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The loss of thick multiyear sea ice in the Arctic leads to weaker sea ice that is more easily broken up by strong winds. As a consequence, extreme sea ice breakup events may become more frequent, even during the middle of winter when the sea ice cover is frozen solid. This can lead to an earlier onset of the melt season and potentially accelerate Arctic sea ice loss. Such extreme breakup events are generally not captured by climate models, potentially limiting our confidence in projections of Arctic sea ice. We investigated the driving forces behind sea ice breakup events during winter and how they change in a future climate. Our sea ice model is the first to reproduce such breakup events and reveals that the combination of strong winds and thin sea ice is a key factor for these breakups. We found that winter breakups have a large effect on local heat and moisture transfer and cause enhanced sea ice production, but also increase the overall movement of the sea ice cover, making it more vulnerable. Finally, we show that if the Arctic sea ice continues to thin, these extreme breakup events could become even more frequent.

Cyclones carry heat and moisture that impact local conditions along their path. Cyclones with different origins can, however, have different life cycles and cause different impacts. To quantify differences in the thermodynamic evolution of cyclones originating from different latitudes during wintertime, we separate the cyclones according to their origin (cyclogenesis location): midlatitude (ML) cyclones originating in the North Atlantic and high-latitude (HL) cyclones originating in the Nordic Seas and Barents Seas. It is found that HL cyclones generally carry lower thermodynamic energy as they originate in a cold environment. In contrast, ML cyclones have much higher thermodynamic energy throughout their lifecycle, even though they lose a large amount of heat as they travel long distances from their origin towards the Arctic. For a given region in the high latitudes (e.g., the Barents Sea), the mean vertical profiles of temperature and moisture from the HL group are colder and drier compared to the ones from the ML group, but the maximum values in the HL group can reach those of the ML group. Further analysis for the top 10% warmest profiles in the HL group suggests that these HL cyclones form in a preconditioned warm and moist environment. The precondioning is set up by the large-scale circulation with influences from the upstream North Atlantic. Under special conditions, the formation of high latitude cyclones in a preconditioned warm and moist environment can lead to extreme warming events in the deep Arctic like the one during New Year’s 2015/16.

Record highs of meltwater production at the surface of the Greenland ice sheet have been recorded with a high recurrence over the last decades. Those melt seasons with longer durations, larger intensities, or with both increased length and melt intensity have a direct impact on the surface mass balance of the ice sheet and on its contribution to sea level rise. Moreover, the surface melt also affects the ice dynamics through the meltwater lubrication feedback. It is still not clear how the meltwater lubrication feedback impacts the long-term ice velocities on the Greenland ice sheet. Here we take a modeling approach with simplified ice sheet geometry and climate forcings to investigate in more detail the impacts of the changing characteristics of the melt season on ice dynamics. We model the ice dynamics through the coupling of the Double Continuum (DoCo) subglacial hydrology model with a shallow shelf approximation for the ice dynamics in the Ice-sheet and Sea-level System Model (ISSM). The climate forcing is generated from the ERA5 dataset to allow the length and intensity of the melt season to be varied in a comparable range of values. Our simulations present different behaviors between the lower and higher part of the glacier, but overall, a longer melt season will yield a faster glacier for a given runoff value. However, an increase in the intensity of the melt season, even under increasing runoff, tends to reduce glacier velocities. Those results emphasize the complexity of the meltwater lubrication feedback and urge us to use subglacial drainage models with both inefficient and efficient drainage components to give an accurate assessment of its impact on the overall dynamics of the Greenland ice sheet.

