There is a growing need for operational oceanographic predictions in both the Arctic and Antarctic polar regions. In the former, this is driven by a declining ice cover accompanied by an increase in maritime traffic and exploitation of marine resources. Oceanographic predictions in the Antarctic are also important, both to support Antarctic operations and also to help elucidate processes governing sea ice and ice shelf stability. However, a significant gap exists in the ocean observing system in polar regions, compared to most areas of the global ocean, hindering the reliability of ocean and sea ice forecasts. This gap can also be seen from the spread in ocean and sea ice reanalyses for polar regions which provide an estimate of their uncertainty. The reduced reliability of polar predictions may affect the quality of various applications including search and rescue, coupling with numerical weather and seasonal predictions, historical reconstructions , aquaculture and environmental management including environmental emergency response. Here, we outline the status of existing near-real time ocean observational efforts in polar regions, discuss gaps, and explore perspectives for the future. Specific recommendations include a renewed call for open access to data, especially real-time data, as a critical capability for improved sea ice and weather forecasting and other environmental prediction needs. Dedicated efforts are also needed to make use of additional observations made as part of the Year of Polar Prediction  to inform optimal observing system design. To provide a polar extension to the Argo network, it is recommended that a network of ice-borne sea ice and upper-ocean observing buoys be deployed and supported operationally in ice-covered areas together with autonomous profiling floats and gliders  in seasonally ice covered seas. Finally, additional efforts to better measure and parameterize surface exchanges in polar regions are much needed to improve coupled environmental prediction. Over the last 10 years, there has been a significant maturing of ocean prediction systems, led by efforts such as GODAE OceanView GOV;  and the We have also seen the implementation of high-resolution operational ice-ocean prediction systems for polar regions providing forecasts on timescales of hours to days. These include the CMEMS Arctic Monitoring and Forecasting Centre (ARC MFC), the U.S. Navy Global Ocean Forecasting System, Environment and Climate Change Canada’s Global and Regional Ice Ocean Prediction Systems among others . While tin situ and from remote sensing). Indeed, Observing System Experiments (OSEs) have shown the delicate balance and complementarity provided by the current basket of observations  or other transmission systems. In ice-free areas various methods are used, including ships, Argo floats, surface drifters, gliders, etc., while in ice-covered areas, only ice-borne instrument systems can operate throughout the year and transmit data in near real-time. Owing to their significant deployment and maintenance costs, the number of these platforms is very limited, resulting in large gaps in the data coverage in the ice-covered Arctic Ocean. Antarctic sea ice is largely single-year (or first-year) ice, which makes it ill-suited for ice based measurement systems. A significant fraction of the ocean data from the Arctic, as well as under-ice Argo profiles from the Antarctic seasonal ice zone, are only available in delayed mode, because underwater platforms in ice-covered areas cannot transmit data via satellite communication. This limits the access to ocean data available in near real-time, which is required by monitoring and forecasting services.In the following section, the most common observing systems for the Arctic Ocean and Antarctic marginal sea are described briefly. Sections “Argo floats are the backbone of the global ocean observing system developed over the last two decades with more than 3500 units currently in operation e.g., . In the There is ongoing development to adapt Argo floats to operate under ice, using ice-sensing algorithms as well as acoustic and optical techniques. In the Southern Ocean, the Argo program has demonstrated success with under-ice profiling floats that delay data transmission until the float is in open water, typically in summer . In particular, the Southern Ocean Carbon and Climate Observations and Modeling project (SOCCOM) has made an effort to deploy a significant number of underice Argo floats in the Southern Ocean. Moreover, RAFOS floats  provide 1. In addition to CTD profile observations, the IAOOS buoy includes ice mass balance measurements (snow and sea ice temperature and thickness), as well as a variety of meteorological sensors (2 (AOFB), and the UpTempO ice-tethered buoy developed by APL-UW  sensor that is repeatedly transported along the mooring cable over the upper 800–1000 m of the water column. Ice-Tethered Profiler (ITP) systems from the Woods Hole Oceanographic Institution  provide information on temperature within snow and ice as well as ice thickness and its motion. Development and use of these buoys have continued for several decades with more than 100 IMBs deployed from 1957 to 2014. The data are transmitted in near realtime, but processing of the temperature profiles is mainly done manually. There are ongoing efforts to develop automated methods for retrieval of snow and ice thickness . It is aCurrently, three different systems are deployed in the Arctic including the CRREL-Dartmouth IMB , the SRSFerrybox systems: The Norwegian Institute for Water Research (NIVA) operates a ferrybox between Tromsø and Longyearbyen/Ny Ålesund. Data are obtained every 2 weeks year-round. This system is fairly sustainable through support from a new infrastructure project led by NIVA.Ship-based CTD data during scientific cruises and fishery management cruises: Several research vessels in the North Atlantic/Nordic seas deliver CTD observations in near real-time. The data are provided more or less regularly, depending on the schedule of the research vessels.Profiling gliders: Several institutions conduct ocean glider experiments in the Arctic  providing CTD data in near real-time. These experiments are mainly in the summer season, however, acoustically navigated ice-capable Seagliders (developed by APL-UW) were successfully used for the year-round missions in Davis Strait and in the Beaufort Sea including under ice measurements in winter . Glider 2) information over multiple months at a time and with high resolution  are becoming the most numerous patterns .Acoustic tomography: Acoustic sources and receivers have been deployed in the Arctic in the past  and offeMoored Arrays: Several long-term observatories have been running in both ice-covered and open-water areas with the capacity to provide real-time data. Examples include the German long-term observatory FRAM . Actual lifetimes of the full ITP system are often less than this, 3, the National Environmental Data Center and the Arctic Data Center, support a range of scientific investigations and student projects. The basin-wide and year-round coverage facilitates studies of seasonal-to-interannual physical and biogeochemical processes  program. Fifteen new types of technology have been developed or advanced for Arctic use under this program, including the Air-Launched Autonomous Micro-Observer (ALAMO), the Saildrone autonomous marine vehicle, and the Oculus Coastal Glider.Since 2014, NOAA Pacific Marine Environmental Laboratory (PMEL) and the University of Washington’s Joint Institute for the Study of the Atmosphere and Ocean (JISAO) have been developing and field testing a series of autonomous marine systems designed for Arctic applications. This work has been carried out in collaboration with scientists, forecasters, and industry, primarily under the auspices of the Innovative Technologies for Arctic Exploration  see  are beinA Government of Canada initiative called CONCEPTS  and transmit ocean measurements. Additionally, the float observed temperature and salinity measurements during winter that deviated significantly from climatological conditions . As thesAs part of the YOPP see , this ef6, Takuvik deploys Biogeochemical Argo floats  in the Arctic Ocean to study the dynamics of ice-edge phytoplankton spring blooms as controlled by sea ice dynamics, vertical mixing, light and nutrients. BGC Argo floats are more specialized profilers, equipped with sensors capable of sampling additional essential ocean variables  to be operated under ice, was founded by the French project NAOSer layer .The PRO-ICE floats use a combination of three technologies to detect ice: a reversed altimeter (active acoustics), an Ice Sensing Algorithm  (ISA) baFurthermore, the resolution provided by an altimeter is not sufficient to detect a thin-ice layer. For this, Takuvik has developed an ice-detection system based on laser polarimetry . Since sA potential solution to data transmission issues caused by an inability to surface under the ice cover may be provided by underwater acoustic networks. Multipurpose underwater acoustic networks can provide under-ice positioning . The data policy set for Argo mandates free access to the data for all interested scientists, research groups and operational agencies. The data management is designed to facilitate easy and immediate access to data not only in real time, but also in delayed mode.Data acquired by Takuvik’s PRO-ICE floats are available in the Argo database at the CORIOLIS Global Data Assembly Centre10, 11). Over the Arctic Ocean and its peripheral seas (north of 60°N), there were about 120 buoys reporting as of August 2018. Most of these buoys were located in the North American sector, with only a handful reporting in the Eurasian sector of the Arctic. This gap in the Arctic Observing Network creates a significant uncertainty in the analyzed fields of sea level pressure, temperature and winds  there were about 50 buoys as of August, 2018. Although over 100 buoys were deployed during the Austral summer near the coast of Antarctica, most of these buoys were destroyed by the sea ice during freeze up or have been blown north, away from the coast by the prevailing winds.Maintaining the polar observing networks near the coasts around most of Antarctica, and in the Eurasian Arctic is an ongoing challenge, since the prevailing winds and ocean currents quickly transport the buoys away from the coast. Ideally, the IABP and IPAB networks should be reseeded during the winter, but it is difficult to deploy buoys from ships and aircraft during the polar night and extreme cold and harsh conditions of winter.The participants of the IABP and IPAB strive to release their data onto the WMO/IOC GTS in near real-time by both the global research and operational weather and ice forecasting communities.Satellite observations of polar oceans have been acquired for more than four decades by different measuring systems. The most prominent record comes from microwave radiometers that have been documenting the reduction of sea ice extent . Remote Satellite-based sea ice observations are required for assimilation to provide accurate polar environmental forecasts. These observations have been proven beneficial in improving prediction skill at different temporal scales when assimilated e.g., . In addiObserving SIT from space is a challenge , and griSea ice thickness is typically derived from radar altimetry observations of freeboard using the hydro-static equilibrium assumption e.g., . Both thPrevious studies