freeze dataset, Stroeve et al. (2017)
showed Baffin and GrIS melt and freeze behaviors to be synchronous. The
authors noted that years with anomalously early sea ice melt tended to have
strong, upward turbulent heat fluxes and westerly winds atop developing open
water that transported surplus heat and moisture onto the ice sheet. Both
studies indicated that the synoptic, upper-level circulation pattern is
critical for modulating poleward heat and moisture transport and the surface
warming/melt processes toward the end of the melt season. Ballinger et al. (2018a) proposed a sea-ice–heat-flux feedback whereby upward turbulent heat
fluxes from Baffin Bay help maintain the high-pressure block aloft, with
anticyclonic southerly winds both inhibiting the autumn/winter ice pack
formation and transporting warm marine air onto the western Greenland coast.
This potential mechanism may have contributed to record Greenland blocking
events that occurred in October over successive years during the early to
mid-2000s (Hanna et al., 2018a).
Study area map with PROMICE and IMAU K-transect sites and adjacent
terrestrial DMI stations (Kangerlussuaq, WMO code 4231; and Sisimiut, WMO
code 4234). The inset displays the northwest Atlantic Arctic region with
superimposed GrIS topographically defined boundaries (adopted from Ohmura
and Reeh, 1991).
A paucity of literature focused on the Baffin Bay open water influence on
GrIS melt and SMB has left open the question of potential physical linkages.
Our primary goal in this paper is to evaluate and determine whether the
local ocean–atmosphere interactions have played a role in late-season GrIS
melt events spanning the end of boreal summer through autumn (e.g., Doyle et
al., 2015; Stroeve et al., 2017). We posit that if Baffin Bay open water
were to influence GrIS late-season melt events, the heat accumulated in the
marine layer from ocean-to-atmosphere turbulent fluxes would be transferred
directly to the ice sheet by onshore westerly winds. In addressing this
hypothesis, our analyses are geographically focused on the western slope of
the GrIS with emphasis on the K-transect (Fig. 1) as this area – with its
two on-ice automatic weather station (AWS) networks (described in Sect. 2.1) – is rich with in situ
records relative to the remainder of the ice sheet. We analyze data from
these in situ sources and additionally from a global atmospheric reanalysis
and regional climate models to address potential links between GrIS late-season melt and the local-scale Baffin Bay marine layer for the period of
overlapping data, 2011–2015. For completeness, we subsequently expand the
scale of meteorological analyses to consider the influence of greater
northwest Atlantic synoptic patterns on the melt episodes. The paper is
organized in the following manner: Sect. 2 outlines data sources, Sect. 3 describes methods employed, Sect. 4 covers the local and synoptic-scale
atmospheric interactions with GrIS melt, Sect. 5 discusses key results,
and Sect. 6 offers concluding remarks and makes suggestions for future
research.
DataPassive microwave records
Sea ice data are from the National Oceanic and Atmospheric
Administration/National Snow and Ice Data Center (NSIDC) Climate Data Record
of passive microwave SIC v3r1 product distributed by NSIDC (Meier et al., 2017). We use the “Goddard-merged” SICs that are produced using a
combination of the NASA Team and Bootstrap algorithms applied to satellite
passive microwave brightness temperatures (Peng et al., 2013). Daily
observations are available over the 1979–2015 period at a 25km×25km nominal grid spacing. The time series of daily SIC at each grid cell were
used to identify the sea ice date of advance (DOA), which is the date when
SIC increases to 15 % for the first time following the sea ice extent
(SIE) minima after Steele et al. (2019). Regional mean DOAs for Baffin Bay
were obtained from Bliss et al. (2019). The local DOA was determined from
the time series of SICs between 1 October and 31 March at each grid cell,
and then the local mean DOA was computed from 13 grid cells within the domain
66.5 to 67.5∘ N and 53 to 55∘ W. SIE was computed by
summing the area of grid cells (in km2) where SIC ≥15 %. At the
same spatial resolution as the SIC product, the passive microwave daily GrIS
melt time series of Mote (2007, 2014) is also used to classify the ice
surface environment in a binary manner (i.e., melt/no melt). Following the
Ohmura and Reeh (1991) topographic regions, we assess GrIS melt conditions
on the west-central portion of the ice sheet bounding the K-transect.
AWS data
Meteorological conditions from two AWS networks, the Programme for
Monitoring of the Greenland Ice Sheet (PROMICE; stations prefix “KAN”) and
Utrecht University Institute for Marine and Atmospheric Research (hereafter
IMAU; stations prefix “S”), are used in this study (Fig. 1). To examine
the possible Baffin Bay open water influence on observed surface air
temperatures from the approximate terminus position nearest the ocean
upslope across the longitudinal extent of the K-transect (referenced herein
as the combination of PROMICE and IMAU stations), we conduct analyses based
on temperature conditions monitored at KAN_B (see Sect. 3
for details). The operational record of KAN_B began in 2011
and represents the starting year for analysis, while the DOA record
concludes in 2015 marking the end of our study period. Data are obtained and
analyzed from seven weather stations distributed across the K-transect at
∼67∘ N during this period. The transect spans an
area from low-elevation tundra, approximately 1 km inland from the ice sheet
glacier terminus (KAN_B), to the lower accumulation area
(∼1800 m) at >140 km from the Russell Glacier terminus (KAN_U; see Fig. 1 and Table 1). AWS data used here
are recorded at approximately 2–3 m above the surface, though the heights
of the air temperature sensors are known to fluctuate due to snow
accumulation and melt season ablation (Charalampidis et al., 2015). Daily
mean air temperature (∘C), wind speed (m s-1), and wind
direction (0–360∘) are obtained from IMAU and PROMICE station
networks. The data series are mostly complete for the study period, and the
few missing values are filtered out prior to analyses. Additional details on
the respective PROMICE and IMAU AWS programs can be found in van As et al. (2011) and Smeets et al. (2018). We supplement K-transect data with daily
mean DMI AWS surface air temperatures obtained from Sisimiut (WMO code 4234)
and Kangerlussuaq (WMO code 4321). These data are used to further evaluate
spatial links between local Baffin Bay open water and air temperatures from
the tundra regions below the K-transect (Cappelen, 2018, 2019; Fig. 1).
Summary details of the PROMICE and IMAU AWS stations utilized in
this study, including their approximate geographic position (in decimal
degrees), elevation, and distance from the ice sheet terminus moving west to
east. KAN_B is located on the tundra, roughly 1 km to the
west of the terminus. Distances are rounded to the nearest km as on-ice AWS
sites are known to move ∼50–150 m yr-1 (van de Wal
et al., 2015).
