Barents-2.5km v2.0: An operational data-assimilative coupled ocean and sea ice ensemble prediction model for the Barents Sea and Svalbard

An operational ocean and sea ice forecast model, Barents-2.5, is implemented at MET Norway for short-term forecasting at the coast off Northern Norway, the Barents Sea, and waters around Svalbard. Primary forecast parameters are the sea ice concentration (SIC), sea surface temperature (SST), and ocean currents. The model is also a substantial input for drift modeling of pollutants, ice berg, and in search-and-rescue pertinent applications in the Arctic domain. Barents-2.5 has recently been upgraded to include an Ensemble Prediction System with 24 daily realizations of the model state. SIC, SST and in-situ hydrography are constrained through the Ensemble Kalman Filter (EnKF) data assimilation scheme executed in daily forecast cycles with lead time up to 66 hours. While the ocean circulation is not directly constrained by assimilation of ocean currents, the model ensemble represents the given uncertainty in the short-term current field by retaining the current state for each member throughout forecast cycles. Here we present the model setup and a validation in terms of SIC, SST and in-situ hydrography. The performance of the ensemble to represent the models uncertainty, and the performance of the EnKF to constrain the model state are discussed, in addition to the model&rsquo;s forecast capabilities for SIC and SST.</p

Assimilation of satellite swaths versus daily means of sea ice concentration in a regional coupled ocean–sea ice model

Operational forecasting systems routinely assimilate daily means of sea ice concentration (SIC) from microwave radiometers in order to improve the accuracy of the forecasts. However, the temporal and spatial averaging of the individual satellite swaths into daily means of SIC entails two main drawbacks: (i) the spatial resolution of the original product is blurred (especially critical in periods with strong sub-daily sea ice movement), and (ii) the sub-daily frequency of passive microwave observations in the Arctic are not used, providing less temporal resolution in the data assimilation (DA) analysis and, therefore, in the forecast. Within the SIRANO (Sea Ice Retrievals and data Assimilation in NOrway) project, we investigate how challenges (i) and (ii) can be avoided by assimilating individual satellite swaths (level 3 uncollated) instead of daily means (level 3) of SIC. To do so, we use a regional configuration of the Barents Sea (2.5 km grid) based on the Regional Ocean Modeling System (ROMS) and the Los Alamos Sea Ice Model (CICE) together with the ensemble Kalman filter (EnKF) as the DA system. The assimilation of individual swaths significantly improves the EnKF analysis of SIC compared to the assimilation of daily means; the mean absolute difference (MAD) shows a 10 % improvement at the end of the assimilation period and a 7 % improvement at the end of the 7 d forecast period. This improvement is caused by better exploitation of the information provided by the SIC swath data, in terms of both spatial and temporal variance, compared to the case when the swaths are combined to form a daily mean before assimilation.</p

Changes in global ocean bottom properties and volume transports in CMIP5 models under climate change scenarios

Changes in bottom temperature, salinity and density in the global ocean by 2100 for CMIP5 climate models are investigated for the climate change scenarios RCP4.5 and RCP8.5. The mean of 24 models shows a decrease in density in all deep basins except the North Atlantic which becomes denser. The individual model responses to climate change forcing are more complex: regarding temperature, the 24 models predict a warming of the bottom layer of the global ocean; in salinity, there is less agreement regarding the sign of the change, especially in the Southern Ocean. The magnitude and equatorward extent of these changes also vary strongly among models. The changes in properties can be linked with changes in the mean transport of key water masses. The Atlantic Meridional Overturning Circulation weakens in most models and is directly linked to changes in bottom density in the North Atlantic. These changes are due to the intrusion of modified Antarctic Bottom Water, made possible by the decrease in North Atlantic Deep Water formation. In the Indian, Pacific and South Atlantic, changes in bottom density are congruent with the weakening in Antarctic Bottom Water transport through these basins. We argue that the greater the 1986-2005 meridional transports, the more changes have propagated equatorwards by 2100. However, strong decreases in density over 100 years of climate change cause a weakening of the transports. The speed at which these property changes reach the deep basins is critical for a correct assessment of the heat storage capacity of the oceans as well as for predictions of future sea level rise

