ALBERT

Description: Phytoplankton form the base of the marine food web by transforming CO2 into organic carbon via photosynthesis. Despite the importance of phytoplankton for marine ecosystems and global carbon cycling, projections of phytoplankton biomass in response to climate change differ strongly across Earth system models, illustrating uncertainty in our understanding of the underlying processes. Differences are especially large in the Southern Ocean, a region that is notoriously difficult to represent in models. Here, we argue that total (depth-integrated) phytoplankton biomass in the Southern Ocean is projected to largely remain unchanged under climate change by the Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model ensemble because of a shifting balance of bottom-up and top-down processes driven by a shoaling mixed-layer depth. A shallower mixed layer is projected on average to improve growth conditions, consequently weaken bottom-up control, and confine phytoplankton closer to the surface. An increase in the phytoplankton concentration promotes zooplankton grazing efficiency, thus intensifying top-down control. However, large differences across the model ensemble exist, with some models simulating a decrease in surface phytoplankton concentrations. To reduce uncertainties in projections of surface phytoplankton concentrations, we employ an emergent constraint approach using the observed sensitivity of surface chlorophyll concentration, taken as an observable proxy for phytoplankton, to seasonal changes in the mixed-layer depth as an indicator for future changes in surface phytoplankton concentrations. The emergent constraint reduces uncertainties in surface phytoplankton concentration projections by around one-third and increases confidence that surface phytoplankton concentrations will indeed rise due to shoaling mixed layers under global warming, thus favouring intensified top-down control. Overall, our results suggest that while changes in bottom-up conditions stimulate enhanced growth, intensified top-down control opposes an increase in phytoplankton and becomes increasingly important for the phytoplankton response to climate change in the Southern Ocean.

Description: Events of extreme precipitation pose a hazard to many parts of Europe but are typically not well represented in climate models. Here, we evaluate daily extreme precipitation over Europe during 1982–2019 in observations (GPCC), reanalysis (ERA5) and a set of atmosphere-only simulations at low- (100 km), medium- (50 km) and high- (25 km) horizontal resolution with identical vertical resolutions using OpenIFS (version 43r3). We find that both OpenIFS simulations and reanalysis underestimate the rates of extreme precipitation compared to observations. The biases are largest for the lowest resolution (100 km) and decrease with increasing horizontal resolution (50 and 25 km) simulations in all seasons. The sensitivity to horizontal resolution is particularly high in mountain regions (such as the Alps, Scandinavia, Iberian Peninsula), likely linked to the sensitivity of vertical velocity to the representation of topography. The sensitivity of precipitation to model resolution increases dramatically with increasing percentiles, with modest biases in the 70th–80thpercentile range and large biases above the 99th percentile range. We also find that precipitation above the 99th percentile mostly consists of large-scale precipitation (~80 %) in winter, while in summer it is mostly large-scale precipitation in Northern Europe (~70 %) and convective precipitation in Southern Europe (~70 %). Compared to ERA5, the OpenIFS overestimates large-scale precipitation extremes in winter, but underestimates in summer. The discrepancy between OpenIFS and ERA5 decreases with increasing horizontal resolutions. We also examine the sensitivity of extreme precipitation to model time step and find that the convective contribution to extreme precipitation is more sensitive to the model time step than the horizontal resolution. This is likely due to the sensitivity of convective activity to model time step. On the other hand, the large-scale contribution to extreme precipitation is more sensitive to horizontal resolution than the model time step, which may be due to sharper fronts and steeper topography at higher horizontal resolution.

Description: Weather causes extremes in photovoltaic and wind power production. Here we present a comprehensive climatology of anomalies in photovoltaic and wind power production associated with weather patterns in Europe considering the 2019 and potential 2050 installations, and hourly to ten-day events. To that end, we performed kilometer-scale numerical simulations of hourly power production for 23 years and paired the output with a weather classification which allows a detailed assessment of weather-driven spatio-temporal production anomalies. Our results highlight the dependency of low-power production events on the installed capacities and the event duration. South-shifted Westerlies (Anticyclonic South-Easterlies) are associated with the lowest hourly (ten-day) extremes for the 2050 (both) installations. Regional power production anomalies can differ from the ones in the European mean. Our findings suggest that weather patterns can serve as indicators for expected photovoltaic and wind power production anomalies and may be useful for early warnings in the energy sector.

