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Satellite datasets are increasingly used to evaluate NOx emissions inventories. Such studies often require the use of a chemical transport model or a complex statistical framework to account for meteorological factors that can complicate the comparison. Here, we apply a novel method to compare inventory-based emissions directly to Tropospheric Monitoring Instrument (TROPOMI) NO2 data without a chemical transport model by accounting for the two most important meteorological factors: wind speed and direction. We oversample the satellite data over multiple years and filter to use data on stagnant wind days only, and then use this satellite average to evaluate the spatial representativeness of the 1 × 1 km2 inventory-based Neighborhood Emission Mapping Operation (NEMO). In nine out of ten US cities, spatial r2-values between NEMO NOX emissions and TROPOMI NO2 exceeded 0.75. This suggests that the 108 spatial surrogates used by NEMO to spatially disaggregate NOx emissions from the U.S. county-level (5-200 km length scale) to the neighborhood level (~1 km length scale) are generally appropriate. However, this analysis also suggests some areas for improvement. Areas with dense warehouse operations appear to underestimate NOx emissions. Conversely, we find that NOx emissions in wealthy communities often appear to be overestimated using standard surrogates to disaggregate the inventory. Globally, we find spatial agreement between the EDGAR NOX inventory and NO2 observed by TROPOMI, which indicates that most NOx sources are properly included in the inventory. The inventory and satellite measurements agreed most closely in the U.S (

Ice sheet models, calibrated using observational data, provide a means of projecting our current best state of the knowledge of the system state into the future, so as to obtain information about possible future behaviour. However it is important to be able to estimate the uncertainty associated with these projections. The problem of quantifying ice sheet parametric uncertainty is considered, focusing specifically on the problem of quantifying the posterior uncertainty in inferred basal sliding and rheology coefficients. These measures of uncertainty are projected forwards in time to obtain measures of uncertainty in future quantities of interest. Automated code generation and automated differentiation tools are utilised, leading to an extensible approach. The role of the observational error model in defining parametric uncertainty is considered.

The components Antarctica's subglacial hydrology -for instance water sources, sinks, flow paths and catchments- are still poorly constrained. In this work we assess the subglacial hydrology of the continent at high resolution (500m) using (1) water inputs from frictional melting derived with a higher order ice flow model combined with existing geothermal heat flux products, (2) BedMachine topography, and (3) a water flow routing model taking uncertainties into account.We present the following modelling results: probabilistic maps of water flow paths and catchments, potential subglacial lake locations, fluxes across the grounding line, and melt or freeze-on rates due to water flow. We also present locations where the drainage system configuration, such as the catchment size, is sensitive to model inputs and thus where future field investigations would be particularly valuable.

The impacts of upper-ocean mixing on primary productivity are complex and range from an entrainment of nutrients to modulating light limitations. Sea ice in turn plays an important role in determining mixing conditions through its cycles of formation and melt, and by moderating wind forcing. With sea ice conditions in the Southern Ocean projected to undergo large changes over the course of the century, understanding the relationship between sea ice and upper-ocean mixing is crucial for understanding the impacts of climate change on biological production in this region. Due to the inaccessibility of sea ice-covered waters however, mixed layer depth observations are often not available at a high temporal and spatial resolution. Here we present an analysis of sea ice-mixed layer depth relationships during a 40-year regional ocean-sea ice simulation of the West Antarctic Peninsula (WAP) and Bellingshausen Sea, a highly biologically productive region of global importance. The relationship between winter sea ice and spring mixed layer depth shows clear differences on and off the WAP continental shelf, with decadal variations in the location of the boundary between negative and positive correlations. Potential mechanisms causing this effect are considered in detail, including the nonlinear relationship between sea ice cover and turbulent mixing, the transport of sea ice within the region, and a difference in the timing of the sea ice seasonal cycle between the two regions. The transport of warm Circumpolar Deep Water onto the shelf is also discussed. The presented findings have implications for the spatial distribution of primary producers in a more ice-free future WAP.

