"Wissenschaft fürs Wohnzimmer" – two years of interactive, scientific livestreams weekly on YouTube

Science communication is becoming increasingly important to connect academia and society, and to counteract fake news among climate change deniers. Online video platforms, such as YouTube, offer great potential for low-threshold communication of scientific knowledge to the general public. In April 2020 a diverse group of researchers from the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research launched the YouTube channel "Wissenschaft fürs Wohnzimmer" (translated to "Sitting Room Science") to stream scientific talks about climate change and biodiversity every Thursday evening. Here we report on the numbers and diversity of content, viewers, and presenters from 2 years and 100 episodes of weekly livestreams. Presented topics encompass all areas of polar research, social issues related to climate change, and new technologies to deal with the changing world and climate ahead. We show that constant engagement by a group of co-hosts, and presenters from all topics, career stages, and genders enable a continuous growth of views and subscriptions, i.e. impact. After 783 days the channel gained 30,251 views and 828 subscribers and hosted well-known scientists while enabling especially early career researchers to improve their outreach and media skills. We show that interactive and science-related videos, both live and on-demand, within a pleasant atmosphere, can be produced voluntarily while maintaining high quality. We further discuss challenges and possible improvements for the future. Our experiences may help other researchers to conduct meaningful scientific outreach and to push borders of existing formats with the overall aim of developing a better understanding of climate change and our planet

Consistency and Challenges in the Ocean Carbon Sink Estimate for the Global Carbon Budget

Based on the 2019 assessment of the Global Carbon Project, the ocean took up on average, 2.5 ± 0.6 PgC yr−1 or 23 ± 5% of the total anthropogenic CO2 emissions over the decade 2009–2018. This sink estimate is based on simulation results from global ocean biogeochemical models (GOBMs) and is compared to data-products based on observations of surface ocean pCO2 (partial pressure of CO2) accounting for the outgassing of river-derived CO2. Here we evaluate the GOBM simulations by comparing the simulated surface ocean pCO2 to observations. Based on this comparison, the simulations are well-suited for quantifying the global ocean carbon sink on the time-scale of the annual mean and its multi-decadal trend (RMSE <20 μatm), as well as on the time-scale of multi-year variability (RMSE <10 μatm), despite the large model-data mismatch on the seasonal time-scale (RMSE of 20–80 μatm). Biases in GOBMs have a small effect on the global mean ocean sink (0.05 PgC yr−1), but need to be addressed to improve the regional budgets and model-data comparison. Accounting for non-mapped areas in the data-products reduces their spread as measured by the standard deviation by a third. There is growing evidence and consistency among methods with regard to the patterns of the multi-year variability of the ocean carbon sink, with a global stagnation in the 1990s and an extra-tropical strengthening in the 2000s. GOBMs and data-products point consistently to a shift from a tropical CO2 source to a CO2 sink in recent years. On average, the GOBMs reveal less variations in the sink than the data-based products. Despite the reasonable simulation of surface ocean pCO2 by the GOBMs, there are discrepancies between the resulting sink estimate from GOBMs and data-products. These discrepancies are within the uncertainty of the river flux adjustment, increase over time, and largely stem from the Southern Ocean. Progress in our understanding of the global ocean carbon sink necessitates significant advancement in modeling and observing the Southern Ocean carbon sink including (i) a game-changing increase in high-quality pCO2 observations, and (ii) a critical re-evaluation of the regional river flux adjustment

Changes in spectral quality of underwater light alter phytoplankton community composition

Light is a fundamental resource for phytoplankton. To utilize the available light, most phytoplankton species possess pigments in taxon‐specific combinations and quantities, which in turn result in a specific use of certain wavelengths. This optimizes the light use efficiency, allows for a complementary use of light, and may be an additional driver for community structure. While the effects of light intensity on phytoplankton biomass production and community composition have been intensively studied, here we focused on the effects of specific light spectrum quality (thus light color) on a natural phytoplankton community. In a controlled mesocosm experiment we reduced the supplied wavelength range to its blue, green, or red part of the light spectrum and compared the responses of each treatment to a full spectrum control over 28 d. Highest community growth rates were observed under blue, lowest under red light. Light absorption by the communities showed adaptation toward the supplied wavelength range. Community composition was significantly affected by light quality treatments, driven by Bacillariophyta and Chlorophyta, whereas pigment composition was not. Furthermore, lower species richness but higher evenness occurred when communities were exposed to red light compared to the full spectrum. We expected the response of phytoplankton communities to changes in the light spectrum to be driven by a combination of species sorting and pigment acclimation; however, the effect of species sorting turned out to be stronger. Our study showed that, even if species might acclimate, changes in the available light spectrum affect primary production and phytoplankton community composition

Ocean-atmosphere CO2 fluxes: Simulations with the ocean-ecosystem model FESOM2.1-REcoM2