showed that assimilation of SMOS ice thickness significantly improves the first-year ice estimates . FurtherSatellite SST retrievals in polar regions are challenging. SST is estimated from instruments operating in the infrared (IR) and microwave regions of the spectrum through the so-called atmospheric window regions. IR retrievals in polar regions are often limited by the observed abnormal (often very dry) atmospheric conditions . In addiin situ data to account for both deficiencies in their calibration as well as correcting for atmospheric attenuation. The lack of in situ data should be addressed and new innovative approaches are needed , the Special Sensor Microwave/Imager (SSM/I) and SSMI/Sounder (SSMIS), and the Advanced Very-High-Resolution Radiometer (AVHRR) are used. Currently, daily products e.g.,  typicallSequences of SAR images can be used to derive higher resolution drift information. Algorithms have been developed to calculate ice drift from successive pairs of SAR images covering a common area. They are generally based on a spatial correlation calculation between these images, at several resolution scales (from the coarsest to the finest). In Europe, Sentinel-1 is used by DMI to produce an operational sea ice drift product as part of CMEMS . SAR datRevisit is the key here: higher revisit of SAR images is naturally required. Algorithms often use image tracking features between consecutive images. This type of algorithms perform better if the images are taken with the same frequency, short interval, and ideally same geometry. Joint acquisition of multifrequency SAR would enable accurate sea ice drift products, which is not possible with stand-alone current mono-frequency SAR missions. Cross-pol channel is often preferred as it is less sensitive to incidence angle variation (at least for C-band SAR). Drift cannot be calculated in areas without characteristics . These are of course only estimates of the integrated ice trajectories between the time instants corresponding to the SAR acquisition times. Lagrangian drift products are typically 2-day trajectories with coarse resolution (62.5 km) and are not often assimilated even though the accuracy is satisfactory (3 km for 2-days drift). The TOPAZ4 system does assimilate these sea ice drift operationally, although the effect is relatively weak . A diffein situ air-sea or air-ice flux observations are extremely sparse in polar regions . Flux observations are essential for understanding the global energy budget , for evans e.g., , with alns e.g.,  or in icns e.g., . QuantifSince there are few reliable near-surface atmospheric observations to serve as constraints, reanalyses and satellite derived surface flux products have major errors and vary considerably between products . For exaThere are significant advantages to forecasting with a coupled atmosphere-ice-ocean system, especially on longer timescales. The intrinsic turbulence of the atmosphere limits predictive skill to timescales of days to weeks , whereasin situ estimates of air-sea-ice exchanges in the context of large-scale properties informing how to minimize errors in the bulk formulae parameterizations. Efforts such as YOPP, MOSAiC and ONR Marginal Ice Zone (MIZ) project are examples of projects aiming to address this gap.A particular limitation in this regard is with respect to the significant uncertainty in the atmosphere-ocean boundary layer, made even more egregious when considering sea ice. Boundary layer dynamics involve vertical scales unresolved by coupled forecasting systems, which must be parameterized e.g., . The excWe recommend further research to determine how best to represent these exchanges in a coupled forecasting system, with a focus on determining what aspects of boundary layer physics need to be resolved and what can be skillfully parameterized. For parameterized physics, we require that process studies be carried out to determine parameterizations and parameterization coefficients, including identifying the observations that should be sustained to validate estimated fluxes. Addressing these areas are primary goals to enable weekly-to-seasonal skillful predictions in the polar regions.Understanding how assimilating more observations will impact modeled analyses and short-term forecasts is of fundamental importance as new coupled models are being developed. For instance, preliminary results using a regional coupled model [CAFS from the NOAA Earth System Research Laboratory (ESRL)] demonstrated that current ocean reanalyses do not include realistic representation of subsurface water masses relative to observations taken in 2015 and 2016 (including Arctic Heat data). Forecast experiments using a high-resolution fully coupled regional model show that these water masses impact sea ice evolution on synoptic time scales through upper-ocean mixing and heat flux at the ice–ocean interface. It is expected these effects will increase as sea ice continues to decline and surface heat flux processes increase. In addition, assimilating real-time ocean observations in the initial forecast conditions allows for the identification of biases in the coupled system, which are difficult to isolate when the ocean is allowed to drift away from the observed state. Some studies e.g.,  have begThe ability to forecast sea ice conditions is of crucial importance for maritime operational planning . The curAssimilation of observational data is performed to reduce errors in model forecasts that can result from many factors including non-linear processes that are not deterministic responses to atmospheric forcing, poorly parameterized physical processes, limitations in numerical algorithms, and limitations in model resolution. Polar observational data assimilation is an essential part of GOFS forecasts. Sea ice concentration observations are currently assimilated from the Defense Meteorological Satellite Program (DMSP) SSMIS and AMSR2. These observations are used in conjunction with the Interactive Multi-sensor Snow and Ice Mapping System produced by the U.S. National Ice Center NIC; . A full The impact of data assimilation in the U.S. Navy models is significant. One measure that the U.S. Navy uses to determine the accuracy of the modeled sea ice edge  compared that of GOFS. Higher resolution (less than 1 km) sea ice concentration observations are available from the Suomi NPP Visible/Infrared (VIIRS). Although VIIRS observations can be obstructed by clouds, including high resolution VIIRS ice concentration into our data assimilation further reduced GOFS ice edge error by 19% (5 km) in the Arctic and 11% (4 km) in the Antarctic. This result points to the need for higher resolution sea ice concentration observations to use in model applications.In an earlier study using ACNFS to examine the impacts of sea ice concentration observations in ship routing and planning in boreal winter (January–March), assimilating satellite ice concentration observations reduced the projected track an ice breaker would take to a ship near the sea ice edge by an average of 150 km versus not assimilating sea ice concentration observations. This improved the time for planning operations by 12 h and reduced the distance a ship needs to prepare to encounter ice by 212 km.SIT observations are also important. Currently, pan-Arctic SIT observations on a daily basis are not available. Only limited satellite tracks per day are available that are aggregated on a monthly basis. In a recent study by The rapid evolution of the sea ice cover can have important impacts on coupled environmental predictions through a variety of processes . These iAs an illustration of the sensitivity of sea ice evolution to ocean mixing, an evaluation of the skill of two sets of sea ice forecasting experiments is shown in From There have been special observing periods of the Arctic and Antarctic in the past, in particular the successive International Polar Years (IPYs), the latest of which took place in 2007–2009 . Looking back at the impact of a recent IPY in a period with similar low-ice-coverage conditions in the Arctic, expanded sea ice in the Antarctic, and similar satellite coverage as today can provide another measure of the expected impact of the YOPP Special Observing Periods.in situ observations using an Ensemble Kalman Filter  regional coupled-model Arctic forecasts using global 0.5° GFS forecast fields for lateral forcing. The current configuration of the model includes the POP2 dynamical ocean model  SSTs and sea ice concentration. The MUR SSTs are used to initialize the ocean mixed layer with a mixed-layer depth diagnosed from the model. In order to identify whether using these satellite products in the initial conditions increases the skill of the 10-day forecasts, a series of 10-day hindcasts were performed for the time period of the ONR SeaState DRI, Oct. 1-Nov. 5 2015. The hindcasts are setup exactly like the real-time forecasts except the lateral boundary conditions are the GFS analyses instead of the GFS forecasts, in order to identify potential model biases. In addition, similar to the forecasts, hydrometeor mass and number are initialized with fields from the first day of the previous day’s hindcast to reduce spin-up time of cloud fields.Intensive measurements were taken of the ocean, surface, and atmospheric state during the SeaState campaign. This provides for a comprehensive observational database for model validation. C(x), that is consistent with the observational uncertainty, C(d), and the prior uncertainty of the control vector, 0)C(x [M′(N′) denotes the sensitivity of the vector of observations (the target quantity) with respect to the control vector, as simulated by the modeling system, and σ(ymocd) is the residual uncertainty in the simulation of the target quantity that remains even for a perfect control vector. The approach represents a network through observational locations and times and the observational uncertainty, but does not require real observations. Consequently, it can evaluate hypothetical networks/space missions based on assumed instrumental specifications and space-time coverage. Observations can range from point-scale (in situ) to gridded data sets or level-1 satellite data, if appropriate forward models/observation operators mapping the model’s state variables onto the respective data stream (The Quantitative Network Design (QND) approach constitutes a computationally efficient alternative to Observing System Experiments . The appr, C(x0) . In the r, C(x0) . Both sta stream  are avaiin situ sampling network for atmospheric CO2. For the physical sea ice-ocean system in the Arctic domain, Historically, QND was first applied by M′ for observations of SIT, sea ice freeboard, radar freeboard, laser freeboard, and snow depth along with precomputed model sensitivities N′ for forecasts of snow and ice volumes for three regions along the Northern Sea Route (North-East Passage) respectively denoted by West Laptev Sea, Outer New Siberian Islands, and East Siberian Sea. These sensitivities were computed with the Max-Planck-Institute Ocean Model  (which acts as an offset) is set to zero (perfect model scenario). Comparison of the top and middle panels shows the added value of the hypothetical snow product, not only for the snow volume forecast but also for the sea ice volume (SIV) forecast. SIV is sensitive not only to initial SIT but also to initial ice concentration and snow depth, which are both constrained by the snow depth product. SIV is also sensitive to some of the process parameters that are constrained by