bluuebunny/crossref_metadata_2025 huggingface dataset:
Modelling the evolution of Arctic multiyear sea ice over 2000-2018
Authors: Regan Heather , Rampal Pierre , Olason Einar , Boutin Guillaume , Korosov Anton
Published: February 2023

Multiyear sea ice (MYI) cover in the Arctic has been monitored for decades using increasingly sophisticated remote sensing techniques, and these have documented a significant decline in MYI over time. However, such techniques are unable to differentiate between the processes affecting the evolution of the MYI. Further, estimating the thickness, and thus the volume of MYI remains challenging. Here we use the neXtSIM sea ice model, coupled to the ocean component of NEMO, to investigate the changes to MYI over the period 2000-2018. We exploit the Lagrangian framework of the sea ice model to introduce a new method of tracking MYI area and volume, which is based on identifying MYI during freeze onset each autumn. The model is found to successfully reproduce the spatial distribution and evolution of observed MYI extent. We discuss the balance of the processes (melt, ridging, export, and replenishment) linked to the general decline in MYI cover. The model suggests that rather than one process dominating the losses, there is an episodic imbalance between the different sources and sinks of MYI. We identify those key to the significant observed declines of 2007 and 2012; while melt and replenishment are important in 2012, sea ice dynamics play a significant role in 2007. Notably, the model suggests that convergence of the ice, through ridging, can result in large reductions of MYI area without a corresponding loss of MYI volume. This highlights the benefit of using models alongside satellite observations to aid interpretation of the observed MYI evolution in the Arctic. Based on the MYI tracking method here, we demonstrate how MYI is now implemented in the neXtSIM-F forecasts distributed by the CMEMS platform.
Extraction of fluids to mitigate the seismic risk associated with post-injection aseismic slip
Authors: Sáez Alexis , Lecampion Brice
Published: February 2023

Subsurface fluid injections are commonly accompanied by seismicity which can sometimes result in earthquakes of relatively large magnitude that pose a serious hazard for the geo-energy industry. Current efforts to manage the seismic risk associated with fluid injections work generally under the tacit assumption that mitigation measures will become shortly effective in preventing the occurrence of earthquakes of larger magnitude than some pre-defined threshold. A common operational measure is shutting in the wells indefinitely. Unfortunately, seismicity after shut-in is common and, even more, it is not rare that the largest events of injection-induced seismic sequences occur during the post-injection stage. Understanding the physical mechanisms underpinning post-injection seismicity is thus of first importance for the successful development of geo-energy projects. Moreover, gaining knowledge in this matter may ultimately help to design physics-based strategies to mitigate the seismic risk associated with fluid injection operations. From a pure hydro-mechanical perspective, there are two well-known triggering mechanisms for post-injection-induced seismicity, namely, the diffusion of pore-fluid pressure (Parotidis et al., 2004) and poroelastic stressing (Segall and Lu, 2015). Recently, Sáez and Lecampion (2023) have investigated a third mechanism where injection-induced aseismic slip in pre-existing fractures and faults may keep propagating after shut-in and continue stressing even larger and more distant regions from the injector during time scales that could span even months for fluid injections of only few days, if the reactivated fracture/fault is critically stressed. This result has motivated us to develop a physics-based strategy to mitigate the seismic risk associated with post-injection aseismic slip. The idea is to extract fluids as an operational measure instead of just stopping the injection. It is shown that fluid withdrawal has not only the effect of reducing the further increase of pore pressure during the post-injection stage, but also the effect of decreasing both the spatial extent and exposure time of the surrounding rock mass to quasi-static changes of stresses due to aseismic slip. The main parameter controlling the reduction of the spatial extent and exposure time is the ratio between the extraction rate and injection rate.  We make use of realistic field configurations to provide examples that show the significant reduction of the exposure time that can be achieved by extracting fluids. We also discuss some field evidence that support the plausibility of this extraction strategy.
Building an Open Source Infrastructure for Next Generation End User Climate Services
Authors: Gräler Benedikt , Demmich Katharina , Schnell Johannes , Vogel Merel , Bagli Stefano , Mazzoli Paolo
Published: February 2023

Climate Services (CS) are crucial in empowering citizens, stakeholders and decision-makers in defining resilient pathways to adapt to climate change and extreme weather events. Despite advances in scientific data and knowledge (e.g. Copernicus, GEOSS), current CS fail to achieve their full value proposition to end users. Challenges include incorporation of social and behavioral factors, local needs, knowledge and the customs of end users. In I-CISK, we put forward a co-design based requirement analysis to develop a Spatial Data Infrastructure and Platform that empowers a next generation of end user CS, which follow a social and behaviorally informed approach to co-producing services that meet climate information needs of the Living Labs of the European I-CISK project. Core to the project are climate extremes such as droughts, floods and heatwaves. The use-cases touch upon agriculture, forestry, tourism, energy, health, and the humanitarian sectors. We will present the summarized stakeholders' requirements regarding the new climate-service platform and their technical implications for the open source spatial infrastructure. The design also includes assessing, managing and presenting uncertainties that are an inherent component of climate models.
Investigation of the microphysical processes during the rapid intensity changes of tropical cyclones over the Bay of Bengal: A modelling approach
Authors: Nekkali Yerni Srinivas , Osuri Krishna Kishore , Das Ananda Kumar , Niyogi Dev
Published: February 2023

