ALBERT

Description: 〈jats:p〉Climate change combined with anthropogenic stressors (e.g. overfishing, habitat destruction) may have particularly strong effects on threatened populations of coastal invertebrates. The collapse of the population of European lobster (〈jats:italic〉Homarus gammarus〈/jats:italic〉) around Helgoland constitutes a good example and prompted a large-scale restocking program. The question arises if recruitment of remaining natural individuals and program-released specimens could be stunted by ongoing climate change. We examined the joint effect of ocean warming and acidification on survival, development, morphology, energy metabolism and enzymatic antioxidant activity of the larval stages of the European lobster. Larvae from four independent hatches were reared from stage I to III under a gradient of 10 seawater temperatures (13–24°C) combined with moderate (∼470 µatm) and elevated (∼1160 µatm) seawater 〈jats:italic〉p〈/jats:italic〉CO〈jats:sub〉2〈/jats:sub〉 treatments. Those treatments correspond to the shared socio-economic pathways (SSP), SSP1-2.6 and SSP5-8.5 (i.e. the low and the very high greenhouse gas emissions respectively) projected for 2100 by the Intergovernmental Panel on Climate Change. Larvae under the elevated 〈jats:italic〉p〈/jats:italic〉CO〈jats:sub〉2〈/jats:sub〉 treatment had not only lower survival rates, but also significantly smaller rostrum length. However, temperature was the main driver of energy demands with increased oxygen consumption rates and elemental C:N ratio towards warmer temperatures, with a reducing effect on development time. Using this large temperature gradient, we provide a more precise insight on the aerobic thermal window trade-offs of lobster larvae and whether exposure to the worst hypercapnia scenario may narrow it. This may have repercussions on the recruitment of the remaining natural and program-released specimens and thus, in the enhancement success of future lobster stocks.〈/jats:p〉

Description: The variety of Earth’s organisms is manifold. However, it is the small-scale marine community that makes the world goes round. Microbial organisms of pro- and eukaryotic origin drive the carbon supply and nutrient cycling, thus are mediating the primary productivity within the world largest ecosystem called ocean. But due to the ocean’s great size and large number of biogeographically habitats, the total of microbial species can hardly be grabbed and therefore their functional roles not fully described. However, recent advances in high-throughput sequencing technologies are revolutionizing our understanding of the marine microbial diversity, ecology and evolution. Nowadays, research questions on species differentiation can be solved with genomic approaches such as metabarcoding, while transcriptomics offers the possibility to assign gene functions even to a single cell, e.g., single-cell transcriptomics. On the other hand, due to the diversified amount of sequencing data, the certainty of a data crisis is currently evolving. Scientists are forced to broaden their view on bioinformatics resources for analysis and data storage in from of, e.g., cloud services, to ensure the data’s exchangeability. Which is why time resources are now shifting toward solving data problems rather than answering the eco-evolutionary questions stated in the first place. This review is intended to provide exchange on *omics approaches and key points for discussions on data handling used to decipher the relevant diversity and functions of microbial organisms in the marine ecosystem.

Description: Comparing the output of general circulation models to observations is essential for assessing and improving the quality of models. While numerical weather prediction models are routinely assessed against a large array of observations, comparing climate models and observations usually requires long time series to build robust statistics. Here, we show that by nudging the large-scale atmospheric circulation in coupled climate models, model output can be compared to local observations for individual days. We illustrate this for three climate models during a period in April 2020 when a warm air intrusion reached the MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition in the central Arctic. Radiosondes, cloud remote sensing and surface flux observations from the MOSAiC expedition serve as reference observations. The climate models AWI-CM1/ECHAM and AWI-CM3/IFS miss the diurnal cycle of surface temperature in spring, likely because both models assume the snowpack on ice to have a uniform temperature. CAM6, a model that uses three layers to represent snow temperature, represents the diurnal cycle more realistically. During a cold and dry period with pervasive thin mixed-phase clouds, AWI-CM1/ECHAM only produces partial cloud cover and overestimates downwelling shortwave radiation at the surface. AWI-CM3/IFS produces a closed cloud cover but misses cloud liquid water. Our results show that nudging the large-scale circulation to the observed state allows a meaningful comparison of climate model output even to short-term observational campaigns. We suggest that nudging can simplify and accelerate the pathway from observations to climate model improvements and substantially extends the range of observations suitable for model evaluation.

Description: 〈jats:p〉Persistent cold temperatures, a paucity of nutrients, freeze-thaw cycles, and the strongly seasonal light regime make Antarctica one of Earth’s least hospitable surface environments for complex life. Cyanobacteria, however, are well-adapted to such conditions and are often the dominant primary producers in Antarctic inland water environments. In particular, the network of meltwater ponds on the ‘dirty ice’ of the McMurdo Ice Shelf is an ecosystem with extensive cyanobacteria-dominated microbial mat accumulations. This study investigated intact polar lipids (IPLs), heterocyte glycolipids (HGs), and bacteriohopanepolyols (BHPs) in combination with 16S and 18S rRNA gene diversity in microbial mats of twelve ponds in this unique polar ecosystem. To constrain the effects of nutrient availability, temperature and freeze-thaw cycles on the lipid membrane composition, lipids were compared to stromatolite-forming cyanobacterial mats from ice-covered lakes in the McMurdo Dry Valleys as well as from (sub)tropical regions and hot springs. The 16S rRNA gene compositions of the McMurdo Ice Shelf mats confirm the dominance of Cyanobacteria and Proteobacteria while the 18S rRNA gene composition indicates the presence of Ochrophyta, Chlorophyta, Ciliophora, and other microfauna. IPL analyses revealed a predominantly bacterial community in the meltwater ponds, with archaeal lipids being barely detectable. IPLs are dominated by glycolipids and phospholipids, followed by aminolipids. The high abundance of sugar-bound lipids accords with a predominance of cyanobacterial primary producers. The phosphate-limited samples from the (sub)tropical, hot spring, and Lake Vanda sites revealed a higher abundance of aminolipids compared to those of the nitrogen-limited meltwater ponds, affirming the direct affects that N and P availability have on IPL compositions. The high abundance of polyunsaturated IPLs in the Antarctic microbial mats suggests that these lipids provide an important mechanism to maintain membrane fluidity in cold environments. High abundances of HG keto-ols and HG keto-diols, produced by heterocytous cyanobacteria, further support these findings and reveal a unique distribution compared to those from warmer climates.〈/jats:p〉

Description: 〈jats:p〉Abstract. Computation of barotropic and meridional overturning streamfunctions for models formulated on unstructured meshes is commonly preceded by interpolation to a regular mesh. This operation destroys the original conservation, which can be then artificially imposed to make the computation possible. An elementary method is proposed that avoids interpolation and preserves conservation in a strict model sense. The method is described as applied to the discretization of the Finite volumE Sea ice – Ocean Model (FESOM2) on triangular meshes. It, however, is generalizable to colocated vertex-based discretization on triangular meshes and to both triangular and hexagonal C-grid discretizations. 〈/jats:p〉

Description: 〈jats:p〉Abstract. A realistic simulation of the surface mass balance (SMB) is essential for simulating past and future ice-sheet changes. As most state-of-the-art Earth system models (ESMs) are not capable of realistically representing processes determining the SMB, most studies of the SMB are limited to observations and regional climate models and cover the last century and near future only. Using transient simulations with the Max Planck Institute ESM in combination with an energy balance model (EBM), we extend previous research and study changes in the SMB and equilibrium line altitude (ELA) for the Northern Hemisphere ice sheets throughout the last deglaciation. The EBM is used to calculate and downscale the SMB onto a higher spatial resolution than the native ESM grid and allows for the resolution of SMB variations due to topographic gradients not resolved by the ESM. An evaluation for historical climate conditions (1980–2010) shows that derived SMBs compare well with SMBs from regional modeling. Throughout the deglaciation, changes in insolation dominate the Greenland SMB. The increase in insolation and associated warming early in the deglaciation result in an ELA and SMB increase. The SMB increase is caused by compensating effects of melt and accumulation: the warming of the atmosphere leads to an increase in melt at low elevations along the ice-sheet margins, while it results in an increase in accumulation at higher levels as a warmer atmosphere precipitates more. After 13 ka, the increase in melt begins to dominate, and the SMB decreases. The decline in Northern Hemisphere summer insolation after 9 ka leads to an increasing SMB and decreasing ELA. Superimposed on these long-term changes are centennial-scale episodes of abrupt SMB and ELA decreases related to slowdowns of the Atlantic meridional overturning circulation (AMOC) that lead to a cooling over most of the Northern Hemisphere. 〈/jats:p〉

Description: Germany has been operating permanently crewed research stations in Antarctica for more than 45 years. The opening of the Georg Forster Station (1976) and Georg von Neumayer Station (1981) initiated a period of continuous environmental monitoring that allowed both the former East Germany and West Germany to become contracting parties in, and achieve consultative status with, the framework of the Antarctic Treaty. This marked a milestone in German polar research. Continuous research at the Neumayer Station III, its two predecessors, and the now-dismantled former German Democratic Republic (GDR) Georg Forster Station is undertaken by teams of so-called “overwinterers”, presently with nine members, who stay at the base for longer than an entire Antarctic winter. Their long-term stay in Antarctica is defined by isolation, separation from civilization, routine work to sustain long-term scientific observations, and unique personal experiences. This article is dedicated to them and outlines their part and role in the German Antarctic research landscape.

Description: 〈jats:p〉Abstract. We developed a new version of the Alfred Wegener Institute Climate Model (AWI-CM3), which has higher skills in representing the observed climatology and better computational efficiency than its predecessors. Its ocean component FESOM2 (Finite-volumE Sea ice–Ocean Model) has the multi-resolution functionality typical of unstructured-mesh models while still featuring a scalability and efficiency similar to regular-grid models. The atmospheric component OpenIFS (CY43R3) enables the use of the latest developments in the numerical-weather-prediction community in climate sciences. In this paper we describe the coupling of the model components and evaluate the model performance on a variable-resolution (25–125 km) ocean mesh and a 61 km atmosphere grid, which serves as a reference and starting point for other ongoing research activities with AWI-CM3. This includes the exploration of high and variable resolution and the development of a full Earth system model as well as the creation of a new sea ice prediction system. At this early development stage and with the given coarse to medium resolutions, the model already features above-CMIP6-average skills (where CMIP6 denotes Coupled Model Intercomparison Project phase 6) in representing the climatology and competitive model throughput. Finally we identify remaining biases and suggest further improvements to be made to the model. 〈/jats:p〉

Description: Organic matter (OM) degradation in marine sediments is largely controlled by its reactivity and profoundly affects the global carbon cycle. Yet, there is currently no general framework that can constrain OM reactivity on a global scale. In this study, we propose a reactive continuum model based on a lognormal distribution (l-RCM), where OM reactivity is fully described by parameters μ (the mean reactivity of the initial OM bulk mixture) and σ (the variance of OM components around the mean reactivity). We use the l-RCM to inversely determine μ and σ at 123 sites across the global ocean. The results show that the apparent OM reactivity (〈k〉=μ⋅exp⁡(σ2/2)) decreases with decreasing sedimentation rate (ω) and that OM reactivity is more than 3 orders of magnitude higher in shelf than in abyssal regions. Despite the general global trends, higher than expected OM reactivity is observed in certain ocean regions characterized by great water depth or pronounced oxygen minimum zones, such as the eastern–western coastal equatorial Pacific and the Arabian Sea, emphasizing the complex control of the depositional environment (e.g., OM flux, oxygen content in the water column) on benthic OM reactivity. Notably, the l-RCM can also highlight the variability in OM reactivity in these regions. Based on inverse modeling results in our dataset, we establish the significant statistical relationships between 〈k〉 and ω and further map the global OM reactivity distribution. The novelty of this study lies in its unifying view but also in contributing a new framework that allows predicting OM reactivity in data-poor areas based on readily available (or more easily obtainable) information. Such a framework is currently lacking and limits our abilities to constrain OM reactivity in global biogeochemical or Earth system models.