snow depth, notably the ice strength, see 3.As an example, The ArcMBA can be extended to cover further Earth Observation (EO) products and further target variables. In the setup used here, the model can simulate a range of sea ice-ocean variables in addition to those considered in the present study . Switching to a more comprehensive model configuration would enable the investigation of yet further variables. For example the model can be operated with its biogeochemistry module HAMOCC activated  or in a Various international efforts contribute to coordinate and support the vast and complex polar observing networks. These networks are maintained by a collection of national and international efforts and scientific projects. These include national efforts outlined above, such as IAOOS, FRAMs and NorArgo as well as diverse multi-platform observing projects such as the US SODA (Stratified Ocean Dynamics of the Arctic) program  that incA clear need for a coordinated approach for the Arctic has arisen following the International Polar Year (IPY) and is being developed through a series of bi-annual Arctic Observing Summits . These sWhile these efforts aim to address a broad range of societal needs, in this section we describe several particular initiatives that work to address specific gaps in the observing system important for environmental prediction.in situ part of the observing systems, which represent the largest component of the integrated observing system. Satellite Earth Observation programs provide the most developed and operational components of the system, which are run by space agencies and satellite monitoring services such as Copernicus13. The satellite systems provide data for near real-time monitoring as well as for long-term climate observations. Validation of the satellite-derived variables is an important part of the operational services. In situ observations play an important role for this validation, but there is very limited access to such data from the Arctic Ocean. Furthermore, most of the ocean observations are only available in delayed mode, because they are provided by underwater moorings and seafloor observatories. Some platforms that operate at the surface can transmit data in near real-time and can therefore contribute to operational monitoring of sea ice and ocean variables.INTAROS is a research and innovation project under the European Union Horizon 2020 program, running from 2016 to 2021, with objective to build an efficient integrated Arctic Observation System in the Arctic. This requires collaborative efforts among many institutions to extend, improve and unify existing systems, which in many cases are designed and developed for specific scientific disciplines. INTAROS focuses on the in situ data under INTAROS started in 2017 and will continue through 2020, coinciding with and contribute to the extensive data collection in the MOSAiC program , the water column and the seafloor. INTAROS contributes to all these components in collaboration with other observing programs and projects, by deploying new sensors and platforms to enhance the observing capacity in different Arctic regions. The collection of new gram see ; a netwo15. Community-based monitoring can also provide valuable data that cannot be obtained from normal research and monitoring programs. In the circumpolar Arctic region there are a number of observing programs addressing sea ice, oceanographic data and observations of marine mammals and fish which are very important for the communities.Arctic observing systems will benefit greatly from collaboration with local communities . INTAROS16, with the objective to examine the current status of Arctic data and to assess how fit-for-purpose the Arctic data are.Observations of the ocean are usually made for specific purposes. In order to save costs and improve marine knowledge, the European Union is now moving to a new paradigm where data are collected once and then used for many purposes. This paradigm is being implemented as part of the European Marine Observation and Data Network (EMODnet) consisting of a variety of organizations working together to assemble marine data and products, and to facilitate the dissemination of these resources to both public and private users. EMODnet is currently in its third development phase with the target to be fully deployed by 2020. Six Sea Basin Checkpoint programs were initiated as part of EMODnet, including the Sea Basin Checkpoint ArcticThe project (2015–2018) aimed to identify problems and knowledge gaps and was organized in 10 challenges: wind farm sitting, marine protected areas, oil platform leak, climate change, coasts, fisheries management, fisheries impact, river input, bathymetry and alien species. Within the project, each dataset found  was assessed on its spatial and temporal coverage, its accessibility and cost to access, the responsiveness and the temporal and vertical resolution. Also, each assessment report using a dataset  was assessed on its adequacy for the project. For the oil spill challenge an oil accident was simulated. This demonstrated the necessity for rapid acquisition and inspection of ocean current and wind data in order to provide a reliable response capacity.An important Arctic observing project called MOSAiC . The PPP was created under the auspices of the World Meteorological Organisation’s World Weather Research Programme (WWRP) to “promote cooperative international research enabling development of improved weather and environmental prediction services for the polar regions, on time scales from hourly to seasonal.” YOPP is a PPP flagship activity  has motivated an international effort called the Polar Prediction Project  a comprehensive real-time ocean observing network able to supplement Argo for polar regions has yet to be put in place, hindering progress toward coupled polar prediction. It is therefore recommended that a network of ice-borne measurement systems be deployed and supported operationally in ice-covered areas. These platforms represent well-proven technologies for year-round data collection and near-real time data transmission via satellites.The presence of a seasonal ice cover limits the availability of real-time Antarctic measurements are also needed, in particular, to evaluate changes that could be harbingers of continental ice melt. Recent studies also highlight the importance of measuring and understanding the intra-hemispheric ocean interactions on numerical weather prediction to climate time-scales . Ice-borConditions are changing rapidly with the loss of summer sea ice extent in the Arctic and changing ice-cover patterns in Antarctic marginal seas. Phenomena long considered negligible in the Arctic and Antarctic may be becoming important  and its positive impact in preliminary assimilation experiments call for symmetrical efforts in the Antarctic ocean, where such products do not exist at the moment.in situ methods provide poor spatial coverage. Neither is currently able to address the need for high spatial and temporal resolution observations of sea ice deformation over large regions. Observations providing information regarding ice deformation and redistribution during ridging are also lacking. There is a need for high-resolution  remotely sensed snow and ice property data for both the Arctic and Southern Ocean with sufficient temporal resolution to address these relevant features.Polar surface properties are often dominated by various forms of ice that vary rapidly on small spatial scales. Some remote sensing methods of ice properties  are not mature and offer little and/or coarse-resolution information from within the ice, whereas The value of polar observations for multi-range environmental prediction emerged during the last decade from a variety of impact studies. The importance of SIT initialization for seasonal forecasting, the significance of sub-surface initialization in ice-covered areas, are non-exhaustive examples that call for coordinated efforts  to enhance the Arctic and Southern Ocean observing networks.To date, few data withholding experiments (OSEs) or observation design experiments (OSSEs) have been undertaken for polar regions using real-time prediction systems. Performing such experiments using additional observations available during YOPP  is suggested to provide valuable information to guide the design of a sustainable real-time observing system for polar regions suitable for environmental prediction. In particular, multisystem exercises shall be encouraged to gain robustness in the observation impact assessments.Polar environmental prediction using coupled atmosphere-ice-ocean models is strongly sensitive to errors in fluxes across the surface interface and thus requires collocated information about the state of the atmosphere, sea ice and ocean, to be used for improving interface fluxes  and eventually data assimilation. Direct flux covariance measurements, in particular, would be immensely valuable in constraining bulk parameterizations used to represent fluxes in models.in situ observations in polar regions to global data assembly centers must be prioritized in order to make the observational efforts suitable for environmental prediction applications.Open access to data, especially real-time data, is a critical capability for improved sea-ice and weather forecasting and other environmental prediction needs. The optimal observing system will no doubt include a suite of different instrument types, since no single platform can be optimized for the full range of observing needs , and hence multi-platform coordination will be necessary, including coordination with local community-based observatories. This means that real-time dissemination of International collaboration will continue to be key for facilitating deployment of polar ocean instrument systems, including the fielding of drifting and anchored buoys, floats and gliders and free, rapid dissemination of the resulting data.The relative remoteness and harsh environmental conditions over polar regions will always hinder efforts to provide adequate observations for polar prediction. Over recent years, we have seen improvements in observing technology and capabilities that create new possibilities for how to construct and maintain the polar ocean observing system. The technologies make an adequate polar ocean observing system feasible, but the question remains, is it worth the cost? YOPP aims to help address this question by coordinating international observing activities and fostering efforts to assess the impact of additional observations on environmental prediction skill, including impacts on downstream users and products. Following the YOPP core period (2017–2019), there will be a consolidation phase to assess these impacts and develop recommendations toward sustained polar observation. This effort will culminate in a YOPP Final Summit planned for summer 2022, providing an ideal opportunity for funding and implementation agencies to benefit from this community effort.