The Amundsen Sea Sector has some of the highest thinning rates of ice shelves in Antarctica, thought to be driven by high, but interannually variable, ocean driven melt rates. This thinning can lead to increased ice flow speeds, eventually leading to sea level rise. To fully represent these processes and other feedbacks, a fully coupled ice/ocean model must be used. Therefore, a fully synchronous mass conservative coupled ice-sheet/ocean model of the Amundsen Sea Sector has been developed. This new coupled model builds upon previous coupling developments and involves coupling of the WAVI ice-sheet model to the 3D ocean model MITgcm, via the Streamice ice-sheet model. Coupled model projections are presented, examining ice grounding line retreat rates and ice mass loss, along with ocean driven melt rate evolution. The sensitivity of these results to ocean forcings is shown, specifically the thickness of the relatively warm Circumpolar Deep Water layer and its variability. In addition, we discuss the impact of the present-day initialisation and tuning of the coupled model.

We use numerical modelling to address several questions related to the future evolution of Thwaites Glacier over the next 50 years. The importance of Thwaites Ice Shelf for upstream grounded flow is investigated by quantifying the buttressing stresses along the grounding line. Removing the ice shelf changes the stress regime along the grounding line by less than 20%. This change is small compared to many, if not most, grounding lines of the Antarctic Ice Sheet, and much smaller than corresponding changes for the neighboring Pine Island and Pope, Smith and Kohler glaciers. Transient ice-flow modelling experiments show that mass loss from Thwaites Glacier over the next 50 years is insignificantly affected by removal of the ice shelf. We then explore the consequences of the proposed marine ice-cliff instability for Thwaites Glacier. For recently proposed calving laws, where the calving rate increases sharply with cliff height, we do not observe an onset of an unstable calving front retreat. Further numerical modelling experiments for future climatic forcing scenarios will be presented, including uncertainty quantification. Interactions between the ice and the ocean are studied using a coupled ice+ocean modelling framework. As shown before in several studies, we find when simulating its future evolution, that Thwaites Glacier can enter unstable periods of self-enhancing retreat. This appears to be a very robust result, and this behavior is found in all model runs, including coupled ice+ocean simulations.

The COVID-19 pandemic created an extreme natural experiment in which sudden changes in human behavior and economic activity resulted in significant declines in nitrogen oxide (NOx) emissions, immediately after strict lockdowns were imposed. Here we examined the impact of multiple waves and response phases of the pandemic on nitrogen dioxide (NO2) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO2 pollution in post-pandemic New York City. Long term (> 3.5 years), high frequency measurements from a network of ground-based Pandora spectrometers were combined with TROPOMI satellite retrievals, meteorological data, mobility trends, and atmospheric transport model simulations to quantify changes in NO2 across the New York metropolitan area. The stringent lockdown measures after the first pandemic wave resulted in a decline in top-down NOx emissions by approx. 30 % on top of long-term trends, in agreement with sector-specific changes in NOx emissions. Ground-based measurements showed a sudden drop in total column NO2 in spring 2020, by up to 36 % in Manhattan and 19 %–29 % in Queens, New Jersey (NJ), and Connecticut (CT), and a clear weakening (by 16 %) of the typical weekly NO2 cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO2 across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO2 coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO2 biassing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO2 conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO2 declines than expected based on changes in transportation emissions alone. Meteorology played a key role in shaping the relative contributions from different emission sectors to NO2 pollution in the city, with low-speed (

Ice sheet models are the main tool to generate forecasts of ice sheet mass loss; a significant contributor to sea-level rise, thus knowing the likelihood of such projections is of critical societal importance. However, to capture the complete range of possible projections of mass loss, ice sheet models need efficient methods to quantify the forecast uncertainty. Uncertainties originate from the model structure, from the climate and ocean forcing used to run the model and from model calibration. Here we quantify the latter, applying an error propagation framework to a realistic setting in West Antarctica. As in many other ice-sheet modelling studies we use a control method to calibrate grid-scale flow parameters (parameters describing the basal drag and ice stiffness) with remotely-sensed observations. Yet our framework augments the control method with a Hessian-based Bayesian approach that estimates the posterior covariance of the inverted parameters. This enables us to quantify the impact of the calibration uncertainty on forecasts of sea-level rise contribution or volume above flotation (VAF), due to the choice of different regularisation strengths (prior strengths), sliding laws and velocity inputs. We find that by choosing different satellite ice velocity products our model leads to different estimates of VAF after 40 years. We use this difference in model output to quantify the variance that projections of VAF are expected to have after 40 years and identify prior strengths that can reproduce that variability. We demonstrate that if we use prior strengths suggested by L-curve analysis, as is typically done in ice-sheet calibration studies, our uncertainty quantification is not able to reproduce that same variability. The regularisation suggested by the L-curves is too strong and thus propagating the observational error through to VAF uncertainties under this choice of prior leads to errors that are smaller than those suggested by our 2-member “sample” of observed velocity fields. Additionally, our experiments suggest that large amounts of data points may be redundant, with implications for the error propagation of VAF.

