bluuebunny/crossref_metadata_2025 huggingface dataset:
Impacts of Climate Change on Desert Dunes
Authors: Delobel Lucie , Baas Andreas
Published: March 2022

Desert dunes and sand seas cover approximately 20% of the world’s arid zones, and their morphology and patterning are an important diagnostic of environmental surface conditions not only on Earth but also on other planetary bodies.

Encroachment of moving dunes can pose significant threats to transportation infrastructure, agriculture, industry, and settlements. Migrating sand dunes can be agents of desertification and they play an important role in dust emissions into the atmosphere at globally significant dust sources. Understanding potential future changes in desert dune morphology, mobility, and migration direction due to changes in wind climate therefore has a range of important socio-economic ramifications. Changing wind climate also plays a key role in the potential expansion of dune fields and sand seas, as well as reactivation of currently dormant fields.

In this study we analyse wind data from CMIP6 climate simulations in the context of Drift Potential (DP) to determine projected changes, by the end of this century, in sand-moving wind regime parameters in the world’s arid zones under the high-emission scenario. We interpret the projected changes in different desert regions around the globe to infer potential increases as well as decreases in dune field activity, shifts in migration direction of mobile sand dunes, changes in dune shapes and pattern, and impacts on currently dormant dune fields.
The frictional layer in the observed momentum budget of the trades
Authors: Nuijens Louise , Savazzi Alessandro , de Boer Gijs , Brilouet Pierre-Etienne , Lothon Marie , George Geet , Zhang Dongxiao
Published: March 2022

Profiles of eddy momentum flux divergence are calculated as the residual in the momentum budget constructed from from airborne circular dropsonde arrays (~ 220 km) for thirteen days during the EUREC4A/ATOMIC field study east of Barbados. The observed dynamical forcing averaged over all flight days agrees broadly with ECMWF IFS forecasts. They suggest a flux divergence, or friction on the mean flow, over a 1.5 km deep layer in the prevailing wind direction. Assuming only vertical flux divergence that is zero near a local wind maximum, the observed friction corresponds to a 10 m momentum flux of ~ 0.1 Nm-2, comparable to in-situ turbulence measurements by a Saildrone. Between 1 - 1.5 km the momentum flux divergence is counter-gradient and vertical wind shear exceeds the observed thermal wind. An averaged momentum flux divergence in the cross-wind direction is also observed and corresponds to a veering of the wind that promotes flow parallel to the isobars. 

The along- and cross-wind flux divergence differ substantially between days, whereby a number of flights capture ascending branches of shallow circulations where only weak flux divergence near the surface is found and flux convergence (an acceleration of the mean flow) in the cloud and inversion layer. Budget-derived and in-situ measured momentum fluxes disagree on individual days. Turbulence measurements on board the SAFIRE ATR-42 (ATR) aircraft and the UAV CU RAAVEN reveal pronounced spatial variability (5 - 60 km) of momentum flux, which suggests that convectively-driven (mesoscale) flows can compensate turbulence-induced friction within the dropsonde array.
An improved Local Grid-Refined Numerical Groundwater Model Based on the Vertex-centred Finite-Volume Method
Authors: Qian Yingzhi , Zhu Yan , Guadagnini Alberto
Published: March 2022

A variety of algorithms have been proposed to cope with issues associated with local refinements of numerical grids typically employed to cope with subsurface flow driven by sources acting on diverse scales (e.g., pumping wells, channels or ditches or abrupt changes in hydraulic conductivity distributions). In this context, here we focus on grid refinement associated with nonmatching grids, which still pose significant challenges in terms of accuracy. We propose a numerical modeling scheme based on a new algorithm that has an improved accuracy when compared against approaches that are typically used in conjunction with nonmatching grids. Our approach is based on the vertex-centred finite-volume method (VCFVM), the key feature of the algorithm resting on setting all unknowns on vertices of the mesh elements while the flux crossing a lateral surface of the control volume centred around a mesh vertex is expressed as a function of the hydraulic heads at the vertices of the element containing the lateral surface. A given row of the stiffness matrix of the system includes the entries associated with mass conservation formulated for the control volume associated with a corresponding grid node. Since the algorithm sets all unknowns on element vertices and a control volume can be defined for each vertex, our scheme readily embeds treatment of nonmatching grids in the presence of local grid refinement. Hydraulic heads evaluated through our algorithm are benchmarked against (a) results obtained from the widely used and tested MODFLOW and MODFLOW6 groundwater modeling suites in the presence of a variety of boundary conditions and considering high resolution matching (for MODFLOW) and nonmatching (for MODFLOW6) grids, and (b) a test analytical solution. Our results show that the average value of relative root mean square error (RRMSE) resulting from comparing our approach against the analytical solution and the MODFLOW simulations performed on the highly resolved grid (which we consider as reference) was always lower than 0.50%, thus imbuing us with confidence with respect to the accuracy of our proposed scheme. Additionally, while the requirement of CPU time associated with our algorithm is of the same order (on average) as the one associated with MODFLOW6 (benefits being noted mainly for settings involving flow in confined groundwater scenarios), our scheme is highly flexible in terms of spatial discretization and is characterized by higher accuracy for a given discretization.
Evaluating the adequacy-for-purpose of downscaling methods and products
Authors: Parker Wendy
Published: March 2022