Description: Antarctic sea ice prediction has garnered increasing attention in recent years, particularly in the context of the recent record lows of February 2022 and 2023. As Antarctica becomes a climate change hotspot, as polar tourism booms, and as scientific expeditions continue to explore this remote continent, the capacity to anticipate sea ice conditions weeks to months in advance is in increasing demand. Spurred by recent studies that uncovered physical mechanisms of Antarctic sea ice predictability and by the intriguing large variations of the observed sea ice extent in recent years, the Sea Ice Prediction Network South (SIPN South) project was initiated in 2017, building upon the Arctic Sea Ice Prediction Network. The SIPN South project annually coordinates spring-to-summer predictions of Antarctic sea ice conditions, to allow robust evaluation and intercomparison, and to guide future development in polar prediction systems. In this paper, we present and discuss the initial SIPN South results collected over six summer seasons (December-February 2017-2018 to 2022-2023). We use data from 22 unique contributors spanning five continents that have together delivered more than 3000 individual forecasts of sea ice area and concentration. The SIPN South median forecast of the circumpolar sea ice area captures the sign of the recent negative anomalies, and the verifying observations are systematically included in the 10-90% range of the forecast distribution. These statements also hold at the regional level except in the Ross Sea where the systematic biases and the ensemble spread are the largest. A notable finding is that the group forecast, constructed by aggregating the data provided by each contributor, outperforms most of the individual forecasts, both at the circumpolar and regional levels. This indicates the value of combining predictions to average out model-specific errors. Finally, we find that dynamical model predictions (i.e., based on process-based general circulation models) generally perform worse than statistical model predictions (i.e., data-driven empirical models including machine learning) in representing the regional variability of sea ice concentration in summer. SIPN South is a collaborative community project that is hosted on a shared public repository. The forecast and verification data used in SIPN South are publicly available in near-real time for further use by the polar research community, and eventually, policymakers.

Description: Arctic Ocean simulations in 19 global ocean-sea-ice models participating in the Ocean Model Intercomparison Project (OMIP) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are evaluated in this paper. Our findings show no significant improvements in Arctic Ocean simulations from the previous Coordinated Ocean-ice Reference Experiments phase II (CORE-II) to the current OMIP. Large model biases and inter-model spread exist in the simulated mean state of the halocline and Atlantic Water layer in the OMIP models. Most of the OMIP models suffer from a too thick and deep Atlantic Water layer, a too deep halocline base, and large fresh biases in the halocline. The OMIP models qualitatively agree on the variability and change of the Arctic Ocean freshwater content; sea surface height; stratification; and volume, heat, and freshwater transports through the Arctic Ocean gateways. They can reproduce the changes in the gateway transports observed in the early 21st century, with the exception of the Bering Strait. We also found that the OMIP models employing the NEMO ocean model simulate relatively larger volume and heat transports through the Barents Sea Opening. Overall, the performance of the Arctic Ocean simulations is similar between the CORE2-forced OMIP-1 and JRA55-do-forced OMIP-2 experiments.

Description: We utilize a nudged simulation with the coupled regional atmosphere-ocean-sea ice model HIRHAM–NAOSIM over the Arctic to conduct an in-depth analysis of the impact of a sequence of three intense cyclones on the sea ice cover in the Barents and Kara Seas in February 2020. To clarify the underlying mechanisms we decompose changes in sea ice concentration (SIC) and thickness (SIT) into their dynamic and thermodynamic contributions and analyze them in concert with simulated changes in the wind forcing and the surface energy budget. Our findings reveal that changes in SIT during and after the cyclone passages are mostly driven by dynamic processes such as increased ice drift and deformation. With respect to SIC, the relative importance of dynamics and thermodynamics depends on the considered time scale and on the general conditions of the cyclone passages. If cyclones follow on each other in rapid succession, dynamic mechanisms dominate the SIC response for time scales of more than 2 weeks and thermodynamic effects via advection of warm-moist/cold-dry air masses on the cyclone’s front/back side only play a secondary role. However, if sufficiently long time elapses until the arrival of the next storm, thermodynamic SIC increase due to refreezing under the influence of cold and dry air at the backside of the cyclone becomes the dominating mechanism during the days following the cyclone passage.

Description: Ice shelves surrounding the Antarctic perimeter moderate ice discharge towards the ocean through buttressing. Ice-shelf evolution and integrity depend on the local surface accumulation, basal melting and on the spatially variable ice-shelf viscosity. These components of ice-shelf mass balance are often poorly constrained by observations and introduce uncertainties in ice-sheet projections. Isochronal radar stratigraphy is an observational archive for the atmospheric, oceanographic and ice-flow history of ice shelves. Here, we predict the stratigraphy of locally accumulated ice on ice shelves with a kinematic forward model for a given atmospheric and oceanographic scenario. This delineates the boundary between local meteoric ice (LMI) and continental meteoric ice (CMI). A large LMI to CMI ratio hereby marks ice shelves whose buttressing strength is more sensitive to changes in atmospheric precipitation patterns. A mismatch between the steady-state predictions of the kinematic forward model and observations from radar can highlight inconsistencies in the atmospheric and oceanographic input data or be an indicator for a transient ice-shelf history not accounted for in the model. We discuss pitfalls in numerical diffusion when calculating the age field and validate the kinematic model with the full Stokes ice-flow model Elmer/Ice. The Roi Baudouin Ice Shelf (East Antarctica) serves as a test case for this approach. There, we find a significant east–west gradient in the LMI / CMI ratio. The steady-state predictions concur with observations on larger spatial scales (〉10 km), but deviations on smaller scales are significant, e.g., because local surface accumulation patterns near the grounding zone are underestimated in Antarctic-wide estimates. Future studies can use these mismatches to optimize the input data or to pinpoint transient signatures in the ice-shelf history using the ever growing archive of radar observations of internal ice stratigraphy.

Description: 〈jats:p〉Abstract. The subglacial hydrological system affects (i) the motion of ice sheets through sliding, (ii) the location of lakes at the ice margin, and (iii) the ocean circulation by freshwater discharge directly at the grounding line or (iv) via rivers flowing over land. For modeling this hydrology system, a previously developed porous-media concept called the confined–unconfined aquifer system (CUAS) is used. To allow for realistic simulations at the ice sheet scale, we developed CUAS-MPI, an MPI-parallel C/C++ implementation of CUAS (MPI: Message Passing Interface), which employs the Portable, Extensible Toolkit for Scientific Computation (PETSc) infrastructure for handling grids and equation systems. We validate the accuracy of the numerical results by comparing them with a set of analytical solutions to the model equations, which involve two types of boundary conditions. We then investigate the scaling behavior of CUAS-MPI and show that CUAS-MPI scales up to 3840 MPI processes running a realistic Greenland setup on the Lichtenberg HPC system. Our measurements also show that CUAS-MPI reaches a throughput comparable to that of ice sheet simulations, e.g., the Ice-sheet and Sea-level System Model (ISSM). Lastly, we discuss opportunities for ice sheet modeling, explore future coupling possibilities of CUAS-MPI with other simulations, and consider throughput bottlenecks and limits of further scaling. 〈/jats:p〉

Description: The Maritime Continent (MC) forms the western boundary of the tropical Pacific Ocean, and relatively small changes in this region can impact the climate locally and remotely. In the mid-Piacenzian warm period of the Pliocene (mPWP; 3.264 to 3.025 Ma) atmospheric CO2 concentrations were ∼ 400 ppm, and the subaerial Sunda and Sahul shelves made the land–sea distribution of the MC different to today. Topographic changes and elevated levels of CO2, combined with other forcings, are therefore expected to have driven a substantial climate signal in the MC region at this time. By using the results from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), we study the mean climatic features of the MC in the mPWP and changes in Indonesian Throughflow (ITF) with respect to the preindustrial. Results show a warmer and wetter mPWP climate of the MC and lower sea surface salinity in the surrounding ocean compared with the preindustrial. Furthermore, we quantify the volume transfer through the ITF; although the ITF may be expected to be hindered by the subaerial shelves, 10 out of 15 models show an increased volume transport compared with the preindustrial. In order to avoid undue influence from closely related models that are present in the PlioMIP2 ensemble, we introduce a new metric, the multi-cluster mean (MCM), which is based on cluster analysis of the individual models. We study the effect that the choice of MCM versus the more traditional analysis of multi-model mean (MMM) and individual models has on the discrepancy between model results and data. We find that models, which reproduce modern MC climate well, are not always good at simulating the mPWP climate anomaly of the MC. By comparing with individual models, the MMM and MCM reproduce the preindustrial sea surface temperature (SST) of the reanalysis better than most individual models and produce less discrepancy with reconstructed sea surface temperature anomalies (SSTA) than most individual models in the MC. In addition, the clusters reveal spatial signals that are not captured by the MMM, so that the MCM provides us with a new way to explore the results from model ensembles that include similar models.

Description: In the past decades the Arctic has experienced stronger temperature increases than any other region globally. Shifts in hydrological regimes and accelerated permafrost thawing have been observed and are likely to increase mobilization of organic carbon and its transport through rivers into the Arctic Ocean. In order to better quantify changes to the carbon cycle, Arctic rivers such as the Lena River in Siberia need to be monitored closely. Since 2018, a sampling program provides frequent in situ observations of dissolved organic carbon (DOC) and colored dissolved organic matter (CDOM) of the Lena River. Here, we utilize this ground truth dataset and aim to test the potential of frequent satellite observations to spatially and temporally complement and expand these observations. We explored all available overpasses (~3250) of the Ocean and Land Colour Instrument (OLCI) on Sentinel-3 within the ice-free periods (May – October) for four years (2018 to 2021) to develop a new retrieval scheme to derive concentrations of DOC. OLCI observations with a spatial resolution of ~300 m were corrected for atmospheric effects using the Polymer algorithm. The results of this study show that using this new retrieval, remotely sensed DOC concentrations agree well with in situ DOC concentrations (MAPD=10.89%, RMSE=1.55 mg L−1, r²=0.92, n=489). The high revisit frequency and wide swath of OLCI allow it to capture the entire range of DOC concentrations and their seasonal variability. Estimated satellite-derived DOC export fluxes integrated over the ice-free periods of 2018 to 2021 show a high interannual variability and agree well with flux estimates from in situ data (RMSD=0.186 Tg C, MAPD=4.05%). In addition, 10-day OLCI composites covering the entire Lena River catchment revealed increasing DOC concentration and local sources of DOC along the Lena from south to north. We conclude that moderate resolution satellite imagers such as OLCI are very capable of observing DOC concentrations in large/wide rivers such as the Lena River despite the relatively coarse spatial resolution. The global coverage of remote sensing offers the expansion to more rivers in order to improve our understanding of the land-ocean carbon fluxes in a changing climate.

Description: Understanding the dominant climate forcings in the Pliocene is crucial to assessing the usefulness of the Pliocene as an analogue for our warmer future. Here, we implement a novel yet simple linear factorisation method to assess the relative influence of CO2 forcing in seven models of the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) ensemble. Outputs are termed “FCO2” and show the fraction of Pliocene climate change driven by CO2. The accuracy of the FCO2 method is first assessed through comparison to an energy balance analysis previously used to assess drivers of surface air temperature in the PlioMIP1 ensemble. After this assessment, the FCO2 method is applied to achieve an understanding of the drivers of Pliocene sea surface temperature and precipitation for the first time. CO2 is found to be the most important forcing in the ensemble for Pliocene surface air temperature (global mean FCO2=0.56), sea surface temperature (global mean FCO2=0.56), and precipitation (global mean FCO2=0.51). The range between individual models is found to be consistent between these three climate variables, and the models generally show good agreement on the sign of the most important forcing. Our results provide the most spatially complete view of the drivers of Pliocene climate to date and have implications for both data–model comparison and the use of the Pliocene as an analogue for the future. That CO2 is found to be the most important forcing reinforces the Pliocene as a good palaeoclimate analogue, but the significant effect of non-CO2 forcing at a regional scale (e.g. orography and ice sheet forcing at high latitudes) reminds us that it is not perfect, and these additional influencing factors must not be overlooked. This comparison is further complicated when considering the Pliocene as a state in quasi-equilibrium with CO2 forcing compared to the transient warming being experienced at present.