Ice shelf shape directly controls ocean heat intrusions, melting near the grounding line, and buttressing. Little is known about what determines ice-shelf shape because ice-ocean coupled simulations typically aim at projecting Antarctica's contribution to sea-level rise and they do not resolve small-scale ice-ocean interactive processes. We conduct ice-ocean coupled simulations for an idealized high-resolution, Pine-Island-like model configuration. We show that ocean melting and ice stretching caused by acceleration thin the ice shelf from the grounding line toward the ice shelf front, consistent with previous studies. In the across-flow direction, ocean melting and ice advection cancel each other out and flatten the ice shelf. More than one-third of the ice thinning from grounding line to ice front can be attributed to ocean melting at depths shallower than 500 m. Our results emphasize the importance of interactive processes between the entire ice shelf and the ocean for determining the ice shelf shape. Plain Language Summary Antarctic ice flows into the ocean and forms a floating extension of land ice called an ice shelf. The ice shelf shape directly controls the amount of ocean heat intrusions, melting near the grounding line, and buttressing. However, little is understood about ice-ocean interactive processes determining ice shelf shape because (a) ocean modelers apply a constant cavity geometry, (b) ice modelers mostly assume simplified melting parameterization, and (c) ice-ocean coupled simulations typically aim at projections of Antarctica's sea-level contributions and they require long model integration. We conduct ice-ocean coupled simulations for an idealized high-resolution Pine-Island-like model configuration. Basal melting and ice stretching create a typical ice shelf shape with steep thinning near the grounding line followed by gradual thinning toward the ice shelf front. In the across-flow direction, ice divergence from the center advects ice toward edges, compensating for melt-driven thinning and flattening ice shelf shape. We also show that ice melting at shallow depths contributes to about one-third of ice-shelf thinning. Although it is thought that ice shelf melting at the grounding line dominantly controls ice shelf behavior, our results suggest the importance of ice-ocean interactive processes for the entire ice shelf cavity for determining the ice shelf shape.

The COVID-19 pandemic created an extreme natural experiment in which sudden changes in human behavior and economic activity resulted in significant declines in nitrogen oxide (NO(x)) emissions, immediately after strict lockdowns were imposed. Here we examined the impact of multiple waves and response phases of the pandemic on nitrogen dioxide (NO(2)) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO(2) pollution in post-pandemic New York City. Long term (> 3.5 years), high frequency measurements from a network of ground-based Pandora spectrometers were combined with TROPOMI satellite retrievals, meteorological data, mobility trends, and atmospheric transport model simulations to quantify changes in NO(2) across the New York metropolitan area. The stringent lockdown measures after the first pandemic wave resulted in a decline in top-down NO(x) emissions by approx. 30% on top of long-term trends, in agreement with sector-specific changes in NO(x) emissions. Ground-based measurements showed a sudden drop in total column NO(2) in spring 2020, by up to 36% in Manhattan and 19%–29% in Queens, New Jersey (NJ), and Connecticut (CT), and a clear weakening (by 16%) of the typical weekly NO(2) cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO(2) across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO(2) coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO(2) biassing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO(2) conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO(2) declines than expected based on changes in transportation emissions alone. Meteorology played a key role in shaping the relative contributions from different emission sectors to NO with low-speed (< 5 ms(−1)) SW-SE winds enhancing contributions from the high-emitting power-generation sector in NJ and Queens and driving particularly high NO(2) pollution episodes in Manhattan, even during – and despite – the stringent early lockdowns. These results have important implications for air quality management in New York City, and highlight the value of high resolution NO(2) measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NO(x) emission control strategies.

Programs offering reproductive genetic carrier screening (RGCS) to high school students within the Ashkenazi Jewish community in several countries including Canada and Australia have demonstrated high uptake and retention of educational messages over time. This study was undertaken to evaluate whether testing for an expanded number of conditions in a high school setting would impact the effectiveness of education. In this questionnaire-based study, genetic carrier testing for nine conditions was offered to 322 year 11 students from five high schools, with students attending a compulsory 1-h education session prior to voluntary testing. Comparison of pre- and post-education measures demonstrated a significant increase in knowledge, positive attitudes, and reduced concern immediately after the education session. Retention of knowledge, measures of positive attitude, and low concern over a 12-month period were significantly higher than baseline, although there was some reduction over time. In total, 77% of students exhibited informed choice regarding their intention to test. A significant increase in baseline knowledge scores and positive attitude was also demonstrated between our original 1995 evaluation (with testing for only one condition) and 2014 (testing for nine conditions) suggesting community awareness and attitudes to RGCS have increased. These findings validate the implementation of effective education programs as a key component of RGCS and are relevant as gene panels expand with the introduction of genomic technologies. Supplementary Information The online version contains supplementary material available at 10.1007/s12687-021-00567-8.