How should downscaling methods, and the products of downscaling, be evaluated? An adequacy-for-purpose approach attempts to determine whether a method or product can be used successfully for specific purposes of interest. Purposes can take various forms: predicting variable X in region R with a specified level of accuracy, guiding a particular policy decision, etc. Depending on the purpose, different tests or checks will be performed and different levels of performance, on different metrics, will be deemed acceptable. A product that is grossly inaccurate in some respects may nevertheless be entirely adequate for the purpose at hand. Likewise, higher-resolution products are not necessarily more adequate (or fit); it depends on whether they provide the information required for the purpose of interest and in a way that can be interpreted and employed by users.
Less heatwave-driving blocking under global warming
Authors: Chan Pak Wah , Catto Jennifer , Collins Matthew
Published: March 2022

Summer heatwaves often occur under persistent anticyclones, or blocking. Here we quantify the sole effect of blocking changes on the frequency of heatwaves under global warming in the CMIP6 climate models. We employ an optimized blocking index that best correlates with summer continental heatwaves. Our optimized index gives a Pearson correlation of 0.7 with continental heatwaves and a 1σ uncertainty of 0.20% in projecting 10-year-mean heatwave frequency. The index optimization is achieved by excluding blocking over the ocean, tuning thresholds, mandating perfect stationarity and detecting only anticyclonic anomalies. Counting only the effect of changes in blocking, we project a one fifth decrease in Northern Hemisphere heatwave frequency under SSP585 (a frequency decrease of 0.3% in comparison with the historical frequency of 1.7%). We also find that both the blocking–heatwave correlation and the index thresholds (amplitude and duration) giving the highest correlation, vary insignificantly over different continents and in the future. Therefore, the future increase of around 60% in heatwave frequency under SSP585 is not caused by blocking changes, but by factors, like those of thermodynamics, that boost blocking's capability in driving heatwaves.
Approach to make an I/O server performance-portable across different platforms: OpenIFS-XIOS integration as a case study
Authors: Streffing Jan , Yepes-Arbós Xavier , C. Acosta Mario , Serradell Kim
Published: March 2022

Current Earth System Models (ESMs) produce a large amount of data due to an increase in the simulated complexity of the models and their demanded rising spatial resolution. With the exascale era approaching rapidly, an efficient I/O will be critical to sustain model throughput. The most commonly adopted approach in ESMs is the use of scalable parallel I/O solutions that are intended to minimize the overhead of writing data into the storage system. However, I/O servers with inline diagnostics introduce more complexity and many parameters that need to be tuned. This means that it is necessary to achieve an optimal trade-off between throughput and resource usage.

ESMs are usually run on different platforms which might have different architectural specifications: latency, bandwidth, number of cores and memory per node, file system, etc. In addition, a single ESM can run different configurations which require different amounts of resources, resolution, output frequency, number of fields, etc. Since each individual case is particular, the I/O server should be tuned accordingly to each platform and model configuration.

We present an approach to identify and tune a series of important parameters that should be considered in an I/O server. In particular, we focus on the XML Input/Output Server (XIOS) and we use it integrated with OpenIFS –an atmospheric general circulation model– as a case study. We do not only tune basic parameters such as number of XIOS servers, number of servers per node, type and frequency of post-processing operations, etc., but also specific ones such as XIOS buffer size, splitting of NetCDF files across I/O servers, Lustre striping, 2-level server mode of XIOS, etc.

The evaluation of different configurations on different machines proves that it is possible and necessary to find a proper setup for XIOS to achieve a good throughput using an adequate consumption of computational resources. In addition, the results show that the OpenIFS-XIOS integration is performant on the platforms evaluated. This suggests that the integration is portable, though it was initially developed for a specific platform.
Deep-learning based classification of ice crystals: habits and mircophysical processes
Authors: Zhang Huiying , Binder Alexander , Pasquier Julie , Krummenacher Benjamin , Ramelli Fabiola , Storelvmo Trude , David Robert Oscar , Henneberger Jan
Published: March 2022

Ice crystals are an important component of clouds due to their strong impact on cloud radiative properties and precipitation formation. The shape of an ice crystal impacts its radiative effect, riming efficiency, and fall speed.  The ice crystal shapes are dependent on (i) the environment (temperature and humidity) that they grow in and (ii) the microphysical processes (i.e. riming, aggregation) that they have experienced. These connections offer a great opportunity to trace back the previous in-cloud conditions and the microphysical processes in clouds. Thus, ice crystal shape classification is crucial to better understand radiation properties and precipitation formation of clouds.