AWS stationNetworkLatitudeLongitudeElevationDistance to/from(∘ N)(∘ W)(m a.s.l.)terminus (km)KAN_BPROMICE67.1350.183501S5IMAU67.0850.105006KAN_LPROMICE67.1049.9567012S6IMAU67.0749.38100037KAN_MPROMICE67.0748.84127061S9IMAU67.0548.22150088KAN_UPROMICE67.0047.031840142Atmospheric reanalysis and regional climate model fields
A number of ERA-Interim reanalysis (Dee et al., 2011) variables are analyzed
at their native 80 km spatial resolution to assess atmospheric conditions
across Greenland and the northwestern Atlantic Arctic sector. ERA-Interim
surface and upper-air temperatures, wind speeds, and moisture conditions
exhibit relatively small biases compared to Arctic observations (Bromwich et
al., 2016). The regional climate models MAR (Modèle Atmosphérique Régional) and RACMO (Regional
Atmospheric Climate Model) are also forced with
ERA-Interim fields at their lateral boundaries. Tropospheric winds and
specific humidity from the 1000 to 200 hPa (1000–200) atmospheric layer are
used to calculate a moisture flux variable referred to as integrated water
vapor transport (IVT); IVT is then classified using a self-organizing map
(SOM) approach (see formal description in Sect. 3). Surface–atmosphere interactions and regional atmospheric circulation
characteristics are further evaluated using 80 km native resolution
ERA-Interim fields including mean sea-level pressure (MSLP), 10 m
winds, latent and sensible heat fluxes, 500 hPa geopotential heights (GPH),
and winds averaged over the 1000–700 hPa layer.
Wind speed and direction at 10 m and 850 hPa from MAR and RACMO are
evaluated to understand low-level atmospheric flow over ocean–land–ice-sheet
areas surrounding the K-transect. Secondarily, we briefly discuss
intermodel differences within the planetary boundary layer and biases
against AWS observations. Both regional climate models are specifically
developed for simulating polar weather and climate, in particular over the
Greenland ice sheet (e.g., Fettweis et al., 2011; Noël et al., 2018).
MAR v3.9 fields at 15 km are used here (see Fettweis et al., 2017, for a
detailed model description). Relative to MAR v3.8 used in Delhasse et al. (2018), the main changes to MAR v3.9 consist of enhanced computational
efficiency, adjustments to some of the snow model parameters to better
compare with in situ observations, and improved MAR dynamical stability by
increasing the atmospheric filtering. RACMO2.3p2 fields (hereafter
referenced as RACMO2) at a horizontal resolution of 5.5 km are also used
(Noël et al., 2018). Model physics have not changed relative to the
previous 11 km version described in Noël et al. (2018). The refined
spatial resolution of the host model improves the depiction of
topographically complex terrain at the GrIS margins, such as small
peripheral glaciers and ice caps, and the representation of near-surface,
local winds.
North Atlantic atmospheric indices
Daily atmospheric indices are examined to characterize near-surface and
upper-level conditions within a historical context. The Greenland Blocking
Index (GBI) (Hanna et al., 2018a) describes daily mean 500 hPa GPH values
from 60–80∘ N and 20–80∘ W. The North Atlantic
Oscillation (NAO) index used here is adapted from Cropper et al. (2015) and
represents station-based daily MSLP differences between Iceland and the
Azores. Both versions of the respective indices are normalized by their day-of-year means and standard deviations for the common 1951–2000 base period.
Methods
Above-freezing daily air temperatures at on-ice AWS locations represent an
indicator of ice-sheet melt (Hock, 2005). A composite approach is applied to
characterize atmospheric conditions underlying late-season GrIS melt events,
defined here as occurring at the conclusion of boreal summer (i.e., late
August) and during autumn preceding sea ice advance on Baffin Bay (Table S1 in the Supplement). Two constraints are placed on the composite analyses. The first
constraint involves the length of the analysis period prior to DOA. Baffin
Bay ice freeze onset dates and sea surface temperatures have shown a 2-month lead time and positive, significant correlation with west Greenland
coastal air temperature variations (Hanna et al., 2009; Ballinger et al., 2018). Composites are constructed over a similar 2-month (60 d) period
with data additionally subdivided into 60–31 d (i.e., [-60,-31]) and 30–1 d (i.e., [-30,-1]) bins preceding each Baffin Bay DOA from 2011 to 2015.
Regarding the second constraint, the composite technique is intended to
isolate meteorological processes most common during KAN_B
daily mean air temperature events of ≥0∘C (T+) vs.
<0∘C (T-) and the spatial consistency of such conditions
across the longitudinal extent of the transect. To resolve the spatial
cohesiveness of melt events along the K-transect, daily mean air
temperatures at each K-transect station are composited (i.e., averaged) for
KAN_B T+ and T- days in the [-60,-31] and [-30,-1] periods. On average during 2011–2015, KAN_B T+ events
characterize ∼46 % of days in the [-60,-31] period, while
[-30,-1] events are less frequent and occur on 9 % of days preceding Baffin
Bay DOA. T+ comparisons between KAN_B and other K-transect
stations are provided in Table 2. Temporal overlap between above-freezing
temperatures at KAN_B vs. S5 (77 %) and
KAN_L (46 %) in columns 2–3 of Table 2 suggests spatial
coherence in the physical mechanisms forcing melt at least across part of
the lower ablation area.
Counts of above-freezing daily mean air temperature (T+) events
(n), 2011–2015, and the percentage of contemporaneous overlap (%) between
T+ events at KAN_B and S5, KAN_L, S6, KAN_ M, S9, or KAN_U. The [-60,-31] and
[-30,-1] periods reference time windows before respective annual dates of
Baffin Bay sea ice advance (DOA). As an example, 77 % of the time in the
30 to 60 d (i.e., [-60,-31]) window preceding Baffin DOA the T+ air
temperature threshold at KAN_B is also observed at S5.
AWS T compareT+T+T+T+T+n[-60,-31]%[-60,-31]n[-30,-1]%[-30,-1]%[-60,-1]S5 vs. KAN_B537796976KAN_L vs. KAN_B324686249S6 vs. KAN_B101432316KAN_M vs. KAN_B23184S9 vs. KAN_B110–1KAN_U vs. KAN_B0–0––∑ KAN_B T+ events69–13––
In a similar fashion to Carr et al. (2017), a Wilcoxon test is used to
evaluate differences in atmospheric variables and indices between T+
and T- events. This nonparametric test is intended for continuous data
series that do not follow underlying assumptions of the normal distribution,
making it appropriate for comparative analyses between extreme and
nonextreme meteorological observations. The null hypothesis of no
difference in atmospheric conditions between cases is rejected at the 95 % confidence level when p≤0.05.
To classify synoptic patterns of atmospheric moisture transport about
Greenland, integrated water vapor transport (IVT) is calculated from
ERA-Interim data following Eq. (1):
IVT=1g∫1000hPa200hPaqVdp,
where g is gravitational acceleration (9.80665 m s-2), q is specific
humidity (g kg-1), V is the vector wind (m s-1), and dp represents the difference between atmospheric pressure levels. Pressure levels are spaced at 50 hPa intervals between 1000 and 500 hPa, as well as 100 hPa
intervals from 500 to 200 hPa. To control for the IVT seasonal cycle,
the percentile rank of IVT (IVT PR) is calculated by comparing 6-hourly IVT
values at each grid point to the distribution of all IVT values within a
31 d centered window at that grid point during 1980–2016. The four
6-hourly IVT PR values during each day are then averaged to generate daily
mean IVT PR values.