TGR5 may service as a new target in the control of diabetic cardiomyopathy.Left ventricular hypertrophy is an independent risk factor in diabetic patients. TGR5 is shown to express in hearts, but its functional role in diabetes-induced cardiac hypertrophy remained unclear. The current study investigated the role of TGR5 on high glucose-induced hypertrophy of H9C2 cells. After incubation with a high level of glucose, H9C2 cells showed hypertrophic responses. Activation of TGR5 by lithocholic acid (LCA) ameliorated cell hypertrophy and enhanced SERCA2a and phosphorylated phospholamban (PLN) expression in H9C2 cells. Triamterene inhibited these effects at an effective dose to block TGR5. However, LCA failed to modify the free radical elevation induced by high-glucose in the H9c2 cells. Moreover, PKA inhibitors, but not an Epac blocker, markedly improved hyperglycemia-induced hypertrophy and attenuated the increased SERCA2a expression by LCA; it also attenuated the phosphorylated PLN and SERCA2a protein expression levels in high glucose-treated H9C2 cells. In conclusion, TGR5 activation stimulated protein kinase A (PKA) to enhance PLN phosphorylation, which activated SERCA2a to remove Ca Recently, BAs were also recognized as signaling molecules that may integrate with TGR5 or muscarinic receptors, the plasma membrane G-protein-coupled receptors, in addition to the nuclear receptors, including the farnesoid (FXR) and pregnane (PXR) xenobiotic receptors. The roles of BAs in regulating metabolic homeostasis and other important physiological functions have been documented3. BA binding sites and/or receptors are known to express in cardiovascular tissue, but the details regarding BA-induced changes in cardiovascular function are still unclear4.Bile acids (BAs) have been introduced as the byproducts of cholesterol metabolism in liver to secret into the duodenum5. TGR5 expression has been identified in cardiomyocytes6. However, most observations were challenged to conduct the association between TGR5 and cardiac modulation without a direct effect4.TGR5, also named as M-BAR, BG37 or GPBAR1, is belonged to G-protein-coupled receptors (GPCRs). Therefore, TGR5 activation may induce cyclic AMP (cAMP) accumulation7. Additionally, cardiac hypertrophy is also introduced as an elevation in protein synthesis and/or reactivation of the fetal gene program in cellular levels8. During the hypertrophic stimulation, calcineurinn dephosphorylated the nuclear factor of activated T-cells (NFAT) that may translocate into the nucleus to promote the gene expression, partly after forming a complex with GATA4. Therefore, calcineurin and NFAT are known for activation of the fetal gene program in response to hypertrophic stimuli, and they function as essential effectors during the formation of cardiac hypertrophy9. Consequently, atrial natriuretic peptide (ANP) and B-type natriuretic peptide (BNP) levels, which are raised as a result of hypertrophic gene expression, are used as clinical indicators10. Interestingly, ANP has shown antihypertrophic properties11. Moreover, the Ca2+ -calcineurin-NFAT signaling may integrate with another pathway, such as protein kinase C or mitogen-activated protein kinases (MAPKs), to coordinate the hypertrophic response12. Additionally, more transcription factors participated in cardiac hypertrophy were mentioned to explain it in detail13.Cardiac hypertrophy, one of the initial disorders in cardiovascular system, is known to induce heart failure. Cardiac hypertrophy is usually identified by an increase in cell size including physiological and pathological hypertrophy14. Many studies have used H9c2 cells to investigate hyperglycemia-induced cardiac damage16. However, the effect of TGR5 on DCM remains unknown4. Llithocholic acid (LCA), has been shown to modulate the bile acid pool and can specifically activate TGR517. Thus, we used LCA to activate TGR5 and investigated the mechanism for alleviating the hyperglycemia-induced cardiac hypertrophy in cultured cardiac H9c2 cells. Additionally, cyclic AMP (cAMP) is the major cellular signal coupled to TGR55. In the cAMP signaling pathway, protein kinase A (PKA) is activated by elevations in cAMP, and the exchange protein directly activated by cAMP (Epac) has been reported as another regulator of cAMP in the heart18. Therefore, we used specific inhibitors to investigate the potential mediation of LCA-induced effects in H9c2 cells by PKA or Epac.Diabetic cardiomyopathy (DCM) is one of the diabetic complication; cardiomyocytes exposed to high glucose levels exacerbates the hypertrophic response19. High-glucose treatment significantly increased in cardiomyocyte size compared to that of the normal group. Moreover, LCA inhibited high glucose-induced increases in cell size in a dose-dependent manner , which was similar (P > 0.05) to the level in vehicle-treated samples (173.7 ± 7.0 nM) induced by LCA (10 μM) under high-glucose condition.High glucose treatment resulted in markedly increased calcium levels in H9c2 cells Table . LCA sig14, ROS induces DNA damage, which was markedly increased in H9c2 cells by high glucose ; the SERCA2a mRNA level promoted by LCA did not differ between the cells pretreated with exendin (9–39) and vehicle (0.97 ± 0.16 vs. 0.98 ± 0.17) under the high-glucose conditions. Therefore, mediation of GLP-1 receptor activation by LCA appears unlikely.Western blotting analysis shown in Fig. We utilized pharmacological inhibitors to identify major signaling pathways involved in H9c2 cell hypertrophy. As shown in Fig. 6. TGR5 activation has been reported to have cytoprotective effects in the mouse heart21. TGR5 belonged to G-protein-coupled receptor, also named as M-BAR, GPBAR1 or BG37, is an established target of bile acids. Therefore, TGR5 activation may result in cAMP accumulation and/or receptor internalization5. cAMP is introduced to stimulate cardiac function22, but mice with biliary fibrosis show cardiac dysfunction6. The influence of bile acids in heart seems likely due to an integration with TGR5 and muscarinic receptors, the plasma membrane G-protein-coupled receptors, in addition to the nuclear receptors, such as the FXR and PXR xenobiotic receptors3.The present study found that TGR5 activation might ameliorate hyperglycemia-induced hypertrophy in H9c2 cells. These novel results demonstrate the effectiveness of TGR5 in a relevant cell line. The presence of the TGR5 receptor in the heart has previously been demonstrated23. The cells were exposed to high glucose to mimic diabetic cardiomyopathy as described previously15. Similarly, hypertrophy was identified in H9c2 cells under hyperglycemic conditions and was induced through the calcineurin/NFAT hypertrophic pathway based on Western blotting analysis. Then, we used the established cell model to investigate the influence of TGR5 activation using LCA, which has previously been documented as a physiological ligand for TGR524. Interestingly, LCA ameliorated the hypertrophy in H9c2 cells in a dose-dependent manner. The effects of LCA were reduced by triamterene treatment at a dose used to inhibit TGR520. Therefore, TGR5 activation alleviated hyperglycemia-induced hypertrophy in a cell model. These novel findings were supported by Western blotting data, which showed changes in hypertrophy-associated signaling proteins, and by RT-PCR, which was used to evaluate mRNA levels of hypertrophic biomarkers.We used the rat-derived H9c2 cell line in current study to investigate the role of TGR5 activation according to previous report25 and is related to the development of diabetic cardiomyopathy26. The ROS-induced oxidative stress in cardiac and vascular myocytes is mentioned to link with cardiac hypertrophy27. The diabetic cardiomyopathy is developed by oxidative stress mainly due to the elevated ROS production and/or decreased antioxidant defenses28. High-glucose produces a marked elevation in ROS, including oxygen free radicals, in H9c2 cells29. Moreover, TGR5 activation appears to exert several effects on ROS production30. Our data showed that LCA reduced oxidative stress in hypertrophic H9c2 cells, which was consistent with previous reports31. However, LCA failed to modulate elevated free radical levels, which were significantly attenuated by treatment with the antioxidant tiron in H9c2 cells. This finding is similar to the effects of GLP-1 receptor activation, which showed that Exendin-4 did not affect the ROS levels elevated by high-glucose in neonatal cardiomyocytes32. Thus, the effects are downstream of free radicals and are likely associated with endoplasmic reticulum stress. Moreover, apoptosis is popularly used indicate the hyperglycemia-induced cardiac damage32. However, hypertrophic and apoptotic signaling pathways are known to be regulated by ROS in cardiac myocytes27. Cells possessed various sensitivities to oxidative stress, which leads to myocyte-specific hypertrophy and apoptosis phenotypes. H2O2 has been shown to induce hypertrophy at a dose lower than that used to produce apoptosis in H9c2 cells33 and adult rat cardiac myocytes34. In addition to observations in clinical practice, cardiac hypertrophy has been identified in mice with excess bile acid levels6. Therefore, we focused on hypertrophic changes in cardiac cells.Oxidative stress is mentioned to involve in hyperglycemia-induced cardiac injury12. Although cardiac transcription factors are involved in hypertrophic responses13, the Ca2+-calcineurin-NFAT cascade has been established as the main pathway responsible for cardiac hypertrophy12. In the present study, high glucose levels increased Ca2+ levels in cardiac myocytes35. LCA attenuated the increased Ca2+ levels in a dose-dependent manner, and triamterene treatment revered these effects at a dose enough to inhibit TGR5. However, atropine treatment did not modify the effectiveness of LCA in H9c2 cells. The muscarinic M2 receptor has been reported to mediate bile acid-induced protection of arrhythmia in the heart36. These results agreed with a recent report using neonatal murine cardiomyocytes37 showing that ursodeoxycholic acid (UDCA) is a specific agonist of TGR5 but not FXR or M2 receptors. Therefore, LCA may reduce intracellular Ca2+ levels in H9c2 cells primarily through TGR5 activation.Calcium ions are known as the key-regulator of cardiac hypertrophy2+ levels in H9c2 cells in response to TGR5 activation did not associate with a decrease in free radicals, as shown above. Diabetic cardiomyopathy is related with a reduction in sarco/endoplasmic reticulum Ca2+ ATPase-2a (SERCA2a) expression and/or activity32. A decrease in SERCA2a levels is known to correlate with a lower myocardial function in addition to the impaired force-frequency and diastolic responses that may appear during the heart failure41. The membrane protein PLN is known to bind to SERCA2a, and phosphorylation of PLN may reduce SERCA2a inhibition and enhance SERCA2a function38. In current study, SERCA2a expression is markedly decreased by high-glucose in H9c2 cells32. Similarly, phosphorylated PLN was reduced. Triamterene blocked the effects of LCA at a dose used to inhibit TGR5. Our findings are similar to previous results regarding the GLP-1 receptor activation in neonatal mouse cardiomyocytes32. However, exendin-(9–39), the specific antagonist of GLP-1 receptor, did not modulate the LCA-induced changes in SERCA2a mRNA levels, which indicated that direct stimulation of GLP-1 receptors by LCA appears unlikely to occur.The mechanisms underlying the reduction in Ca39. TGR5 is known to enhance the cAMP accumulation5. Thus, TGR5 activation may promote PLN phosphorylation, as has been characterized in the current study. The classical cAMP effectors, e.g., PKA, and the exchange protein directly activated by cAMP (Epac), have been indicated in heart tissue38. We were therefore using pharmacological inhibitors to investigate the potential mediation by PKA or Epac on LCA-induced effects in H9c2 cells. Two pharmacologic inhibitors of PKA attenuated the effectiveness of LCA, however, an Epac blocker failed to produce similar inhibition. Thus, the