ALBERT

Description: This julia package implements various tools for working with simple, non-marked, one dimensional point processes. In special it implements a bootstrap-based goodness-of-fit test for parametric models.

Description: To better understand possible reasons for the diverse modeling results and large discrepancies of the detected solar fingerprints, we took one step back and assessed the "initial" solar signals in the middle atmosphere based on large ensemble simulations with multiple climate models — FOCI, EMAC, and MPI-ESM-HR. Consistent with previous work, we find that the 11-year solar cycle signals in the short wave heating rate (SWHR) and ozone anomalies are robust and statistically significant in all three models. These "initial" solar cycle signals in SWHR, ozone, and temperature anomalies are sensitive to the strength of the solar forcing. Correlation coefficients of the solar cycle with the SWHR, ozone, and temperature anomalies linearly increase along with the enhancement of the solar cycle amplitude, and this reliance becomes more complex when the solar cycle amplitude exceeds a certain threshold. In addition, the cold bias in the tropical stratopause of EMAC dampens the subsequent results of the "initial" solar signal. The warm pole bias in MPI-ESM-HR leads to a weak polar night jet (PNJ), which may limit the top-down propagation of the initial solar signal. Although FOCI simulated a so-called top-down response as revealed in previous studies in a period with large solar cycle amplitudes, its warm bias in the tropical upper stratosphere results in a positive bias in PNJ and can lead to a "reversed" response in some extreme cases. We suggest a careful interpretation of the single model result and further re-examination of the solar signal based on more climate models.

Description: The mesopelagic or ocean twilight zone (OTZ) in the ocean contains huge numbers of fish in a relatively pristine environment and may therefore attract interest as a commercial fishery. In this study we evaluate in economic terms, the likely trade-offs between the different services provided by the mesopelagic layer in the Bay of Biscay and the societal benefits of its commercial exploitation. Benefits arise mainly from the likely use of this group of species as raw material for producing fishmeal and fish oil. Costs are derived from the loss in climate regulating and cultural, services, but also from the loss in the provisioning service of other commercial species. To do so we compare the current non-exploited status with a situation in where mesopelagic fishes are harvested at levels capable of producing the Maximum Sustainable Yield. Results suggest that if mesopelagic fishes are harvested, a mean value of 1.2 million Euro loss in a year will be created in the Bay of Biscay, although in a range between 42 million Euro loss and 48 Euro million benefits. This uncertainty comes, mainly, from the limited existing knowledge of the mesopelagic fishes’ biomass but also from the uncertainty on the biomass of the rest of the species of the studied ecosystem. The large range indicates that a better understanding of the mesopelagic ecosystem is needed, however, results also show that ecosystem services under no exploitation provided by the OTZ could be more valuable than the fishmeal and fish oil that potentially could be obtained from the fishes harvested in this sea layer.

Description: In the framework of a changing climate, it is useful to devise methods capable of effectively assessing and monitoring the changing landscape of air-sea CO2 fluxes. In this study, we developed an integrated machine learning tool to objectively classify and track marine carbon biomes under seasonally and interannually changing environmental conditions. The tool was applied to the monthly output of a global ocean biogeochemistry model at 0.25° resolution run under atmospheric forcing for the period 1958–2018. Carbon biomes are defined as regions having consistent relations between surface CO2 fugacity (fCO2) and its main drivers (temperature, dissolved inorganic carbon, alkalinity). We detected carbon biomes by using an agglomerative hierarchical clustering (HC) methodology applied to spatial target-driver relationships, whereby a novel adaptive approach to cut the HC dendrogram based on the compactness and similarity of the clusters was employed. Based only on the spatial variability of the target-driver relationships and with no prior knowledge on the cluster location, we were able to detect well-defined and geographically meaningful carbon biomes. A deep learning model was constructed to track the seasonal and interannual evolution of the carbon biomes, wherein a feed-forward neural network was trained to assign labels to detected biomes. We find that the area covered by the carbon biomes responds robustly to seasonal variations in environmental conditions. A seasonal alternation between different biomes is observed over the North Atlantic and Southern Ocean. Long-term trends in biome coverage over the 1958–2018 period, namely a 10 % expansion of the subtropical biome in the North Atlantic and a 10 % expansion of the subpolar biome in the Southern Ocean, are suggestive of long-term climate shifts. Our approach thus provides a framework that can facilitate the monitoring of the impacts of climate change on the ocean carbon cycle and the evaluation of carbon cycle projections across Earth System Models.

Description: Tropical sea surface temperature (SST) biases can cause atmospheric biases on global scales, hence SST needs to be represented well in climate models. A major source of uncertainties is the representation of turbulent mixing in the oceanic boundary layer, or mixed layer (ML). In the present study we focus on near-inertial wave (NIW) induced mixing. The performance of two mixing schemes, Turbulent Kinetic Energy and K-profile parameterization (KPP), is assessed at two sites (11.5°N, 23°W and 15°N, 38°W) in the tropical Atlantic. At 11.5°N, turbulence observations (eddy diffusivities, shear and stratification) are available for comparison. We find that the schemes differ in their representation of NIWs, but both under-represent the observed enhanced diffusivities below the observed ML. However, we find that the models do mix below the ML at 15°N when a storm passes nearby. The near-inertial oscillations remain below the ML for the following 10 days. Near-inertial kinetic energy (NIKE) biases in the models are not directly correlated with the wind speed, the MLD biases, or the stratification at the ML base. Instead, NIKE biases are sensitive to the vertical mixing scheme parameterization. NIKE biases are lowest when the KPP scheme is used. Key Points: - Observations of inertial oscillations are used to evaluate the performance of two vertical mixing schemes in two high-resolution models - Both the K-profile parameterization and the Turbulent Kinetic Energy closure underestimate the NIW-induced mixing - Near-inertial kinetic energy biases are sensitive to the vertical mixing parameterization