Mass loss due to dynamic changes in ice sheets is a significant contributor to sea level rise, and this contribution is expectedto increase in the future. Numerical codes simulating the evolution of ice sheets can potentially quantify this future contribution.However, the uncertainty inherent in these models propagates into projections of sea level rise, and hence is crucialto understand. Key variables of ice sheet models, such as basal drag or ice stiffness, are typically initialized using inversionmethodologies to ensure that models match present observations. Such inversions often involve tens or hundreds of thousandsof parameters, with unknown uncertainties and dependencies. The computationally intensive nature of inversions along withtheir high number of parameters mean traditional methods such as Monte Carlo are expensive for uncertainty quantification.Here we develop a framework to estimate the posterior uncertainty of inversions, and project them onto sea level change projections over the decadal timescale. The framework treats parametric uncertainty as multivariate Gaussian, and exploits theequivalence between the Hessian of the model and the inverse covariance of the parameter set. The former is computed efficientlyvia algorithmic differentiation, and the posterior covariance is propagated in time using a time-dependent model adjointto produce projection error bars. This work represents an important step in quantifying the internal uncertainty of projectionsof ice-sheet models.

There is significant uncertainty over how ice sheets and glaciers will respond to rising global temperatures. Limited knowledge of the topography and rheology of ice-bed interface is a key cause of this uncertainty, as models show that small changes in the bed can have a large influence on predicted rates of ice loss. Most of our detailed knowledge of bed topography comes from airborne and ground-penetrating radar observations. However, these direct observations are not spaced closely enough to meet the requirements of ice-sheet models, so interpolation and inversion methods are used to fill in the gaps. Here we present the results of a new inversion of surface-elevation and velocity data over Thwaites Glacier, West Antarctica, for bed topography and slipperiness (i.e. the degree of basal slip for a given level of drag). The inversion is based on a steady-state linear perturbation analysis of the shallow-ice-stream equations. The method works by identifying disturbances to surface flow which are caused by obstacles or sticky patches in the bed, and can therefore be applied wherever the shallow-ice-stream equations hold and where surface data are available, even where the ice thickness is not well known. We assess the performance of the inversion for topography with the available radar data. Although the topographic output from the inversion is less successful where the bed slopes steeply, it compares well with radar data from the central trunk of the glacier. This method could therefore be useful as either an independent test of other interpolation methods such as mass conservation and kriging, or as a complementary technique in regions where those techniques fail. We do not have data to allow us to assess the success of the slipperiness results from our inversions, but we provide maps that may guide future seismic data collection across Thwaites Glacier. The methods presented here show significant promise for using high-resolution satellite datasets, calibrated by the sparser field datasets, to generate high resolution bed topography products across the ice sheets, and therefore contribute to reduced uncertainty in predictions of future sea-level rise.

Stigma is an under-recognized health malady that is both rampant for vulnerable communities and difficult to measure for researchers. Stigma has enormous and compounding negative health impacts, associated with lower education levels, employment and income, and poorer control of chronic conditions and illness. When stigma is embedded in the systems that govern daily life, it is considered structural stigma. Structural stigma in law has a particularly potent impact on the health and recovery of patients with substance use disorder (SUD) and addiction. Stigmatizing laws against individuals with addiction have a powerful role in downstream health, including opportunities for employment, access to health insurance, self-stereotyping, and reduced willingness to access recovery resources. Understanding and dismantling structural stigma in law, therefore, is a necessary component in comprehensively addressing SUD and addiction in collaboration with other evidence-based interventions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Dynamically coupled ice sheet-ocean models are beginning to be used to study the response of the Antarctic Ice Sheet to fluctuations in ocean temperatures. However, initialising a coupled ice-ocean model for realistic settings is challenging and can introduce nonphysical transients. The extent to which such transients can affect model evolution and projection is unclear. Here, we use a synchronously-coupled model of ice-ocean dynamics to investigate the evolution of Pope, Smith and Kohler Glaciers, West Antarctica, over the next half-century. Two methods of coupled initialisation are used: in one, the ice-sheet model is constrained to fit observed velocities in its initial state; in the other, the model is constrained with both velocities and grounded thinning rates over a 4-year period while forced with simulated ocean melt rates. For each method, two climate scenarios are considered -- one where ocean conditions during this initialisation period persist indefinitely, and one where the ocean is in a permanent ``warm'' state -- as well as two ice-sheet basal sliding laws. At first, the model runs initialised with thinning rates exhibit volume loss much closer to observed values than those initialised with velocity only, but after 1-2 decades the forcing primarily determines rates of retreat. This ``crossover’’ timescale is expected to vary by glacier, however. Under the ``warm’’ scenario, grounding line retreat of ~30 km is simulated for Smith and Kohler, but it is questionable whether this will continue due to narrowing of submarine troughs and limiting of heat transport by controlling obstacles.