increase in PLN phosphorylation by TGR5 activation is likely primarily PKA-dependent, which is similar to the GLP-1 receptor activation in neonatal murine cardiomyocytes32. PKA activates PLN via phosphorylation at Ser1639. It is interesting that LCA enhanced both SERCA2a and phosphorylated PLN levels. However, administration of PKA inhibitors and an Epac inhibitor did not affect the activation of TGR5 induced by LCA, which implied that a TGR5-triggered PKA/cAMP signaling pathway appears unidirectional. SERCA2a removes Ca2+ from cytosolic fraction to the sarcoplasmic reticulum, which is consistent with the reduction in the cellular Ca2+ levels induced by TGR5 activation. In animals, SERCA2a overexpressed hearts show an enhanced contractility, while SERCA2a knock-out mice develop heart failure earlier than the wild-type mice after pressure overload39. However, treatment with a TGR5 agonist did not modify the contractility in cardiomyocytes37. SERCA2a activated by a TGR5 agonist appears largely responsible for removing Ca2+ to the sarcoplasmic reticulum, which may alleviate hypertrophic responses in H9c2 cells. Therefore, as shown in Fig. Phosphorylation of PLN has been suggested to be cAMP-dependentThere are certain limitations to the present study. Application of an animal model of hyperglycemia, primary rat cardiomyocyte culture and genetic manipulation of TGR5 to further clarify the role of TGR5 in cardiac hypertrophy will be included in future work.2+ from cytosolic fraction and reduce hypertrophic signaling, e.g., via the calcineurin/NFAT pathway, to alleviate hypertrophy in H9c2 cells.In summary, we report novel findings that TGR5 activation may ameliorate the hypertrophic response in cardiac cells. TGR5 activation may stimulate PKA to enhance the phosphorylation of PLN, which activates SERCA2a to remove CaAtropine and exendin (9–39) from Sigma-Aldrich  were prepared in solution using culture medium. Additionally, lithocholic acid and triamterene from same supplier were prepared in dimethyl sulfoxide (DMSO) as stock solutions. The PKA inhibitor 14–22 amide (PKA I) is myristoylated at the N-terminus, which enhances its cell permeability . H89 is a potent selective inhibitor of PKA (Sigma-Aldrich). ESI-09 (Sigma-Aldrich) has been shown to block EPAC activity and function. Other reagents from indicated suppliers were all of analytical grade.40, in H9c2 cells was not varied with that in primary rat neonatal cardiomyocytes. It is the same as a previous report that hypertrophic responses in H9C2 cell line were similar as primary neonatal cardiomyocyte cells in vitro41.H9c2 cardiomyoblast cell line (BCRC No. 60096) was cultured in Dulbecco’s modified Eagle’s medium (DMEM) and Supplemented with 10% FBS. To generate the cellular model of cardiac hypertrophy, high-glucose medium containing 30 mmol/L glucose and 2% FBS H9c2 cells were used to incubate with H9c2 cells for 48 h after achieving 70% confluence. The D-glucose (Sigma) was dissolved in normal medium to prepare a medium with 30 mmol/L glucose. In preliminary experiments, the hypertrophic responses were compared between H9c2 cells and primary rat neonatal cardiomyocytes under high-glucose conditions using RT-PCR. The mRNA level of hypertrophic genes, such as BNP and β-MHC42.Cells seeded into a 24-well plate were starved in the serum-free medium for 4 h before the treatment with a TGR5 agonist (lithocholic acid) for 72 h. Following treatment, at room temperature, we fixed the cells with 4% paraformaldehyde for 15 min and permeabilized them with 0.5% Triton X-100 for another 5 min. The actin filaments in cells were characterized after staining with rhodamine phalloidin  for 20 min. Then, the nucleus was identified with 4–6-diamidino-2-phenylindole dihydrochloride (DAPI)  after staining for 15 min. Cells were imaged under fluorescence microscope  with an imaging system (DP2-BSW) from same supplier. We measured the myocytes that completely observed in the field. Changes in cell size were then quantified using NIH ImageJ software43, H9c2 cells were seeded at a density of 7.5 × 103 cells/ml in 24-well plates to incubate overnight. The cells were starved for 4 h and then exposed to LCA at the effective doses for another 72 h. After treatment, cells were incubated with 10 μM of DHE for 30 min at 37 °C. They were then fixed and imaged as described previously43. Five images of each sample were randomly selected under a microscope, and the average was used for analysis. We compared the results shown as percentage of the ROS level in cells from the image analysis as described above42.In the present study, dihydroethidium (DHE)  is applied to detect the intracellular ROS levels. Similar to a previous report44. Changes in fluorescence were recorded using a fluorescence spectrofluorometer . The [Ca2+]i values were estimated according to our previous report44. Background autofluorescence obtained from the unloaded cells was subtracted from all measurements. Additionally, the inhibitor effectiveness was compared after a 30-min pretreatment.We measured the intracellular calcium levels using fura-2, a fluorescent probe, as described previously45.Nuclear fractions were extracted by the application of CNMCS Compartmental Protein Extraction Kit  following a previous report46, we estimated the mRNA level of each signaling target gene in current study. Briefly, TRIzol reagent  is applied to extract the total RNA from cell lysates. Then, 200 ng of the total RNA was reverse-transcribed into cDNA using the random hexamer primers . All PCR experiments were performed using a LightCycler . The primers for ANP, BNP, β-myosin heavy chain (β-MHC), SERCA2a, and β-actin are as follows:Following our previous reportANP F: 5′-CACAGATCTGATGGATTTCAAGA-3′;ANP R: 5′-CCTCATCTTCTACCGGCATC-3′;BNP F: 5′-GTCAGTCGCTTGGGCTGT-3′;BNP R: 5′-CCAGAGCTGGGGAAAGAAG-3′;β-MHC F: 5′-CATCCCCAATGAGACGAAGT-3′;β-MHC R: 5′-GGGAAGCCCTTCCTACAGAT-3′;SERCA2a F: 5′-ATTGTTCGAAGTCTGCCTTCTGTGG-3′;SERCA2a R: 5′-CATAGGTTGATCCAGTTATGGTAAA-3′;β-actin F: 5′-CTAAGGCCAACCGTGAAAAG-3′;β-actin R: 5′-GCCTGGATGGCTACGTACA-3′.42. Protein extract were loaded at equal amounts into SDS-PAGE and transferred to a polyvinylidene difluoride membrane. Western blots were preformed to probe for calcineurin , NFAT3 , SERCA2a , phospholamban (PLN) , and phosphorylated PLN (P-PLN)  in addition to the internal standard, β-actin  and Histone H3 . Subsequently, membranes were washed with 1 × PBS-Tween and hybridized with appropriate secondary antibody (1:5000). Membranes were incubated with the ECL detection reagent and imaged using the Avegene imaging system . Densities of the bands were quantified using NIH ImageJ software and normalized to β-actin or Histone H3 expression45. This assay was replicated with 4 independent experiments.Western blotting analysis was performed using our previous methodResults shown as means ± SEM were calculated from the determined samples (n) in each group. Statistical analysis using two-way analysis of variance (ANOVA) followed by Tukey’s post hoc analysis was used to compare the differences. Then, p < 0.05 was considered significant.Supplementary Information SREP-18-39317


It is important to find criteria for preventive measures and appropriate assistive devices to reduce pedestrian injuries and increase walking in winter. Reducing the rate of falls on icy surfaces and improving people’s ability to safely cross a street in winter conditions by achieving an adequate walking speed, for example, need to be considered. This study explores pedestrian perceptions of fall risk, balance, and footfall transitions while using different designs for anti-slip devices on ice and snow-covered ice and relates these to measures of gait speed and friction. Trials were performed with nine pedestrians testing 19 anti-slip devices on ice and ice covered with snow. Laboratory tests of the dynamic coefficient of friction (DCOF) on plain ice were also performed. The findings suggest that there was conformity in the participants’ perceptions of good balance and low fall risk for one-fifth of the devices (three whole-foot designs and one design with built-in spikes). We also found that gait speed on icy pedestrian crossings is related to perceived fall-risk and balance control, but not to DCOF of the anti-slip devices. Slip-induced falls in winter are a substantial cause of pedestrian injuries ,2,3, andA slip may occur when the required friction between the shoe and the ground surface is insufficient . One metAnother aspect to consider is the capability of the human postural control system to recover from slip perturbations ,11. PostThis study explores pedestrian perceptions of fall risk, balance, and footfall transitions while using different designs for anti-slip devices on ice and snow-covered ice and relates these to measures of gait speed and friction. The research questions were: 1. How did the pedestrians rate their fall risk, balance, heel strike, and toe off on plain ice and snow-covered ice in the different anti-slip devices? 2. How were the measures of gait speed related to ratings of fall risk and balance and to the dynamic coefficients of friction (DCOF) of the devices?This research was conducted within a larger project for the development of test methods and criteria for efficient anti-slip devices . The resNineteen anti-slip devices, reflecting various designs, were selected for testing. The devices were classified into four design groups. The first three groups were devices attached to the subjects’ shoes: 1) A forefoot device that covers only the front of the sole (three devices/2–3 studs); 2) a heel device that covers only the rear of the sole (three devices/4–5 studs); 3) a whole-foot device that covers the entire sole . The fourth group were two shoes with different designs for built-in studs . Most devices are made of different polymers that hold together the construction and metal as friction-increasing material (except that with sandpaper) and are available in small, medium, and large sizes . The International Organisation for Standardisation (ISO) is a worldwide coalition of national standards organisations. An ISO document is developed as an international standard, and an EN preface to the document indicates that it is intended to be used in the European Union.In this experiment, the DCOF of the devices were tested in ambient laboratory conditions at FIOH using a method amended from EN ISO 13287:2012, which is the standard for safety shoes. FIOH further developed the method to suite conditions with ice and anti-slip devices or shoes with built-in spikes.The air temperature in the laboratory was +21 °C. Devices were tested on a smooth ice surface (5 mm thick), −4.6 to −5.4 °C, and the mean hardness of the ice was 13.54 MPa. The hardness corresponds to natural outdoor ice  and was The devices were tested in random order. Each device was mounted to a reference shoe on an artificial foot, and 12 tests in a row were performed per device. Mean and standard deviations were calculated . Each test was performed on a new ice surface: 1) A normal force of 500 ± 25 N was applied on the ice surface through a reference shoe  and attached device, at a 90° angle to the surface; 2) sliding the device parallel to the ice in a forward direction was performed with a sliding velocity of 0.3 (±0.03) m/s. The frictional force was measured against the direction of movement . Four test tracks were prepared at the indoor ice rink, each one 10 metres long and 1.2 metres wide: Plain ice, ice covered with 3–5 mm snow, a dry concrete floor, and