Daily mean IVT PR data are classified using the SOM technique to produce a
matrix of moisture transport patterns, or nodes, that typically occur over
the Greenland region. The SOM is based on an unsupervised machine learning
algorithm that classifies each daily IVT PR field into the closest matching
SOM node. As in Mattingly et al. (2016), we utilize a 5×4 SOM configuration. We further classify SOM nodes – based on visual inspection of IVT PR patterns over Greenland – into “wet” (anomalously high IVT PR over
Greenland), “neutral” (near climatological median IVT PR), and “dry”
(anomalously low IVT PR) SOM node groups, and we test whether the frequency of
IVT patterns falling into each node group differs across T+ and T- events.
ResultsCharacteristics of Baffin Bay and west Greenland late-season melt
Time series depicting the conclusion of melt conditions across Baffin Bay
and the western GrIS are shown in Fig. 2. Later sea ice formation is
apparent in the DOA series, particularly from around 2000. Similarly, the
start of the last ≥3 d sequence of the Region 3 (west-central Greenland;
see inset in Fig. 1) 2 % or 4 % melt area also suggests progressively
later melt (and a later onset of freezing conditions). A significant break
in the 2 % series is highlighted by a drastic increase in variability from
1979–1999 (σ=21.17) to 2000–2015 (σ=44.25) that is
also present in the annual discharge records from the nearby Watson River
and Tasersiaq ice sheet catchments (Ahlstrøm et al., 2017; van As et al., 2018). Differences between the beginning of Baffin Bay sea ice advance and
the end of the ice sheet melt season have clearly narrowed in part due to
regional melt season lengthening. Some GrIS melt events since 2000 have
notably occurred after seasonal sea ice formation (i.e., 2002, 2004–2005,
2010).
Passive microwave-derived time series, 1979–2015, of the Baffin
Bay sea ice date of advance (DOA) and the date marking the beginning of the
last 3 d period of at least 2 % and 4 % melt over Region 3 (see inset in Fig. 1) of the Greenland Ice Sheet (GrIS).
Relative to the climatology defined as 1981–2010, sea ice advanced
∼11 d earlier in 2011 and on average ∼6 d later in 2012–2015 (Table S1). Inspection of the DOA for individual grid cells adjacent to the Sisimiut AWS, which is labeled 4234 in Fig. 1 and located ∼150 km west of the K-transect ice sheet margin, reveals a northward-extending notch where ice forms ∼30–60 d later than
the Baffin-wide DOA (Fig. 3). Interannual differences in the region's ice
cover advance, such as those observed 2011–2015, often depend on physical
factors including regional winds, ocean heat transport, and water-mass
changes (Myers et al., 2009; Ribergaard, 2014). For instance, strong
offshore winds and poleward circulation of warm water from the West
Greenland Slope Current often contribute to the local open water
persistence, while southward Arctic Water transports support earlier ice
formation patterns found in the east and north (Curry et al., 2014).
Maps of the Baffin Bay date of sea ice advance (DOA) for (a–e) 2011–2015. The location of Sisimiut (WMO code 4234) is marked in cyan, white indicates locations where DOA was not observed, and gray indicates land. Panel (f) shows reference grid coordinates for maps (a–e). DOY after 365 (or 366 in 2012) indicates that DOA occurs after 1 January the following year. Time series of sea ice extent (SIE) for the Baffin Bay region (black) and mean sea ice concentration (SIC) for the local domain (blue), 66.5 to 67.5∘ N and 53 to 55∘ W (blue polygon shown in a–f),
relative to the Baffin-wide DOA (vertical red line) for (g–k) 2011–2015. The vertical blue line shows the mean DOA for the local domain. The horizontal dotted line represents the 15 % SIC threshold used to identify the DOA.
Local meteorology of melt vs. nonmelt cases
Composites of air temperature, wind speed, and direction by
KAN_B T+ and T- events are shown in Fig. 4. Across the
transect, composite air temperature differences (T+ minus T- events) are
warmer by roughly 7 to 8 ∘C in the [-60,-31] window and 12 to
13 ∘C in the [-30,-1] period (Fig. 4a). These differences tend to be smallest near the coast and increase to S6 in the mid-ablation area
(∼1000 m a.s.l.) where contemporaneous melt occurs
∼14 %–16 % of the time (Table 2).
Composites of (a) near-surface air temperature, (b) wind speed, and (c) wind direction for the T+ and T- events at KAN_B preceding the Baffin Bay date of sea ice advance (DOA), 2011–2015.
Significant differences (p≤0.05) between T+ and T- composites over
similar time windows are shown by an asterisk (*) between the bars. Panel (d) shows daily mean wind speed as a function of direction for select, roughly equidistant K-transect PROMICE stations.
KAN_B receives stronger, more southerly winds during T+
events that tend to become weaker and more southerly in autumn (i.e.,
[-30,-1]). There tends to be a general wind speed increase during T+
events, while direction remains more or less unaltered. Statistically
significant directional change is more southerly, which is evident above the
long-term equilibrium line altitude at S9. These katabatic winds are
deflected to the right (southeasterly) by the Coriolis force as they travel
toward Baffin Bay (van den Broeke et al., 2009) and may be aided
additionally by synoptically driven southerly winds. There is also evidence
of wind speed intensification during [-60,-31]T+ events
(∼1–2 m s-1), and to a lesser magnitude similar
relationships hold during the [-30,-1] period (Fig. 4b). Increased wind
speeds in T+ vs. T- events are likely affected by the seaward
enhancement of the pressure gradient aided by longer periods of nearshore
open water (Fig. 5), while increased synoptic cyclone activity and lower
MSLP over Baffin Bay during the summer–autumn season transition may also
enhance offshore flows (McLeod and Mote, 2015). Wind speed increases may
also initiate positive (downward) sensible heat fluxes associated with low-elevation ice melt (Fig. 6). Just offshore, sensible and latent heat fluxes
are generally negative (upward) in T- events and near zero to slightly
positive during melt occurrences; positive turbulent flux differences in
T+ vs. T- events are apparent over oceanic areas from the Labrador Sea
extending northward into Baffin Bay and the western edge of Greenland. This
indicates decreased heat transfer from the ocean to atmosphere during T+
events relative to T- conditions, with southerly near-surface winds
indicative of warm air advection (Fig. 6).
North Atlantic mean sea-level pressure (MSLP) and 10 m wind
composites from ERA-Interim for T+ and T- events at KAN_B
and their differences for the two periods preceding the Baffin Bay date of
sea ice advance (DOA).
North Atlantic sensible heat flux (SHF), latent heat flux (LHF), and 10 m wind composites from ERA-Interim for T+ and T- events at KAN_B and their differences for the two periods preceding the Baffin Bay date of sea ice advance (DOA).