Scientists have explored and developed various algorithms to automatically classify ice crystal shapes in the past decades. Among those, the machine learning algorithm Convolutional Neural Network (CNN), shows a good performance due to its ability to catch the main features that describe ice crystal habits and recognize patterns between images. However, the existing classification methods all show an overlap between physical process categories (i.e. rimed) and basic habit categories (i.e. column) of ice crystals due to the existence of compound ice (i.e. column-rimed), especially in situations conducive to light riming.

A CNN was trained using over 10’000 images of pristine and complex ice crystals recorded by a holographic imager during the NASCENT campaign  (Pasquier et al., BAMS, in revision) in Fall 2019, in Ny-Ålesund, Svalbard. To avoid the overlap between physical process and basic habit categories of ice crystals, each ice label contains two properties; one of 7 basic habits property (i.e. column) and up to 3 physical process properties (aggregate, rimed, aged). The trained model gives us both the basic habit and the physical processes information, which helps us to better understand the microphysical processes in clouds.
Evaluating climate change and coastal erosion risks on the Venice coastline: a Machine Learning approach supporting multi-risk scenario analysis
Authors: Dal Barco Maria Katherina , Pham Hung Vuong , Fogarin Stefano , Zanetti Marco , Cadau Marco , Harris Remi , Rubinetti Sara , Rubino Angelo , Zanchettin Davide , Barbariol Francesco , Benetazzo Alvise , Furlan Elisa , Torresan Silvia , Critto Andrea
Published: March 2022

Climate change and its consequences on coastal erosion, flooding and water quality are becoming a major concern for a significant percentage of littorals in the world. This issue is particularly challenging for gentle-sloping sandy coasts which are vulnerable to slow and continuous changes related to rising sea-levels and to extreme storm surge and wave events.

Here we present a multidisciplinary research combining satellite image with machine learning and GIS spatial analysis tools to analyze coastal erosion risk in the Venice shoreline over the period 2015-2019. Firstly, an advanced image preprocessing was performed on satellite images (e.g. co-registration, colors normalization) to prepare the input dataset. Secondly, different supervised and unsupervised machine learning classification methods were tested to accurately define shoreline position by recognizing land-sea areas in each image and the Digital Shoreline Analysis System (DSAS) tool in ArcGis was applied to evaluate the net shoreline movement overtime. Finally, a GIS-based Bayesian Network (BN) approach was developed, to evaluate the probability and uncertainty of coastal erosion risks, and the cascading effects on water quality variation, against multiple ‘what-if’ scenarios related to extreme sea levels and wave conditions under climate change for the period 2040-2050.

According to the spatial resolution of the available data for the case study of Venice (Veneto Region-Italy), the proposed BN-model was trained and validated by considering atmospheric, oceanographic and water quality parameters over the 2015-2019 timeframe, allowing to capture local-scale coastal progression and related driving forces.

Results showed general shoreline stability in the considered reference timeframe. However, the high presence of anthropogenic structures (e.g. jetties, breakwaters) induces the formation of well-delimited hotspots of erosion/accretion. Future trends from the BN-based scenario analysis, according to RCP8.5 scenario within the 2040-2050 period, showed that, even if in minor extent, water quality parameters (i.e. suspended matter, diffuse attenuation) will increase. On the other hand, shoreline evolution trend will face a decreasing probability of the stable class, which in turn will increase instability.

Despite constraints posed by the spatial resolution of the available data for the investigated case, the outcomes of the performed assessment represent valuable information to support adaptive policy pathways in the context of Integrated Coastal Zone Management and Disaster Risk Reduction in the Venice coastal area.
Evaluation of various regionalization techniques for the seasonal precipitation IDF estimates of Baden Württemberg
Authors: Amin Bushra , Bárdossy András
Published: March 2022

This research addresses a strong need to precisely improve the statewide seasonal precipitation intensity duration frequency (IDF) estimates at ungauged locations. In order to obtain IDFs at unvisited sites, IDFs observation locations are interpolated. Therefore, different deterministic and geostatistical approaches include Inverse Distance Weighted (IDW), Ordinary kriging (OK), Regression Kriging (RK), Co-Kriging (CoK), Kriging with External Drift (KED), and Functional Kriging (FK) have been taken into account for comparison. Apart from visual assessment, a cross-validation approach is used to compare these methods to judge their prediction accuracy.

Annual or intra-annual IDF calculations across the state is not well correlated with other variables except elevation, thus directionally smoothed altitude is only considered as a covariate that offered a significant reduction in bias.  All results indicate that IDW interpolation is incapable of improving the regional point IDF approximations provided by kriging algorithms except in the case of annual IDF predictions at shorter scales where its performance is more or less similar to OK.  Whereas summer IDF observations are well predicted by KED that also exhibits good behavior for longer duration extremes of all seasons. Moreover, the shorter duration winter IDF guesstimates are best achieved with CoK. From now, it can be noticed that the accuracy of the interpolator changes according to the hydrological seasons and storm durations.