a compact snow track outside the ice rink. The devices were tested in random order and according to a procedure developed in earlier experiments [In this study, data from the trials on plain ice and snow-covered ice are analysed. The experiment was performed over four days. The hardness of the smooth ice surface was tested, and temperature and humidity were measured on the ice surface and two metres above the ice surface. Measures on the four days showed minor variations in hardness, with mean values of 9.36 MPa for the indoor ice. The air temperature on the surface of the ice varied by 1.5 °C (mean −3.9 °C), which was considered not to have an impact on the results. The indoor air temperature varied by 2.1 °C (mean 4.9 °C). There were smaller variations in humidity on the ice surface than in the air. The degree of humidity on the ice can affect how the snow attaches to the ice. The participants, five women and four men, with a mean age of 47 (41–71) years, corresponded to a normal population in terms of variations in background parameters, previously described in detail . Of thesThe study was performed in compliance with the ethical principles for good research practice. This includes that informed consent was obtained from each participant. Risks involved were managed by protective equipment (kneepads and helmet) provided, and participants were encouraged not to expose themselves to unnecessary risks or exceed their ability during the trials on ice tracks. Participants’ indoor gait patterns were registered by a 10-metre timed walking test at a comfortable speed and maximum speed, respectively . To evalBaseline indoor gait speed, as well as stride length and double-support phase, varied between participants .During the trials, participants were asked to rate different qualities of the gait cycle, including heel strike, toe off, balance, and risk of falling, on a VAS scale (0−100)  for eachBaseline data on gait were analysed with GAITRite®. IBM® SPSS® Statistics 25  was used to analyse data on time and participants’ ratings on scales, and these are presented with a median (max and min) value. Mean and standard deviation measures were used to show the DCOF. To identify significant qualities of anti-slip devices, we defined ‘good walking balance’ as ≥80 points and ‘low fall risk’ as ≤20 points on a 100-point scale. Participants matching ratings for the impact of the device on balance and fall-risk was defined as inter-subject variations ≤30 points on a 100-point scale. A ‘higher maximum gait speed’ was defined as ≥160 cm/sec. Wilcoxon signed ranks test was used to assess the difference between two measurements on a single sample. and fall risk, respectively. Another five devices—heel device #4, whole-foot devices #7, #11, and #12, and in-built spikes #18—received good ratings concerning fall risk and walking balance, although the participants’ perceptions varied more  and a good walking balance (≥80 points) on uncovered ice. For four of these—whole-foot devices #13, #14, and #15 and one in-built device, #19—the participants agreed in their perceptions  of balance ied more .On the snow-covered ice, 12 devices received good ratings for providing low fall risk and good walking balance. Shared views were shown for three devices—whole-foot devices #14, #15 (sand) and built-in spikes, #19—for good walking balance, and for one device—the whole-foot device #11—in terms of low fall risk . p < 0.05) for devices #2, #8, #9, #12, #16, and #17. On snow covered ice, the speed was significantly reduced for device #2. The participants tended to walk a bit slower on the ice track with most devices  in compaTheir ability to reach their maximum gait speed when asked to walk as fast as possible was significantly reduced in the experimental situation with all 19 devices on ice  and snowThere seems to be a pattern that six  of the nine devices with low fall risk/good balance also had a higher maximum gait speed (>160 cm/sec) during the trials on uncovered ice. On the tracks with snow-covered ice, participants could walk at a higher speed with 11 of the devices. Nine of these  also received ratings for good balance and low fall risk. The DCOF of the devices varied between 0.20 and 0.54 . The device with the highest DCOF was device #2, designed with two studs under the front part of the shoe attached by a rubber band around the forefoot. In addition, whole-foot devices #7 and #8 (both whole-foot devices with 10–12 studs) also had high DCOF. Conversely, the least DCOF was found for three whole-foot devices designed with sandpaper (device #15), ropes (device #16), and ropes/springs  of the three devices with the highest DCOF was perceived to offer good walking balance and low fall risk. Also, for the three devices with the lowest DCOF, there was a lack of correspondence between DCOF and subjective ratings of fall risk and balance. Despite low DCOF, device #15 was perceived as providing good balance and low fall risk.With a few exceptions, there was little consensus between the participants in their perceptions of fall risk, balance, heel strike, or toe off when walking on uncovered ice with the different devices. This can be explained by the variation in the background characteristics due to the selection of the test group to represent a normal population of pedestrians. They differed in age, experiences, and perceptions, as well as balance abilities and their usual movement/gait patterns including step length, footfall transitions (toe/heel), or preferred walking speed. It is not surprising that people may need devices with different designs. However, of 19 tested devices, the participants agreed on three whole-foot devices and one built-in device, which they all felt provided both low fall risk and good walking balance on uncovered ice. Another five devices also stood out as providing low fall risk and good balance, but here, the pedestrians’ ratings varied more. One design that would fit all would be the best , therefoThe correspondence between the laboratory measures of DCOF and the participants’ perceptions of walking safety or risk of falling with the devices on uncovered ice was low. Only one  of the devices with the highest DCOF also offered low fall risk and walking balance. In contrast, another device  provided good balance and low fall risk on ice, despite low DCOF. In general, the pedestrians’ comfortable and maximum gait speed decreased during the trials on the ice tracks. Nevertheless, devices viewed as providing low fall risk/good balance also generated the highest maximum gait speeds. Earlier research has shown that self-selected pace and step length are two independent variables that increase walking stability and reduce the risk of slipping . Age-relThe static position with the anti-slip device sliding parallel to the ice during experimental measurements of DCOF does not reflect the rolling foothold transition during usual gait. This could explain why the present study showed no associations when comparing measures of the DCOF of the device with subjective ratings and speed. Nonetheless, for one-fifth of the devices, the pedestrians agreed in their perceptions of good balance and low fall risk, and the related measures of higher gait speed on uncovered ice.There is, therefore, an indication that a standardised test method for classification of anti-slip devices has to a high degree be based on subjective ratings and observations of compensatory mechanisms to obtain walking safety, speed, and balance control. To be included in a standard, the measuring of DCOF has to be changed to better simulate the change in friction properties through a normal rollover from heel-strike to toe-off instead as it is now measured in a linear process with the device in a fixed position.The test conditions maximum gait speed and uncovered ice distinguished devices providing high speed/balance and low fall risk. There was also a conformity in the pedestrians’ ratings. However, when the ice was covered with a thin layer of snow, the results differed, which indicates a need to test devices on a variety of walkway qualities encountered in urban environments. A strength of the study design is that the participants in this experimental study represented a normal population of pedestrians. They performed extensive trials indoors and on four different winter walkway surfaces with 19 anti-slip devices and answered qualitative surveys, hence providing multidimensional data. Repeated measurements were made on the same individuals, and data were presented mainly descriptively. Studies with an increased number of subjects and the use of random effects models to estimate the various parameters for each performance variable are needed to verify these results. In general, there was little consensus among pedestrians regarding perceptions of fall risk, balance, heel strike, or toe off using the different devices on icy pedestrian crossings. There was agreement on good balance/low fall risk for one-fifth of the tested devices (three whole-foot designs and one design with built-in spikes). The ratings for good balance/low fall risk corresponded with higher maximum gait speed, but not with DCOF. These findings imply that measures to increase the DCOF also need to account for the distribution of the friction points under the sole to ensure speed and walking safety/balance. To safely cross an urban street, both sufficient speed and perceived walking safety/balance are required. Methods to evaluate anti-slip devices has to reflect the rolling foothold, with its transition and forces, during gait. Especially when speeding up, the forces placed on devices through longer strides and shorter double-support phases increases the need for friction at heel strike and toe off. Also, the balance enabling properties of the device has to be satisfying, for the pedestrian to be able to walk fast with maintained balance control and perceived safety when crossing a street.