The K-transect offshore flows appear to represent a dynamic barrier to
Baffin Bay marine layer intrusions. To further examine lower tropospheric
flow across the ocean–land–ice interface, we similarly composite MAR and
RACMO2 winds at 10 m and 850 hPa (Figs. 7 and 8). In general, the MAR and
RACMO2 winds show directional consistency with overlaid PROMICE and IMAU
winds with a slight southerly bias in both products for [-30,-1] at
KAN_M and S9 in the upper ablation area. Simulated wind
speeds are ∼20 %–50 % stronger during T+ vs. T- events
(not shown) as corroborated by most of the AWS observations (Fig. 4b),
helping enhance sensible heat flux into the ice sheet in areas where
near-surface temperatures are above freezing. T+ events in RACMO2 and MAR
generally capture AWS observed wind speeds in the upper ablation area at
KAN_M (r2≥0.77) and lower accumulation area at
KAN_U (r2≥0.77) with low root mean squared errors
(RMSE <1.50 m s-1 in all cases). A slight, positive bias in
model-derived wind speed is evident at the ice sheet edge near
KAN_B (MAR r2=0.33, RACMO2 r2=0.58). We
note that height and therefore surface roughness differences between the AWS
measurements (2–3 m) and regional model 10 m winds may explain a portion of the bias at KAN_B. The 10 m winds extending from the west Greenland tundra into eastern Baffin Bay are notably weak and northerly in T- events while T+ events are comparably stronger and southerly (Figs. 7 and 8).
Composites of MAR 10 m (black arrows) and 850 hPa (green arrows)
vector winds for the T+ and T- events at KAN_B preceding
the Baffin Bay date of sea ice advance (DOA), 2011–2015. Wind observations
from PROMICE (red) and IMAU (yellow arrows) are overlaid for reference.
Composites of RACMO2 10 m (black arrows) and 850 hPa (green
arrows) vector winds for the T+ and T- events at KAN_B
preceding the Baffin Bay date of sea ice advance (DOA), 2011–2015. Wind observations from PROMICE (red arrows) and IMAU
(yellow arrows) are overlaid for reference.
The role of North Atlantic atmospheric patterns
Overplots of 500 hPa GPH, 1000–700 hPa mean wind, and IVT for Greenland and the surrounding northwest Atlantic region are shown in Fig. 9. Whereas T-
events tend to be characterized by northerly winds over the 1000–700 hPa
layer, the T+ events indicate southerly, on-ice transfer of subpolar air
aided by the presence of an upper-level trough over Baffin Island and
downwind ridging over Greenland (see left vs. right panel plots in Fig. 9, respectively). Higher GPH values are found over the ice sheet during T+
events as the 540 dam (i.e., 5400 m) contour extends across central
Greenland, while the same contour is located south of the island in T-
events. In both T+ cases, 1000–700 winds circulate poleward over the north
Labrador Sea aiding the heat and moisture transfer (as shown by heightened
IVT values in T+ relative to T-) to the western Greenland ice sheet during
[-60,-31] and [-30,-1] (Fig. 9). One notable difference between T+ cases
is that low-level southerly winds originate deeper (∼50∘ N) in the North Atlantic during the T+[-30,-1] case. Local
IVT maxima in both T+ events are concentrated over the southwest tip of
the island but remain ∼100 kg m-1 s-1 near the
K-transect. Comparatively, the depth-integrated moisture flux over much of
the west coast increases by a factor of 2–3 (4–5) during [-60,-31] ([-30,-1]) T+ vs. T- events. This finding suggests that moist,
onshore flow drives late-season GrIS melt events, and moreover higher IVT is
necessary to produce melt conditions as autumn progresses.
Composite plots of integrated vapor transport (IVT), 1000–700 hPa
winds, and 500 hPa GPH from ERA-Interim for T+ and T- events at
KAN_B for the two periods preceding the Baffin Bay date of
sea ice advance (DOA).
To further characterize and differentiate weather conditions by T±
event, we utilize a SOM of IVT PR fields and composite SOM-classified daily
IVT wet, dry, and neutral patterns (Fig. 10a, b). Analyses of the aggregated
frequencies suggest that the wet patterns (with anomalously high IVT vs.
climatology) occur significantly more often in T+ vs. T- events, and
such nodes are more common by a factor of >4.5 in the [-30,-1]
period (Fig. 10b). While some caution should be exercised as the absolute
frequency of these patterns decreases from roughly early ([-60,-31]) to late
([-30,-1]) autumn, humid atmospheric conditions appear to cause late-season
melt. Increased incidence of wet patterns coincides with negative (positive)
NAO (GBI) (both >|0.50| in T+ events; Fig. 10c) and a synoptic environment characterized by high surface (upper-level)
pressure anomalies. This is confirmed by Fig. 9 whereby the higher 500 GPH
values and 1000–700 mean winds during T+ events transport warm and moist
air masses from Labrador Sea and southerly maritime latitudes to much of the
western slope of the ice sheet to facilitate ablation-area melt.
Percentile rank of integrated vapor transport fields (IVT PR)
from ERA-Interim classified using a self-organizing map (SOM) approach (a)
and composites of (b) IVT PR SOM node frequencies by wet, neutral, and dry types (%), which are outlined in green, blue, and red respectively in the above figure. SOM aggregates in panel (b) represent the ratio of each pattern's occurrence to the sum of all patterns for each time period, and similarly colored bars sum to 100 %. Composites presented in panel (c) represent normalized Greenland Blocking Index (GBI) and North Atlantic Oscillation (NAO) values (unitless) for T+ and T- events at KAN_B for the two periods preceding the Baffin Bay date of
sea ice advance (DOA). Significant differences (p≤0.05) between T+
and T- composites over similar time windows are shown by an asterisk (*) between the bars.
Discussion
West Greenland summer and autumn air temperature variability and trends
during the last 3–4 decades have shown a strong response to increased
frequency and intensity of Greenland high-pressure blocking, negative NAO
patterns, and positive North Atlantic SST anomalies aided by background
anthropogenic forcing (Hanna et al., 2016; McLeod and Mote, 2016; Ballinger
et al., 2018a; Graeter et al., 2018). The current North Atlantic warm
period since the mid-1990s is characterized by a positive Atlantic
Multidecadal Oscillation phase and rising SSTs around southwestern Greenland
(Myers et al., 2009; Ribergaard, 2014), including just offshore of Sisimiut
(WMO code 4234 in Fig. 1) (orthogonal trend =+0.03∘C yr-1, p<0.05, for 1995–2015 period using the SST product
described in Ballinger et al., 2018b). Warming waters around the island are
influencing Baffin Bay sea ice and west GrIS melt processes (Hanna et al., 2013; McLeod and Mote, 2015; Ballinger et al., 2018a) and seasonality toward
earlier melt and later freeze (Stroeve et al., 2017). This melt area about
K-transect suggests local low SIC and open water, inferred upward turbulent
atmospheric heating, and onshore winds could influence nearby terrestrial
melt events. Moreover, Sisimiut SSTs fluctuate with air temperatures (over
the 60 d preceding DOA) in a statistically significant fashion for
2013–2015 at most K-transect stations with some distance decay noted upslope
from the edge of the ablation area at S9 (Fig. S1 in the Supplement). Summer and autumn west
Greenland near-coastal air temperatures are modulated by the thermal
properties of bordering SSTs (Hanna et al., 2009; Ballinger et al., 2018a).
Interannual differences in the strength of SST–air temperature relationships
(i.e., 2013–2015 vs. 2011–2012) suggest (1) processes driving warming
ocean waters and air temperatures over the GrIS are independent when
disparate wind directions occur at or near the ocean–tundra–ice-sheet
boundaries in years of weak-to-zero correlation (e.g., katabatic flows
contrasting near-coastal barrier flows; van den Broeke and Gallée,
1996) or alternatively (2) large-scale atmospheric circulation (i.e.,
near-surface and upper-level meridional winds) during years of positive,
statistically significant correlations modulates the nearshore surface
open water and ice sheet air temperatures (Stroeve et al., 2017). We
recognize that synoptic patterns may not necessarily be mutually exclusive
in these examples, but the study objectives do not include comparison of
high- and low-pressure features around Greenland for specific melt and
nonmelt events.