Overall, this study ensures to design of a well-planned map in advance for the entire state of Baden Wurttemberg on the basis of accurate forecasting of seasonal IDF estimates of precipitation extremes at unsampled sites. Hence, this crucial step will surely help us to tackle the natural disasters due to climate change before time.
New environmental restrictions - aggregate effects on the Norwegian power system
Authors: Schönfelder Lennart , Harby Atle , Arvesen Anders , Graabak Ingeborg
Published: March 2022

Over 93% of Norway's power production stems from hydropower. The Nordic power market is constantly transforming, current main drivers include climate change effects on hydrology, an increase of variable renewable energy production, increasing interconnector capacity, and revision of concession terms for hydropower plants. A common plant layout is comprised of a reservoir and an underground penstock leading to a downstream located hydropower plant (HPP); in many cases several reservoirs and power plants are interconnected in complex systems. Consequently, the natural hydrology of many lakes and rivers are heavily impacted by hydropower operation.

Hydropower operation is legally regulated by concessions that include regulations to limit negative environmental and societal impacts. More than 400 HPPs currently undergo a revision of terms of their concessions, which will likely impact hydropower operations and subsequently the Nordic power market. Updated or new environmental restrictions of three main types may have significant impact: 1) r 2) requirements for minimum discharge and restricted flow variation downstream of power plants and 3) filling requirements for hydropower reservoirs for the summer season. The joint effect likely has impacts on the power-balance and the hydropower system’s flexibility at multiple timescales from seconds to seasons.

The objective of this cross-disciplinary study was to investigate the impacts of an ensemble of updated or new environmental restrictions on hydropower operations and on the Norwegian power market in the future. We developed a nationwide framework to quantify probable future environmental restrictions. . Additionally, a market model dataset for a 2030 scenario was created and input data adjusted, e.g. energy mix development in grid-coupled regions such as central Europe. Implemented in a state-of-the-art market optimization model, we modelled a range of restriction scenarios for the year 2030,

We analyzed resulting future price scenarios. Preliminary results show an increase in average yearly production loss in the range of 5 TWh (or 3% of total hydropower production) due to new environmental restrictions. Modelled market response is an increase of average spot-price by about 0.8 €/MWh for all regions of Norway. Norwegian export of electricity to other countries is reduced. Another effect is that reservoir filling levels are typically higher than in the current situation, likely due to filling restrictions and model tendencies to avoid risk of violating reservoir filling restrictions, as well as increased inflow during winter.
Anthropogenic tufa at legacy industrial sites: Potential for metal capture
Authors: Kalabová Marta , Cumberland Susan , Renshaw Joanna , MacDonald John
Published: March 2022

Uncontrolled leaching from legacy industrial waste may release toxic elements, which poses long-term risks of water and soil contamination. In some situations, secondary mineralisation from the leachates may occur downstream from waste sites, thus potentially limiting contaminant migration. An example is tufa, a surface freshwater CaCO3 (calcite) deposit which forms as a result of atmospheric CO2 absorption into Ca-rich hyperalkaline leachates. The tufa develops a range of morphologies and varies in hardness across the deposit. Moreover, it may also incorporate other elements into its mineral structure during precipitation. Understanding the processes of secondary mineralisation which are able to capture toxic metals would provide beneficial insights into controlling hazardous leaching.

This work characterises tufa occurring within anthropogenic contexts. Several tufas were found forming on or adjacent to anthropogenic sites (colliery spoil and steel slag heaps) in central Scotland, UK and studied for their geochemistry. A combination of direct field measurements of water physico-chemistry is complemented by alkalinity and elemental analyses of leachate source, water and tufa by ion chromatography (IC) and ICP-OES. The results from these analyses will help understand the processes involved in tufa formation and can be applied to the re-creation of tufa with the purpose of metal capture under controlled laboratory conditions. Early experiments have focused on CaCO3 precipitation onto different media by bubbling CO2 into CaCl2 solutions. The aim of these experiments is to create an engineered metal-capturing tufa system which can be applied across different post-industrial settings as a low-cost technique which beneficially captures CO2.
Study of unregulated flow conditions in Norwegian rivers- Strategy for improving lake outflow using HYPE model
Authors: Saldana Espinoza Carolina Isabel , Schönfelder Lennart , Seidel Jochen
Published: March 2022

Norway's authorities are delayed in implementing the European Water Framework Directive (EU-WFD). A common challenge for the implementation of EU-WFD is finding natural reference conditions in water bodies, which can be challenging for lakes that have been regulated and used for hydropower production before any physical variables were made. Hydrological modelling of unregulated lakes can be a solution.  Modelling water level fluctuations in unregulated lakes allow us to determine the ecological functioning of the lake and the water storage that could be used for different sectors such as hydropower, agriculture and others.