Vegetation memory describes the effect of antecedent environmental and ecological conditions on the present ecosystem state and has been proposed as an important proxy for vegetation resilience. In particular, strong vegetation-memory effects have been identified in dryland regions, but the factors underlying the spatial patterns of vegetation memory remain unknown.We aim to map the components and drivers of vegetation memory in dryland regions using state-of-the-art climate reanalysis data and refined approaches to identify vegetation-memory characteristics across dryland regions worldwide.Using a framework which distinguishes between intrinsic and extrinsic ecological memory, we show that: (i) intrinsic memory is a much stronger component than extrinsic memory in the majority of dryland regions; and (ii) climate reanalysis data sets change the detection of extrinsic vegetation memory effects in some global dryland regions.Synthesis. Our study offers a global picture of the vegetation response to two climate forcing variables using satellite data, information which is potentially relevant for mapping components and properties of vegetation responses worldwide. However, the large differences in the spatial patterns in intrinsic vegetation memory in our study compared to previous analyses show the overall sensitivity of this component in particular to the initial choice of extrinsic forcing variables. As a result, we caution against using the oversimplified link between intrinsic vegetation-memory and vegetation recovery rates at large spatial scales.

Emiliania huxleyi (Lohmann) evolved from the genus Gephyrocapsa Kamptner (Prymneosiophyceae) of the coccolithophore family Naёlaerhadaceae. Over the past 100 thousand years E. huxleyi has acquired the status of the most ecologically predominant coccolithophore due to its remarkable adaptability to a variety of environmental conditions and interspecific competitiveness. E. huxleyi plays an important role in both the marine carbon system and carbon cycling between the atmosphere and ocean due to its ability to produce organic and inorganic carbon as well as to form massive blooms throughout the world ocean. This study examines both older information and recent findings to shed light on the current tendencies in the two-way interactions between E. huxleyi blooms and the immediate and global environment under conditions of climate change. The assembled knowledge has emerged from laboratory and mesocosm instrumental investigations, retrievals of satellite remote sensing data, machine learning/statistical analyses, and numerical simulations. Special attention is given to both the quantitative data reported over the last two decades on such interactions, and the only very recently appearing mid-term projections of E. huxleyi bloom dynamics across the world ocean. These blooms strongly affect the atmosphere and ocean carbon cycles. They reduce CO2 fluxes from by ~50% to ~150% as is documented for the North Atlantic, and on the global scale release particulate inorganic carbon as calcium calcite in the amounts assessed at 0.4 to 4.8 PgC/yr. At the same time, they are also sensitive to the atmospheric and oceanic state. This results in E. huxleyi blooms having an increased impact on the environment in response to ongoing global warming.

International audience; Arctic sea ice is thinning (Meier, 2017) in conjunction with the decrease in the area covered by thick multiyear ice (MYI) (Kwok, 2018), which is replaced by thinner first-year ice (FYI) that is more mobile and less dynamically stable (Rampal et al., 2009; J. Zhang et al., 2012). This makes the ice cover more vulnerable to intense winds breaking up the sea ice. In the Beaufort Sea in particular, the loss of MYI may contribute to the earlier onset of the melt season in recent years (Johnson & Eicken, 2016). When sea ice breaks up, it exposes the underlying warmer ocean within narrow, linear openings in the ice cover known as leads. This has important consequences for air-sea exchange, ocean eddy generation and dynamics, sea ice production, and Arctic Ocean properties in general (Cohanim et al., 2021; Graham et al., 2019; Nguyen et al., 2009), especially during the winter months when heat fluxes over sea ice are generally small (Andreas & Cash, 1999). In addition, breakup in winter weakens the ice cover, potentially preconditioning the minimum ice extent in summer (Y. Zhang et al., 2018; Babb et al., 2019) and thus creating a positive feedback to Arctic amplification (Dai et al., 2019). Therefore, extreme breakup events are of crucial interest for understanding the seasonal and long-term evolution of Arctic sea ice, which in turn affect weather, ecosystems, and local communities in polar regions and beyond (Forbes et al., 2016; Vihma, 2014).