Description: Information about sea ice surface topography and related deformation is crucial for studies of sea ice mass balance, sea ice modeling, and ship navigation through the ice pack. The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2), part of the National Aeronautics and Space Administration (NASA) Earth Observing System, has been on orbit for over 4 years, sensing the sea ice surface topography with six laser beams capable of capturing individual features such as pressure ridges. To assess the capabilities and uncertainties of ICESat-2 products, coincident high-resolution measurements of sea ice surface topography are required. During the yearlong Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the Arctic Ocean, we successfully carried out a coincident underflight of ICESat-2 with a helicopter-based airborne laser scanner (ALS), achieving an overlap of more than 100 km. Despite the comparably short data set, the high-resolution centimeter-scale measurements of the ALS can be used to evaluate the performance of ICESat-2 products. Our goal is to investigate how the sea ice surface roughness and topography are represented in different ICESat-2 products as well as how sensitive ICESat-2 products are to leads and small cracks in the ice cover. Here, we compare the ALS measurements with ICESat-2's primary sea ice height product, ATL07, and the high-fidelity surface elevation product developed by the University of Maryland (UMD). By applying a ridge-detection algorithm, we find that 16 % (4 %) of the number of obstacles in the ALS data set are found using the strong (weak) center beam in ATL07. Significantly higher detection rates of 42 % (30 %) are achieved when using the UMD product. While only one lead is indicated in ATL07 for the underflight, the ALS reveals many small, narrow, and only partly open cracks that appear to be overlooked by ATL07.

Description: Rapid Arctic warming accelerates permafrost thaw, causing an additional release of terrestrial organic matter (OM) into rivers and, ultimately, after transport via deltas and estuaries, to the Arctic Ocean nearshore. The majority of our understanding of nearshore OM dynamics and fate has been developed from freshwater rivers despite the likely impact of highly dynamic estuarine and deltaic environments on the transformation, storage, and age of OM delivered to coastal waters. Here, we studied particulate organic carbon (POC) dynamics in the Lena River delta and compared them with POC dynamics in the Lena River main stem along a ∼ 1600 km long transect from Yakutsk, downstream to the delta. We measured POC, total suspended matter (TSM), and carbon isotopes (δ13C and Δ14C) in POC to compare riverine and deltaic OM composition and changes in OM source and fate during transport offshore. We found that TSM and POC concentrations decreased by 70 % during transit from the main stem to the delta and Arctic Ocean. We found deltaic POC to be strongly depleted in 13C relative to fluvial POC. Dual-carbon (Δ14C and δ13C) isotope mixing model analyses indicated a significant phytoplankton contribution to deltaic POC (∼ 68 ± 6 %) and suggested an additional input of permafrost-derived OM into deltaic waters (∼ 18 ± 4 % of deltaic POC originates from Pleistocene deposits vs. ∼ 5 ± 4 % in the river main stem). Despite the lower concentration of POC in the delta than in the main stem (0.41 ± 0.10 vs. 0.79 ± 0.30 mg L−1, respectively), the amount of POC derived from Yedoma deposits in deltaic waters was almost twice as large as the amount of POC of Yedoma origin in the main stem (0.07 ± 0.02 and 0.04 ± 0.02 mg L−1, respectively). We assert that estuarine and deltaic processes require consideration in order to correctly understand OM dynamics throughout Arctic nearshore coastal zones and how these processes may evolve under future climate-driven change.

Description: This study is based on multiproxy data gained from a 14C-dated 6.5 m long sediment core and a 210Pb-dated 23 cm short core retrieved from Lake Rauchuagytgyn in Chukotka, Arctic Russia. Our main objectives are to reconstruct the environmental history and ecological development of the lake during the last 29 kyr and to investigate the main drivers behind bioproduction shifts. The methods comprise age-modeling, accumulation rate estimation, and light microscope diatom species analysis of 74 samples, as well as organic carbon, nitrogen, and mercury analysis. Diatoms have appeared in the lake since 21.8 ka cal BP and are dominated by planktonic Lindavia ocellata and L. cyclopuncta. Around the Pleistocene–Holocene boundary, other taxa including planktonic Aulacoseira, benthic fragilarioid (Staurosira), and achnanthoid species increase in their abundance. There is strong correlation between variations of diatom valve accumulation rates (DARs; mean 176.1×109 valves m2 a1), organic carbon accumulation rates (OCARs; mean 4.6 g m−2 a−1), and mercury accumulation rates (HgARs; mean 63.4 µg m−2 a−1). We discuss the environmental forcings behind shifts in diatom species and find moderate responses of key taxa to the cold glacial period, postglacial warming, the Younger Dryas, and the Holocene Thermal Maximum. The short-core data likely suggest recent change of the diatom community at the beginning of the 20th century related to human-induced warming but only little evidence of atmospheric deposition of contaminants. Significant correlation between DAR and OCAR in the Holocene interglacial indicates within-lake bioproduction represents bulk organic carbon deposited in the lake sediment. During both glacial and interglacial episodes HgAR is mainly bound to organic matter in the lake associated with biochemical substrate conditions. There were only ambiguous signs of increased HgAR during the industrialization period. We conclude that if increased short-term emissions are neglected, pristine Arctic lake systems can potentially serve as long-term CO2 and Hg sinks during warm climate episodes driven by insolation-enhanced within-lake primary productivity. Maintaining intact natural lake ecosystems should therefore be of interest to future environmental policy.

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1% relative to 2020, with fossil emissions at 10.1±0.5GtCyr-1 (9.9±0.5GtCyr-1 when the cement carbonation sink is included), and ELUC was 1.1±0.7GtCyr-1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9±0.8GtCyr-1 (40.0±2.9GtCO2). Also, for 2021, GATM was 5.2±0.2GtCyr-1 (2.5±0.1ppmyr-1), SOCEAN was 2.9 ±0.4GtCyr-1, and SLAND was 3.5±0.9GtCyr-1, with a BIM of -0.6GtCyr-1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71±0.1ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0% (0.1% to 1.9%) globally and atmospheric CO2 concentration reaching 417.2ppm, more than 50% above pre-industrial levels (around 278ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959-2021, but discrepancies of up to 1GtCyr-1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at 10.18160/GCP-2022 (Friedlingstein et al., 2022b).

Description: Climate warming and related drivers of soil thermal change in the Arctic are expected to modify the distribution and dynamics of carbon contained in perennially frozen grounds. Thawing of permafrost in the Mackenzie River watershed of northwestern Canada, coupled with increases in river discharge and coastal erosion, triggers the release of terrestrial organic matter (OMt) from the largest Arctic drainage basin in North America into the Arctic Ocean. While this process is ongoing and its rate is accelerating, the fate of the newly mobilized organic matter as it transits from the watershed through the delta and into the marine system remains poorly understood. In the framework of the European Horizon 2020 Nunataryuk programme, and as part of the Work Package 4 (WP4) Coastal Waters theme, four field expeditions were conducted in the Mackenzie Delta region and southern Beaufort Sea from April to September 2019. The temporal sampling design allowed the survey of ambient conditions in the coastal waters under full ice cover prior to the spring freshet, during ice breakup in summer, and anterior to the freeze-up period in fall. To capture the fluvial-marine transition zone, and with distinct challenges related to shallow waters and changing seasonal and meteorological conditions, the field sampling was conducted in close partnership with members of the communities of Aklavik, Inuvik and Tuktoyaktuk, using several platforms, namely helicopters, snowmobiles, and small boats. Water column profiles of physical and optical variables were measured in situ, while surface water, groundwater, and sediment samples were collected and preserved for the determination of the composition and sources of OMt, including particulate and dissolved organic carbon (POC and DOC), and colored dissolved organic matter (CDOM), as well as a suite of physical, chemical, and biological variables. Here we present an overview of the standardized datasets, including hydrographic profiles, remote sensing reflectance, temperature and salinity, particle absorption, nutrients, dissolved organic carbon, particulate organic carbon, particulate organic nitrogen, CDOM absorption, fluorescent dissolved organic matter intensity, suspended particulate matter, total particulate carbon, total particulate nitrogen, stable water isotopes, radon in water, bacterial abundance, and a string of phytoplankton pigments including total chlorophyll. Datasets and related metadata can be found in (10.1594/PANGAEA.937587).

Description: 〈jats:p〉Abstract. Airborne in situ cloud measurements were carried out over the northern Fram Strait between Greenland and Svalbard in spring 2019 and summer 2020. In total, 811 min of low-level cloud observations were performed during 20 research flights above the sea ice and the open Arctic ocean with the Polar 5 research aircraft of the Alfred Wegener Institute. Here, we combine the comprehensive in situ cloud data to investigate the distributions of particle number concentration N, effective diameter Deff, and cloud water content CWC (liquid and ice) of Arctic clouds below 500 m altitude, measured at latitudes between 76 and 83∘ N. We developed a method to quantitatively derive the occurrence probability of their thermodynamic phase from the combination of microphysical cloud probe and Polar Nephelometer data. Finally, we assess changes in cloud microphysics and cloud phase related to ambient meteorological conditions in spring and summer and address effects of the sea ice and open-ocean surface conditions. We find median N from 0.2 to 51.7 cm−3 and about 2 orders of magnitude higher N for mainly liquid clouds in summer compared to ice and mixed-phase clouds measured in spring. A southerly flow from the sea ice in cold air outbreaks dominates cloud formation processes at temperatures mostly below −10 ∘C in spring, while northerly warm air intrusions favor the formation of liquid clouds at warmer temperatures in summer. Our results show slightly higher N in clouds over the sea ice compared to the open ocean, indicating enhanced cloud formation processes over the sea ice. The median CWC is higher in summer (0.16 g m−3) than in spring (0.06 g m−3), as this is dominated by the available atmospheric water content and the temperatures at cloud formation level. We find large differences in the particle sizes in spring and summer and an impact of the surface conditions, which modifies the heat and moisture fluxes in the boundary layer. By combining microphysical cloud data with thermodynamic phase information from the Polar Nephelometer, we find mixed-phase clouds to be the dominant thermodynamic cloud phase in spring, with a frequency of occurrence of 61 % over the sea ice and 66 % over the ocean. Pure ice clouds exist almost exclusively over the open ocean in spring, and in summer the cloud particles are most likely in the liquid water state. The comprehensive low-level cloud data set will help us to better understand the role of clouds and their thermodynamic phase in the Arctic radiation budget and to assess the performance of global climate models in a region of the world with the strongest anthropogenic climate change. 〈/jats:p〉

Description: 〈jats:p〉Abstract. The ocean mixed layer is the interface between the ocean interior and the atmosphere or sea ice and plays a key role in climate variability. It is thus critical that numerical models used in climate studies are capable of a good representation of the mixed layer, especially its depth. Here we evaluate the mixed-layer depth (MLD) in six pairs of non-eddying (1∘ grid spacing) and eddy-rich (up to 1/16∘) models from the Ocean Model Intercomparison Project (OMIP), forced by a common atmospheric state. For model evaluation, we use an updated MLD dataset computed from observations using the OMIP protocol (a constant density threshold). In winter, low-resolution models exhibit large biases in the deep-water formation regions. These biases are reduced in eddy-rich models but not uniformly across models and regions. The improvement is most noticeable in the mode-water formation regions of the Northern Hemisphere. Results in the Southern Ocean are more contrasted, with biases of either sign remaining at high resolution. In eddy-rich models, mesoscale eddies control the spatial variability in MLD in winter. Contrary to a hypothesis that the deepening of the mixed layer in anticyclones would make the MLD larger globally, eddy-rich models tend to have a shallower mixed layer at most latitudes than coarser models do. In addition, our study highlights the sensitivity of the MLD computation to the choice of a reference level and the spatio-temporal sampling, which motivates new recommendations for MLD computation in future model intercomparison projects. 〈/jats:p〉

Description: Modern humans are the only fully terrestrial ape. All other apes are \npartially arboreal, particularly as infants and juveniles. Precocial locomotor \ndevelopment, high frequency of arboreal locomotion in early ontogeny, and \nincreased terrestriality throughout development are ubiquitous amongst the \nhominines and likely represent the ancestral state. The role of climbing in \nhominin evolution has been debated for decades, but if hominins climbed \nregularly then subadults likely relied on it most frequently. Investigating the \nrole of climbing throughout hominin evolution requires reliable developmentally \nplastic traits that are responsive to locomotor loading and can be identified in the \nfossil record. Chimpanzees and gorillas provide a natural experiment to examine \nthe relationship between age-related variation locomotor activities and bone \nstructure. Chimpanzees and gorillas are most arboreal during infancy and \nbecome more terrestrial throughout development. Gorillas are comparatively \nmore terrestrial and transition to predominantly terrestrial locomotion at an \nearlier age. This paper has two main objectives. First, to examine if interspecific \ndifferences in the rate of locomotor development is reflected in bone structure. \nSecond, to determine if ontogenetic reductions in the frequency of arboreal \nlocomotion correspond to age-related variation in bone structure.