A number of studies have suggested that Baffin Bay marine layer interaction
with the ice sheet boundary layer is obstructed by zonal and meridional
flows such as the west coast plateau jet feature and katabatic winds (Hanna
et al., 2009; Moore et al., 2013; Noël et al., 2014). Moore et al. (2013) noted a directionally consistent southerly 10 m wind field extending
over the western half of Greenland in summer and winter, while observational
studies similarly indicate a high frequency of southerly-to-southeasterly
winds over the K-transect (van den Broeke et al., 2009). Southerly
(easterly) 10 m winds are strongly linked to melt across two-thirds (the
southern third) of the ice sheet (Cullather and Nowicki, 2018). For an
expanded spatial perspective, we briefly examine air temperatures at the
next PROMICE station installment approximately 700 km north at Upernavik
(UPE; 72.89∘ N). We find UPE_L (220 m a.s.l. on the
ice sheet) melt occurs on the day of KAN_B T+ events on
>50 % of occasions in both [-60,-31] and [-30,-1] windows (not
shown). This suggests that above-freezing near-surface air often penetrates
at least to PROMICE station UPE_L with a relatively warm air
mass engulfing much of the west coast. Our observational and regional model
analyses further show that homogenous low-level winds extend coastward at
least to the tundra–ice-sheet interface near KAN_B (see Figs. 4c, 7, and 8) and produce a blocking effect that inhibits the inland
penetration of near-surface air from Baffin Bay (Noël et al., 2014). Of
note is the fact that the katabatic mechanism becomes stronger as the Baffin Bay DOA approaches
in late autumn, with more pronounced radiational cooling over the ice sheet
further supporting winds that prevent incursions of local marine air (van As
et al., 2014).
If late-season K-transect melt is minimally influenced by local Baffin Bay
open water, then what physical mechanisms drive the melt events? Composites
of the AWS K-transect observations and complementary regional model output
indicate that recent late-season melt events tend to be driven by southerly
synoptic patterns as opposed to local marine forcing. We provide evidence of
this physical forcing by [-60,-31] and [-30,-1]T+ composites that
show southerly flows of more warm, moist maritime air of lower latitude
origins relative to T- cases. As shown in Fig. 9, during the former event
period, air is transferred off the northern Labrador Sea to the west coast,
while a path of more southerly flow directs moist North Atlantic air masses
onto Baffin Bay and southwestern Greenland in the period immediately
preceding DOA. These wet synoptic patterns occur frequently under
anomalous (>|1σ|) positive GBI and
negative NAO values (Fig. 10b, c). We surmise from Mattingly et al. (2018)
that such patterns are particularly moisture-rich (≥85th percentile IVT climatological values) and often accompanied by atmospheric
rivers impacting Greenland; and their occurrence causes ablation-area melt
in nonsummer, low-insolation months through cloud radiative effects (i.e.,
increased downward longwave radiation transfer into the ice surface),
condensational latent heat release, increased near-surface winds and
turbulent heat flux, and liquid precipitation (Doyle et al., 2015; Binder et
al., 2017; Oltmanns et al., 2019). The southerly winds that propagate
moisture northward off the northwestern Atlantic Ocean are a product of
amplified upper-level geopotential height patterns and meridional winds in
T+ vs. T- events extending from the Denmark Strait and Irminger Sea on the
east coast of Greenland onto the ice sheet (Fig. 9). Mid-tropospheric
ridging, which is more pronounced in [-30,-1] than [-60,-31] events,
supports southerly winds that funnel heat and moisture from likely deeper in
the Atlantic basin to Baffin Bay and southwest Greenland to stimulate sea
ice and GrIS ablation-area melt conditions (Ahlstrøm et al., 2017;
Ballinger et al., 2018a, b; Hanna et al., 2018a). Cullather and Nowicki (2018)
similarly find that collocated, positive MSLP and 500 hPa GPH anomalies over
the Denmark Strait and Irminger Sea tend to be associated with melt events in
the basin encompassing the K-transect. Our analyses suggest that
ocean-to-atmosphere turbulent fluxes are suppressed over Baffin Bay during
T+ events, presumably due to the synoptic-scale warm air advection regime
reducing the temperature and humidity gradients between the sea surface and
atmosphere (Aemisegger and Papritz, 2018). Results further support North
Atlantic-air–ice-sheet coupling, rather than localized Baffin Bay
ocean–atmosphere processes, as a strong driver of transition season melt
before sea ice advances south of the K-transect. Synoptic patterns
associated with negative summer NAO and positive GBI incidence strongly
influence these melt events (Fig. 10a, b, c), prompting decreases in SMB,
and increase in the K-transect equilibrium line altitude over the last 10–15 years (Hanna et al., 2013; Smeets et al., 2018).
Conclusions
Temporal covariability between GrIS and Arctic sea ice mass loss suggests a
possible feedback whereby adjacent open water conditions,
ocean-to-atmosphere heat flux, and on-ice winds affect inland melt during
the end of the melt season. Based on our 2011–2015 analyses bridging the
end-of-summer/early autumn melt to the date of first-year Baffin Bay sea ice
advance, we do not find evidence to support the hypothesis that local open
water, resultant turbulent heating, and onshore winds have a pronounced
impact on inland ice melt events. These thermodynamic processes, in
particular, directly influence coastal air temperatures and have a
fingerprint on marine outlet glacier behaviors (Carr et al., 2017) but are
shown here to be inhibited by topographically influenced flows and synoptic
patterns whose interactions are not mutually exclusive. Furthermore, Baffin
Bay warming coupled with a longer autumn open water period has been
hypothesized to stimulate and invigorate upper-level, high-pressure blocking
that promotes southerly air advection over the west Greenland coast
(Ballinger et al., 2018a). This is consistent with the main conclusions of
Noël et al. (2014), which suggest that while warming waters around
Greenland minimally affect SMB beyond enhancing tidewater glacier retreat
rates SST forcing may indirectly influence GrIS SMB changes through impacts
on atmospheric circulation. However, in terms of direct forcing by the local
marine layer, beyond a near-coastal influence, our AWS, regional, and
synoptic wind analyses suggest that Baffin Bay does not represent a
substantial advective heat and moisture source to the ice sheet during our
5-year analyses.
