Reply on RC1

Goelzer et al (2012) paint a portentous picture of what is likely to happen to the global sea-level over the next 1000 years. This worrying assessment is based on our current best understanding of how the world's giant ice sheets of Greenland and Antarctica, as well as a quarter of a million smaller glacial ice masses, and the ocean collectively respond to ongoing climate change. Theirs is a state of the science study that integrates these key contributors of sea-level change based on the latest models and current understanding, and an integrated Earth systems modelling approach termed LOVECLIM. As they point out in their study, only a handful of global climate models to date—i.e. models that are used to make predictions of future climate change—incorporate dynamically (fully) coupled ice-sheet models.

<strong class="journal-contentHeaderColor">Abstract.</strong> Climate change is particularly strong in Greenland, primarily as a result of changes in the transport of heat and moisture from lower latitudes. The atmospheric structures involved influence the surface mass balance (SMB) of the Greenland Ice Sheet (GrIS), and their patterns are largely explained by climate oscillations, which describe the internal climate variability. By using <span class="inline-formula"><i>k</i></span>-means clustering, we name the combination of the Greenland Blocking Index, the North Atlantic Oscillation index and the vertically integrated water vapor as NAG (North Atlantic influence on Greenland) with the optimal solution of three clusters (positive, neutral and negative phase). With the support of a polar-adapted regional climate model, typical climate features marked under certain NAG phases are inter-seasonally and regionally analyzed in order to assess the impact of large-scale systems from the North Atlantic on the surface energy budget (SEB) components over the GrIS. Given the pronounced summer mass loss in recent decades (1991–2020), we investigate spatio-temporal changes in SEB components within NAG phases in comparison to the reference period 1959–1990. We report significant atmospheric warming and moistening across all NAG phases. The pronounced atmospheric warming in conjunction with the increase in tropospheric water vapor enhance incoming longwave radiation and thus contribute to surface warming. Surface warming is most evident in winter, although its magnitude and spatial extent depend on the NAG phase. In summer, increases in net shortwave radiation are mainly connected to blocking systems (<span class="inline-formula">+</span> NAG), and their drivers are regionally different. In the southern part of Greenland, the atmosphere has become optically thinner due to the decrease in water vapor, thus allowing more incoming shortwave radiation to reach the surface. However, we find evidence that, in the southern regions, changes in net longwave radiation balance changes in net shortwave radiation, suggesting that the turbulent fluxes control the recent SEB changes. In contrast to South Greenland under <span class="inline-formula">+</span> NAG, the moistening of North Greenland has contributed to decreases in surface albedo and has enhanced solar radiation absorption. Regardless of the NAG phase, increases in multiple atmospheric variables (e.g., integrated water vapor and net longwave radiation) are found across the northern parts of Greenland, suggesting that atmospheric drivers beyond heat and moisture originated from the North Atlantic. Especially in the northern ablation zone, sensible heat flux has significantly increased in summer due to larger vertical and horizontal temperature gradients combined with stronger near-surface winds. We attribute the near-surface wind intensification to the emerging open-water feedback, whereby surface pressure gradients between the ice/snow-covered surface and adjacent open seas are intensified.