Description: Turbulent mixing in the ocean, lakes and reservoirs facilitates the transport of momentum, heat, nutrients, and other passive tracers. Turbulent fluxes are proportional to the rate of turbulent kinetic energy dissipation per unit mass, ε. A common method for ε measurements is using microstructure profilers with shear probes. Such measurements are now widespread, and a non-expert practitioner will benefit from best practice guidelines and benchmark datasets. As a part of the Scientific Committee on Oceanographic Research (SCOR) working group on “Analysing ocean turbulence observations to quantify mixing” (ATOMIX), we compiled a collection of five benchmark data of ε from measurements of turbulence shear using shear probes. The datasets are processed using the ATOMIX recommendations for best practices documented separately. Here, we describe and validate the datasets. The benchmark collection is from different types of instruments and covers a wide range of environmental conditions. These datasets serve to guide the users to test their ε estimation methods and quality-assurance metrics, and to standardize their data for archiving.

Description: Sea spray aerosols (SSA) greatly affect the climate system by scattering solar radiation and acting as seeds for cloud droplet formation. The ecosystems in the Arctic Ocean are rapidly changing due to global warming, and the effects these changes have on the generation of SSA, and thereby clouds and fog formation in this region, are unknown. During the ship-based Arctic Century Expedition, we examined the dependency of forced SSA production on the biogeochemical characteristics of seawater using an on-board temperature-controlled aerosol generation chamber with a plunging jet system. Our results indicate that mainly seawater salinity and organic content influence the production and size distribution of SSA. However, we observed a 2-fold higher SSA production from waters with similar salinity collected north of 81°N compared to samples collected south of this latitude. This variability was not explained by phytoplankton and bacterial abundances or Chlorophyll-a concentration but by the presence of glucose in seawater. The synergic action of sea salt (essential component) and glucose or glucose-rich saccharides (enhancer) accounts for 〉80% of SSA predictability throughout the cruise. Our results suggest that besides wind speed and salinity, SSA production in Arctic waters is also affected by specific organics released by the microbiota.

Description: The spreading of crushed olivine-rich rocks in coastal seas to accelerate weathering reactions sequesters atmospheric CO2 and reduces atmospheric CO2 concentrations. Their weathering rates depend on different factors, including temperature and the reaction surface area. Therefore, this study investigates the variations in olivine-based enhanced weathering rates across 13 regional coasts worldwide. In addition, it assesses the CO2 sequestration within 100 years and evaluates the maximum net-sequestration potential based on varying environmental conditions. Simulations were conducted using the geochemical thermodynamic equilibrium modeling software PHREEQC. A sensitivity analysis was performed, exploring various combinations of influencing parameters, including grain size, seawater temperature, and chemistry. The findings reveal significant variation in CO2 sequestration, ranging from 0.13 to 0.94 metric tons (t) of CO2 per ton of distributed olivine-rich rocks over 100 years. Warmer coastal regions exhibit higher CO2 sequestration capacities than temperate regions, with a difference of 0.4 t CO2/t olivine distributed. Sensitivity analysis shows that smaller grain sizes (10 µm) exhibit higher net CO2 sequestration rates (0.87 t/t) in olivine-based enhanced weathering across all conditions, attributed to their larger reactive surface area. However, in warmer seawater temperatures, olivine with slightly larger grain sizes (50 and 100 µm) displays still larger net CO2 sequestration rates (0.97 and 0.92 t/t), optimizing the efficiency of CO2 sequestration while reducing grinding energy requirements. While relying on a simplified sensitivity analysis that does not capture the full complexity of real-world environmental dynamics, this study contributes to understanding the variability and optimization of enhanced weathering for CO2 sequestration, supporting its potential as a sustainable CO2 removal strategy.

Description: Enhancing ocean productivity by artificial upwelling is evaluated as a nature-based solution for food security and climate change mitigation. Fish production is intended through diatom-based plankton food webs as these are assumed to be short and efficient. However, our findings from mesocosm experiments on artificial upwelling in the oligotrophic ocean disagree with this classical food web model. Here, diatoms did not reduce trophic length and instead impaired the transfer of primary production to crustacean grazers and small pelagic fish. The diatom-driven decrease in trophic efficiency was likely mediated by changes in nutritional value for the copepod grazers. Whilst diatoms benefitted the availability of essential fatty acids, they also caused unfavorable elemental compositions via high carbon-to-nitrogen ratios (i.e. low protein content) to which the grazers were unable to adapt. This nutritional imbalance for grazers was most pronounced in systems optimized for CO 2 uptake through carbon-to-nitrogen ratios well beyond Redfield. A simultaneous enhancement of fisheries production and carbon sequestration via artificial upwelling may thus be difficult to achieve given their opposing stoichiometric constraints. Our study suggest that food quality can be more critical than quantity to maximize food web productivity during shorter-term fertilization of the oligotrophic ocean.