Previous studies showed that lakes had a strong influence on the performance of models when using the Hydrological Predictions for the Environment (HYPE) model. This study aims to develop model strategies for improving lake dynamic modelling with natural flow conditions in terms of discharge and water stage in HYPE. We modelled seven lakes in Norway with areas more than 5 km2 and a gauging station at the output. Each lake was calibrated independently, and each model was set up from an existing one for the mainland of Norway. Stepwise calibration was implemented to create separate discharge and water stage models. Rating curves for lakes were calculated and introduced to the model for water discharge and stage calibration following the equation Q=k(w-wo)p. Where w is the observed water level, wo is the reference water level, k is the rate, and p is the exponent. The model performance was evaluated in terms of Kling–Gupta efficiency (KGE). Preliminary results showed improvement of model performance for water stage modelling when employing a pre-calibrated model with discharge time series data. Also, improved model performance in discharge was found when using rating curves for calibration
ISROC—Inundation Signatures on ROcky Coastlines—A new Research Coordination Network targeting coastal boulder deposits
Authors: Engel Max , Cox Rónadh , Kennedy Andrew B. , Berke Melissa A. , Guannel Gregory , Lau A. Y. Annie , Mori Nobuhito
Published: March 2022

Intertidal and supratidal coastal boulder deposits (CBD) result from extreme marine inundation on rocky shores. They are important for understanding long-term coastal wave patterns, have predictive value for future events and can support coastal hazard assessment. But they are poorly studied, and their interpretation remains contentious, with debate on whether they record storms, tsunami, or both. In the case of older deposits, uncertainties about paleo-sea level contribute additional uncertainty. These ambiguities impact risk analysis: should CBD data be part of tsunami risk catalogues, or storminess indices? The hydrodynamics and climatology leading to CBD generation are also still uncertain. Two main obstacles to deeper understanding have been identified: a lack of data on CBD worldwide; and discrepant approaches that lead to difficulties in comparing data from different sites. Building community and interaction among CBD researchers, and awareness of CBD as research targets, can help grow our knowledge and tackle these obstacles.

ISROC (www.isroc.network)—Inundation Signatures on Rocky Coastlines—is an NSF-funded Research Coordination Network to define the CBD problem chain and identify research gaps by developing a broad and diverse network of researchers. The authors of this paper are the PIs and steering group. We plan to extend the community of researchers, in particular to include underrepresented groups; to facilitate development of standards and best practices for gathering and archiving CBD data; to develop cyberinfrastructure for uploading, visualizing, and analyzing data; and train the next generation of CBD researchers. To do this, we will create opportunities for cross-disciplinary collaboration and exchange. Using CBD to reconstruct coastal inundation history and extreme climatological states is a prime example of convergence research that cannot be solved by one discipline. The network includes geologists, geographers, oceanographers, engineers, hydrodynamicists, geophysicists, climatologists and paleoclimatologists. Activities include meetings, student training and exchanges; sessions in future years at major conferences in geoscience and coastal engineering; consolidation of survey/mapping approaches; building a global database; and user-friendly, fully accessible online data archiving. Understanding past inundation and how CBD form and evolve will both help to quantify present-day risk and will provide guidance for what to expect from future climate and sea level.
Study of the runaway greenhouse effect with a 3D global climate model
Authors: Chaverot Guillaume , Bolmont Emeline , Turbet Martin
Published: March 2022

The runaway greenhouse effect [1-4] is a very interesting process for terrestrial planets, studied in particular to determine the inner limit of the Habitable Zone (HZ). This limit is usually defined via the calculation of the asymptotic limit of thermal emission of the planet (OLR = Outgoing Longwave Radiation), also called Simpson-Nakajima limit. We have recently shown, using a 1D radiative-convective model, that a radiatively inactive gas such as nitrogen (N2) strongly modifies the OLR of the atmosphere [5] and can extend the inner edge of the HZ towards the host star [6]. We have also highlighted the importance of some physical processes sometimes considered as second order processes (e.g., collisional broadening of water lines).

In continuation of this work, we use a 3D global climate model, LMD-Generic, to study the onset of the runaway greenhouse for similar atmospheres. Some studies have shown that evaporation can lead to a moist stable state [7, 8], while others suggest an inevitable runaway greenhouse effect [9].

Here, we re-explore these possible moist stable states to better understand the key physical processes that potentially lead an Earth-like planet to a surface warming of several thousand degrees. We compare the results from 3D and 1D simulations, based on the conclusions of our previous study [5], in order to better understand the contribution of each process with a focus on clouds and dynamics, which are inherently three-dimensional processes.