Description: The energy and mass balance of mountain glaciers translate into volume changes that play out as area changes over time. From this, together with former moraines during maximum advances, information on past climate conditions and the climatic drivers behind during glacier advances can be obtained. Here, we use the distributed COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY) to simulate the present state of an Italian glacier, named Fürkeleferner, for the mass balance years 2013–2017. Next, we investigate the local climate during the time of the last “Little Ice Age” (LIA) maximum glacier advance using COSIPY together with the LIA glacier outline retrieved from moraine mapping and a digital elevation model (DEM) adapted for the glacier’s geometry at the time of the LIA as a benchmark. Furthermore, the glacier’s sensitivity to future air temperature increase of +1 K and +2 K is investigated using the same model. For all simulations, meteorological data of closely located climate stations are used to force the model. We show the individual monthly contribution of individual energy and mass balance components. Refreezing during the summer months is an important component of the energy and mass balance, on average about 9 % relative to total annual ablation. The results from simulating past climate show a 2.8 times larger glacier area for Fürkeleferner during the LIA than today. This further implies a 2.5 K colder climate, assuming that the amount of precipitation was 10 %–20 % in excess of today’s value. Concerning further temperature increase of 2 K, the glacier would only consist of the ablation area implying sustained mass loss and eventual total mass loss. Even under current climatic conditions, the glacier area would have to decrease to 17 % of its current area to be in a steady state. We discuss the reliability of the results by comparing simulated present mass balance to measured mass balances of neighboring glaciers in the European Alps and with short-term measurements on Fürkeleferner itself. In conclusion, we are able to show how the glacier responds to past and future climate change and determine the climatic drivers behind.

Description: Arctic amplification (AA) is a coupled atmosphere-sea ice-ocean process. This understanding has evolved from the early concept of AA, as a consequence of snow-ice line progressions, through more than a century of research that has clarified the relevant processes and driving mechanisms of AA. The predictions made by early modeling studies, namely the fall/winter maximum, bottom-heavy structure, the prominence of surface albedo feedback, and the importance of stable stratification have withstood the scrutiny of multi-decadal observations and more complex models. Yet, the uncertainty in Arctic climate projections is larger than in any other region of the planet, making the assessment of high-impact, near-term regional changes difficult or impossible. Reducing this large spread in Arctic climate projections requires a quantitative process understanding. This manuscript aims to build such an understanding by synthesizing current knowledge of AA and to produce a set of recommendations to guide future research. It briefly reviews the history of AA science, summarizes observed Arctic changes, discusses modeling approaches and feedback diagnostics, and assesses the current understanding of the most relevant feedbacks to AA. These sections culminate in a conceptual model of the fundamental physical mechanisms causing AA and a collection of recommendations to accelerate progress towards reduced uncertainty in Arctic climate projections. Our conceptual model highlights the need to account for local feedback and remote process interactions within the context of the annual cycle to constrain projected AA. We recommend raising the priority of Arctic climate sensitivity research, improving the accuracy of Arctic surface energy budget observations, rethinking climate feedback definitions, coordinating new model experiments and intercomparisons, and further investigating the role of episodic variability in AA.

Description: The concepts of CO2 emission, global warming, climate change, and their environmental impacts are of utmost importance for the understanding and protection of the ecosystems. Among the natural sources of gases into the atmosphere, the contribution of geogenic sources plays a crucial role. However, while subaerial emissions are widely studied, submarine outgassing is not yet well understood. In this study, we review and catalog 122 literature and unpublished data of submarine emissions distributed in ten coastal areas of the Aegean Sea. This catalog includes descriptions of the degassing vents through in situ observations, their chemical and isotopic compositions, and flux estimations. Temperatures and pH data of surface seawaters in four areas affected by submarine degassing are also presented. This overview provides useful information to researchers studying the impact of enhanced seawater CO2 concentrations related either to increasing CO2 levels in the atmosphere or leaking carbon capture and storage systems.

Description: Published

Description: 775247

Description: 6V. Pericolosità vulcanica e contributi alla stima del rischio

Description: JCR Journal

Description: 〈jats:p〉Sexually produced juvenile scleractinian corals play a key role in the adaptation process of coral reefs, as they are considered to possess an innate plasticity and thus can adjust to changing environmental parameters within a certain range. In this study we investigated in detail the early life stages of the brooding species 〈jats:italic〉Leptastrea purpurea〈/jats:italic〉 to identify, categorize and visualize the critical steps of the complex transformation process from a swimming coral larva to a sessile coral recruit and later to a coral colony. For that, we performed settlement experiments using previously known cues: cycloprodigiosin (CYPRO) and crustose coralline algae (CCA) as well as novel cues: crude extracts of 〈jats:italic〉Pseudoalteromonas espejiana〈/jats:italic〉 and 〈jats:italic〉P. piscicida〈/jats:italic〉 to identify a general, cue-independent settlement pathway. We monitored the development of 〈jats:italic〉L. purpurea〈/jats:italic〉 over 12 months using bright field and fluorescence microscopy. Also we identified the fluorescence signals of 〈jats:italic〉L. purpurea〈/jats:italic〉 with confocal microscopy at four crucial development steps: (A) swimming larva, (B) metamorphosing larva, (C) coral recruit and (D) adult coral. Our methodological approach allowed us to observe an ontogenetic shift of fluorescence signals which provokes the hypothesis that certain fluorescence patterns might be connected to distinct sequential functions in the early life cycle of scleractinian corals. Our observations showed great similarities to the early development of other brooding and spawning corals, making 〈jats:italic〉L. purpurea〈/jats:italic〉 a prospective candidate to be used as a model organism for coral research. Furthermore, our in-depth picture series provides a robust monitoring reference for coral nurseries or field applications and demonstrates the potential of fluorescence as an indicator to instantly determine the growth stage of a developing coral recruit.〈/jats:p〉

Description: 〈jats:p〉Abstract. The mid-Pliocene warm period (3.264–3.025 Ma) is the most recent geological period in which the atmospheric CO2 concentration was approximately equal to the concentration we measure today (ca. 400 ppm). Sea surface temperature (SST) proxies indicate above-average warming over the North Atlantic in the mid-Pliocene with respect to the pre-industrial period, which may be linked to an intensified Atlantic Meridional Overturning Circulation (AMOC). Earlier results from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2) show that the ensemble simulates a stronger AMOC in the mid-Pliocene than in the pre-industrial. However, no consistent relationship between the stronger mid-Pliocene AMOC and either the Atlantic northward ocean heat transport (OHT) or average North Atlantic SSTs has been found. In this study, we look further into the drivers and consequences of a stronger AMOC in mid-Pliocene compared to pre-industrial simulations in PlioMIP2. We find that all model simulations with a closed Bering Strait and Canadian Archipelago show reduced freshwater transport from the Arctic Ocean into the North Atlantic. This contributes to an increase in salinity in the subpolar North Atlantic and Labrador Sea that can be linked to the stronger AMOC in the mid-Pliocene. To investigate the dynamics behind the ensemble's variable response of the total Atlantic OHT to the stronger AMOC, we separate the Atlantic OHT into two components associated with either the overturning circulation or the wind-driven gyre circulation. While the ensemble mean of the overturning component is increased significantly in magnitude in the mid-Pliocene, it is partly compensated by a reduction in the gyre component in the northern subtropical gyre region. This indicates that the lack of relationship between the total OHT and AMOC is due to changes in OHT by the subtropical gyre. The overturning and gyre components should therefore be considered separately to gain a more complete understanding of the OHT response to a stronger mid-Pliocene AMOC. In addition, we show that the AMOC exerts a stronger influence on North Atlantic SSTs in the mid-Pliocene than in the pre-industrial, providing a possible explanation for the improved agreement of the PlioMIP2 ensemble mean SSTs with reconstructions in the North Atlantic. 〈/jats:p〉

Description: 〈jats:p〉Plastic debris is ubiquitous in all ecosystems and has even reached locations that humans will hardly reach such as the deep ocean floor and the atmosphere. Research has highlighted that plastic debris is now pervasive even in remote Arctic regions. While modeling projections indicated local sources and long-distance transport as causes, empirical data about its origin and sources are scarce. Data collected by citizen scientists can increase the scale of observations, especially in such remote regions. Here, we report abundance and composition data of marine debris collected by citizen scientists on 14 remote Arctic beaches on the Spitsbergen archipelago. In addition, citizen scientists collected three large, industrial sized canvas bags (hereafter: big packs), filled with beached debris, of which composition, sources and origin were determined. A total debris mass of 1,620 kg was collected on about 38,000 m〈jats:sup〉2〈/jats:sup〉 (total mean = 41.83 g m〈jats:sup〉-2〈/jats:sup〉, SEM = ± 31.62). In terms of abundance, 23,000 pieces of debris were collected on 25,500 m〈jats:sup〉2〈/jats:sup〉 (total mean = 0.37 items of debris m〈jats:sup〉-2〈/jats:sup〉, SEM = ± 0.17). Although most items were plastic in both abundance and mass, fisheries waste, such as nets, rope, and large containers, dominated in mass (87%), and general plastics, such as packaging and plastic articles, dominated in abundance (80%). Fisheries-related debris points to local sea-based sources from vessels operating in the Arctic and nearby. General plastics could point to both land- and ship based sources, as household items are also used on ships and debris can be transported to the north 〈jats:italic〉via〈/jats:italic〉 the oceans current. Overall, 1% of the items (206 out of 14,707 pieces) collected in two big packs (2017 and 2021), bore imprints or labels allowing an analysis of their origin. If the categories ‘global’ and ‘English language’ were excluded, most of identifiable items originated from Arctic states (65%), especially from Russia (32%) and Norway (16%). But almost a third of the items (30%) was of European provenance, especially from Germany (8%). Five percent originated from more distant sources (e.g. USA, China, Korea, Brazil). Global measures such as an efficient and legally binding plastic treaty with improved upstream measures and waste management are urgently needed, to lower the amount of plastic entering our environments and in turn lifting the pressure on the Arctic region and its sensitive biota.〈/jats:p〉

Description: 〈jats:p〉Abstract. Dimethyl sulfide (DMS) plays an important role in the atmosphere by influencing the formation of aerosols and cloud condensation nuclei. In contrast, the role of methanethiol (MeSH) for the budget and flux of reduced sulfur remains poorly understood. In the present study, we quantified DMS and MeSH together with the trace gases carbon monoxide (CO), isoprene, acetone, acetaldehyde and acetonitrile in North Atlantic and Arctic Ocean surface waters, covering a transect from 57.2 to 80.9∘ N in high spatial resolution in May–June 2015. Whereas isoprene, acetone, acetaldehyde and acetonitrile concentrations decreased northwards, CO, DMS and MeSH retained substantial concentrations at high latitudes, indicating specific sources in polar waters. DMS was the only compound with a higher average concentration in polar (31.2 ± 9.3 nM) than in Atlantic waters (13.5 ± 2 nM), presumably due to DMS originating from sea ice. At eight sea-ice stations north of 80∘ N, in the diatom-dominated marginal ice zone, DMS and chlorophyll a markedly correlated (R2 = 0.93) between 0–50 m depth. In contrast to previous studies, MeSH and DMS did not co-vary, indicating decoupled processes of production and conversion. The contribution of MeSH to the sulfur budget (represented by DMS + MeSH) was on average 20 % (and up to 50 %) higher than previously observed in the Atlantic and Pacific oceans, suggesting MeSH as an important source of sulfur possibly emitted to the atmosphere. The potential importance of MeSH was underlined by several correlations with bacterial taxa, including typical phytoplankton associates from the Rhodobacteraceae and Flavobacteriaceae families. Furthermore, the correlation of isoprene and chlorophyll a with Alcanivorax indicated a specific relationship with isoprene-producing phytoplankton. Overall, the demonstrated latitudinal and vertical patterns contribute to understanding how concentrations of central marine trace gases are linked with chemical and biological dynamics across oceanic waters. 〈/jats:p〉

Description: When parents of two dierent species have babies together, those \nbabies are called hybrids. In nature, hybrids are often born in the \nregion where the ranges of their parent species meet. This region is \ncalled a hybrid zone. We know that species change their ranges all the \ntime, and we also know that some species compete with each other \nfor food or living space. This means that, if one of the two parent \nspecies manages to expand its range, the other species may be forced \nto retreat. If that were to happen, the hybrid zone between the two \nspecies\xe2\x80\x99 ranges should move, right? Even though researchers used \nto think that hybrid zone movement was rare, recent studies suggest \notherwise. In this article, we will tell you what hybrid zones are, how \nthey form, why their position may shift over time, and what we can \nlearn from this movement

