Abstract: Surface melting on the Antarctic Ice Sheet has been monitored by satellite microwave radiometry for over 40 years. Despite this long perspective, our understanding of the microwave emission from wet snow is still limited, preventing the full exploitation of these observations to study supraglacial hydrology. Using the Snow Microwave Radiative Transfer (SMRT) model, this study investigates the sensitivity of microwave brightness temperature to snow liquid water content at frequencies from 1.4 to 37 GHz. We first determine the snowpack properties for eight selected coastal sites by retrieving profiles of density, grain size and ice layers from microwave observations when the snowpack is dry during wintertime. Second, a series of brightness temperature simulations is run with added water. The results show that (i) a small quantity of liquid water (≈0.5 kg m−2) can be detected, but the actual quantity cannot be retrieved out of the full range of possible water quantities; (ii) the detection of a buried wet layer is possible up to a maximum depth of 1 to 6 m depending on the frequency (6–37 GHz) and on the snow properties (grain size, density) at each site; (iii) surface ponds and water-saturated areas may prevent melt detection, but the current coverage of these waterbodies in the large satellite field of view is presently too small in Antarctica to have noticeable effects; and (iv) at 1.4 GHz, while the simulations are less reliable, we found a weaker sensitivity to liquid water and the maximal depth of detection is relatively shallow (<10 m) compared to the typical radiation penetration depth in dry firn (≈1000 m) at this low frequency. These numerical results pave the way for the development of improved multi-frequency algorithms to detect melt intensity and the depth of liquid water below the surface in the Antarctic snowpack.

Abstract: The Regional Ocean Modeling System (ROMS), including an ice shelf component, has been applied on a circum-Antarctic domain to derive estimates of ice shelf basal melting. Significant improvements made compared to previous models of this scale are the inclusion of tides and a horizontal spatial resolution of 2 km, which is sufficient to resolve on-shelf heat transport by bathymetric troughs and eddy-scale circulation. We run the model with ocean–atmosphere–sea ice conditions from the year 2007 to represent nominal present-day climate. We force the ocean surface with buoyancy fluxes derived from sea ice concentration observations and wind stress from ERA-Interim atmospheric reanalysis. Boundary conditions are derived from the ECCO2 ocean state estimate; tides are incorporated as sea surface height and barotropic currents at the open boundary. We evaluate model results using satellite-derived estimates of ice shelf melting and established compilations of ocean hydrography. The Whole Antarctic Ocean Model (WAOM v1.0) qualitatively captures the broad scale difference between warm and cold regimes as well as many of the known characteristics of regional ice–ocean interaction. We identify a cold bias for some warm-water ice shelves and a lack of high-salinity shelf water (HSSW) formation. We conclude that further calibration and development of our approach are justified. At its current state, the model is ideal for addressing specific, process-oriented questions, e.g. related to tide-driven ice shelf melting at large scales.

Abstract: Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.

Abstract: Individuals differ in many ways. Most produce few offspring; a handful produce many. Some die early; others live to old age. It is tempting to attribute these differences in outcomes to differences in individual traits, and thus in the demographic rates experienced. However, there is more to individual variation than meets the eye of the biologist. Even among individuals sharing identical traits, life history outcomes (life expectancy and lifetime reproduction) will vary due to individual stochasticity, that is to chance. Quantifying the contributions of heterogeneity and chance is essential to understand natural variability. Interindividual differences vary across environmental conditions, hence heterogeneity and stochasticity depend on environmental conditions. We show that favourable conditions increase the contributions of individual stochasticity, and reduce the contributions of heterogeneity, to variance in demographic outcomes in a seabird population. The opposite is true under poor conditions. This result has important consequence for understanding the ecology and evolution of life history strategies.

Abstract: Aim In the context of intensifying threats of climate change on marine communities, ecological models are widely applied for conservation strategies, though polar studies remain scarce given the limited number of datasets available. Correlative (e.g. species distribution models, SDM) and mechanistic (e.g. dynamic energy budget models, DEB) modelling approaches are usually used independently in studies. Using both approaches in integrative, hybrid models could help to better estimate the species potential ecological niche, as mechanistic and correlative models complement each other very well, giving more insights into species potential response to fast-changing environmental conditions. Location The study focusses on the Baie du Morbihan, a silled basin located in the east of the Kerguelen Islands (sub-Antarctic). Methods A hybrid, correlative-mechanistic model was implemented to predict the response of the endemic sea urchin Abatus cordatus (Verrill, 1876). We compared the performances of classic and integrated approaches to predict A. cordatus distribution according to two dates representing seasonal contrasts. Two integrated approaches were studied and performed by either (1) including the spatial projection of the DEB model as an input layer inside the SDM (‘integrated SDM-DEB’) or (2) using a Bayesian procedure to use DEB model outputs as priors of the SDM (‘integrated Bayesian’ approach). Results Results show higher performances of ‘integrated Bayesian’ approaches to evaluate A. cordatus potential ecological niche compared with ‘classic’ and ‘integrated SDM-DEB’ methods. The influence of environmental conditions on model predictions is further captured with these Bayesian procedures and better highlights the environmental influence on the species-predicted distribution. Model performance is good for the different simulations, and uncertainty in predictions is well-highlighted. Main conclusions The good performances of ‘integrated Bayesian’ approaches to estimate species potential ecological niche opens perspectives for future applications to a broad panel of natural examples, noteworthy for decision-making and conservation management purposes.