The Arctic is experiencing amplified climate warming, decreasing sea ice extent, increasingly earlier springtime snowmelt, and a related increase in fire activity. The transition from cold to warm season in the Arctic strongly varies between years, but our understanding of temperature and surface energy budget changes over the springtime is limited. Here we investigate intraseasonal variability of Arctic springtime temperature extremes, the subsequent surface energy budget component response, and their interannual trends over 40 years (1981 &amp;#8211; 2020) across the terrestrial Arctic (above 60&amp;#176; N) using ERA5-Land reanalysis data. We found the central and western Siberian regions to have the highest interannual variability in spring temperature anomaly among all Arctic regions during the 40-year period. Also in this region, we discovered the strength increased for heat extremes and decreased for cold extremes when comparing the first and the last 20 years of our study. Peaks in composited extreme temperature and surface energy budget anomalies were observed to occur concurrently, indicating temperature extremes are not driven by surface energy budget components. Lastly, by utilizing power spectrum analyses, we identified the primary driver of temperature anomaly interannual variability to be operating at a 1 to 2 week frequency. Based on our findings and observations in the recent literature, we hypothesize that the observed interannual variability in springtime temperature can be attributed to increased Arctic sea ice decline and an increase in the frequency and strength of associated atmospheric blocking events.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Greenland Ice Sheet has been losing mass at an accelerating rate over the past two decades. Understanding ice mass and glacier changes during the preceding several hundred years, prior to geodetic measurements, is more difficult because evidence of past ice extent in many places was later overridden. Saltmarshes provide the only continuous records of Relative Sea Level (RSL) from close to the Greenland Ice Sheet that span the period of time during and since the Little Ice Age (LIA) and can be used to reconstruct ice mass gain and loss over recent centuries. Saltmarsh sediments collected at the mouth of Dronning Marie Dal, close to the Greenland Ice Sheet margin in southeast Greenland, record RSL changes over the past c. 300 years through changing sediment and diatom stratigraphy. These RSL changes record a combination of processes that are dominated by local/regional changes in Greenland Ice Sheet mass balance during this critical period that spans the maximum of the LIA and 20th Century warming. In the early part of the record (1725&ndash;1762 CE) the rate of RSL rise is higher than reconstructed from the closest isolation basin at Timmiarmiut, but between 1762&ndash;1880 CE the RSL rate is within the error range of rate of RSL change recorded in the isolation basin. RSL begins to slowly fall around 1880 CE and then accelerates since the 1990s, with a total amount of RSL fall of 0.08 &plusmn;0.1 m in the last 140 years. Modelled RSL, which takes into account contributions from post-LIA Greenland Ice Sheet Glacio-isostatic Adjustment (GIA), ongoing deglacial GIA, the global non-ice sheet glacial melt fingerprint, contributions from thermosteric effects, the Antarctic mass loss sea-level fingerprint and terrestrial water storage, over-predicts the amount of RSL fall since the end of the LIA by at least 0.5 m. The GIA signal caused by post-LIA Greenland Ice Sheet mass loss is by far the largest contributor to this modelled RSL, and error in its calculation can have a large impact on RSL predictions at Dronning Marie Dal. We cannot reconcile the modelled RSL and the saltmarsh observations, even when moving the termination of the LIA to 1800 CE and reducing the post-LIA Greenland mass loss signal by 30 %, and a &lsquo;budget residual&rsquo; of +~2.5 mm/yr since the end of the LIA remains unexplained.

Rainfall events over Greenland ice sheet (GrIS) have become more frequent in recent decades. Several observed extreme rainfall (ER) events are accompanied by high GrIS surface melt. However, their role in surface energy budgets and the associated physical mechanisms remain poorly understood. Here we employ a surface energy balance (SEB) model to quantify the relative contributions of energy terms to surface melt energy (Qm) during ER events at QAS_L and QAS_U stations in southern GrIS. We further investigate the energy anomalies in terms of synoptic‐scale atmospheric conditions during ER events lasting three or more days (ER+3d). Our results indicate that during ER+3d events, nonradiative energy contributes 54% of Qm at QAS_L, near the ice sheet margin, with turbulent fluxes serving as the primary energy source. In contrast, at QAS_U, closer to the equilibrium line, Qm remains dominated by radiative energy, accounting for 61% of Qm. The contribution of rainfall heat flux remains small, at approximately 4% at QAS_L and 2% at QAS_U. Rainfall‐related atmospheric conditions trigger positive anomalies in turbulent fluxes and net radiation, due to strengthened cloud radiative forcing and increased turbulence scales in the near surface, which collectively contribute to high surface melt during ER+3d events. Therefore, the increased rainfall events have the potential to exacerbate surface mass loss by adding excess radiative and turbulent energy inputs in the future.

[1] In the paper “Climatic effects of 30 years of landscape change over the Greater Phoenix, Arizona, region: 1. Surface energy budget changes” by (Journal of Geophysical Research, 114, D05110, doi:10.1029/2008JD010745, 2009), the affiliations for C. P. Weaver are incorrect. He is not affiliated with Program on Food Security and the Environment, Stanford University, Stanford, California, USA. The correct affiliations are as follows: [2] Center for Environmental Prediction, Department for Environmental Sciences, Rutgers University, New Brunswick, New Jersey, USA. [3] Now at Global Change Research Program, U.S. Environmental Protection Agency, Washington, D. C., USA. [4] Also, there is a spelling error in G. Miguez-Macho's affiliation. Universidad is misspelled. The correct spelling is Universidade: Non-Linear Physics Group, Universidade de Santiago de Compostela, Galicia, Spain.