The observed warming in the Arctic is more than double the global average, and this enhanced Arctic warming is projected to continue throughout the 21st century. This rapid warming has a wide range of impacts on polar and sub-polar marine ecosystems. One of the examples of such an impact on ecosystems is that of coccolithophores, particularly Emiliania huxleyi, which have expanded their range poleward during recent decades. The coccolithophore E. huxleyi plays an essential role in the global carbon cycle. Therefore, the assessment of future changes in coccolithophore blooms is very important. Currently, there are a large number of climate models that give projections for various oceanographic, meteorological, and biochemical variables in the Arctic. However, individual climate models can have large biases when compared to historical observations. The main goal of this research was to select an ensemble of climate models that most accurately reproduces the state of environmental variables that influence the coccolithophore E. huxleyi bloom over the historical period when compared to reanalysis data. We developed a novel approach for model selection to include a diverse set of measures of model skill including the spatial pattern of some variables, which had not previously been included in a model selection procedure. We applied this method to each of the Arctic and sub-Arctic seas in which E. huxleyi blooms have been observed. Once we have selected an optimal combination of climate models that most skilfully reproduce the factors which affect E. huxleyi, the projections of the future conditions in the Arctic from these models can be used to predict how E. huxleyi blooms will change in the future. Here, we present the validation of 34 CMIP5 (fifth phase of the Coupled Model Intercomparison Project) atmosphere–ocean general circulation models (GCMs) over the historical period 1979–2005. Furthermore, we propose a procedure of ranking and selecting these models based on the model's skill in reproducing 10 important oceanographic, meteorological, and biochemical variables in the Arctic and sub-Arctic seas. These factors include the concentration of nutrients ( NO3 , PO4 , and SI), dissolved CO2 partial pressure ( pCO2 ), pH, sea surface temperature (SST), salinity averaged over the top 30 m (SS 30 m ), 10 m wind speed (WS), ocean surface current speed (OCS), and surface downwelling shortwave radiation (SDSR). The validation of the GCMs' outputs against reanalysis data includes analysis of the interannual variability, seasonal cycle, spatial biases, and temporal trends of the simulated variables. In total, 60 combinations of models were selected for 10 variables over six study regions using the selection procedure we present here. The results show that there is neither a combination of models nor one model that has high skill in reproducing the regional climatic-relevant features of all combinations of the considered variables in target seas. Thereby, an individual subset of models was selected according to our model selection procedure for each combination of variable and Arctic or sub-Arctic sea. Following our selection procedure, the number of selected models in the individual subsets varied from 3 to 11. The paper presents a comparison of the selected model subsets and the full-model ensemble of all available CMIP5 models to reanalysis data. The selected subsets of models generally show a better performance than the full-model ensemble. Therefore, we conclude that within the task addressed in this study it is preferable to employ the model subsets determined through application of our procedure than the full-model ensemble.

We present velocity images across a bottom-simulating reflector (BSR) recovered using 3D high-resolution full-waveform inversion (FWI) and discuss its use as a tool for understanding the nature of the BSR.FWI is a seismic imaging technique which generates highly resolved physical property models of the subsurface. FWI uses the full recorded waveform for inversion which leads to a superior resolution compared to other imaging methods, but also makes it computationally more expensive. Relative to 2D inversions, 3D FWI leads to image improvements due to an increase in azimuthal coverage and ability to map out-of-plane arrivals to the correct location, which is particularly important in a complex geological setting. Therefore, next to the advantage of a fully resolved 3D structure, the model will also be more accurate.Caused by gas hydrate in an upper layer and/or free gas in a lower layer, a BSR indicates the base of the gas hydrate stability zone. This significant change of the physical properties in the upper few hundred meters of the marine sediment produces a distinct reflection, i.e. the BSR, that can be seen in the seismic image.We are imaging and investigating a BSR at Puke Ridge, a thrust ridge on the accretionary wedge of the northern Hikurangi subduction margin, offshore the North Island of New Zealand. We are using seismic multichannel streamer data, belonging to the NZ3D dataset collected in 2018, to invert for the P-wave velocity. The resolved velocity model displays the geometry and the structure of a BSR characterised by a velocity increase followed by a sudden decrease and provides us with accurate velocities which we can use for rock physics modelling and interpretation.