The West Antarctic Ice Sheet has the potential to contribute up to 3m of sea level rise over the next few centuries. There is considerable uncertainty over the rate at which ice loss will occur, caused in part by a lack of knowledge about the bed topography beneath the ice sheet, which influences ice flow and retreat. Since direct bed topography observations are often further apart than ice sheet models require, we explore instead what we can learn about bed topography from high resolution observations of the ice surface, which are openly available. We apply an inversion methodology based on linear perturbation theory and developed by Gudmundsson (2003, 2008) to ice surface data from Pine Island Glacier, and present the bed topography results. Comparison to high-resolution radar sounding of the bed topography of Pine Island Glacier from the iSTAR 2013-14 ground surveys allows us to assess the success of the inversion methodology. We identify regions of the glacier where the landforms we see are likely to be artefacts, and regions where unknown and interesting landforms are likely to exist. This methodology has the potential to be extremely useful in regions where direct observations of bed topography are sparse, and for identifying areas where more observations would be of particularly high benefit.

Subglacial water at the base of the ice sheet has been shown to impact ice flow and its discharge into the ocean – which modifies ocean properties and melt rates of fringing ice shelves. Subglacial water, generated from frictional heating and geothermal heat flux, collects in hydrological sinks which store and release water in episodic events. These events, interpreted as water moving in and out of active lakes, have a signature at the surface of the ice sheet which can be detected and quantified by satellite altimetry. By quantifying the volume of water involved in these active events, it is possible to obtain insight into processes otherwise hidden from view. In particular, observing the gain in volume following a drainage event provides constraints on hydrological recharge rates, subglacial water fluxes, and processes leading to basal melt water production. Such a method was applied to the inventory of Antarctic active subglacial lakes using CryoSat’s radar altimeter observations over the 2010-2020 period. Out of 136 known lakes, 13 lakes show clear signs of recharge during the observation period. From these we can extract recharge rates, which act as a lower bound on subglacial melt production. These rates are compared against rates of recharge derived by routing modelled subglacial melt production across the Antarctic Ice Sheet. We demonstrate that, for connected subglacial lake networks, satellite observations can provide a robust validation dataset for sub-glacial melt models. Our results show that, at a local level, estimates of melt water flux is highly dependent on the routing method chosen. We also highlight subglacial lakes where observed rates of recharge are too high to be explained by our current knowledge of the bed and of processes responsible for subglacial melting rates.

Meltwater forms at the base of the Antarctic Ice Sheet due to geothermal heat flux (GHF) and basal frictional dissipation. Despite the relatively small volume, this meltwater has a profound effect on ice-sheet stability, controlling the dynamics of the ice sheet and the interaction of the ice sheet with the ocean. However, observations of subglacial melting and hydrology in Antarctica are limited. Here we use numerical modelling to assess subglacial melt rates and hydrology beneath the Antarctic Ice Sheet. Our case study, focused on the Amery Ice Shelf catchment, shows that total subglacial melting in the catchment is 6.5 Gt yr-1, over 50% larger than previous estimates. Uncertainty in estimates of GHF leads to a variation in total melt of ±7%. The meltwater provides an extra 8% flux of freshwater to the ocean in addition to contributions from iceberg calving and melting of the ice shelf. GHF and basal dissipation contribute equally to the total melt rate, but basal dissipation is an order of magnitude larger beneath ice streams. Remote-sensing observations, from CryoSat-2, indicating active subglacial lakes and ice-shelf basal melting constrain subglacial hydrology modelling. We observe a network of subglacial channels that link subglacial lakes and trigger isolated areas of sub-ice-shelf melting close to the grounding line. Building upon this Amery case study, we expand our analysis to quantify subglacial melt rates and hydrology beneath the entire Antarctic Ice Sheet.