Being a vast carbon pool, ocean is an important component of the climate system. It absorbs not only the heat trapped by the greenhouse gasses in the atmosphere, but also a quarter of the anthropogenic carbon dioxide (CO2) emissions itself. Ocean carbon uptake, however, decreases the pH in seawater that has negative implications for marine life. Despite the progress over the last decades, observational data is still sparse in the global oceans. Moreover, there are still gaps in understanding key processes and relevant feedbacks of global ocean carbon source/sink in response to atmospheric CO2 scenarios. Marine biogeochemical models are helpful tools to bridge these gaps. In this study we coupled the Finite-volumE Sea ice-Ocean Model (FESOM2.1) to the Regulated Ecosystem Model (REcoM2). Compared to the previous version FESOM1.4-REcoM2, the model utilizes a new dynamical core based on a finite volume discretization instead of finite elements, but retains the biogeochemical part. Mocsy2.0 computes carbonate chemistry including water vapor correction. It operates on variable mesh resolution. Unlike standard structured-mesh ocean models, the mesh flexibility allows for a realistic representation of small-scale dynamics in key regions at affordable computational cost. Here we present an assessment of the ocean and biogeochemical states simulated with FESOM2.1-REcoM2 in a relatively low spatial resolution global configuration forced with JRA55-do atmospheric reanalysis. A bias present in the previous model version FESOM1.4-REcoM2 in annual mean global ocean-atmosphere CO2 flux can be significantly reduced. Besides, the computational efficiency is about 2-3 times higher than FESOM1.4-REcoM2. Thus, the new coupled model is a promising tool for ocean biogeochemical modelling applications

Evaluation of air-sea CO2 fluxes in the ocean-ecosystem model FESOM-REcoM and in the Global Carbon Budget Models

We assessed air-sea CO2 fluxes in the ocean circulation ecosystem model FESOM-REcoM. FESOM is a finite element sea ice-ocean model, with a variable resolution ocean mesh. The mesh used here has a nominal resolution of 150 km in the open ocean and reaches 25 km in the tropics and in the Arctic region. While FESOM-REcoM has previously been used to study biogeochemical cycles and physics-ecosystem interactions, we have now evaluated the air-sea CO2 exchange in a preindustrial control simulation and in a historical simulation with varying climate and increasing atmospheric CO2 concentrations. We evaluate the total annual CO2 uptake and its regional distribution of the historical run and compare modelled pCO2 to observed pCO2 from the SOCAT data-base. The relative interannual variability mismatch and RMSE are similar to that calculated with the same biogeochemical model coupled to the MITgcm ocean circulation model. These numbers and further metrics for model evaluation e.g. natural CO2 fluxes, mismatch time-series, seasonal cycle are set into context by providing the same evaluation for the Global Carbon Budget (GCB) Models. This closes a gap, as these estimates of the ocean carbon sink are used in the community, but their performance has not been documented in detail. We’ll further present methodological updates to the ocean carbon sink estimate in the latest GCB release

Marine carbohydrates in Arctic aerosol particles and fog – diversity of oceanic sources and atmospheric transformations

Carbohydrates, originating from marine microorganisms, enter the atmosphere as part of sea spray aerosol (SSA) and can influence fog and cloud microphysics as cloud condensation nuclei (CCN) or icenucleating particles (INP). Particularly in the remote Arctic region, significant knowledge gaps persist about the sources, the sea-to-air transfer mechanisms, atmospheric concentrations, and processing of this substantial organic group. In this ship-based field study conducted from May to July 2017 in the Fram Strait, Barents Sea, and central Arctic Ocean, we investigated the sea-to-air transfer of marine combined carbohydrates (CCHO) from concerted measurements of the bulk seawater, the sea surface microlayer (SML), aerosol particles and fog. Our results reveal a wide range of CCHO concentrations in seawater (22–1070 μg L-1), with notable variations among different sea-ice-related sea surface compartments. Enrichment factors in the sea surface microlayer (SML) relative to bulk water exhibited variability in both dissolved (0.4–16) and particulate (0.4–49) phases, with the highest values in the marginal ice zone (MIZ) and aged melt ponds. In the atmosphere, CCHO was detected in super- and submicron aerosol particles (CCHOaer;super: 0.07–2.1 ngm-3; CCHOaer;sub: 0.26–4.4 ngm-3) and fog water (CCHOfog;liquid: 18–22 000 μg L-1; CCHOfog;atmos: 3–4300 ngm-3). Enrichment factors for sea–air transfer varied based on assumed oceanic emission sources. Furthermore, we observed rapid atmospheric aging of CCHO, indicating both biological/enzymatic processes and abiotic degradation. This study highlights the diverse marine emission sources in the Arctic Ocean and the atmospheric processes shaping the chemical composition of aerosol particles and fog