 

References

[1] Komabayasi, M. 1967, Journal of the Meteorological Society of Japan. Ser. II

[2] Ingersoll, A. 1969, Journal of the Atmospheric Sciences

[3] Nakajima, S., Hayashi, Y.-Y., & Abe, Y. 1992, Journal of the Atmospheric Sciences

[4] Goldblatt, C. & Watson, A. J. 2012, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

[5] Chaverot G., Bolmont, E., Turbet, M., Leconte, J. 2021, Astronomy & Astrophysics

[6] Goldblatt, C., Robinson, T. D., Zahnle, K. J., & Crisp, D. 2013, Nature Geoscience

[7] Wolf, E. T., Toon, O. B. 2015, Journal of Geophysical Research

[8] Pop, M., Schmidt, H., Marotzke, J. 2016, Nature Communications

[9] Leconte, J., Forget, F., Charnay, B. et al., 2013, Nature
Improving the representation of glyoxal in the global EMAC model using TROPOMI retrievals and air-borne campaign data
Authors: Rosanka Simon , Kluge Flora , Pfeilsticker Klaus , Lerot Christophe , Taraborrelli Domenico
Published: March 2022

Glyoxal (CHOCHO) is the simplest and one of the most abundant atmospheric α-dicarbonyls. In the atmosphere, it is mainly produced by the oxidation of other non-methane volatile organic compounds originating from natural and anthropogenic sources. Against photooxidation, it has a rather short lifetime of about 1 to 3 hours. Due to its high solubility, it quickly partitions into cloud droplets and deliquescent aerosols where it is known to form oligomers leading to secondary organic aerosols (SOA). In order to assess its significance for air pollution, it is thus necessary that global atmospheric chemistry models satisfactorily predict its abundance.

On board of the Sentinel-5 Precursor satellite, the TROPOspheric Monitoring Instrument (TROPOMI) provides tropospheric glyoxal columns. These tropospheric columns are generated with an improved version of the BIRA-IASB scientific retrieval algorithm relying on the Differential Optical Absorption Spectroscopy (DOAS) approach. By combining these retrievals with glyoxal measurements obtained during multiple air-borne campaigns using the High Altitude and Long Range Research Aircraft (HALO), we evaluate the capabilities of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model to reproduce the global distribution and abundance of glyoxal. In its standard configuration, EMAC uses the detailed Mainz Organic Mechanism (MOM) to represent gas-phase chemistry. Additionally, we use the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Emissions Database for Global Atmospheric Research (EDGAR, v4.3.2) to represent natural and anthropogenic emissions, respectively. When analysing an EMAC simulation using this standard configuration, we find that EMAC tends to overestimate tropospheric glyoxal columns over continental regions close to strong natural (e.g., Amazon Basin) and anthropogenic emission sources (e.g., China). At the same time, EMAC tends to underestimate glyoxal columns over tropical oceanic regions.

In this study, we perform a series of sensitivity simulations and demonstrate that the model bias over continental regions is mainly resolved by including detailed aqueous-phase chemistry from the Jülich Aqueous-phase Mechanism of Organic Chemistry (JAMOC) and by reducing biogenic emissions towards the latest estimates. In addition, by implementing additional glyoxal precursors from oceanic sources, we demonstrate that the model bias over the tropical ocean is reduced. Following the more realistic model representation of glyoxal levels, we present a revised tropospheric glyoxal budget.
Insights into the Formation of Southeastern Mediterranean Seep Carbonates
Authors: Weidlich Reinhard , Bialik Or , Rüggeberg Andres , Grobéty Bernard , Vennemann Torsten , Makovsky Yizhaq , Foubert Anneleen
Published: March 2022

Authigenic seep carbonates, which are found globally at continental margins, can serve to characterise the seepage of hydrocarbon-enriched fluids into the oceans. This study aims to identify past seepage activity and gas migration pathways on the south-eastern margin of the Mediterranean, based on the analysis of authigenic seep carbonates collected during the 2016 EUROFLEETS 2 SEMSEEP expedition aboard the RV AEGEO. Seep carbonates with three different morphologies (chimneys, crusts and pavements), are studied using standard sediment petrography (fluorescence, CL and standard optical microscopy), as well as X-ray diffraction, Raman spectroscopy and stable isotope analyses. Recurrent cement and replacement phases identified contain different amounts of aragonite, low-magnesium calcite (LMC), high-magnesium calcite (HMC) and dolomite. Carbonate chimneys consist of micrite (δ13CVPDB of -10 to +5 ‰) with dispersed barite and dolomite crystals and fan-shaped aragonite (δ13CVPDB of -52 to -30 ‰). Locally, aragonite fans are replaced by LMC spherulites and blocky HMC. Botryoidal LMC cements are forming in small cavities. Carbonate crusts consist mainly of micrite rich in fossils and detrital grains with LMC breccias, HMC nodules (δ13CVPDB of -35 to -20 ‰) and cements and fan-shaped aragonite cement. These are partly replaced by LMC microsparite and show several growth stages. Carbonate pavements consist mainly of micritic dolomite and HMC. LMC microsparite can be identified as well. Fan-shaped aragonites are locally present as pore-lining cement. Fe-oxides are coating the low- and high-Mg calcitic and dolomitic cements. Raman spectroscopic analyses confirm the presence of aragonite, dolomite and specific organic compounds associated to different crystals.