Future late-season analyses, perhaps reconstructing K-transect
meteorological conditions back to the origins of the modern sea ice record,
might be insightful in comparing local ocean–ice-sheet interactions spanning
the 1990s shift from colder to warmer Baffin Bay summer SSTs (Ballinger et
al., 2018a). Assessing the temperature and pressure gradients and their
vertical profiles derived from retrospective analyses would also be useful
to categorize the structure, magnitude, and direction of regional winds,
including the katabatic regime, in attempting to provide a longer-term
perspective of analyses presented in this paper. Noël et al. (2014)
hypothesized that future sea-surface warming may exacerbate the division
between the local ocean and ice sheet by intensifying the temperature and
pressure gradient and hence resulting katabatic winds. Baffin Bay climate
and cryospheric changes in the last two decades suggest such an increased
blocking mechanism may already be underway. Moreover, stronger katabatic
winds might be enhanced further by an increasing intensity of autumn mid-troposphere high pressure over Greenland (Hanna et al., 2018a; see their
Fig. 1e). Synergistic future research should continue to monitor the spatial
extent, drivers, and physical effects of late-season melt through
observational products and regional modeling tools, including quantification
of late-season K-transect mass loss and runoff through the Watson River,
contributions to subsurface/firn processes, and preconditioning effects on
the following year's melt season.
Data availability
The DOA data are available at https://nsidc.org/data/NSIDC-0747/versions/1 (Steele et al., 2019). The AWS series can be obtained from DMI (https://www.dmi.dk/), IMAU (http://www.projects.science.uu.nl/iceclimate/), and PROMICE (https://www.promice.dk/home.html. The ERA-Interim data were downloaded from https://apps.ecmwf.int/datasets/. The GBI series are available at https://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/GBI_UL/. MAR and RACMO outputs are available from XF and BN, respectively, upon request. The datasets were last accessed on 10 July 2019.
The supplement related to this article is available online at: https://doi.org/10.5194/tc-13-2241-2019-supplement.
Author contributions
TJB and TLM conceived the study. TJB analyzed the observational data, with
assistance from MP and SG and led the writing of the manuscript. TLM
developed and processed the satellite-derived GrIS melt data. KSM conducted
the IVT classification and assisted with the creation of several figures.
ACB developed the DOA series and contributed related figures. EH provided
the daily GBI series, and DvA, CHR, PCJPS, MHR, and JC provided AWS or
oceanographic data and support. BN and XF developed and processed regional
model wind fields for RACMO2.3p2 and MAR v3.9, respectively. All authors
provided insights, feedback, and edited the manuscript drafts.
Competing interests
The authors declare that they have no conflict of interest.
Acknowledgements
The KAN PROMICE weather stations are funded by the Greenland Analogue
Project, and the IMAU K-transect stations are funded by the Netherland
Institute for Scientific Research and its Netherlands Polar Programme. Thomas J. Ballinger acknowledges support from Texas State University, as well as IASC, NSF, and UAF for sponsoring and facilitating an APECS travel grant to attend the POLAR 2018
Open Science Conference where valuable project-related feedback was
received. Brice Noël acknowledges funding from the Polar Program of the Netherlands
Organization for Scientific Research (NWO) and the Netherlands Earth System
Science Centre (NESSC). The authors thank David Bromwich and Jeffrey Miller
for constructive comments on early results, as well as Thomas Cropper for making
available his daily NAO series. Constructive remarks by the editor and referees were helpful in guiding manuscript improvements.
Review statement
This paper was edited by Valentina Radic and reviewed by Charalampos Charalampidis and two anonymous referees.
ReferencesAemisegger, F. and Papritz, L.: A climatology of strong large-scale ocean
evaporation events. Part I: Identification, global distribution, and
associated climate conditions, J. Climate, 31, 7287–7312,
10.1175/JCLI-D-17-0591.1, 2018.Ahlstrøm, A. P., Petersen, D., Langen P. L., Citterio, M., and Box, J. E.:
Abrupt shift in the observed runoff from the southwestern Greenland ice
sheet, Science Advances, 3, e1701169, 10.1126/sciadv.1701169, 2017.Ballinger, T. J., Hanna, E., Hall, R. J. Miller, J., Ribergaard, M. H., and
Høyer, J. L.: Greenland coastal air temperatures linked to Baffin Bay and
Greenland Sea ice conditions during autumn through regional blocking
patterns, Clim. Dynam., 50, 83–100, 10.1007/s00382-017-3583-3, 2018a.Ballinger, T. J., Hanna, E., Hall, R. J., Miller, J., Ribergaard, M. H.,
Overland, J. E., and Høyer, J. L.: Anomalous blocking over Greenland
preceded the 2013 extreme early melt of local sea ice, Ann. Glaciol., 59,
181-190, 10.1017/aog.2017.30, 2018b.Bamber, J. L., Westaway, R. M., Marzeion, B., and Wouters, B.: The land ice
contribution to sea level during the satellite era, Environ. Res. Lett., 13,
063008, 10.1088/1748-9326/aac2f0, 2018.Binder, H., Boettcher, M., Grams, C. M., Joos, H., and Wernli, H.:
Exceptional air mass transport and dynamical drivers of an extreme
wintertime Arctic warm event, Geophys. Res. Lett., 44, 12028–12036,
10.1002/2017GL075841, 2017.Bliss, A. C., Steele, M., Peng, G., Meier, W. N., and Dickinson, S.: Regional
variability of Arctic sea ice seasonal change climate indicators from a
passive microwave climate data record, Environ. Res. Lett., 14, 045003,
10.1088/1748-9326/aafb84, 2019,Bromwich, D. H., Wilson, A. B., Bai, L.-S., Moore, G. W. K., and Bauer, P.: A
comparison of the regional Arctic System Reanalysis and the global
ERA-Interim Reanalysis for the Arctic, Q. J. Roy. Meteor. Soc., 142, 644–658, 10.1002/qj.2527, 2016.
Cappelen, J. (Ed.): Weather observations from Greenland 1958–2017 – Observation
data with description, DMI Report 18-08, Danish Meteorological Institute (DMI), Copenhagen, Denmark, 2018.