Description: The MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition was the largest Arctic field campaign ever conducted. MOSAiC offered the unique opportunity to monitor and characterize aerosols and clouds with high vertical resolution up to 30 km height at latitudes from 80 to 90 N over an entire year (October 2019 to September 2020). Without a clear knowledge of the complex aerosol layering, vertical structures, and dominant aerosol types and their impact on cloud formation, a full understanding of the meteorological processes in the Arctic, and thus advanced climate change research, is impossible. Widespread ground-based in situ observations in the Arctic are insufficient to provide these required aerosol and cloud data. In this article, a summary of our MOSAiC observations of tropospheric aerosol profiles with a state-of-the-art multiwavelength polarization Raman lidar aboard the icebreaker Polarstern is presented. Particle optical properties, i.e., light-extinction profiles and aerosol optical thickness (AOT), and estimates of cloud-relevant aerosol properties such as the number concentration of cloud condensation nuclei (CCN) and ice-nucleating particles (INPs) are discussed, separately for the lowest part of the troposphere (atmospheric boundary layer, ABL), within the lower free troposphere (around 2000 m height), and at the cirrus level close to the tropopause. In situ observations of the particle number concentration and INPs aboard Polarstern are included in the study. A strong decrease in the aerosol amount with height in winter and moderate vertical variations in summer were observed in terms of the particle extinction coefficient. The 532 nm light-extinction values dropped from 〉50 Mm-1 close to the surface to 〈5 Mm-1 at 4-6 km height in the winter months. Lofted, aged wildfire smoke layers caused a re-increase in the aerosol concentration towards the tropopause. In summer (June to August 2020), much lower particle extinction coefficients, frequently as low as 1-5 Mm-1, were observed in the ABL. Aerosol removal, controlled by in-cloud and below-cloud scavenging processes (widely suppressed in winter and very efficient in summer) in the lowermost 1-2 km of the atmosphere, seems to be the main reason for the strong differences between winter and summer aerosol conditions. A complete annual cycle of the AOT in the central Arctic could be measured. This is a valuable addition to the summertime observations with the sun photometers of the Arctic Aerosol Robotic Network (AERONET). In line with the pronounced annual cycle in the aerosol optical properties, typical CCN number concentrations (0.2 % supersaturation level) ranged from 50-500 cm-3 in winter to 10-100 cm-3 in summer in the ABL. In the lower free troposphere (at 2000 m), however, the CCN level was roughly constant throughout the year, with values mostly from 30 to 100 cm-3. A strong contrast between winter and summer was also given in terms of ABL INPs which control ice production in low-level clouds. While soil dust (from surrounding continents) is probably the main INP type during the autumn, winter, and spring months, local sea spray aerosol (with a biogenic aerosol component) seems to dominate the ice nucleation in the ABL during the summer months (June-August). The strong winter vs. summer contrast in the INP number concentration by roughly 2-3 orders of magnitude in the lower troposphere is, however, mainly caused by the strong cloud temperature contrast. A unique event of the MOSAiC expedition was the occurrence of a long-lasting wildfire smoke layer in the upper troposphere and lower stratosphere. Our observations suggest that the smoke particles frequently triggered cirrus formation close to the tropopause from October 2019 to May 2020.

Description: 〈jats:p〉Abstract. The transport of water masses with ocean circulation is a key component of the global climate system. In this context, the Filchner Trough in the southern Weddell Sea is critical, as it is a hotspot for the cross-shelf-break exchange of Dense Shelf Water and Warm Deep Water. We present results from Lagrangian particle tracking experiments in a global-ocean–sea-ice model (FESOM-1.4) which includes ice-shelf cavities and has eddy-permitting resolution on the southern Weddell Sea continental shelf. With backward and forward experiments, we assess changes between a present-day and a future (SSP5-8.5) time slice in the origin of waters reaching the Filchner Ice Shelf front and the fate of waters leaving it. We show that particles reaching the ice-shelf front from the open ocean originate from 173 % greater depths by 2100 (median; 776 m as compared to 284 m for the present day), while waters leaving the cavity towards the open ocean end up at 35 % shallower depths (550 m as compared to 850 m for the present day). Pathways of water leaving the continental shelf increasingly occur in the upper ocean, while the on-shelf flow of waters that might reach the ice-shelf cavity, i.e., at deeper layers, becomes more important by 2100. Simultaneously, median transit times between the Filchner Ice Shelf front and the continental shelf break decrease (increase) by 6 (9.5) months in the backward (forward) experiments. In conclusion, our study demonstrates the sensitivity of regional circulation patterns in the southern Weddell Sea to ongoing climate change, with direct implications for ice-shelf basal melt rates and local ecosystems. 〈/jats:p〉

Description: 〈jats:p〉Abstract. Radiocarbon is a tracer that provides unique insights into the ocean's ability to sequester CO2 from the atmosphere. While spatial patterns of radiocarbon in the ocean interior can indicate the vectors and timescales for carbon transport through the ocean, estimates of the global average ocean–atmosphere radiocarbon age offset (B-Atm) place constraints on the closure of the global carbon cycle. Here, we apply a Bayesian interpolation method to compiled B-Atm data to generate global interpolated fields and mean ocean B-Atm estimates for a suite of time slices across the last deglaciation. The compiled data and interpolations confirm a stepwise and spatially heterogeneous “rejuvenation” of the ocean, suggesting that carbon was released to the atmosphere through two swings of a “ventilation seesaw” operating between the North Atlantic and both the Southern Ocean and the North Pacific. Sensitivity tests using the Bern3D model of intermediate complexity demonstrate that a portion of the reconstructed deglacial B-Atm changes may reflect “phase-attenuation” biases that are unrelated to ocean ventilation and that arise from independent atmospheric radiocarbon dynamics instead. A deglacial minimum in B-Atm offsets during the Bølling–Allerød could partly reflect such a bias. However, the sensitivity tests further demonstrate that when correcting for such biases, ocean “ventilation” could still account for at least one-third of deglacial atmospheric CO2 rise. This contribution to CO2 rise appears to have continued through the Younger Dryas, though much of the impact was likely achieved by the end of the Bølling–Allerød, indicating a key role for marine carbon cycle adjustment early in the deglacial process. Our global average B-Atm estimates place further new constraints on the long-standing mystery of global radiocarbon budget closure across the last deglaciation and suggest that glacial radiocarbon production levels are likely underestimated on average by existing reconstructions. 〈/jats:p〉

Description: The cycling of carbon in the oceans is affected by feedbacks driven by changes in climate and atmospheric CO2. Understanding these feedbacks is therefore an important prerequisite for projecting future climate. Marine biogeochemistry models are a useful tool but, as with any model, are a simplification and need to be continually improved. In this study, we coupled the Finite-volumE Sea ice–Ocean Model (FESOM2.1) to the Regulated Ecosystem Model version 3 (REcoM3). FESOM2.1 is an update of the Finite-Element Sea ice–Ocean Model (FESOM1.4) and operates on unstructured meshes. Unlike standard structured-mesh ocean models, the mesh flexibility allows for a realistic representation of small-scale dynamics in key regions at an affordable computational cost. Compared to the previous coupled model version of FESOM1.4–REcoM2, the model FESOM2.1–REcoM3 utilizes a new dynamical core, based on a finite-volume discretization instead of finite elements, and retains central parts of the biogeochemistry model. As a new feature, carbonate chemistry, including water vapour correction, is computed by mocsy 2.0. Moreover, REcoM3 has an extended food web that includes macrozooplankton and fast-sinking detritus. Dissolved oxygen is also added as a new tracer. In this study, we assess the ocean and biogeochemical state simulated with FESOM2.1–REcoM3 in a global set-up at relatively low spatial resolution forced with JRA55-do (Tsujino et al., 2018) atmospheric reanalysis. The focus is on the recent period (1958–2021) to assess how well the model can be used for present-day and future climate change scenarios on decadal to centennial timescales. A bias in the global ocean–atmosphere preindustrial CO2 flux present in the previous model version (FESOM1.4–REcoM2) could be significantly reduced. In addition, the computational efficiency is 2–3 times higher than that of FESOM1.4–REcoM2. Overall, it is found that FESOM2.1–REcoM3 is a skilful tool for ocean biogeochemical modelling applications.

Description: Soils in the permafrost region have acted as car- bon sinks for thousands of years. As a result of global warming, permafrost soils are thawing and will potentially release greenhouse gases (GHGs) such as methane (CH4) and carbon dioxide (CO2). However, small-scale spatial heterogeneities of GHG production have been neglected in previous incubation studies. Here, we used an anaerobic incubation experiment to simulate permafrost thaw along a transect from upland Yedoma to the floodplain on Kurungnakh Island. Potential CO2 and CH4 production was measured during incubation of the active layer and permafrost soils at 4 and 20 ◦C, first for 60 d (approximate length of the growing season) and then continuing for 1 year. An assessment of methanogen abundance was performed in parallel for the first 60 d. Yedoma samples from upland and slope cores remained in a lag phase during the growing season simulation, while those located in the floodplain showed high production of CH4 (6.5 × 103 μg CH4-C g−1 C) and CO2 (6.9 × 103 μg CO2-C g−1 C) at 20 ◦C. The Yedoma samples from the permafrost layer started producing CH4 after 6 months of incubation. We conclude that landscape position is a key factor triggering CH4 production during the growing season time on Kurungnakh Island.

Description: Late Pleistocene permafrost of the Yedoma type constitutes a valuable paleo-environmental archive due to the presence of numerous and well-preserved floral and faunal fossils. The study of the fossil Yedoma inventory allows for qualitative and quantitative reconstructions of past ecosystem and climate conditions and variations over time. Here, we present the results of combined paleo-proxy studies including pollen, chironomid, diatom and mammal fossil analyses from a prominent Yedoma cliff on Sobo-Sise Island in the eastern Lena Delta, NE Siberia to complement previous and ongoing paleo-ecological research in western Beringia. The Yedoma Ice Complex (IC) cliff on Sobo-Sise Island (up to 28 m high, 1.7 km long) was continuously sampled at 0.5 m resolution. The entire sequence covers the last about 52 cal kyr BP, but is not continuous as it shows substantial hiatuses at 36–29 cal kyr BP, at 20–17 cal kyr BP and at 15–7 cal kyr BP. The Marine Isotope Stage (MIS) 3 Yedoma IC (52–28 cal kyr BP) pollen spectra show typical features of tundra–steppe vegetation. Green algae remains indicate freshwater conditions. The chironomid assemblages vary considerably in abundance and diversity. Chironomid-based TJuly reconstructions during MIS 3 reveal warmer-than-today TJuly at about 51 cal kyr BP, 46-44 and 41 cal kyr BP. The MIS 2 Yedoma IC (28–15 cal kyr BP) pollen spectra represent tundra-steppe vegetation as during MIS 3, but higher abundance of Artemisia and lower abundances of algae remains indicate drier summer conditions. The chironomid records are poor. The MIS 1 (7–0 cal kyr BP) pollen spectra indicate shrub-tundra vegetation. The chironomid fauna is sparse and not diverse. The chironomid-based TJuly reconstruction supports similar-as-today temperatures at 6.4–4.4 cal kyr BP. Diatoms were recorded only after about 6.4 cal kyr BP. The Sobo-Sise Yedoma record preserves traces of the West Beringian tundra-steppe that maintained the Mammoth fauna including rare evidence for woolly rhinoceros’ presence. Chironomid-based TJuly reconstructions complement previous plant-macrofossil based TJuly of regional MIS 3 records. Our study from the eastern Lena Delta fits into and extends previous paleo-ecological Yedoma studies to characterize Beringian paleo-environments in the Laptev Sea coastal region.

Description: Ocean color remote sensing has been used for more than 2 decades to estimate primary productivity. Approaches have also been developed to disentangle phytoplankton community structure based on spectral data from space, in particular when combined with in situ measurements of photosynthetic pigments. Here, we propose a new ocean color algorithm to derive the relative cell abundance of seven phytoplankton groups, as well as their contribution to total chlorophyll a (Chl a ) at the global scale. Our algorithm is based on machine learning and has been trained using remotely sensed parameters (reflectance, backscattering, and attenuation coefficients at different wavelengths, plus temperature and Chl a ) combined with an omics-based biomarker developed using Tara Oceans data representing a single-copy gene encoding a component of the photosynthetic machinery that is present across all phytoplankton, including both prokaryotes and eukaryotes. It differs from previous methods which rely on diagnostic pigments to derive phytoplankton groups. Our methodology provides robust estimates of the phytoplankton community structure in terms of relative cell abundance and contribution to total Chl a concentration. The newly generated datasets yield complementary information about different aspects of phytoplankton that are valuable for assessing the contributions of different phytoplankton groups to primary productivity and inferring community assembly processes. This makes remote sensing observations excellent tools to collect essential biodiversity variables (EBVs) and provide a foundation for developing marine biodiversity forecasts.