Fenics_ice is a finite element model framework written in Python that quantifies the initialization uncertainty for time-dependent ice sheet models. Here, we apply for the first time this framework to real ice streams in the Amundsen basin: Smith, Pope and Kohler Glaciers. We quantify the degree to which observational uncertainty translates to parametric uncertainty (posterior uncertainty of inversions for basal drag and ice stiffness fields) and to uncertainty in projected quantities of interest (QoIs) such as sea level contribution. The framework implements the Shallow Shelf Approximation (SSA), and implements a control methods approach to invert for the basal drag and ice stiffness fields. Beginning with a cost function optimization which can allow for either gridded or point-cloud velocities, we generate a low-rank approximation to the posterior covariance of the parameters through the use of the cost function Hessian. In our work, the Hessian is calculated through algorithmic differentiation (AD) using the “complete” Hessian rather than the Gauss–Newton approximation. We then project the covariance on a linearization of the time-dependent ice sheet model (again using AD to generate the linearization) to estimate the growth of QoI uncertainty over time. We then show the model framework and capabilities when applied to these ice streams and our future plans to scale our framework into a larger domain.

Cordillera Blanca glaciers represent the greatest glacial freshwater reserve in tropical South America and have been shrinking substantially over recent decades, posing a threat to future water resources in the Peruvian Ancash region. A crucial step to better understand the evolution of these glaciers under changing conditions is to establish robust reconstructions of their past response to climate fluctuations. Such reconstructions are limited in the tropical Andes, which inhibits our understanding of the climatic drivers of tropical glacier length and surface mass balance changes. The relative importance of temperature versus precipitation rate changes on glacier length changes is therefore still debated in the region. Here, we present 42 cosmogenic 10Be exposure ages from moraine boulder samples, establishing for the first time a comprehensive chronology for Late-glacial, Holocene and Neoglacial advances of four distinct Cordillera Blanca mountain glaciers. We use this chronology to constrain a series of moraine-matching numerical model-run simulations conducted for each dated glacier advance using a spatially-distributed ice-flow model coupled with a positive degree-day surface mass balance parameterisation. These simulations aim at modelling and estimating former three-dimensional glacier geometries, equilibrium line altitudes, surface mass balance properties and their evolution through time. This analysis also enables us to use glacier surface mass balance as a proxy for past atmospheric temperature and precipitation variations at the time of the reconstructed glacier advances. This new, multi-method glacier reconstruction enables, for the Cordillera Blanca: 1) novel glacio-geomorphological interpretations, 2) an improved understanding of glacier extent, surface mass balance and volume change during the Late-glacial, Holocene and Neoglacial phases of advance, and 3) new estimations of paleoclimate conditions required for the reconstructed glacier events to occur.

Ice shelf melt rates near grounding lines are a few orders of magnitude higher than other locations. This intense melting close tothe grounding zone is crucial as it induces ice shelf thinning, further acceleration of ice flow, and grounded ice loss. However,little is revealed about ice and ocean processes determining peak ice shelf melt rates close to the grounding line because (1) oceanmodelers apply a constant cavity geometry, (2) ice modelers typically assume some parameterizations for determining ice shelf melt rates,and (3) ice-ocean coupled simulations typically require long model integration, necessitating coarse resolution, and they are not able toresolve small-scale processes near grounding zones. Here, we develop an idealized high-resolution Pine-Island-like model configuration (250m, 500m, and 1km horizontal and 10 m vertical grid spacings) and conduct ice-ocean coupled simulation for 20 years after 60 years ofinitialization. We show that ice slope and ice shelf melt rate close to the grounding zone increases with higher grid resolution but iceshelf geometry converges towards the highest resolution solution. We are also able to simulate the formation of sub-ice shelf channels byapplying seasonally varying oceanic conditions. We also present our preliminary results of ice-ocean coupled realistic Pine Islandsimulation using unprecedentedly high horizontal and vertical resolution (200m horizontal and 10 m vertical grid spacings). This isa step towards understanding the ice-ocean interacting mechanisms determining ice shelf shape and melt rate, which is crucial forimproved projections of future Antarctic ice loss.