Cappelen, J. (Ed.): Weather observations from Greenland 1958–2018 – Observation data with description, DMI Report 19-08, Danish Meteorological Institute (DMI), Copenhagen, Denmark, 2019.Carr, J. R., Stokes, C. R., and Vieli, A. S.: Threefold increase in
marine-terminating outlet glacier retreat rates across the Atlantic Arctic:
1992–2010, Ann. Glaciol., 58, 72–91, 10.1017/aog.2017.3, 2017.Charalampidis, C., van As, D., Box, J. E., van den Broeke, M. R., Colgan, W. T., Doyle, S. H., Hubbard, A. L., MacFerrin, M., Machguth, H., and Smeets, C. J. P. P.: Changing surface–atmosphere energy exchange and refreezing capacity of the lower accumulation area, West Greenland, The Cryosphere, 9, 2163–2181, 10.5194/tc-9-2163-2015, 2015.Cropper, T., Hanna, E., Valente, M. A., and Jónsson, T.: A daily
Azores-Iceland North Atlantic Oscillation index back to 1850, Geosci. Data
J., 2, 12–24, 10.1002/gdj3.23, 2015.Cullather, R. I. and Nowicki, S. M. J.: Greenland ice sheet surface melt and
its relation to daily atmospheric conditions, J. Climate, 31, 1897–1919,
10.1175/JCLI-D-17-0447.1, 2018.Curry, B. Lee, C. M., Petrie, B., Moritz, R. E., and Kwok, R.: Multiyear
volume, liquid freshwater, and sea ice transports through Davis Strait,
2004–2010, J. Phys. Oceanogr., 44, 1244–1266, 10.1175/JPO-D-13-0177.1, 2014.Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B. K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137, 553–597,
10.1002/qj.828, 2011.Delhasse, A., Fettweis, X., Kittel, C., Amory, C., and Agosta, C.: Brief communication: Impact of the recent atmospheric circulation change in summer on the future surface mass balance of the Greenland Ice Sheet, The Cryosphere, 12, 3409–3418, 10.5194/tc-12-3409-2018, 2018.Doyle, S., Hubbard, A., van de Wal, R. S., Box, J., van As, D., Scharrer, K.,
Meierbachtol, T. W., Smeets, P. C. J. P., Harper, J. T., Johansson, E., Mottram, R. H., Mikkelsen, A. B., Wilhelms, F., Patton, H., Christoffersen, P., and Hubbard, B.: Amplified melt and flow of the Greenland ice sheet driven by late-summer cyclonic rainfall, Nat. Geosci., 8, 647–653,
10.1038/ngeo2482, 2015.Fettweis, X., Tedesco, M., van den Broeke, M., and Ettema, J.: Melting trends over the Greenland ice sheet (1958–2009) from spaceborne microwave data and regional climate models, The Cryosphere, 5, 359–375, 10.5194/tc-5-359-2011, 2011.Fettweis, X., Box, J. E., Agosta, C., Amory, C., Kittel, C., Lang, C., van As, D., Machguth, H., and Gallée, H.: Reconstructions of the 1900–2015 Greenland ice sheet surface mass balance using the regional climate MAR model, The Cryosphere, 11, 1015–1033, 10.5194/tc-11-1015-2017, 2017.Graeter, K. A., Osterberg, E. C., Ferris, D. G., Hawley, R. L., Marshall, H. P., Lewis, G., Meehan, T., McCarthy, F., Overly, T., and Birkel, S. D.: Ice core records of west Greenland melt and climate forcing, Geophys. Res. Lett., 45, 3164–3172, 10.1002/2017GL076641, 2018.Graham, R. M., Cohen, L., Petty, A. A., Boisvert, L. N., Rinke, A., Hudson,
S. R., Nicolaus, M., and Granskog, M. A.: Increasing frequency and duration of Arctic winter warming events, Geophys. Res. Lett., 44, 6974–6983,
10.1002/2017GL073395, 2017.Hanna, E., Cappelen, J., Fettweis, X., Huybrechts, P., Luckman, A., and
Ribergaard, M. H.: Hydrologic response of the Greenland ice sheet: the role
of oceanographic warming, Hydrol. Process., 23, 7–30, 10.1002/hyp.7090, 2009.Hanna, E., Mernild, S. H., Cappelen, J., and Steffen, K.: Recent warming in
Greenland in a long-term instrumental (1881–2012) climatic context: I. Evaluation of surface air temperature records, Environ. Res. Lett., 7, 045404, 10.1088/1748-9326/7/4/045404, 2012.Hanna, E., Jones, J. M., Cappelen, J., Mernild, S. H., Wood, L., Steffen, K.,
and Huybrechts, P.: The influence of North Atlantic atmospheric and oceanic
forcing effects on 1900–2010 Greenland summer climate and ice melt/runoff,
Int. J. Climatol., 33, 862–880, 10.1002/joc.3475, 2013.
Hanna, E., Fettweis, X., Mernild, S. H., Cappelen, J., Ribergaard, M. H.,
Shuman, C. A., Steffen, K., Wood, L., and Mote, T. L.: Atmospheric and oceanic climate forcing of the exception Greenland ice sheet surface melt in summer 2012, Int. J. Climatol., 34, 1022–1037, 2014.Hanna, E., Cropper, T. E., Hall, R. J., and Cappelen, J.: Greenland Blocking
Index 1851–2015: a regional climate change signal, Int. J. Climatol., 36,
4847–4861, 10.1002/joc.4673, 2016.Hanna E., Hall, R. J., Cropper, T. E., Ballinger, T. J., Wake, L., Mote, T.,
and Cappelen, J.: Greenland Blocking Index daily series 1851–2015: analysis
of changes in extremes and links with North Atlantic and UK climate
variability and change, Int. J. Climatol., 38, 3546–3564,
10.1002/joc.5516, 2018a.Hanna, E., Fettweis, X., and Hall, R. J.: Brief communication: Recent changes in summer Greenland blocking captured by none of the CMIP5 models, The Cryosphere, 12, 3287–3292, 10.5194/tc-12-3287-2018, 2018b.Hock, R.: Glacier melt: a review of processes and their modelling, Prog.
Phys. Geog., 29, 362–391, 10.1191/0309133305pp453ra, 2005.Holland, D. M., Thomas, R. H., de Young, B., Ribergaard, M. H., and Lybert, B.: Acceleration of Jakobshavn Isbrae triggered by warm subsurface ocean waters, Nat. Geosci., 1, 659–664, 10.1038/ngeo316, 2008.Markus, T., Stroeve, J. C., and Miller, J.: Recent changes in Arctic sea ice
melt onset, freeze-up, and melt season length, J. Geophys. Res., 114,
C12024, 10.1029/2009JC005436, 2009.Mattingly, K. S., Ramseyer, C. A., Rosen, J. J., Mote, T. L., and Muthyala, R.: Increasing water vapor transport to Greenland Ice Sheet revealed using
self-organizing maps, Geophys. Res. Lett., 43, 9250–9258,
10.1002/2016GL070424, 2016.Mattingly, K. S., Mote, T. L., and Fettweis, X. L.: Atmospheric river impacts
on Greenland ice sheet surface mass balance, J. Geophys. Res.-Atmos., 123,
8538–8560, 10.1029/2018JD028714, 2018.McLeod, J. T. and Mote, T. L.: Assessing the role of precursor cyclones on
the formation of extreme Greenland blocking episodes and their impact on
summer melting across the Greenland ice sheet, J. Geophys. Res., 120,
12357–12377, 10.1002/2015JD023945, 2015.McLeod, J. T. and Mote, T. L.: Linking interannual variability in extreme
Greenland blocking episodes to the recent increase in summer melting across
the Greenland ice sheet, Int. J. Climatol., 36, 1484–1499,
10.1002/joc.4440, 2016.Meier, W., Fetterer, F., Savoie, M., Mallory, S., Duerr, R., and Stroeve,
J.: NOAA/NSIDC Climate Data Record of Passive Microwave Sea Ice
Concentration, Version 3, Revision 1, National Snow & Ice Data Center,
Boulder, Colorado, 10.7265/N59P2ZTG, 2017.Mernild, S. H., Hanna, E., Yde, J. C., Cappelen, J., and Malmros, J. K.:
Coastal Greenland air temperature extremes and trends 1890–2010: annual and
monthly analysis, Int. J. Climatol., 34, 1472–1487, 10.1002/joc.3777,
2014.Moore, G. W. K.: The December 2015 North Pole Warming Event and increasing
occurrence of such events, Scientific Reports, 6, 39084, 10.1038/srep39084, 2016.Moore, G. W. K., Renfrew, I. A., and Cassano, J. J.: Greenland plateau jets,
Tellus A, 65, 1748, 10.3402/tellusa.v65i0.17468, 2013.Mote, T. L.: Greenland surface melt trends 1979–2007: Evidence of a large
increase in 2007, Geophys. Res. Lett., 34, L22507,
10.1029/2007GL0311976, 2007.Mote, T. L.: MEaSUREs Greenland Surface Melt Daily 25 km EASE-Grid 2.0,
Version 1, Boulder, Colorado USA, NASA National Snow and Ice Data Center
Distributed Active Archive Center, 10.5067/MEASURES/CRYOSPHERE/nsidc-0533.001, 2014.Myers, P. G., Donnelly, C., and Ribergaard, M. H.: Structure and variability
of the west Greenland Current in summer derived from 6 repeat standard
sections, Prog. Oceanogr., 80, 93–112, 10.1016/j.pocean.2008.12.003, 2009.Noël, B., Fettweis, X., van de Berg, W. J., van den Broeke, M. R., and Erpicum, M.: Sensitivity of Greenland Ice Sheet surface mass balance to perturbations in sea surface temperature and sea ice cover: a study with the regional climate model MAR, The Cryosphere, 8, 1871–1883, 10.5194/tc-8-1871-2014, 2014.Noël, B., van de Berg, W. J., van Wessem, J. M., van Meijgaard, E., van As, D., Lenaerts, J. T. M., Lhermitte, S., Kuipers Munneke, P., Smeets, C. J. P. P., van Ulft, L. H., van de Wal, R. S. W., and van den Broeke, M. R.: Modelling the climate and surface mass balance of polar ice sheets using RACMO2 – Part 1: Greenland (1958–2016), The Cryosphere, 12, 811–831, 10.5194/tc-12-811-2018, 2018.