Description: 〈jats:p〉Abstract. Sea ice formation dominates surface salt forcing in the southern Weddell Sea. Brine rejected in the process of sea ice production results in the production of High Salinity Shelf Water (HSSW) that feeds the global overturning circulation and fuels the basal melt of the adjacent ice shelf. The strongest sea ice production rates are found in coastal polynyas, where steady offshore winds promote divergent ice movement during the freezing season. We used the Finite Element Sea ice–ice shelf–Ocean Model (FESOM) forced by output from the regional atmospheric model COSMO-CLM (CCLM) with 14 km horizontal resolution to investigate the role of polynyas for the surface freshwater flux of the southern Weddell Sea (2002–2017). The presence of stationary icescape features (i.e., fast-ice areas and grounded icebergs) can influence the formation of polynyas and, therefore, impact sea ice production. The representation of the icescape in our model is included by prescribing the position, shape and temporal evolution of a largely immobile ice mélange formed between the Filchner–Ronne Ice Shelf (FRIS) and a major grounded iceberg based on satellite data. We find that 70 % of the ice produced on the continental shelf of the southern Weddell Sea is exported from the region. While coastal polynyas cover 2 % of the continental shelf area, sea ice production within the coastal polynyas accounts for 17 % of the overall annual sea ice production (1509 km3). The largest contributions come from the Ronne Ice Shelf and Brunt Ice Shelf polynyas and polynyas associated with the ice mélange. Furthermore, we investigate the sensitivity of the polynya-based ice production to the (i) representation of the icescape and (ii) regional atmospheric forcing. Although large-scale atmospheric fields determine the sea ice production outside polynyas, both the treatment of the icescape and the regional atmospheric forcing are important for the regional patterns of sea ice production in polynyas. The representation of the ice mélange is crucial for the simulation of polynyas westward/eastward of it, which are otherwise suppressed/overestimated. Compared to using ERA-Interim reanalysis as an atmospheric forcing data set, using CCLM output reduces polynya-based ice production over the eastern continental shelf due to weaker offshore winds, yielding a more realistic polynya representation. Our results show that the location and not just the strength of the sea ice production in polynyas is a relevant parameter in setting the properties of the HSSW produced on the continental shelf, which in turn affects the basal melting of the Filchner–Ronne Ice Shelf. 〈/jats:p〉

Description: As an expansion of a time-series study on meiobenthos in the Arctic deep sea, the diversity of free-living nematode communities along nine stations along a bathymetric transect was investigated morphologically in taxonomic and functional regards (feeding-type composition, life-history traits, tail-shape composition) and compared with previous studies of the same transect to investigate possible changes in the nematode community composition. Special emphasis was given on the analysis of sedimentary environmental parameters, which are used as proxies for food availability and sediment porosity. Multivariate statistics performed on nematode abundance data revealed a bathymetric zonation into four bathymetric zones: upper bathyal (1300 – 2000 m), lower bathyal (2500 - 3500 m), abyssal (5100 – 5600 m) and an additional ‘outgroup’ consisting of two stations with low nematode densities. Nematode densities generally decreased with increasing depth. Taxonomic diversity (EG〈jats:sub〉(50)〈/jats:sub〉, H’〈jats:sub〉(log2)〈/jats:sub〉, J’) decreased in a unimodal pattern peaking in the lower bathyal zone. A distance-based linear model revealed that 44% of the total variation in nematode abundances could be explained by the measured environmental parameters. Microbial feeders are the dominant feeding type along the transect with increasing dominance in the abyssal zone. The maturity index, a measure of environmental disturbance, decreased with depth, indicating a more colonizer-dominated community in the abyssal zone. Nematodes with long conico-cylindrical tails also become more dominant in the abyssal zone. A previous study of the same transect conducted in 2005 found a similar bathymetric zonation, but with a strikingly different dominant feeding type, i.e. epistrate feeders. Between the 2005 study and the year 2010 we conducted our study, the composition of the plankton community in the Fram Strait changed significantly due to a warm water anomaly in the region. We argue that through bentho-pelagic coupling, effects of this warm water anomaly on plankton communities could be a reason for the drastic change in dominant nematode feeding types.

Description: 〈jats:p〉 〈/jats:p〉

Description: The highly populated coasts of the Bay of Bengal are particularly vulnerable to water-borne diseases, pollution and climatic extremes. The environmental factors behind bacterial community composition and Vibrio distribution were investigated in an estuarine system of a cholera-endemic region in the coastline of Bangladesh. Higher temperatures and sewage pollution were important drivers of the abundance of toxigenic Vibrio cholerae. A closer relation between non-culturable Vibrio and particulate organic matter (POM) was inferred during the post-monsoon. The distribution of operational taxonomic units (OTUs) of Vibrio genus was likely driven by salinity and temperature. The resuspension of sediments increased Vibrio abundance and organic nutrient concentrations. The δ13C dynamic in POM followed an increasing gradient from freshwater to marine stations; nevertheless, it was not a marker of sewage pollution. Bacteroidales and culturable coliforms were reliable indicators of untreated wastewater during pre and post-monsoon seasons. The presumptive incorporation of depleted-ammonium derived from ammonification processes under the hypoxic conditions, by some microorganisms such as Cloacibacterium and particularly by Arcobacter nearby the sewage discharge, contributed to the drastic 15N depletion in the POM. The likely capacity of extracellular polymeric substances production of these taxa may facilitate the colonization of POM from anthropogenic origin and may signify important properties for wastewater bioremediation. Genera of potential pathogens other than Vibrio associated with sewage pollution were Acinetobacter, Aeromonas, Arcobacter, and Bergeyella. The changing environmental conditions of the estuary favored the abundance of early colonizers and the island biogeography theory explained the distribution of some bacterial groups. This multidisciplinary study evidenced clearly the eutrophic conditions of the Karnaphuli estuary and assessed comprehensively its current bacterial baseline and potential risks. The prevailing conditions together with human overpopulation and frequent natural disasters, transform the region in one of the most vulnerable to climate change. Adaptive management strategies are urgently needed to enhance ecosystem health.

Description: Arctic soils store large amounts of organic carbon and other elements, such as amorphous silicon, silicon, calcium, iron, aluminum, and phosphorous. Global warming is projected to be most pronounced in the Arctic, leading to thawing permafrost which, in turn, changes the soil element availability. To project how biogeochemical cycling in Arctic ecosystems will be affected by climate change, there is a need for data on element availability. Here, we analyzed the amorphous silicon (ASi) content as a solid fraction of the soils as well as Mehlich III extractions for the bioavailability of silicon (Si), calcium (Ca), iron (Fe), phosphorus (P), and aluminum (Al) from 574 soil samples from the circumpolar Arctic region. We show large differences in the ASi fraction and in Si, Ca, Fe, Al, and P availability among different lithologies and Arctic regions. We summarize these data in pan-Arctic maps of the ASi fraction and available Si, Ca, Fe, P, and Al concentrations, focusing on the top 100cm of Arctic soil. Furthermore, we provide element availability values for the organic and mineral layers of the seasonally thawing active layer as well as for the uppermost permafrost layer. Our spatially explicit data on differences in the availability of elements between the different lithological classes and regions now and in the future will improve Arctic Earth system models for estimating current and future carbon and nutrient feedbacks under climate change (10.17617/3.8KGQUN, Schaller and Goeckede, 2022).

Description: The partitioning of CO2 between atmosphere and ocean depends to a large degree not only on the amount of dissolved inorganic carbon (DIC) but also on alkalinity in the surface ocean. That is also why ocean alkalinity enhancement (OAE) is discussed as one potential approach in the context of negative emission technologies. Although alkalinity is thus an important variable of the marine carbonate system, little knowledge exists on how its representation in models compares with measurements. We evaluated the large-scale alkalinity distribution in 14 CMIP6 Earth system models (ESMs) against the observational data set GLODAPv2 and show that most models, as well as the multi-model mean, underestimate alkalinity at the surface and in the upper ocean and overestimate it in the deeper ocean. The decomposition of the global mean alkalinity biases into contributions from (i) physical processes (preformed alkalinity), which include the physical redistribution of biased alkalinity originating from the soft tissue and carbonates pumps; (ii) remineralization; and (iii) carbonate formation and dissolution showed that the bias stemming from the physical redistribution of alkalinity is dominant. However, below the upper few hundred meters the bias from carbonate dissolution can gain similar importance to physical biases, while the contribution from remineralization processes is negligible. This highlights the critical need for better understanding and quantification of processes driving calcium carbonate dissolution in microenvironments above the saturation horizons and implementation of these processes into biogeochemical models. For the application of the models to assess the potential of OAE to increase ocean carbon uptake, a back-of-the-envelope calculation was conducted with each model's global mean surface alkalinity, DIC, and partial pressure of CO2 in seawater (pCO2) as input parameters. We evaluate the following two metrics: (1) the initial pCO2 reduction at the surface ocean after alkalinity addition and (2) the uptake efficiency (ηCO2) after air–sea equilibration is reached. The relative biases of alkalinity versus DIC at the surface affect the Revelle factor and therefore the initial pCO2 reduction after alkalinity addition. The global mean surface alkalinity bias relative to GLODAPv2 in the different models ranges from −85 mmol m−3 (−3.6 %) to +50 mmol m−3 (+2.1 %) (mean: −25 mmol m−3 or −1.1 %). For DIC the relative bias ranges from −55 mmol m−3 (−2.6 %) to 53 mmol m−3 (+2.5 %) (mean: −13 mmol m−3 or −0.6 %). All but two of the CMIP6 models evaluated here overestimate the Revelle factor at the surface by up to 3.4 % and thus overestimate the initial pCO2 reduction after alkalinity addition by up to 13 %. The uptake efficiency, ηCO2, then takes into account that a higher Revelle factor and a higher initial pCO2 reduction after alkalinity addition and equilibration mostly compensate for each other, meaning that resulting DIC differences in the models are small (−0.1 % to 1.1 %). The overestimation of the initial pCO2 reduction has to be taken into account when reporting on efficiencies of ocean alkalinity enhancement experiments using CMIP6 models, especially as long as the CO2 equilibrium is not reached.