These species were also found south of the marginal ice zone (MIZ). Cells in the water column under the sea ice were typically high-light acclimated, with a mean light saturation index (Ek) of 138 μmol photons m−2 s−1 and a ratio between photoprotective carotenoids (PPC) and Chl a (w:w) of 0.2. Remotely sensed data of [Chl a] showed a 32,000 km2 bloom developing south of the MIZ. In effect, our data suggest that the observed under-ice bloom was in fact a bloom developed in open waters south of the ice edge, and that a combination of northward-flowing water masses and southward drifting sea ice effectively positioned the bloom under the sea ice. This have implications for our general understanding of under-ice blooms, suggesting that their origin and connection with open water may be different in different regions of the Arctic.Under-ice blooms of phytoplankton in the Chukchi Sea have been observed, with strong implications for our understanding of the production regimes in the Arctic Ocean. Using a combination of satellite remote sensing of phytoplankton biomass, in situ observations under sea ice from an autonomous underwater vehicle (AUV), and in vivo photophysiology, we examined the composition, magnitude and origin of a bloom detected beneath the sea ice Northwest of Svalbard (Southern Yermak Plateau) in May 2010. In situ concentration of up to 20 mg chlorophyll a [Chl  Sea ice plays a dual role in the control of high-latitude phytoplankton blooms by influencing both light shading and stratification  in the PAR region, EPAR in μmol quanta m−2 s−1 , the spectral irradiance, E (λ) in μmol quanta m−2 s−1 nm−1, and day length in hours  is a function of three variables, the irradiance (c3 (prymnesiophytes such as Emiliania huxleyi and Phaeocystis pouchetii) and small prasinoxanthin-containing prasinophytes, typical for this area  can be used for chemotaxonomical and photoacclimation information. Different pigment groups can be identified , Chl a fluorescence-based maximum rETR rate, rETRmax , and the corresponding light saturation parameter   and pigment functions (light harvesting versus photoprotective) to provide maximum growth rates  and low-light-  acclimated cells  of spring bloom forming phytoplankton are typically 50–60 μmol photons m−2 s−1 at 0–10 m and 30–50 m depth, respectively in May–June , an AUV deployed under sea ice , vessel-based in situ profiles and corresponding work on cells in the laboratory (in vivo and in vitro). The major “pro” of using polar orbiting satellites equipped with ocean colour multispectral imagers for [Chl a] are the covering of large areas while the “cons” are that the information is restricted to water surface (upper 1–2 m), dependent on illumination from the sun and absence of clouds ”, we combined information of phytoplankton biomass  analyses were performed onboard the vessel, whilst HPLC was done at Norwegian University of Science and Technology (NTNU). Water samples for cell identification, pigment (HPLC) and Chl a samples from CTD Niskin bottles were taken immediately after the CTD profiles and the AUV survey and were filtered through Whatman GF/F glass fiber filters (25 mm diameter) until the filters were coloured . Prior to being measured, the algal pigments on filters were extracted in 5 mL of methanol  and the extracts were refiltered through a 0.2 μm sterile Microsart syringe filter to remove any potential light-scattering particles and debris.Spectrophotometric and fluorometric [Chl a] measurements, filter extracts were measured and the optical density (OD) spectra  were obtained, using methanol (MeOH) as blank (OD at 750 nm). The concentration of Chl a (mg m−3) was calculated using the OD red peak of Chl a, at 665 nm in vitro and the extinction coefficient for Chl a in methanol at 665 nm (Mackinney For spectrophotometric  estimation in the section below.Salinity, temperature and in situ fluorescence of [Chl ine Fig. . The halers Fig. . TypicalEPAR values at 10 m depth  ranged from 50 μmol photons m−2 s−1 at midnight to 670 μmol photons m−2 s−1 at noon.In situ downwelling irradiance profiles were measured in open leads at ice stations 1–3 Fig. . EPAR vaa]  show that the lowest salinities (range 33.85–33.90) corresponded with the lowest temperatures (range − 1.66 to − 1.61 °C). The under-ice photomosaic images from AUV  indicated a patchy and dynamic underwater light field  that varied as a function of ice/snow thickness and leads seen as differences in light intensity and colouration , dark green (thick ice) to brighter green to brownish indicating different [Chl a] in the water masses and as biofilm of ice algae at the underside of sea ice.The undulating AUV transects revealed that under-ice water temperature was generally at − 1.66 °C from 5 to 25 m depth, with corresponding salinity of 33.9 Fig. . The verThalassiosira antarctica var. borealis (Northern cold water to temperate distribution), T. nordenskioeldii (Northern cold water to temperate species) and Chaetoceros socialis species complex . Also, the prymnesiophyte (coccolithophore) Phaeocystis pouchetii was abundant , but comprised low biomass indicated by HPLC. The overall biomass was dominated by diatoms, confirmed by high diatom-specific Chl c1+2 and fucoxanthin concentrations. The chemotaxonomic tracers for Phaeocystis pouchetii indicated low biomass relative to the larger diatoms .The phytoplankton species composition in the water masses underneath the sea ice and sea-ice bottom samples was different Table , Fig. 6.Navicula spp. and Nitzschia frigida. Present in low cell numbers were the pennate sea-ice diatoms Entomoneis sp., Hantzschia weiprechtii, Pseudogomphonema arcticum, Synedropsis hyperborea and the centric diatom Attheya septentrionalis. The ice algal community at St 2 was by numbers totally dominated by the dinoflagellate Polarella glacialis with many resting cysts, followed by diatoms Navicula sp. 1–2 and Nitzschia frigida  from St 1 was characterized by ice algae dominated by the pennate sea-ice diatoms da Table .a, Chl c1+2, fucoxanthin and diadinoxanthin), verified by microscopy, at all depths. In addition, Chl b indicated the presence of the observed Pyramimonas sp., which do not obtain the marker carotenoid prasinoxanthin found in pigment group prasinophyceae II  relative to diatoms. Light-harvesting pigments  to Chl a ratio (w:w) was close to 1 (Table a ratio (w:w) was approximately 0.2. At 10 m depth at St. 3, cells contained both diadino- and diatoxanthin and the PPC to Chl a ratio (w:w) was 0.22.The HPLC pigment chemotaxonomic signatures from St.1 and 3 revealed dominance of diatoms  ratio of 0.9  ratio of 0.8, indicating peak of bloom to start of post-bloom phase , 96 (St 2) and 89 (St 3) μmol photons m−2 s−1, respectively. The maximum photosynthetic rate (rETRmax) was highest in cells from surface and inversely related to α. The mean NPQ at light-saturated photosynthesis (EPAR of 500 μmol m−2-s−1) from cells sampled at St. 1–3 was 1.42 ± 25.9%  from St 1–7 relative to in situ [Chl a] by AUV fluorometer and CTD fluorometer from vessel, gave an in vitro/in situ [Chl a] ratio (w:w) of 2.92 ± 0.86 (n = 7) which indicates that in situ [Chl a] estimations from healthy and photosynthesizing cells (fluorometer from AUV or ship CTD fluorometer) is only 35% relative to in vitro [Chl a], i.e. autofluorescence (pigment extracts) not affected by PQ and NPQ, see discussion , an AUV equipped with environmental sensors and analyses from water samples (from a research vessel). Recent studies in the MIZ north and west of Svalbard  and a NW transport of AW (mean current velocity of 5–10 cm s−1) in the location of this study, the SW flank of the Yermak Plateau. Also, sea-ice data during May 2010 in the examined region showed small variations in extent and sea-ice concentration, but it started to disintegrate from 27 May 2010 . Hence, we can conclude that the prevailing oceanographic and ice conditions are supporting our assumption that the observed bloom is of an advective origin  with only traces found of Chl c3 and acyloxy-fucoxanthin used as chemotaxonomic markers for prymnesiophytes such as Phaeocystis pouchetii  indicating that the under-ice bloom (ambient E < 2 μmol m−2 s−1 at 10 m depth) may have developed in open water and HL conditions. In addition, the taxonomic composition of the healthy phytoplankton community (seen by a] at sea surface (remote sensing image of Chl a for May 2010) from open waters to 31 km north of MIZ, and relatively high amounts of photoprotective carotenoids  also indicates HL-acclimated cells  at ice St 1–3 from 2 to 45 m depth indicate HL-acclimated cells and is comparable with HL-acclimated cells from the Arctic characterized (derived from 14C incubations) with Ek > 60 μmol photons m−2 s−1 , 0.74 ± 0.09 (SE) and 138 ± 28 (SE) μmol m−2 s−1, respectively  that were HL acclimated (grown at E of 400 μmol photons m−2 s−1 at 24 and 12 h day length) and LL acclimated (grown at E of 25 μmol photons m−2 s−1 at 24 and 12 h day length) isolated from the same area in the Barents Sea  obtained typically an Ek of 60 (12 h day length) to 70 (24 h day length) and 31 (12 h) to 35 (24 h) μmol photons m−2 s−1, respectively  technique, often with 20 min EPAR incubation time  into C-fixation rates  difficult. PAM- and O2-electrode-derived Ek values for diatoms may be similar to short time 14C incubations (20–30 min) using the “Photosyntethron” technique . However, it should be noted that Phaeocystis pouchetii generally obtain higher Ek that is 2–3 times higher than diatoms under same ambient light conditions  in three classes of phytoplankton as a function of temperature  using ETR (PAM), O2 evolution and 14C incubation, gave Ek values in agreement with each other from 0 to 15 °C for diatoms . Closest agreement was found between Ek derived from O2 and rETR data, with 14C generally giving lowest Ek values. Since most Ek values in literature are based on 14C method, a direct comparison may be hard to interpret. Still, our Ek data indicate that the diatom cells are HL acclimated and is in the low range of under-ice Ek findings by Assmy et al.  in the thylakoids inside the chloroplasts which induces de-epoxidation of diadinoxanthin to diatoxanthin in diatoms and prymnesiophytes (coccolithophytes) through the “xanthophyll cycle” of PPC  and these two factors cannot explain the high Ek and high PPC indicating HL-acclimated cells  was not acclimated to the ambient light intensities. High cellular contents of diadinoxanthin, indicating ML- (medium) to HL-acclimated cells, were found at St 1 and 3 (Table a ratios (w:w) ranging from 0.17 to 1.19 typical for ML-HL-acclimated cells , which can be regarded as a high density bloom  and at 10 m depth  ranging between 3 and 6.5 mg Chl a m−3. Differences between in situ and in vitro estimations of [Chl a] may be, in addition to patchiness of phytoplankton biomass, due to quenching of Chl a fluorescence in living cells and differences in methodology . In living cells (in vivo) ϕF denotes the fraction of light absorbed and utilized by PSII  that is converted to Chl a fluorescence  measurements can be used to evaluate the effect of photosynthetic absorption and utilization of ambient irradiance by looking at PQ and NPQ. The highest ϕF for Chl a fluorescence will be found in vitro (extracted pigments) since the Chl a has lost its apoproteins and is non-functional in photosynthesis (the rate constant for photochemistry is 0) and a value of ϕF of 30% can be obtained , and the rest, 25–30%, will be used in photochemistry affecting PQ  and light absorption and corresponding heat radiation from PPC thus not sending the absorbed energy further to PSII (reviews in Govindjee Caution regarding in situ (or in vivo) versus in vitro Chl s, Babin ]. The inin . The a] ratios  from research vessel and/or AUV fluorometer we obtained ratios of 1.3–4.4 with a mean ratio of 2.92 ± 0.86 (n = 7), indicating a significant loss in ϕF due to PQ and NPQ  indicated healthy cells with a high fraction of open reaction centres to perform photosynthesis, i.e. cells far from light saturation in the under-ice ambient light . In contrast, Chl a fluorometers have about 100–200 times higher sensitivity than spectrophotometers, but are dependent on calibration from spectrophotometers using Chl a standards  along the entire transect, including the ice stations deepest into the sea ice. Typically, the Chl a maximum was closer to the surface under the ice (around 10 m depth) and deeper within the MIZ and open waters (20 m depth). Also, the, species composition was similar at northernmost ice stations (31 km into the sea ice) and south of the MIZ (open waters). We conclude that the bloom observed beneath the sea ice North of Svalbard in May 2010 was an advective phenomenon, with cells that had developed in open water further South. This advective mechanism is in contrast to the in situ under-ice bloom scenarios elucidated by Arrigo et al. (A coordinated campaign with the main aim of studying the dynamics and origin of an under-ice pelagic bloom north of Svalbard was carried out in May 2010. A continuum of high [Chl o et al.  and Assmo et al.  where uno et al. .