Description: The Peruvian Upwelling System hosts an extremely high productive marine ecosystem. Observations show that the Peruvian Upwelling System is the only Eastern Boundary Upwelling Systems (EBUS) with an out-of-phase relationship of seasonal surface chlorophyll concentrations and upwelling intensity. This "seasonal paradox" triggers the questions: (1) what is the uniqueness of the Peruvian Upwelling System compared with other EBUS that leads to the out of phase relationship; (2) how does this uniqueness lead to low phytoplankton biomass in austral winter despite strong upwelling and ample nutrients? Using observational climatologies for four EBUS we diagnose that the Peruvian Upwelling System is unique in that intense upwelling coincides with deep mixed layers. We then apply a coupled regional ocean circulation-biogeochemical model (CROCO-BioEBUS) to assess how the interplay between mixed layer and upwelling is regulating the seasonality of surface chlorophyll in the Peruvian Upwelling System. The model recreates the "seasonal paradox" within 200 km off the Peruvian coast. We confirm previous findings that deep mixed layers, which cause vertical dilution and stronger light limitation, mostly drive the diametrical seasonality of chlorophyll relative to upwelling. In contrast to previous studies, reduced phytoplankton growth due to enhanced upwelling of cold waters and lateral advection are second-order drivers of low surface chlorophyll concentrations. This impact of deep mixed layers and upwelling propagates up the ecosystem, from primary production to export efficiency. Our findings emphasize the crucial role of the interplay of the mixed layer and upwelling and suggest that surface chlorophyll may increase along with a weakened seasonal paradox in response to shoaling mixed layers under climate change.

Description: Marine sponges and other sessile macro-organisms were collected at a shallow water hydrothermal site in Eyjafjörður, Iceland. Bacteria were isolated from the organisms using selective media for actinomycetes, and the isolates were screened for antimicrobial activity. A total of 111 isolates revealed antimicrobial activity displaying different antimicrobial patterns which indicates production of various compounds. Known test strains were grown in the presence of ethyl acetate extracts from one selected isolate, and a clear growth inhibition of Staphylococcus aureus was observed down to 0.1 % extract concentration in the medium. Identification of isolates shows different species of Actinobacteria with Streptomyces sp. playing the largest role, but also members of Bacilli, Alphaproteobacteria and Gammaproteobacteria. Sponges have an excellent record regarding production of bioactive compounds, often involving microbial symbionts. At the hydrothermal vents, however, the majority of active isolates originated from other invertebrates such as sea anemones or algae. The results indicate that antimicrobial assays involving isolates in full growth can detect activity not visible by other methods. The macro-organisms inhabiting the Eyjafjörður hydrothermal vent area host diverse microbial species in the phylum Actinobacteria with antimicrobial activity, and the compounds responsible for the activity will be subject to further research.

Description: The University of Victoria Earth system climate model of intermediate complexity has been a useful tool in recent assessments of long-term climate changes including paleo-climate modelling. Since the last official release of the UVic ESCM 2.9, and the two official updates during the last decade, a lot of model development has taken place in multiple groups. The new version 2.10 of the University of Victoria Earth System Climate Model (UVic ESCM), to be used in the 6th phase of the coupled model intercomparison project (CMIP6), presented here combines and brings together multiple model developments and new components that have taken place since the last official release of the model. To set the foundation of its use, we here describe the UVic ESCM 2.10 and evaluate results from transient historical simulations against observational data. We find that the UVic ESCM 2.10 is capable of reproducing well changes in historical temperature and carbon fluxes, as well as the spatial distribution of many ocean tracers, including temperature, salinity, phosphate and nitrate. This is connected to a good representation of ocean physical properties. For the moment, there remain biases in ocean alkalinity and dissolved inorganic carbon, which will be addressed in the next updates to the model.

Description: Animals have a deep evolutionary relationship with microbial symbionts, such that individual microbes or an entire microbial community can diverge alongside the host. Here, we explore these host-microbe relationships in Echinometra, a sea urchin genus that speciated with the Isthmus of Panama and throughout the Indo-West Pacific. We find that the eggs from five Echinometra species generally associate with a species-specific bacterial community and that the relatedness of these communities is largely congruent with host phylogeny. Microbiome divergence per million years was higher in more recent speciation events than in older ones. We, however, did not find any bacterial groups that displayed co-phylogeny with Echinometra. Together, these findings suggest that the evolutionary relationship between Echinometra and their microbiota operates at the community level. We find no evidence suggesting that the associated microbiota is the evolutionary driver of Echinometra speciation. Instead, divergence between Echinometra and their microbiota is likely the byproduct of ecological, geographic, and reproductive isolations.

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: 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.