Description: 〈jats:p〉Abstract. In this paper we describe the implementation of the carbon isotopes 13C and 14C (radiocarbon) into the marine biogeochemistry model REcoM3. The implementation is tested in long-term equilibrium simulations where REcoM3 is coupled with the ocean general circulation model FESOM2.1, applying a low-resolution configuration and idealized climate forcing. Focusing on the carbon-isotopic composition of dissolved inorganic carbon (δ13CDIC and Δ14CDIC), our model results are largely consistent with reconstructions for the pre-anthropogenic period. Our simulations also exhibit discrepancies, e.g. in upwelling regions and the interior of the North Pacific. Some of these differences are due to the limitations of our ocean circulation model setup, which results in a rather shallow meridional overturning circulation. We additionally study the accuracy of two simplified modelling approaches for dissolved inorganic 14C, which are faster (15 % and about a factor of five, respectively) than the complete consideration of the marine radiocarbon cycle. The accuracy of both simplified approaches is better than 5 %, which should be sufficient for most studies of Δ14CDIC. 〈/jats:p〉

Description: 〈jats:p〉Abstract. Systematic long-term studies on ecosystem dynamics are largely lacking from the East Antarctic Southern Ocean, although it is well recognized that they are indispensable to identify the ecological impacts and risks of environmental change. Here, we present a framework for establishing a long-term cross-disciplinary study on decadal timescales. We argue that the eastern Weddell Sea and the adjacent sea to the east, off Dronning Maud Land, is a particularly well suited area for such a study, since it is based on findings from previous expeditions to this region. Moreover, since climate and environmental change have so far been comparatively muted in this area, as in the eastern Antarctic in general, a systematic long-term study of its environmental and ecological state can provide a baseline of the current situation, which will be important for an assessment of future changes from their very onset, with consistent and comparable time series data underpinning and testing models and their projections. By establishing an Integrated East Antarctic Marine Research (IEAMaR) observatory, long-term changes in ocean dynamics, geochemistry, biodiversity, and ecosystem functions and services will be systematically explored and mapped through regular autonomous and ship-based synoptic surveys. An associated long-term ecological research (LTER) programme, including experimental and modelling work, will allow for studying climate-driven ecosystem changes and interactions with impacts arising from other anthropogenic activities. This integrative approach will provide a level of long-term data availability and ecosystem understanding that are imperative to determine, understand, and project the consequences of climate change and support a sound science-informed management of future conservation efforts in the Southern Ocean. 〈/jats:p〉

Description: Laboratory experiments showed that the isotopic fractionation of δ13C and of δ18O during calcite formation of planktic foraminifera are species-specific functions of ambient CO32- concentration. This effect became known as the carbonate ion effect (CIE), whose role for the interpretation of marine sediment data will be investigated here in an in-depth analysis of the 13C cycle. For this investigation, we constructed new 160 kyr long mono-specific stacks of changes in both δ13C and δ18O from either the planktic foraminifera Globigerinoides ruber (rub) or Trilobatus sacculifer (sac) from 112 and 40 marine records, respectively, from the wider tropics (latitudes below 38°). Both mono-specific time series Δ(δ13Crub) and Δ(δ13Csac) are very similar to each other, and a linear regression through a scatter plot of both data sets has a slope of ∼ 0.99 – although the laboratory-based CIE for both species differs by a factor of nearly 2, implying that they should record distinctly different changes in δ13C, if we accept that the carbonate ion concentration changes on glacial–interglacial timescales. For a deeper understanding of the 13C cycle, we use the Solid Earth version of the Box model of the Isotopic Carbon cYCLE (BICYLE-SE) to calculate how surface-ocean CO32- should have varied over time in order to be able to calculate the potential offsets which would by caused by the CIE quantified in culture experiments. Our simulations are forced with atmospheric reconstructions of CO2 and δ13CO2 derived from ice cores to obtain a carbon cycle which should at least at the surface ocean be as close as possible to expected conditions and which in the deep ocean largely agrees with the carbon isotope ratio of dissolved inorganic carbon (DIC), δ13CDIC, as reconstructed from benthic foraminifera. We find that both Δ(δ13Crub) and Δ(δ13Csac) agree better with changes in simulated δ13CDIC when ignoring the CIE than those time series which were corrected for the CIE. The combination of data- and model-based evidence for the lack of a role for the CIE in Δ(δ13Crub) and Δ(δ13Csac) suggests that the CIE as measured in laboratory experiments is not directly transferable to the interpretation of marine sediment records. The much smaller CIE-to-glacial–interglacial-signal ratio in foraminifera δ18O, when compared to δ13C, prevents us from drawing robust conclusions on the role of the CIE in δ18O as recorded in the hard shells of both species. However, theories propose that the CIE in both δ13C and δ18O depends on the pH in the surrounding water, suggesting that the CIE should be detectable in neither or both of the isotopes. Whether this lack of role of the CIE in the interpretation of planktic paleo-data is a general feature or is restricted to the two species investigated here needs to be checked with further data from other planktic foraminiferal species.

Description: 〈jats:p〉Abstract. Skillful sea ice drift forecasts are crucial for scientific mission planning and marine safety. Wind is the dominant driver of ice motion variability, but more slowly varying components of the climate system, in particular ice thickness and ocean currents, bear the potential to render ice drift more predictable than the wind. In this study, we provide the first assessment of Arctic sea ice drift predictability in four coupled general circulation models (GCMs), using a suite of “perfect-model” ensemble simulations. We find the position vector from Lagrangian trajectories of virtual buoys to remain predictable for at least a 90 (45) d lead time for initializations in January (July), reaching about 80 % of the position uncertainty of a climatological reference forecast. In contrast, the uncertainty in Eulerian drift vector predictions reaches the level of the climatological uncertainty within 4 weeks. Spatial patterns of uncertainty, varying with season and across models, develop in all investigated GCMs. For two models providing near-surface wind data (AWI-CM1 and HadGEM1.2), we find spatial patterns and large fractions of the variance to be explained by wind vector uncertainty. The latter implies that sea ice drift is only marginally more predictable than wind. Nevertheless, particularly one of the four models (GFDL-CM3) shows a significant correlation of up to −0.85 between initial ice thickness and target position uncertainty in large parts of the Arctic. Our results provide a first assessment of the inherent predictability of ice motion in coupled climate models; they can be used to put current real-world forecast skill into perspective and highlight the model diversity of sea ice drift predictability. 〈/jats:p〉

Description: 〈jats:p〉Abstract. This study evaluates the impact of increasing resolution on Arctic Ocean simulations using five pairs of matched low- and high-resolution models within the OMIP-2 (Ocean Model Intercomparison Project phase 2) framework. The primary objective is to assess whether a higher resolution can mitigate typical biases in low-resolution models and improve the representation of key climate-relevant variables. We reveal that increasing the horizontal resolution contributes to a reduction in biases in mean temperature and salinity and improves the simulation of the Atlantic water layer and its decadal warming events. A higher resolution also leads to better agreement with observed surface mixed-layer depth, cold halocline base depth and Arctic gateway transports in the Fram and Davis straits. However, the simulation of the mean state and temporal changes in Arctic freshwater content does not show improvement with increased resolution. Not all models achieve improvements for all analyzed ocean variables when spatial resolution is increased so it is crucial to recognize that model numerics and parameterizations also play an important role in faithful simulations. Overall, a higher resolution shows promise in improving the simulation of key Arctic Ocean features and processes, but efforts in model development are required to achieve more accurate representations across all climate-relevant variables. 〈/jats:p〉

Description: In continuous permafrost lowlands, thawing of ice-rich deposits and melting of massive ground ice lead to abrupt landscape changes called thermokarst, which have widespread consequences on the thermal, hydrological, and biogeochemical state of the subsurface. However, macro-scale land surface models (LSMs) do not resolve such localized subgrid-scale processes and could hence miss key feedback mechanisms and complexities which affect permafrost degradation and the potential liberation of soil organic carbon in high latitudes. Here, we extend the CryoGrid 3 permafrost model with a multi-scale tiling scheme which represents the spatial heterogeneities of surface and subsurface conditions in ice-rich permafrost lowlands. We conducted numerical simulations using stylized model setups to assess how different representations of micro- and meso-scale heterogeneities affect landscape evolution pathways and the amount of permafrost degradation in response to climate warming. At the micro-scale, the terrain was assumed to be either homogeneous or composed of ice-wedge polygons, and at the meso-scale it was assumed to be either homogeneous or resembling a low-gradient slope. We found that by using different model setups and parameter sets, a multitude of landscape evolution pathways could be simulated which correspond well to observed thermokarst landscape dynamics across the Arctic. These pathways include the formation, growth, and gradual drainage of thaw lakes; the transition from low-centred to high-centred ice-wedge polygons; and the formation of landscape-wide drainage systems due to melting of ice wedges. Moreover, we identified several feedback mechanisms due to lateral transport processes which either stabilize or destabilize the thermokarst terrain. The amount of permafrost degradation in response to climate warming was found to depend primarily on the prevailing hydrological conditions, which in turn are crucially affected by whether or not micro- and/or meso-scale heterogeneities were considered in the model setup. Our results suggest that the multi-scale tiling scheme allows for simulating ice-rich permafrost landscape dynamics in a more realistic way than simplistic one-dimensional models and thus facilitates more robust assessments of permafrost degradation pathways in response to climate warming. Our modelling work improves the understanding of how micro- and meso-scale processes affect the evolution of ice-rich permafrost landscapes, and it informs macro-scale modellers focusing on high-latitude land surface processes about the necessities and possibilities for the inclusion of subgrid-scale processes such as thermokarst within their models.

Description: During the mid-Pliocene warm period (mPWP; 3.264–3.025 Ma), atmospheric CO2 concentrations were approximately 400 ppm, and the Antarctic Ice Sheet was substantially reduced compared to today. Antarctica is surrounded by the Southern Ocean, which plays a crucial role in the global oceanic circulation and climate regulation. Using results from the Pliocene Model Intercomparison Project (PlioMIP2), we investigate Southern Ocean conditions during the mPWP with respect to the pre-industrial period. We find that the mean sea surface temperature (SST) warming in the Southern Ocean is 2.8 °C, while global mean SST warming is 2.4 °C. The enhanced warming is strongly tied to a dramatic decrease in sea ice cover over the mPWP Southern Ocean. We also see a freshening of the ocean (sub)surface, driven by an increase in precipitation over the Southern Ocean and Antarctica. The warmer and fresher surface leads to a highly stratified Southern Ocean that can be related to weakening of the deep abyssal overturning circulation. Sensitivity simulations show that the decrease in sea ice cover and enhanced warming is largely a consequence of the reduction in the Antarctic Ice Sheet. In addition, the mPWP geographic boundary conditions are responsible for approximately half of the increase in mPWP SST warming, sea ice loss, precipitation, and stratification increase over the Southern Ocean. From these results, we conclude that a strongly reduced Antarctic Ice Sheet during the mPWP has a substantial influence on the state of the Southern Ocean and exacerbates the changes that are induced by a higher CO2 concentration alone. This is relevant for the long-term future of the Southern Ocean, as we expect melting of the western Antarctic Ice Sheet in the future, an effect that is not currently taken into account in future projections by Coupled Model Intercomparison Project (CMIP) ensembles.

Description: 〈jats:p〉Abstract. Boreal forests of Siberia play a relevant role in the global carbon cycle. However, global warming threatens the existence of summergreen larch-dominated ecosystems, likely enabling a transition to evergreen tree taxa with deeper active layers. Complex permafrost–vegetation interactions make it uncertain whether these ecosystems could develop into a carbon source rather than continuing atmospheric carbon sequestration under global warming. Consequently, shedding light on the role of current and future active layer dynamics and the feedbacks with the apparent tree species is crucial to predict boreal forest transition dynamics and thus for aboveground forest biomass and carbon stock developments. Hence, we established a coupled model version amalgamating a one-dimensional permafrost multilayer forest land-surface model (CryoGrid) with LAVESI, an individual-based and spatially explicit forest model for larch species (Larix Mill.), extended for this study by including other relevant Siberian forest species and explicit terrain. Following parameterization, we ran simulations with the coupled version to the near future to 2030 with a mild climate-warming scenario. We focus on three regions covering a gradient of summergreen forests in the east at Spasskaya Pad, mixed summergreen–evergreen forests close to Nyurba, and the warmest area at Lake Khamra in the southeast of Yakutia, Russia. Coupled simulations were run with the newly implemented boreal forest species and compared to runs allowing only one species at a time, as well as to simulations using just LAVESI. Results reveal that the coupled version corrects for overestimation of active layer thickness (ALT) and soil moisture, and large differences in established forests are simulated. We conclude that the coupled version can simulate the complex environment of eastern Siberia by reproducing vegetation patterns, making it an excellent tool to disentangle processes driving boreal forest dynamics. 〈/jats:p〉

Description: Shallow-water rhodolith beds are rare in the Mediterranean Sea and generally poorly known. The Punta de la Mona rhodolith bed extends for 16,000 square meters in shallow and oligotrophic waters at the southern coast of Spain, off Almuñecar in the Alborán Sea. We present a detailed analysis of the structure (rhodolith cover and density, rhodolith size and shape, sediment granulometry) and morphospecies composition of the bed along a depth gradient. A stratified sampling was carried out at six depths (9, 12, 15, 18, 21, and 24 m), estimating rhodolith cover and abundance; rhodoliths were collected from one 30 by 30 cm quadrat for each transect, resulting in 18 samples and a total of 656 rhodoliths. The collected rhodoliths were measured and the coralline algal components identified morphoanatomically through a stereomicroscope and SEM. Sediment on the seafloor mainly consisted of pebbles and cobbles; the highest rhodolith cover occurred between 15 and 18 m, and the lowest at the shallowest and deepest transects (9 and 24 m). Mean Rhodolith size was similar throughout the depth range (23–35 mm) with a slight increase at 24 m, although the largest rhodoliths occurred at 21 m. In monospecific rhodoliths, size depended more on the forming species than on depth. We found 25 non-geniculate coralline morphospecies, nearly all rhodolith-forming morphospecies reported in the Mediterranean Sea in recent accounts. The highest morphospecies richness (18–19) and proportional abundance were found at intermediate depths (15–18 m), where rhodolith cover is also highest. Lithophyllum incrustans and Lithophyllum dentatum dominated at shallow depths (9–12 m), whereas Lithothamnion valens was the dominant species at intermediate and greater depths. Overall, the latter species was the most common in the rhodolith bed. The shallow-water rhodolith bed in Punta de la Mona is probably the most diverse in the Mediterranean Sea. This highlights the importance of the conservation of this habitat and, in general, emphasizes the role of the Alborán Sea as a diversity center of coralline algae. The Punta de la Mona example contradicts the common assumption in the geological literature that rhodolith beds are indicative of oligophotic environments with high nutrients levels.