Our understanding of how global climatic changes are translated into ice-sheet fluctuations and sea-level change is currently limited by a lack of knowledge of the configuration of ice sheets prior to the Last Glacial Maximum (LGM). Here, we compile a synthesis of empirical data and numerical modelling results related to pre-LGM ice sheets to produce new hypotheses regarding their extent in the Northern Hemisphere (NH) at 17 time-slices that span the Quaternary. Our reconstructions illustrate pronounced ice-sheet asymmetry within the last glacial cycle and significant variations in ice-marginal positions between older glacial cycles. We find support for a significant reduction in the extent of the Laurentide Ice Sheet (LIS) during MIS 3, implying that global sea levels may have been 30–40 m higher than most previous estimates. Our ice-sheet reconstructions illustrate the current state-of-the-art knowledge of pre-LGM ice sheets and provide a conceptual framework to interpret NH landscape evolution. How global climatic changes are translated into ice-sheet fluctuations and sea-level change is not well understood. Here the authors present a compilation of empirical data and numerical modelling results of pre-LGM Northern Hemisphere ice sheet changes and show pronounced ice-sheet asymmetry within the last glacial cycle and significant variations in ice-marginal positions between older glacial cycles. Accurately reconstructing the former extent of ice sheets is, therefore, vital to understand how global climatic changes are translated into ice-sheet fluctuations, providing important constraints for future predictions of sea-level change2. Furthermore, knowledge of the configuration and evolution of palaeo-ice sheets through time is required to understand their impact on a wide range of important issues across numerous disciplines, including the Earth’s rheology, long-term landscape evolution3, palaeoecology4, genetic diversity5 and anthropology6. Over the last few decades, unprecedented growth in the size and diversity of empirical datasets used to reconstruct the extent of palaeo-ice sheets, together with major improvements in our ability to numerically model their dynamics7, have led to important advances in our understanding of ice-sheet configuration through time. However, the vast majority of these reconstructions12 focus on ice-sheet deglaciation since the Last Glacial Maximum (LGM) c. 26.5 ka13. In contrast, there have been few attempts at constraining the extent of ice sheets prior to the LGM15. This is largely because of the paucity of empirical data, which are highly fragmentary in both space and time16, and has led to an over-reliance on loosely constrained and/or coarse-resolution numerical modelling at the global or hemispheric scale20. Thus, we have very limited knowledge of the Earth-surface conditions of the mid- and high-latitudes throughout most of the Quaternary.The growth and decay of continental ice sheets have formed an integral part of the Earth’s climate system during the Late Cenozoic and particularly over the last 2.6 Ma (the Quaternary Period), resulting in major fluctuations in global sea levelTo address this issue, we take a consistent methodological approach in synthesising empirical data and numerical modelling results related to pre-LGM ice sheets to produce testable hypotheses of Northern Hemisphere (NH) ice-sheet configurations at key time-slices spanning the Quaternary. These hypothesised ice-sheet extents are used to assess spatial differences in ice-sheet configuration within and between glacial periods, produce new first-order estimates of global sea level associated with each time-slice, and explore the implications for long-term landscape evolution.21. In this study, maps showing the available evidence relating to past ice-sheet extent , which encompasses the onset of major NH glaciation recorded by terrestrial evidence, around 2.4–2.5 Ma;26 and the late Gauss Chron (2.6–3.6 Ma), which includes the onset of major NH glaciation recorded by ice-rafted debris in ocean cores, around 2.6–2.7 Ma28 , evidence derived from sedimentological and stratigraphic investigations was incorporated into our reconstructions  represent the likely chronological maximum extent, the mapping of time-transgressive ice margins for time-slices older than the last glacial cycle is precluded by the fragmentary nature of the empirical data and problems of dating older glacial sediments at sub-stage resolution.In total, we reconstruct a maximum, minimum and best-estimate NH ice-sheet extent for 17 separate time-slices prior to the LGM, and a best-estimate for the comparatively well-constrained LGM9 that glaciers and ice sheets developed in continental interiors (i.e. NE Asia and eastern Europe) early in the last glacial cycle, whilst large ice sheets close to maritime moisture sources (i.e. western European Ice Sheet (EIS) and Laurentide Ice Sheet (LIS)) attained their maximum extent towards the end of the glacial cycle. A comparison between the LGM and MIS 4 ice extents  compared to the smaller (and separated) Laurentide ice masses  during the late Gauss Chron  Fig.  has been36. Marine-based ice sheets, such as the present-day West Antarctic Ice Sheet, are more susceptible to rapid and potentially unstable ice-sheet collapse, for example through increased iceberg calving, in response to climatic and sea-level variations37. The Greenland Ice Sheet (GIS) and CIS have a comparatively small magnitude of variation in ice-sheet area between the reconstructed time-slices , although our best-estimates suggest that the NH ice sheets may have been slightly smaller than those of previous studies40. Our expectation is that future work might test and refine any discrepancies . Indeed, the one obvious discrepancy between our estimated ice volumes and the global sea-level curve occurs during MIS 3, when our reconstructions at four time-slices  imply that ice sheets were considerably smaller and that, consequently, global sea level was substantially higher, possibly by as much as 30–40 m  ice-volume variations to high-amplitude, low-frequency (100 ka) variations under similar orbital forcings46.Regions shaded dark red were subject to glaciation 8–10 times through the last 1 Ma and were the main nucleation centres for the NH ice sheets47. Although some of the older ice-sheet reconstructions that informed Fig. 26   were compiled through a literature search of published evidence for the spatial extent of NH Quaternary glaciation. Details of the source publication, methodology and age of glaciation were entered into a database , 5a (72–86 ka), 5b (86–92 ka), 5c (92–108 ka), 5d (108–117 ka), 6 (132–190 ka), 8 (243–279 ka), 10 (337–365 ka), 12 (429–477 ka), 16 (622–677 ka) and 20–24 (790–928 ka), the early Matuyama palaeo-magnetic Chron (1.78–2.6 Ma), and the late Gauss palaeo-magnetic Chron (2.6–3.59 Ma) ). Sedimentological and stratigraphic data (including marine seismic data) were used to supplement empirically derived and numerically modelled ice-sheet outlines and were particularly targeted for the oldest time-slices , for which published ice-sheet outlines are scarce.Our literature search was based on the following general principles. We mapped the changing ice-marginal position of the ice sheets and therefore did not include data points that are located well inside a suggested ice margin. In cases where the same author(s) have published multiple reconstructions for the same area, we used the most recent hypothesised ice-sheet extent. When using ice-sheet outlines that are derived from a synthesis of previously published empirical evidence13. Rather, a best-estimate reconstruction was derived mainly from the compilation of Ehlers et al.14, with modification of the ice-sheet limits in some areas  for the relative warm intervals (e.g. MIS 5a and 5c), and the largest reconstruction (i.e. peak climatic coldness) for all other time-slices.59. We did not plot the locations of areas in which the absence of glaciation has been inferred. However, information on ice-free areas informed the best-estimate reconstructions and is included in the explanations that accompany the maps , which are often regional or ice-sheet wide; modelled outlines of ice-sheet extent (coloured lines), which are typically ice-sheet wide or span the NH; and point-source data (red circles) that show the former occupation of a site by ice . This is because of the broad, hemispheric scale, focus of our reconstructions and their implications for global sea level, as well as the uncertainties involved in reconstructing the extent of mountain glaciation through the Quaternary. The present-day ice cover is incorporated into our reconstructions in all cases apart from the minimum reconstructions for the relatively warm periods of 45 ka, MIS 5a, MIS 5c and the late Gauss palaeo-magnetic Chron.Although mountain glaciers, ice fields and ice caps developed in many high-relief areas of the NH during the Quaternary, including the Himalaya, the European Alps and the Rocky Mountains64.Our reconstructions aim to capture the maximum extent of each ice sheet within each time-slice, with the exception of the comparatively warm periods of 45 ka, MIS 5a and 5c for which we attempt to capture the peak warmth. The maximum extent of glaciation may have occurred at any time(s) within a time-slice; for example, for the long late Gauss palaeo-magnetic Chron (2.6–3.6 Ma), the maximum extent of the EIS probably occurred close to the youngest part of the time-slice, around 2.6–2.7 Ma. We do not capture variations in ice-sheet extent within a time-slice. For example, in the early Matuyama palaeo-magnetic Chron (1.78–2.6 Ma), our best-estimate reconstruction does not show evidence for a reduced GIS during an Early Pleistocene warm period around 2.4 MaDetails about the decisions made in reconstructing the maximum, minimum and best-estimate ice-sheet extents for each separate time-slice are provided in 18O record1 . In order to calculate the area of each ice sheet, the maximum reconstruction for the CIS was used to define the boundary between the CIS and the LIS.To avoid unnecessary complexity, several ice-sheet templates were used for the ice extent in the North American Cordillera, Greenland, Iceland and NE Asia. There are six configurations for the CIS. The first configuration is the maximum Quaternary (pre-Reid) extent in Alaska31. The second configuration is the ice-sheet extent at the LGM31. The third configuration is undefined mountain glaciers/no ice sheet (no outline).In Greenland, there are four ice-sheet configurations. The first configuration shows the ice sheet at the shelf-break. The second configuration shows the ice sheet on the inner- to mid-shelf. Because of the narrow continental shelf around parts of Greenland, we do not differentiate between an inner-shelf or mid-shelf position. The third configuration is the present-day coastline. The fourth configuration is the present-day ice extent. There are three ice-mass configurations for Iceland. The first configuration shows shelf-break glaciation. The second configuration shows the ice sheet at the present-day coastline. The third configuration is the present-day ice extent. There are three configurations for ice masses in NE Asia. The first configuration is a combination of two reconstructions of maximum Quaternary ice-sheet extent18O stack, as described in Supplementary Tables It is interesting to note the generally poor alignment of the published numerical modelling results with the empirical evidence . Different ice masses reached their respective maxima at different times during the last glacial cycle; for example, ice in northern Eurasia and mountain glaciers in mid- to high-latitudes reached their maximum early in the last glacial cycle, whereas most of the LIS and the southern EIS reached their maximum close to the global LGM68.Our maps of ice-sheet extent through the Quaternary show the sea level and topography of the present day Fig. . This isOverall, our maximum, minimum and best-estimate reconstructions are necessarily subjective, but they provide the first systematic and consistent approximations of generalised NH ice-sheet extents through the Quaternary.18O record1. Secondly, a robustness score of 1 suggests that modelled data are available and the ice-sheet extent may have been produced, in whole or in part, from a time-slice with a similar value in the global δ18O record1, or the ice-sheet extent at another time-slice may be used to constrain a modelled outline. Thirdly, a robustness score of 2 indicates that point-source empirical data or localised empirical outlines are available to inform the ice-sheet extent. The ice-sheet extent at another time-slice may inform some of the reconstruction. Fourthly, a robustness score of 3 suggests that local empirical outlines or regional empirical outlines of contrasting extent inform the ice-sheet reconstruction. Fifthly, a robustness score of 4 suggests that a significant portion of the reconstructed ice-sheet margin is derived from empirical outlines. Finally, a robustness score of 5 suggests that almost all of the reconstructed ice-sheet margin is derived from empirical outlines that are in broad agreement.To aid interpretation of our maps, each best-estimate ice-sheet reconstruction has been allocated an overall robustness score (from 0 to 5) Fig. –10. ThisThe robustness scores of individual ice-sheet reconstructions vary considerably between time-slices. Lower scores are generally allocated to older time-slices, interstadial periods , and glacial periods such as MIS 8 and 10 that occurred between glaciations of larger extent. These are the time-slices in which empirical evidence is typically poorly preserved and when modelling efforts are generally lacking.A) to volume (V) to estimate the contribution of individual NH ice sheets to global sea-level changes   is a widely accepted value for ice sheets69. The coefficient c was derived from outputs of three numerical ice-sheet modelling studies70, which have been used previously to synthesie pre-LGM NH ice-sheet configurations. For each ice sheet, different coefficients were calculated and are shown in Table We utilised a scaling power law that converts area (es) Fig. . The equc, the ice-sheet volumes and corresponding global sea-level contributions were calculated for each of the synthesised pre-LGM time-slices. For each time-slice, the volume for the best, minimum and maximum area estimates were translated into global sea-level change by dividing the ice-sheet volume by the area of the world’s ocean, i.e., ~362 million km2. The final values for the best, minimum and maximum global sea-level contribution of the NH ice sheets are shown in Fig. Using equation  with the71. However, if we assume that Antarctica’s sea-level contribution is linear with global sea-level changes, this value would have the same order of magnitude as the uncertainty that is associated with the Lisiecki and Raymo1 dataset, which is between 5 and 22 m.Maximum global sea-level contributions of Antarctic ice sheets are not included in this study. The volume of these ice sheets prior to the LGM remains subject to large uncertainties and published estimates range between 10 and 35 m, depending on the method applied18O record to MIS 8, 10 and 20–241). However, we note that our estimates of eustatic sea-level for MIS 3, which are up to 30–40 m higher than most previously published sea-level curves (Fig. The estimates of eustatic sea-level for MIS 8, 10 and 20–24 are not fully independent because parts of the ice-sheet extent for these periods were derived from the ice-sheet configuration during MIS 4 (which has a similar value in the global δves Fig. , are derSupplementary InformationPeer Review File