The programming of sequences of saccades

Saccadic eye movements move the high-resolution fovea to point at regions of interest. Saccades can only be generated serially (i.e., one at a time). However, what remains unclear is the extent to which saccades are programmed in parallel (i.e., a series of such moments can be planned together) and how far ahead such planning occurs. In the current experiment, we investigate this issue with a saccade contingent preview paradigm. Participants were asked to execute saccadic eye movements in response to seven small circles presented on a screen. The extent to which participants were given prior information about target locations was varied on a trial-by-trial basis: participants were aware of the location of the next target only, the next three, five, or all seven targets. The addition of new targets to the display was made during the saccade to the next target in the sequence. The overall time taken to complete the sequence was decreased as more targets were available up to all seven targets. This was a result of a reduction in the number of saccades being executed and a reduction in their saccade latencies. Surprisingly, these results suggest that, when faced with a demand to saccade to a large number of target locations, saccade preparation about all target locations is carried out in paralle

Very-high-energy γ -Ray Emission from Young Massive Star Clusters in the Large Magellanic Cloud

The Tarantula Nebula in the Large Magellanic Cloud is known for its high star formation activity. At its center lies the young massive star cluster R136, providing a significant amount of the energy that makes the nebula shine so brightly at many wavelengths. Recently, young massive star clusters have been suggested to also efficiently produce very high-energy cosmic rays, potentially beyond PeV energies. Here, we report the detection of very-high-energy γ-ray emission from the direction of R136 with the High Energy Stereoscopic System, achieved through a multicomponent, likelihood-based modeling of the data. This supports the hypothesis that R136 is indeed a very powerful cosmic-ray accelerator. Moreover, from the same analysis, we provide an updated measurement of the γ-ray emission from 30 Dor C, the only superbubble detected at TeV energies presently. The γ-ray luminosity above 0.5 TeV of both sources is (2–3) × 1035 erg s−1. This exceeds by more than a factor of 2 the luminosity of HESS J1646−458, which is associated with the most massive young star cluster in the Milky Way, Westerlund 1. Furthermore, the γ-ray emission from each source is extended with a significance of >3σ and a Gaussian width of about 30 pc. For 30 Dor C, a connection between the γ-ray emission and the nonthermal X-ray emission appears likely. Different interpretations of the γ-ray signal from R136 are discussed

Evolutionary winners are ecological losers among oceanic island plants

Aim Adaptive radiation, in which successful lineages proliferate by exploiting untapped niche space, provides a popular but potentially misleading characterization of evolution on oceanic islands. Here we analyse the respective roles of members of in situ diversified vs. non-diversified lineages in shaping the main ecosystems of an archipelago to explore the relationship between evolutionary and ecological ‘success’. Location Canary Islands. Taxon Vascular plants. Methods We quantified the abundance/rarity of the native flora according to the geographical range (number of islands where present and geographical extent of the range), habitat breadth (climatic niche) and local abundance (cover) using species distribution data based on 500 × 500 m grid cells and 2000 vegetation inventories located all over the archipelago. Results Species of diversified lineages have significantly smaller geographic ranges, narrower climatic niches and lower local abundances than those of non-diversified lineages. Species rarity increased with the degree of diversification. The diversified Canarian flora is mainly comprised by shrubs. At both archipelagic and island level, the four core ecosystems (Euphorbia scrub, thermophilous woodlands, laurel forest and pine forest) were dominated by non-diversified lineages species, with diversified lineages species providing <25% cover. Species of diversified lineages, although constituting 54% of the archipelagic native flora, were only abundant in two rare ecosystems: high mountain scrub and rock communities. Main conclusions Radiated species, endemic products of in situ speciation, are mostly rare in all three rarity axes and typically do not play an important role in structuring plant communities on the Canaries. The vegetation of the major ecosystem types is dominated by plants representing non-diversified lineages (species that derive from immigration and accumulation), while species of evolutionarily successful lineages are abundant only in marginal habitats and could, therefore, be considered ecological losers. Within this particular oceanic archipelago, and we posit within at least some others, evolutionary success in plants is accomplished predominantly at the margins.publishedVersio