&amp;lt;p&amp;gt;The Greenland ice sheet has experienced increased surface melt and mass loss since the mid-1990s. Surface melt and surface mass balance are partially driven by large-scale changes in atmospheric circulation, which can direct anomalously warm and humid air masses over the ice sheet and lead to pulses of extensive melt and high runoff rates. However, the connection between the air mass source regions and ice sheet surface melt is poorly understood. Here we examine extreme melt pulses (&amp;gt;95th percentile melt extent for 3 or more days) for topographically defined regions of the ice sheet during the months of June, July, and August. Daily melt extent is determined from a satellite passive microwave product. The NOAA Air Resources Laboratory HYSPLIT model is used to calculate 10-day back-trajectories leading up to melt pulses. We apply a clustering algorithm separately for each region and initialization altitude to visualize the predominant tracks of air masses that impact the ice sheet during extensive melt events. Potential temperature at 2 PVU is used to trace atmospheric motion prior to melt onset. Particular attention is given to extreme events that led to melt at the highest elevations of the ice sheet, Summit Station. Results show the difference in source region east and west of the ice divide, and the important role of air mass source regions from North America and Europe.&amp;lt;/p&amp;gt;

The Greenland ice sheet has been losing mass in response to increased surface melting (Khan et al. 2015; van den Broeke et al. 2017) as well as discharge of ice from marine terminating outlet glaciers (van den Broeke et al. 2009; Box et al. 2018). Marine terminating outlet glaciers flow to the ocean where they lose mass by e.g. iceberg calving. Currently, the mass loss from the Greenland ice sheet is the largest Arctic contributor to global sea-level rise (van den Broeke et al. 2009, 2017; Box et al. 2018). Therefore, monitoring changes in the Greenland ice sheet is essential to provide policy makers with reliable data. There is a consensus that most marine terminating outlet glaciers have retreated in recent decades, and that the increased calving rates are a response to recent atmospheric and oceanic warming (e.g. Box et al. 2018; Moon et al. 2018). The rate of dynamic mass loss is determined by changes of the glacier calving front (i.e. its terminus) position, ice thickness and changes in ice flow. Ocean temperature and fjord circulation also influence the calving front stability by melting the glacier below the water line, thinning the ice that is in contact with water (Moon et al. 2014). Change in calving front position is therefore an important indicator for monitoring the dynamic behaviour of the upstream area of the ice sheet, which is further modulated by local topographic features and buttressing effects (Rignot &amp; Kanagaratnam 2006; Nick et al. 2009). The Programme for Monitoring of the Greenland Ice Sheet (PROMICE) is dedicated to monitoring changes in the mass budget of the Greenland ice sheet, including monitoring of the calving front lines of marine terminating outlet glaciers. Here, we present an updated collection of annual measurements of end-of-melt-season calving front lines for 47 marine terminating outlet glaciers in Greenland between 1999 and 2018. We also present an example application of the data set, in which we estimate area changes for this group of glaciers since 1999. The Greenland calving front lines were measured from optical satellite imagery obtained from Landsat, Aster, and Sentinel-2 (Table 1). The PROMICE calving front product is freely available for download as ESRI shapefiles.

We provide an updated analysis of instrumental Greenland monthly temperature data to 2019, focusing mainly on coastal stations but also analysing ice‐sheet records from Swiss Camp and Summit. Significant summer (winter) coastal warming of ~1.7 (4.4)°C occurred from 1991–2019, but since 2001 overall temperature trends are generally flat and insignificant due to a cooling pattern over the last 6–7 years. Inland and coastal stations show broadly similar temperature trends for summer. Greenland temperature changes are more strongly correlated with Greenland Blocking than with North Atlantic Oscillation changes. In quantifying the association between Greenland coastal temperatures and Greenland Ice Sheet (GrIS) mass‐balance changes, we show a stronger link of temperatures with total mass balance rather than surface mass balance. Based on Greenland coastal temperatures and modelled mass balance for the 1972–2018 period, each 1°C of summer warming corresponds to ~(91) 116 Gt·yr−1 of GrIS (surface) mass loss and a 26 Gt·yr−1 increase in solid ice discharge. Given an estimated 4.0–6.6°C of further Greenland summer warming according to the regional model MAR projections run under CMIP6 future climate projections (SSP5‐8.5 scenario), and assuming that ice‐dynamical losses and ice sheet topography stay similar to the recent past, linear extrapolation gives a corresponding GrIS global sea‐level rise (SLR) contribution of ~10.0–12.6 cm by 2100, compared with the 8–27 cm (mean 15 cm) “likely” model projection range reported by IPCC in 2019 (SPM.B1.2). However, our estimate represents a lower limit for future GrIS change since fixed dynamical mass losses and amplified melt arising from both melt‐albedo and melt‐elevation positive feedbacks are not taken into account here.