Dissolved and particulate combined carbohydrates, pH, inorganic ions, CDOM and particulate absorption of SML and bulk water in Arctic surface seawater and melt ponds

Arctic sea surface microlayer (SML) and bulk water samples were collected during the PASCAL campaign in the Fram Strait, Barents Sea and central Arctic Ocean on board the German icebreaker RV Polarstern from May until July 2017. SML samples were collected using the glass plate technique, corresponding bulk (subsurface) samples were collected at a defined depth of of 1 m, or at the bottoms of some closed melt ponds, using the telescopic rod method. Following types of water samples were diffentiated: ice-free ocean, leads/polynyas within the pack ice, the marginal ice zone (MIZ) and melt ponds. Following chemical parameters were determined: dissolved combined carbohydrates (DCCHO), particulate combined carbohydrates (PCCHO), pH, sodium, chloride, CDOM and particulate absorption. DCCHO concentrations were measured from filtered (0.2 µm) seawater after a desalination using electro-dialysis and high-performance anion exchange chromatography coupled with pulsed amperometric detection (HPAEC-PAD). PCCHO concentrations were measured from filters (0.2 µm polycarbonate membrane). DCCHO and PCCHO were determined as the sum of individual monosaccharides (e.g. arabinose, glucose, galactose, glucosamine, galactosamine, muramic acid, galacturonic acid, etc.). These data were collected to improve the understanding of the sea-air transfer of carbohydrates in this pristine environment. This data set is complimentary to previous measurements of the same samples published under following doi numbers: https://doi.org/10.1594/PANGAEA.899258 & https://doi.org/10.1594/PANGAEA.89928

Modeling marine biogenic aerosol precursors in the Arctic Ocean

The climate radiative effect of Arctic clouds depends on the presence of liquid or ice as cloud phase, which, among other things, is determined by the abundance of aerosols acting as cloud condensation or ice nuclei. Biogenic aerosols originate from local phytoplankton production in leads or open water. Based on recent publications, we choose acidic polysaccharides (PCHO) and transparent exopolymer particles (TEP) as tracers for biogenic aerosol precursors in the upper ocean layer. We incorporate processes of algal PCHO excretion, PCHO aggregation into TEP, as well as TEP degradation into the ecosystem model REcoM2 coupled to the finite-volume sea ice ocean circulation model FESOM2 with a resolution up to 4 km in the Arctic realm. REcoM2 describes the biogeochemical processes with two functional phytoplankton and one zooplankton class. Especially the ascending and enrichment of TEP to the surface microlayer, but also sinking of larger aggregates, are processes, which will be considered for model improvement. We are aiming at reproducing TEP distribution and seasonality patterns in the Arctic Ocean over two decades. Evaluation of the model results will be done using in-situ measurements (FRAM, MOSAiC). Ultimately, the modeled aerosol precursors will be used as an important input in an accompanied project, in which the net aerosol radiative effects will be quantified with an atmospheric aerosol-climate model. This work is part of the DFG TR 172 Arctic Amplification

High-resolution modelling of marine biogenic aerosol precursors in the Arctic realm

The presence of liquid or ice as cloud phase determines the climate radiative effect of Arctic clouds, and thus, their contribution to surface warming. Biogenic aerosols from phytoplankton production localized in leads or open water were shown to act as cloud condensation nuclei (liquid phase) or ice nuclei (ice phase) in remote regions. As extensive measurements of biogenic aerosol precursors are still scarce, we conduct a modelling study and use acidic polysaccharides (PCHO) and transparent exopolymer particles (TEP) as tracers. In this study, we integrate processes of algal PCHO excretion during phytoplankton growth or under nutrient limitation and processes of TEP formation, aggregation and also remineralization into the ecosystem model REcoM2. The biogeochemical processes are described by two functional phytoplankton and two zooplankton classes, along with sinking detritus and several (in)organic carbon and nutrient classes. REcoM2 is coupled to the finite-volume sea ice ocean circulation model FESOM2 with a high resolution of up to 4.5 km in the Arctic. We will present the first results of simulated TEP distribution and seasonality patterns at pan-Arctic scale over the last decades. We will elucidate drivers of the seasonal cycle and will identify regional hotspots of TEP production and its decay. We will also address possible impacts of global warming and Arctic amplification of the last decades in our evaluation, as we expect a strong effect of global warming on microbial metabolic rates, phytoplankton growth, and composition of phytoplankton functional types. The results will be evaluated by comparison to a set of in-situ measurements (PASCAL, FRAM, MOSAiC). It is further planned that an atmospheric aerosol-climate model will build on the modeled biogenic aerosol precursors as input to quantify the net aerosol radiative effects. This work is part of the DFG TR 172 Arctic Amplification