Sediment petrography, XRD and stable isotope analysis reveal several phases of methane seepage through time. Distinct mineralogies (dolomite and aragonite) within the seep carbonate morphologies, result from different formation mechanisms (anaerobic oxidation of methane during aragonite formation and predominately sulphate reduction during dolomite formation). Raman spectroscopy highlights the presence of organic compounds within specific carbonate phases, which might play an important role in the carbonate formation.
Assessment of water provision under different future land use scenarios in the Cauquenes Catchment, Chile.  
Authors: Grau-Neira Aaron , Manuschevich Daniela , Galleguillos Mauricio , Zambrano-Bigiarini Mauricio , Marinao Rodrigo
Published: March 2022

The landscape of south-central Chile, originally a mosaic of pristine native forests and crops, has been converted into tree plantations and agroindustry. Farmlands and native forests have undergone a rapid conversion to fast-growing non-native pine and eucalyptus plantations, as well as irrigated fruits production for international exports. These two drivers have severely transformed the socio-ecological system, resulting in less biodiversity, more erosion, emigration and work depence, less drinking water, and a fire-prone landscape. A participatory approach helps not only to visualise tensions in the territory, but it is also useful for stakeholders to explore the possible environmental futures. However, frequently the development of land-use scenarios is mostly based on the views of experts and policymakers, missing out a wealth of local knowledge about the environment which experts seek to comprehend. 

This work aims at quantifying the impacts of the aforementioned land cover changes in water provision for the population and ecosystems, by incorporating the views of the people that still live in a drought-prone rural area in the construction of different narratives representing future land management scenarios. The study area is the Cauquenes River Basin, a mediterranean catchment located in central Chile, historically known for wine production and rainfed agriculture. To develop the narratives, we conducted semi-structured interviews to collect and analyse qualitative information using a coding system systematised in the Atlas.ti software. Using 2050 as the simulation target year, narratives gave us the guidelines to develop the spatial scenarios. Then, using an open-source land use change model- called CLUE-s we constructed scenarios of future land use change. The CLUE-s algorithm allocates land uses based on the suitability of each land use as well as spatial regulations. To assess the impact on water provision of each scenario, they were evaluated using a hydrological model (SWAT+).

Our results identified two different narratives: i) rural development: where water availability could increase, if a protection strip is established near water courses, that is, scrublands and native forest are assigned in these areas and, rainfed agriculture is strengthened and reach the extension it had in 1990 and ii) agro-industrial development, in which the central government promotes irrigated agriculture for international export markets, at the same time, passive preservation plans for protect native forest are applied according to the current forestry regulation. We expect that this participatory approach will enrich and strengthen adaptive management capacity at the local level, to be able to face the challenges ahead presented by a drier future.
Preliminary results from IRTF–iSHELL of Jupiter’s aurora during the NASA-Juno mission
Authors: Johnson Rosie , Stallard Tom , Melin Henrik
Published: March 2022

We present a preliminary study of the H3+ auroral emission at Jupiter, which uses data taken with the long-slit Echelle spectrometer, iSHELL, available at the NASA Infrared Telescope Facility (IRTF). Since first light in 2016, iSHELL has been used to provide ground-based support for the NASA-Juno mission, observing Jupiter’s aurora while Juno takes in-situ measurements of the magnetosphere as well as observing the aurora. These ground-based iSHELL measurements are critical as Juno-JIRAM lacks the spectral resolution to measure the Doppler shift of the H3+ spectra, from which the line-of-sight velocity can be derived, and the ionospheric flows inferred.

Previous ground-based H3+ studies have identified several significant ionospheric flows in Jupiter’s auroral region. Sub-rotating flows have been recorded in the dusk-side of the main auroral emission, which is in agreement with our current understanding of the generation of the aurora. However, super-rotating flows were also identified in the dawn-side of the main auroral emission, the origin for which remain uncertain but could lie either in driving from a dynamically changing thermosphere following a solar wind compression or the increase in angular velocity of magnetic field lines past corotation as they rotate into the dawn sector of the magnetosphere and are compressed. Furthermore, previous studies have identified a region of stationary H3+ ions (relative to the magnetic pole) in the polar aurora. This stationary region was originally located coincident to the UV swirl region, however, a more recent study, using a dataset with higher spatial resolution, located the stationary region coincident with the UV dark region, which is also dark in the IR. It is thought that the stationary region is due to coupling to the solar wind either through a Dungey-like process where a single convection cell is confined by the Vasyliunas cycle or through solar wind viscous flow interaction. Therefore, the mechanisms which couple Jupiter’s aurora to the solar wind are yet to be determined.