Ohmura, A. and Reeh, N.: New precipitation and accumulation maps for
Greenland, J. Glaciol., 37, 140–148, 1991.Oltmanns, M., Straneo, F., and Tedesco, M.: Increased Greenland melt triggered by large-scale, year-round cyclonic moisture intrusions, The Cryosphere, 13, 815–825, 10.5194/tc-13-815-2019, 2019.Onarheim, I. H., Eldevik, T., Smedsrud, L. H., and Stroeve, J. C.: Seasonal and regional manifestation of Arctic sea ice loss, J. Climate, 31, 4917–4932, 10.1175/JCLI-D-17-0427.1, 2018.
Overland, J. E. and Wang, M.: Recent extreme Arctic temperatures are due to
a split polar vortex, J. Climate, 29, 5609–5616, 2016.Peng, G., Meier, W. N., Scott, D. J., and Savoie, M. H.: A long-term and reproducible passive microwave sea ice concentration data record for climate studies and monitoring, Earth Syst. Sci. Data, 5, 311–318, 10.5194/essd-5-311-2013, 2013.Rennermalm, A. K., Smith, L. C., Stroeve, J. C., and Chu, V. W.: Does sea ice
influence Greenland ice sheet surface-melt?, Environ. Res. Lett., 4, 024011,
10.1088/1748-9326/4/2/024011, 2009.
Ribergaard, M. H.: Oceanographic investigations off west Greenland 2013, NAFO
Scientific Council Documents, 14/001, 2014.Serreze, M. C. and Stroeve, J.: Arctic sea ice trends, variability and
implications for seasonal forecasting, Philos. T. R. Soc. A, 373, 20140159, 10.1098/rsta.2014.0159,
2015.Smeets, P. C. J. P., Kuipers Munneke, P., van As, D., van den Broeke, M. R.,
Boot, W., Oerlemans, H., Snellen, H., Reijmer, C. H., and van de Wal, R. S. W: The K-transect in west Greenland: Automatic weather station data
(1993–2016), Arct. Antarct. Alp. Res., 50, S100002,
10.1080/15230430.2017.1420954, 2018.Steele, M., Bliss, A. C., Peng, G., Meier, W. N., and Dickinson, S.: Arctic sea ice seasonal change and melt/freeze climate indictors from satellite data, Version 1, National Snow & Ice Data Center Distributed Active Archive Center, Boulder, Colorado, 10.5067/KINANQKEZI4T, 2019.Straneo, F. and Heimbach, P.: North Atlantic warming and the retreat of
Greenland's outlet glaciers, Nature, 504, 36–43, 10.1038/nature12854,
2013.Stroeve, J. C., Mioduszewski, J. R., Rennermalm, A., Boisvert, L. N., Tedesco, M., and Robinson, D.: Investigating the local-scale influence of sea ice on Greenland surface melt, The Cryosphere, 11, 2363–2381, 10.5194/tc-11-2363-2017, 2017.Stroeve, J. C., Schroder, D., Tsamados, M., and Feltham, D.: Warm winter, thin ice?, The Cryosphere, 12, 1791–1809, 10.5194/tc-12-1791-2018, 2018.
van As, D., Fausto, R. S., and PROMICE Project Team: Programme for Monitoring
of the Greenland Ice Sheet (PROMICE): first temperature and ablation
records, Geol. Surv. Den. Greenl., 23, 73–76, 2011.
van As, D., Fausto, R. S., Steffen, K., and PROMICE project team: Katabatic
winds and piteraq storms: observations from the Greenland ice sheet, Geol.
Surv. Den. Greenl., 31, 83–86, 2014.van As, D., Hasholt, B., Ahlstrøm, A. P., Box, J. E., Cappelen, J., Colgan, W., Fausto, R. S., Mernild, S. H., Mikkelsen, A. B., Noël, B. P. Y., Petersen, D., and van den Broeke, M. R.: Reconstructing Greenland Ice
Sheet meltwater discharge through the Watson River (1949–2017), Arct.
Antarct. Alp. Res., 50, S100010, 10.1080/15230430.2018.1433799,
2018.
van den Broeke, M. R. and Gallée, H.: Observation and simulation of
barrier winds at the western margin of the Greenland ice sheet, Q. J. Roy.
Meteor. Soc., 122, 1365–1383, 1996.van den Broeke, M., Smeets, P., and Ettema, J.: Surface layer climate and
turbulent exchange in the ablation zone of the west Greenland ice sheet,
Int. J. Climatol., 29, 2309–2323, 10.1002/joc.1815, 2009.van den Broeke, M. R., Enderlin, E. M., Howat, I. M., Kuipers Munneke, P., Noël, B. P. Y., van de Berg, W. J., van Meijgaard, E., and Wouters, B.: On the recent contribution of the Greenland ice sheet to sea level change, The Cryosphere, 10, 1933–1946, 10.5194/tc-10-1933-2016, 2016.
van den Broeke, M., Box, J., Fettweis, X., Hanna, E., Noël, B., Tedesco,
M., van As, D., van de Berg, W. J., and van Kampenhout, L.: Greenland ice sheet surface mass loss: Recent developments in observation and modeling, Current Climate Change Reports, 3, 345–356, 10.1007/s40641-017-0084-8, 2017.van de Wal, R. S. W., Smeets, C. J. P. P., Boot, W., Stoffelen, M., van Kampen, R., Doyle, S. H., Wilhelms, F., van den Broeke, M. R., Reijmer, C. H., Oerlemans, J., and Hubbard, A.: Self-regulation of ice flow varies across the ablation area in south-west Greenland, The Cryosphere, 9, 603–611, 10.5194/tc-9-603-2015, 2015.