Description: Marine Isotope Stage 5e (MIS 5e; the Last Interglacial, 125 ka) represents a process analog for a warmer world. Analysis of sea-level proxies formed in this period helps in constraining both regional and global drivers of sea-level change. In Southeast Asia, several studies have reported elevation and age information on MIS 5e sea-level proxies, such as fossil coral reef terraces or tidal notches, but a standardized database of such data was hitherto missing. In this paper, we produced such a sea-level database using the framework of the World Atlas of Last Interglacial Shorelines (WALIS; https://warmcoasts.eu/world-atlas.html). Overall, we screened and reviewed 14 studies on Last Interglacial sea-level indicators in Southeast Asia, from which we report 43 proxies (42 coral reef terraces and 1 tidal notch) that were correlated to 134 dated samples. Five data points date to MIS 5a (80 ka), six data points are MIS 5c (100 ka), and the rest are dated to MIS 5e. The database compiled in this study is available at https://doi.org/10.5281/zenodo.5040784 (Maxwell et al., 2021).

Description: Here we present the experimental design and results from a new mid-Pliocene simulation using the latest version of the UK's physical climate model, HadGEM3-GC31-LL, conducted under the auspices of CMIP6/PMIP4/PlioMIP2. Although two other palaeoclimate simulations have been recently run using this model, they both focused on more recent periods within the Quaternary, and therefore this is the first time this version of the UK model has been run this far back in time. The mid-Pliocene Warm Period, ∼3 Ma, is of particular interest because it represents a time period when the Earth was in equilibrium with CO2 concentrations roughly equivalent to those of today, providing a possible analogue for current and future climate change. The implementation of the Pliocene boundary conditions is firstly described in detail, based on the PRISM4 dataset, including CO2, ozone, orography, ice mask, lakes, vegetation fractions and vegetation functional types. These were incrementally added into the model, to change from a pre-industrial setup to a Pliocene setup. The results of the simulation are then presented, which are firstly compared with the model's pre-industrial simulation, secondly with previous versions of the same model and with available proxy data, and thirdly with all other models included in PlioMIP2. Firstly, the comparison with the pre-industrial simulation suggests that the Pliocene simulation is consistent with current understanding and existing work, showing warmer and wetter conditions, and with the greatest warming occurring over high-latitude and polar regions. The global mean surface air temperature anomaly at the end of the Pliocene simulation is 5.1 ∘C, which is the second highest of all models included in PlioMIP2 and is consistent with the fact that HadGEM3-GC31-LL has one of the highest Effective Climate Sensitivities of all CMIP6 models. Secondly, the comparison with previous generation models and with proxy data suggests a clear increase in global sea surface temperatures as the model has undergone development. Up to a certain level of warming, this results in a better agreement with available proxy data, and the “sweet spot” appears to be the previous CMIP5 generation of the model, HadGEM2-AO. The most recent simulation presented here, however, appears to show poorer agreement with the proxy data compared with HadGEM2 and may be overly sensitive to the Pliocene boundary conditions, resulting in a climate that is too warm. Thirdly, the comparison with other models from PlioMIP2 further supports this conclusion, with HadGEM3-GC31-LL being one of the warmest and wettest models in all of PlioMIP2, and if all the models are ordered according to agreement with proxy data, HadGEM3-GC31-LL ranks approximately halfway among them. A caveat to these results is the relatively short run length of the simulation, meaning the model is not in full equilibrium. Given the computational cost of the model it was not possible to run it for a longer period; a Gregory plot analysis indicates that had it been allowed to come to full equilibrium, the final global mean surface temperature could have been approximately 1.5 ∘C higher.

Description: The Maritime Continent (MC) forms the western boundary of the tropical Pacific Ocean, and relatively small changes in this region can impact the climate locally and remotely. In the mid-Piacenzian warm period of the Pliocene (mPWP; 3.264 to 3.025 Ma) atmospheric CO2 concentrations were ∼ 400 ppm, and the subaerial Sunda and Sahul shelves made the land–sea distribution of the MC different to today. Topographic changes and elevated levels of CO2, combined with other forcings, are therefore expected to have driven a substantial climate signal in the MC region at this time. By using the results from the Pliocene Model Intercomparison Project Phase 2 (PlioMIP2), we study the mean climatic features of the MC in the mPWP and changes in Indonesian Throughflow (ITF) with respect to the preindustrial. Results show a warmer and wetter mPWP climate of the MC and lower sea surface salinity in the surrounding ocean compared with the preindustrial. Furthermore, we quantify the volume transfer through the ITF; although the ITF may be expected to be hindered by the subaerial shelves, 10 out of 15 models show an increased volume transport compared with the preindustrial. In order to avoid undue influence from closely related models that are present in the PlioMIP2 ensemble, we introduce a new metric, the multi-cluster mean (MCM), which is based on cluster analysis of the individual models. We study the effect that the choice of MCM versus the more traditional analysis of multi-model mean (MMM) and individual models has on the discrepancy between model results and data. We find that models, which reproduce modern MC climate well, are not always good at simulating the mPWP climate anomaly of the MC. By comparing with individual models, the MMM and MCM reproduce the preindustrial sea surface temperature (SST) of the reanalysis better than most individual models and produce less discrepancy with reconstructed sea surface temperature anomalies (SSTA) than most individual models in the MC. In addition, the clusters reveal spatial signals that are not captured by the MMM, so that the MCM provides us with a new way to explore the results from model ensembles that include similar models.

Description: Despite increasing recognition of the need for more diverse and equitable representation in the sciences, it is unclear whether measurable progress has been made. Here, we examine trends in authorship in coral reef science from 1,677 articles published over the past 16 years (2003–2018) and find that while representation of authors that are women (from 18 to 33%) and from non-OECD nations (from 4 to 13%) have increased over time, progress is slow in achieving more equitable representation. For example, at the current rate, it would take over two decades for female representation to reach 50%. Given that there are more coral reef non-OECD countries, at the current rate, truly equitable representation of non-OECD countries would take even longer. OECD nations also continue to dominate authorship contributions in coral reef science (89%), in research conducted in both OECD (63%) and non-OECD nations (68%). We identify systemic issues that remain prevalent in coral reef science (i.e., parachute science, gender bias) that likely contribute to observed trends. We provide recommendations to address systemic biases in research to foster a more inclusive global science community. Adoption of these recommendations will lead to more creative, innovative, and impactful scientific approaches urgently needed for coral reefs and contribute to environmental justice efforts.

Description: 〈jats:p〉Modern pollen–vegetation–climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen–vegetation–climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended 〈jats:italic〉R〈/jats:italic〉-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), 〈jats:italic〉Larix〈/jats:italic〉, 〈jats:italic〉Betula〈/jats:italic〉, 〈jats:italic〉Picea〈/jats:italic〉, and 〈jats:italic〉Pinus〈/jats:italic〉 are overrepresented while 〈jats:italic〉Alnus〈/jats:italic〉, Cyperaceae, Poaceae, and 〈jats:italic〉Salix〈/jats:italic〉 are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation.〈/jats:p〉

Description: The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen–evergreen transition zone in Central Yakutia and the tundra–taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, https://doi.org/10.1594/PANGAEA.933263). The dataset includes structure-from-motion (SfM) point clouds and red–green–blue (RGB) and red–green–near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot. ii. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, https://doi.org/10.1594/PANGAEA.932821). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future. iii. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch (Larix gmelinii and Larix cajanderi) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, https://doi.org/10.1594/PANGAEA.932795). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species. iv. Dataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, https://doi.org/10.1594/PANGAEA.933268). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities. The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra–taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.

Description: Comparing temporal and spatial vegetation changes between reconstructions or between reconstructions and model simulations requires carefully selecting an appropriate evaluation metric. A common way of comparing reconstructed and simulated vegetation changes involves measuring the agreement between pollen- or model-derived unary vegetation estimates, such as the biome or plant functional type (PFT) with the highest affinity scores. While this approach based on summarising the vegetation signal into unary vegetation estimates performs well in general, it overlooks the details of the underlying vegetation structure. However, this underlying data structure can influence conclusions since minor variations in pollen percentages modify which biome or PFT has the highest affinity score (i.e. modify the unary vegetation estimate). To overcome this limitation, we propose using the Earth mover's distance (EMD) to quantify the mismatch between vegetation distributions such as biome or PFT affinity scores. The EMD circumvents the issue of summarising the data into unary biome or PFT estimates by considering the entire range of biome or PFT affinity scores to calculate a distance between the compared entities. In addition, each type of mismatch can be given a specific weight to account for case-specific ecological distances or, said differently, to account for the fact that reconstructing a temperate forest instead of a boreal forest is ecologically more coherent than reconstructing a temperate forest instead of a desert. We also introduce two EMD-based statistical tests that determine (1) if the similarity of two samples is significantly better than a random association given a particular context and (2) if the pairing between two datasets is better than might be expected by chance. To illustrate the potential and the advantages of the EMD as well as the tests in vegetation comparison studies, we reproduce different case studies based on previously published simulated and reconstructed biome changes for Europe and capitalise on the advantages of the EMD to refine the interpretations of past vegetation changes by highlighting that flickering unary estimates, which give an impression of high vegetation instability, can correspond to gradual vegetation changes with low EMD values between contiguous samples (case study 1). We also reproduce data-model comparisons for five specific time slices to identify those that are statistically more robust than a random agreement while accounting for the underlying vegetation structure of each pollen sample (case study 2). The EMD and the statistical tests are included in the paleotools R package (https://github.com/mchevalier2/paleotools, last access: 3 May 2023).

Description: Traditional morphological methods for species identification are highly time consuming, especially for small organisms, such as Foraminifera, a group of shell-building microbial eukaryotes. To analyze large amounts of samples more efficiently, species identification methods have extended to molecular tools in the last few decades. Although a wide range of phyla have good markers available, for Foraminifera only one hypervariable marker from the ribosomal region (18S) is widely used. Recently a new mitochondrial marker cytochrome oxidase subunit 1 (COI) has been sequenced. Here we investigate whether this marker has a higher potential for species identification compared to the ribosomal marker. We explore the genetic variability of both the 18S and COI markers in 22 benthic foraminiferal morphospecies (orders Miliolida and Rotaliida). Using single-cell DNA, the genetic variability within specimens (intra) and between specimens (inter) of each species was assessed using next-generation sequencing. Amplification success rate was twice as high for COI (151/200 specimens) than for 18S (73/200 specimens). The COI marker showed greatly decreased intra- and inter-specimen variability compared to 18S in six out of seven selected species. The 18S phylogenetic reconstruction fails to adequately cluster multiple species together in contrast to COI. Additionally, the COI marker helped recognize misclassified specimens difficult to morphologically identify to the species level. Integrative taxonomy, combining morphological and molecular characteristics, provides a robust picture of the foraminiferal species diversity. Finally, we suggest the use of a set of sequences (two or more) to describe species showing intra-genomic variability additionally to using multiple markers. Our findings highlight the potential of the newly discovered mitochondrial marker for molecular species identification and metabarcoding purposes.

Description: Lots of creatures live in coral reefs, including some tiny ones you might never have heard of. In this article, we will tell you about the importance of Foraminifera (also called forams), unicellular organisms with shells, that contribute to coral reefs in many ways. Just like corals, some forams living on the seafloor live closely together with microalgae. Some forams also thrive in similar environmental conditions (sunlight, temperature, salt) as corals. For this reason, forams can be used as reef “sensors”, to keep track of the overall health of coral reefs. They can even help to detect poor environmental conditions that might harm coral growth in the future. In this article, we will look at a study of an Indonesian reef ecosystem in which the foram communities living on the seafloor were monitored between 1997 and 2018.