Here we discuss the longevity and variability of the above flows using the preliminary results from the iSHELL dataset. We consider how, moving forwards, these preliminary results can be compared to Juno data to advance our understanding of the generation of Jupiter’s aurora and how it is coupled to the solar wind. 
Silver fir tree ring width: a proxy for winter temperature variability in the Carpathians?
Authors: Popa Ionel , Roibu Catalin , Perșoiu Aurel , Kern Zoltan , Sidor Cristian
Published: March 2022

A composite Silver fir tree ring width chronology from seven mountain sites in the Eastern Carpathian Mountains (Europe) was established for AD 1588-2021, with SSS>0.8 and EPS>0.85 for AD 1750-2012. The bootstrap correlation analysis of the tree ring index with monthly climate parameters (temperature and precipitation) shows a positive and relatively time constant response to mean winter-spring temperature (November to March). The correlation between Silver fir tree ring proxy and winter-spring temperature is high and statistically significant (0.556 at p<0.05). The reconstruction statistics (R2, RE, CE and DW) indicate a good skill of the regression model between proxy data and winter temperature back to 1901. RE and CE statistics range between 0.32 and 0.39, and DW has values between 2.05 and 2.18. These results show good reliability of the model, and for the entire period, the reconstruction explains ~ 30% of winter temperature variability. The temperature reconstruction from AD 1750 shows inter-decadal fluctuation induced by low frequencies sinusoids (waves). The reconstructed mean winter temperatures for the 1750-2012 period was -2.93°C with -0.31°C colder than the 1961-2009 reference period. The longest period with high frequencies of years with low temperatures was recorded in 1740-1800, coinciding with the end of the Little Ice Age. After this coldest winter period, a six-year period with extreme warm winters was identified. The warming trend was more distinguishable science AD 1880 to the present, especially through the high frequency of mild winters. The coldest reconstructed winters for entire period were find in 2003 (anomalies= -1,56), 2012 (anomalies = -1,32) and 1965 (anomalies = -1,24). The warmest winters were recorded in 2001 (anomalies = +1,71), 1998 (anomalies = +1,48) and 2007 (anomalies = +1,37). The pattern of spatial correlation between proxy data and winter-spring temperature releases a wide extend of high correlation (>0.5), covering the North-Western Carpathians, continues with the Eastern chain of the Carpathian Mountains and finishes with the extreme South-East of Romania. Correlation with the Central Europe gridded temperatures is significant (>0.4), and with the Alpine Arc grid, temperatures are quite low (0.3). This result provides a regional scale of the winter-spring temperature reconstruction, suggesting a possible west-east gradient across Europe, potentially influenced by the interplay between the eastward expansion of Atlantic influence and the westward expansion of the West Asian influence.
Variability of mineral protection of organic matter in thawing permafrost peatlands
Authors: Eberle Anne , Gallego-Sala Angela , Kappler Andreas , Pancost Richard D. , Bryce Casey
Published: March 2022

Permafrost preserves huge amounts of carbon in Arctic soils including peatlands, which are common in high latitudes. The potential for carbon release from these peatlands upon permafrost thaw is still a big uncertainty for climate predictions. Protection of organic matter against microbial degradation by association with minerals such as iron minerals has been identified as an important stabilization mechanism for organic carbon in soils [1]. In a permafrost peatland in northern Sweden (Stordalen mire) up to 20% of organic carbon was found associated with iron minerals in oxic peat layers [2]. However, upon thaw and collapse of frozen peat, reducing conditions cause microbial iron reduction and dissolution of minerals, therefore releasing associated carbon. Despite the prevalence of peatlands in the permafrost zone, little is known about the variability and overall importance of mineral protection in permafrost peatlands, and it is still uncertain how this will change upon collapse of palsas (frozen peat mounds). Following optimization of a protocol for Fe-OC quantification from peat, we sampled peat cores and pore water from different thawing palsas in the Torneträsk area of northern Sweden to quantify iron-carbon associations across different sites and estimate the changes in geochemistry upon permafrost thaw. Understanding these changes and differences between peatlands will help to predict the role of permafrost peatlands for carbon emissions triggered by permafrost thaw across larger geographical areas.

[1] Kaiser and Guggenberger (2000), Org. Geochem., 31, 711-725. [2] Patzner et al. (2020), Nat. Commun., 11, 6329.
How do different drought types respond to climate change?
Authors: Hosseinzadehtalaei Parisa , Van Schaeybroeck Bert , Tabari Hossein
Published: March 2022

More frequent, longer, and more intense droughts are expected in many regions of the world because of climate change. Although drought can propagate from precipitation to runoff and soil moisture, the anticipated climate change impact, however, varies with different drought types. We investigate the response of meteorological, hydrological, and agricultural droughts to climate change for the end of this century using a multimodal ensemble of the Coupled Model Intercomparison Project Phase 6 (CMIP6) under the four Tier 1 ScenarioMIP scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). The projected changes in five characteristics (median duration, longest duration, median intensity, peak intensity, and frequency) of the different drought types at the global level are compared on seasonal and annual time scales. Our results show that the spatial extent and magnitude of the increasing signals in all the characteristics rise from meteorological to hydrological and agricultural droughts. This gradient is highest for the median and longest duration of droughts with the largest increases among the five characteristics considered.