The northern Hikurangi subduction margin hosts shallow slow-slip events (SSEs) and multiple historic tsunami earthquakes. The physical mechanisms and properties of the subduction interface which enable these dual modes of fault rupture remain largely enigmatic. In 2017-2018, the NZ3D seismic experiment was conducted offshore of Gisborne to image the structure of the overriding plate and subduction interface and infer the physical properties within the region of shallow SSEs. This experiment included a 3D seismic volume collected with four 6 km long streamers, ocean-bottom seismometers, and land stations. Early results from this project have demonstrated the successful application of 2D full-waveform inversion (FWI) to high frequencies along selected seismic inlines.Here, we present the initial results of acoustic 3D FWI on the collected streamer data. Compared with 2D FWI, 3D FWI benefits from greater azimuthal coverage and the ability to relocate out-of-plane arrivals accurately but is restricted by increased calculation times and file sizes. Velocity models reveal a complex system of thrust faulting, horst and graben structures and bottom-simulating reflectors within the accretionary prism, as well as the decollement below the accretionary prism. Velocity inversions across the imaged thrust faults in the accretionary prism indicate the presence of fluids, potentially supporting the hypothesis that the subduction interface has elevated pore-fluid pressures, which are drained along some thrust faults. Velocity inversions are also observed across bottom-simulating reflectors, which indicate the presence of gas hydrates and free gas. Imaging the shallow decollement reveals an acoustically transparent region of low velocity contrasts in the inferred location of a subducted seamount.

In recent years, temperatures over the Greenland ice sheet have been rising, leading to an increase in surface melt. This increase however can not be reduced to a simple number. Throughout the recent years we have seen some extreme melt seasons with melt extending over the whole surface of the ice sheet (2012) or melt seasons of lower amplitudes but with a longer duration (2010). The effect of those variations on the subglacial system and hence on ice dynamic are poorly understood and are still mainly deduced from studies based on mountain glaciers.Here we apply the Ice-sheet and Sea-level System Model (ISSM) to a synthetic glacier with a geometry similar to a Greenland ice sheet land terminating glacier. The forcing is designed such that it allows to investigate different characteristics of the melt season such as its length or intensity. Subglacial hydrology and ice dynamics are coupled within ISSM allowing to study the response of the system in terms of subglacial water pressure and the final impact on ice dynamics. Of particular interest is the evolution of the distribution of the efficient and inefficient component of the subglacial drainage system which directly impacts the water pressure evolution at the base of the glacier. We note that the initiation of the melt season and the intensity of the melt at this period is a crucial parameter when studying the dynamic response of the glacier to different melt season characteristics.From those results, we can infer a more precise evolution of the dynamics of land terminating glaciers that are heavily driven by their subglacial drainage system. We also highlight which changes in the melt season pattern would be the most damageable for glacier stability in the future.

The thick multi-year sea ice that once covered large parts of the Arctic Ocean is being replaced by thinner and weaker first-year ice, making it increasingly vulnerable to breakup by storms. Here we use a sea ice model to investigate the driving mechanisms behind a large sea-ice breakup event in the Beaufort Sea in response to a series of storms during February–March 2013.These simulations are the first to successfully reproduce the timing, location and propagation of sea-ice leads associated with storm-induced breakup. We found that rheology in the sea-ice model and horizontal resolution in the atmospheric model are both crucial in accurately simulating such breakup events. The sensitivity of the breakup to the initial sea-ice thickness indicates that large breakup events will become more frequent as Arctic sea ice continues to thin. Here we show that large breakup events during winter have a significant impact on ice growth through enhanced air-sea fluxes in open leads, and enhanced drift speeds which increase the export of old, thick ice out of the Beaufort Sea. Overall, this results in a thinner and weaker ice cover that may precondition earlier breakup in spring and accelerate sea-ice loss.