Since the early 1990s, a decrease in the surface mass balance has contributed to about&amp;#160;half of&amp;#160;the observed Greenland Ice Sheet mass loss. Since surface melt is the primary driver of surface mass loss, an accurate representation of surface melt is crucial for understanding the surface mass balance and, ultimately, the total contribution to rising sea levels. Although Regional Climate Models (RCMs) can simulate ice-sheet-wide melt volume, significant variability exists among&amp;#160;state-of-the-art RCMs, underpinning the need for&amp;#160;validation of the&amp;#160;melt. Here, we explore a novel processing of Advanced SCATterometer (ASCAT) data, which provides estimates of the spatiotemporal variability of melt extent across the Greenland Ice Sheet. We apply these new maps to pinpoint differences in the melt products from three RCMs. Using Programme for Monitoring of the Greenland Ice Sheet &amp;amp; Greenland Climate Network (PROMICE GC-net) air temperature observations, we evaluate how well RCM-modeled melt volume aligns with temperature measurements. With this evaluation, we establish thresholds for the RCMs to identify the amount of meltwater before it is observed at the AWS stations, thus allowing us to infer melt extent in RCMs. Results show that applying thresholds, informed by in-situ measurement, reduces the differences between ASCAT and RCMs and minimizes the discrepancies among RCMs. We leverage the differences between modeled melt extent and ASCAT-observed melt extent to further&amp;#160;pinpoint (i) limitations in ASCAT's melt detection, including misclassification in the ablation zone as well as a temporal melt onset bias, and (ii) biases inherent in RCMs, including variability in albedo schemes, snow layer thickness, and temperature and radiation biases in the boundary forcing.

Abstract. The mass of the Greenland Ice Sheet (GrIS) is decreasing due to increasing surface melt and ice dynamics. Snowfall both adds mass to the GrIS and has the capacity to reduce surface melt by increasing surface brightness, reflecting additional solar radiation back to space. Modeling the GrIS’s current and future mass balance and potential contribution to future sea level rise requires reliable observational benchmarks for current snowfall accumulation as well as robust connections between individual snowfall events and the large-scale atmospheric circulation patterns that produce them. Previous work using ground-based observations showed that, for one research station on the GrIS, two distinct snowfall regimes exist: those associated with exclusively ice-phase cloud processes (IC) and those involving mixed-phase processes indicated by the presence of supercooled liquid water (CLW). The two regimes have markedly different accumulation characteristics and dynamical drivers. This study leverages the synergy between two satellite instruments, CloudSat's Cloud Profiling Radar (CPR) and CALIPSO's Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), to identify snowfall cases over the full GrIS and partition them into the IC and CLW regimes. We find that, overall, most CPR observations of snowfall over the GrIS come from IC events (70 %); however, during the summer months, close to half of the snow observed is produced in CLW events (45 %). IC snowfall plays a dominant role in adding mass to the GrIS, producing ∼ 80 % of the total estimated 399 Gt yr−1 accumulation. Beyond the cloud phase that defines the snowfall regimes, the macrophysical cloud characteristics are distinct as well; the mean IC geometric cloud depth (∼ 4 km) is deeper than the CLW geometric cloud depth (∼ 2 km), consistent with previous studies based on surface observations. Two-dimensional histograms of the vertical distribution of CPR reflectivities show that IC events demonstrate consistently increasing reflectivity toward the surface while CLW events do not. Analysis of ERA5 reanalyses shows that IC events are associated with cyclone activity and CLW events generally occur under large-scale anomalously high geopotential heights over the GrIS. When combined with future climate predictions, this snapshot of GrIS snowfall characteristics may shed light on how this source of ice sheet mass might respond to changing synoptic patterns in a warming climate.

The Greenland Ice Sheet (GrIS) is losing mass in an accelerated fashion, which is for ~60% dominated by an increase in surface melting. Clouds exhibit an important control on the GrIS surface energy balance and surface melt. Therefore, to better simulate present and future GrIS climate, it is essential to represent clouds correctly in climate models. Here we use ground (at Summit Station) and satellite remote sensing (from CloudSat‐CALIPSO) observations to evaluate GrIS cloud characteristics in several versions of the Community Atmosphere Model (CAM) over the period 2007–2012. Cloud cover, phase, water path, and radiative effects over the GrIS vary widely across the atmosphere models. Thanks to the inclusion of new cloud physical parameterizations, that is, ice nucleation and prognostic precipitation, in the most recent CAM version (CAM6), this model, amongst the various CAM versions, is best able to represent GrIS clouds, summer temperatures, and surface melting. However, CAM6 shows excessive rainfall over the ice sheet, which is an important outstanding model bias. Our study demonstrates the importance of simulating realistic cloud properties to improve climate model simulations of GrIS climate and climate change.