Climate-induced range shifts shaped the present and threaten the future genetic variability of a marine brown alga in the Northwest Pacific

Glaciation-induced environmental changes during the last glacial maximum (LGM) have strongly influenced species' distributions and genetic diversity patterns in the northern high latitudes. However, these effects have seldom been assessed on sessile species in the Northwest Pacific. Herein, we chose the brown alga Sargassum thunbergii to test this hypothesis, by comparing present population genetic variability with inferred geographical range shifts from the LGM to the present, estimated with species distribution modelling (SDM). Projections for contrasting scenarios of future climate change were also developed to anticipate genetic diversity losses at regional scales. Results showed that S. thunbergii harbours strikingly rich genetic diversity and multiple divergent lineages in the centre-northern range of its distribution, in contrast with a poorer genetically distinct lineage in the southern range. SDM hindcasted refugial persistence in the southern range during the LGM as well as post-LGM expansion of 18 degrees of latitude northward. Approximate Bayesian computation (ABC) analysis further suggested that the multiple divergent lineages in the centre-northern range limit stem from post-LGM colonization from the southern survived lineage. This suggests divergence due to demographic bottlenecks during range expansion and massive genetic diversity loss during post-LGM contraction in the south. The projected future range of S. thunbergii highlights the threat to unique gene pools that might be lost under global changes.UIDB/04326/2020 - PTDC/BIA-CBI/6515/2020 - DL57/2016/CP1361/CT0035info:eu-repo/semantics/publishedVersio

A combined microbial and biogeochemical dataset from high-latitude ecosystems with respect to methane cycle.

High latitudes are experiencing intense ecosystem changes with climate warming. The underlying methane (CH4) cycling dynamics remain unresolved, despite its crucial climatic feedback. Atmospheric CH4 emissions are heterogeneous, resulting from local geochemical drivers, global climatic factors, and microbial production/consumption balance. Holistic studies are mandatory to capture CH4 cycling complexity. Here, we report a large set of integrated microbial and biogeochemical data from 387 samples, using a concerted sampling strategy and experimental protocols. The study followed international standards to ensure inter-comparisons of data amongst three high-latitude regions: Alaska, Siberia, and Patagonia. The dataset encompasses diferent representative environmental features (e.g. lake, wetland, tundra, forest soil) of these high-latitude sites and their respective heterogeneity (e.g. characteristic microtopographic patterns). The data included physicochemical parameters, greenhouse gas concentrations and emissions, organic matter characterization, trace elements and nutrients, isotopes, microbial quantifcation and composition. This dataset addresses the need for a robust physicochemical framework to conduct and contextualize future research on the interactions between climate change, biogeochemical cycles and microbial communities at highlatitudes

Use of Acceleration and Acoustics to Classify Behavior, Generate Time Budgets, and Evaluate Responses to Moonlight in Free-Ranging Snowshoe Hares

Technological miniaturization is driving a biologging revolution that is producing detailed and sophisticated techniques of assessing individual behavioral responses to environmental conditions. Among the many advancements this revolution has brought is an ability to record behavioral responses of nocturnal, free-ranging species. Here, we combine captive validations of acceleration signatures with acoustic recordings from free-ranging individuals to classify behavior at two resolutions. Combining these classifications with ~2 month-long recordings, we describe winter time budgets, and responses of free-ranging snowshoe hares to changing moonlight. We successfully classified snowshoe hare behavior into four categories (not moving, foraging, hopping, and sprinting) using low frequency accelerometry, with an overall model accuracy of 88%, and acoustic recordings to three categories (silence, hopping, and chewing) with an accuracy of 94%. Broad-scale accelerometer-classified categories were composed of multiple fine-scale behavioral states with the composition varying between individuals and across the day. Time budgets revealed that hares spent ~50% of their time foraging and ~50% not moving, with most foraging and feeding occurring at night. We found that hares adjusted timing of activity in response to moon phase, with a 6% reduction in foraging and 30% reduction in traveling during the night when the moon was full. Hares compensated for this lost foraging time by extending foraging into the morning hours of the following day. Using two biologging technologies to identify behavior, we demonstrate the possibility of combining multiple devices when documenting behavior of cryptic species