Mass loss from the two major ice sheets and their contribution to global sea level rise is accelerating. In Antarctica, mass loss is dominated by increased flow velocities of outlet glaciers, following the thinning or disintegration of coastal ice shelves into which they flow. In contrast, ~55% of post‐1992 Greenland ice sheet (GrIS) mass loss is accounted for by surface processes, notably increased meltwater runoff. A subtle process in the surface mass balance of the GrIS is the retention and refreezing of meltwater, currently preventing ~40% of the meltwater to reach the ocean. Here we force a high‐resolution atmosphere/snow model with a mid‐range warming scenario (RCP4.5, 1970–2100), to show that rapid loss of firn pore space, by &gt;50% at the end of the 21st century, quickly reduces this refreezing buffer. As a result, GrIS surface mass loss accelerates throughout the 21st century and its contribution to global sea level rise increases to 1.7 ±0.5 mm yr−1, more than four times the current value.

&amp;lt;p&amp;gt;Mass loss from the Greenland Ice Sheet has increased in recent decades due to significant increases in surface melt and runoff. The fraction of summer melt retains as a liquid water or refreezes as it percolates into the underlying cold firn, acting as a buffer to the summer&amp;amp;#160;runoff. There are challenges to quantifying both infiltration and refreezing of meltwater in this complex heterogeneous cold firn and to understand the spatial variability of these processes. In this study we present continuous in situ measurements of&amp;amp;#160;near-surface temperature and dielectric permittivity, a proxy for volumetric water content, using TDR (Time Domain Reflectometry) methods in the percolation zone of the southern Greenland Ice Sheet. We established two observation sites near Dye 2 in April, 2016, excavating firn pits to depths of 2.2 and 5.3 m. The two sites are 650 m apart to quantify the percolation and refreezing of meltwater and to observe the spatial variability of these processes through summer 2016. Thermistor arrays were used to track the thermal signature of meltwater penetration in firn, through the effects of latent heat release when meltwater refreezes. Through the addition of TDR probes, we attempt to directly quantify meltwater volume as well as hydraulic conductivity of the near-surface snow and firn. An automatic weather station (AWS) configured for surface energy balance monitoring was also installed. AWS data were used to calculate the surface energy balance and model meltwater production. The melting front, characterized by 0&amp;amp;#176;C conditions and direct evidence of liquid water, penetrated to a depth of between 1.8 and 2.1 m in summer 2016; at depths of 2.1 m and greater, temperatures remained below 0&amp;amp;#176;C, there was no evidence of abrupt warming (i.e. latent heat release), and dielectric permittivities remained at their background levels. Meltwater penetrated several thick ice layers, but not until temperatures reached the melting point at these depths, implying that ice layers may transition to a permeable &amp;amp;#8216;slush&amp;amp;#8217; layer, given enough conductive and latent heating, permitting progressive penetration of meltwater to depth. Firn temperatures (sub-zero conditions below ~2 m) appear to have been the main barrier to deep penetration of meltwater during summer 2016.&amp;lt;/p&amp;gt;

&amp;lt;p&amp;gt;Throughout the satellite era, an increasingly positive trend in the extent and duration of seasonal surface melt has been observed across the Greenland Ice Sheet (GrIS). Surface melt, and meltwater runoff now accounts for over half of GrIS mass loss annually, signifying the importance of surface mass balance on the future contribution to global sea level rise. A vast expanse of supraglacial channel networks and lakes now dominate the ablation zone during the melt season, transporting, storing, and evacuating increasingly large volumes of meltwater from the ice surface. The interception of this water, either by moulins or through linked crevasses, can propagate through the ice column and flood the ice-bed interface, influencing ice velocity and, in turn ice discharge over the grounding line.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;To date, much of the hydrological interest on the GrIS has centred around its western and south-western margins, often limited to short windows (days) during the melt season. This study expands surface hydrological mapping to other regions of the GrIS, specifically its northern sector, and explores network evolution across both seasonal (intra-) and inter-annual timescales.&amp;lt;/p&amp;gt;&amp;lt;p&amp;gt;This study utilises a satellite-derived Normalised Difference Water Index (NDWI) alongside an automatic river detection algorithm to effectively delineate active supraglacial channel networks and (hydrologically-connected) saturated slush zones using Sentinel-2 and Landsat optical imagery. This work reveals a transformation of the northern supraglacial channel network from a highly-fragmented system of short channels extending a maximum of ~40 km inland during the 1980&amp;amp;#8217;s, to one dominated by long, parallel channels extending ~80 km inland from 2016. The observations presented in this study have significant implications on both the speed and efficiency of supraglacial meltwater drainage of the GrIS, holding a great potential to impact the dynamic response of outlet glaciers, and ice sheet mass loss.&amp;lt;/p&amp;gt;