Tropical cyclones (TCs) are one of the natural destructive weather phenomena. The accurate prediction of TC intensity is dependent on the understanding of the physical processes behind that. This study exposes the importance of microphysical (MP) processes in the rapid intensity changes of cyclones. For this, tropical cyclone simulations were made from the WRF model with a double nested (9 km-Static and 3 km-moving nests) configuration. This study shows that the heating generated by the MP processes in the TC’s inner-core region is highly (moderately) correlated with precipitated (non-precipitated) hydrometeors. During the rapid intensification (RI) period, heat-released microphysical processes such as condensation, freezing due to the accretion of liquid hydrometeors with ice particles, and deposition, etc., are dominant as compared to cooling-induced processes. In addition, the saturated envelope in the TC Phailin (2013) is responsible for more convection, heating, and hence consecutive RI episodes. While dry air intrusion hampers the prolonged RI episodes in TC Fani (2019). However, rapid weakening (RW) in TC Lehar (2013) is promoted by asymmetric, limited convection, and hence, lesser heating. During this RW period, the warm rain (ice) microphysical processes mainly produce heating (cooling).
Statistical Study of Shock Rippling
Authors: Khotyaintsev Yuri , Lotekar Ajay , Johlander Andreas , Graham Daniel , Lalti Ahmad
Published: February 2023

MMS can resolve the fine structure of the shock ramp, which often shows holes in reduced ion-phase space distributions (integrated along the tangential plane of the shock). This is possible due to the high temporal resolutions of FPI/DIS. Such holes have been associated with ripples propagating along the shock surface but also can be related to the shock reformation. We statistically characterize the ion phase-space holes at the Earth’s bow shock using MMS observations. We establish a systematic procedure to find the shocks exhibiting the phase-space holes. We apply the procedure to ~500 shock crossings for which the burst data necessary to identify the holes is available. We identify phase-space holes for 66% of the crossings. We note that the actual occurrence is likely higher, as the holes are not resolved for fast shock crossings. We characterize the occurrence of the holes as a function of shock parameters such as Mach number and geometry. We find that the holes are widespread at the bow shock and are present for a wide range of shock geometries and Mach numbers (MA) studied. Their occurrence has no dependence on the shock geometry and increases with the Mach number, MA. The highest occurrence (70% probability) is for MA above 5. These results are essential to understanding the non-stationary behavior of collisionless shocks.
Large Area Glacier-Like Forms on Mars: Insights from Impact Crater Morphologies and Crater Retention Ages
Authors: Driver Graham , El-Maarry Mohamed Ramy , Hubbard Bryn , Brough Stephen
Published: February 2023

Ice-rich landforms known as Viscos-Flow Features (VFFs) are common in Mars’ mid-latitudes. Glacier-Like Forms (GLFs) are a distinct sub-category of VFFs and appear morphologically similar to terrestrial valley glaciers or rock glaciers. GLFs are thought to be the result of the redistribution of water ice from the Martian poles during periods of high obliquity (>35o) and the Last Martian Glacial Maximum (LMGM), which ended ~5 Myr. Numerous distinct impact crater morphologies have been observed on these ice-rich terrains. Research has suggested that this variation results from interactions between landform lithologies and surface evolution through depositional and erosional processes. We investigated impact crater quantities and morphologies on 100 GLFs with large surface areas, with the aim of determining Crater Retention Ages (CRAs) for the landforms and exploring the relationships between crater morphology variation and relative surface ages.Our results show GLF ages vary across Mars, with various surface retention ages and crater morphologies populations. There are populations of GLFs with young CRAs (<20 Ma), particularly in the southern hemisphere, suggesting recent glaciation could have been more favourable in the southern mid-latitudes. Our results suggest several scenarios for GLFs across Mars. (1) That some GLFs have the potential to be very young, having perhaps formed in the last few million years during the LMGM. (2) That some GLFs may have formed before the LMGM (>20Ma) but have high resurfacing rates, partially removing their impact records. (3) That some GLFs formed long before the LMGM and have medium to very low resurfacing rates. These GLFs have surfaces with greater quantities and morphological variation of craters. Consequently, they also appear to record more resurfacing events and have more comprehensive CRA ranges. The low resurfacing rates suggest that these GLFs have not been in favourable depositional environments for an extended period and are possibly in low erosional settings. The study hints that while high Martian obliquity periods can favour glaciation, material accumulation, and resurfacing events, this occurs within local geographical constraints and that not all periods of glaciation are favourable to all GLFs across Mars.
Eco2Fly - An aviation climate impact assessment
Authors: Dahlmann Katrin , Grewe Volker , Matthes Sigrun , Hendricks Johannes , Righi Mattia , Weder Christian , Mertens Mariano , Brinkop Sabine
Published: February 2023

Air traffic facilitates our society’s requirements for mobility. However, air traffic also contributes to climate change. Especially in view of the 2°C-climate target, it is important to make aviation eco-efficient. Here, the project Eco2Fly aimed at revising the estimate of the climate impact of aviation, by means of numerical simulations as well as in-situ and remote sensing measurements. Eco2Fly was a DLR funded project, which focuses on the climate impact of aviation, how atmospheric processes can be better understood and how we can reduce the climate impact of aviation. In this poster we focus on the aviation climate impact assessment.Lee et al. (2021) published already a comprehensive climate impact assessment two years ago, which gives an excellent overview of the different climate species and their contribution to nowadays climate impact. Here, we like to add some new methods and processes to a climate impact assessment. One point is the difference between perturbation und tagging approach. While the perturbation approach provides the impact of changed emissions in the chemistry-climate system, the tagging approach gives the contribution of one sector to the total climate impact. Additionally, new insights from numerical simulations for the direct and indirect aerosol impact were obtained.It is important for such a climate impact assessment, to use model results which are based on a realistic spatial distribution of emissions as different emission inventories can cause significantly different climate impact estimates, despite unchanged total emissions. In cooperation with the DLR project TraK (Transport and Climate) emission calculation and climate modelling approaches are applied to assess the climate impacts of the 2019 aviation emissions.
Innovative tools to narrate the importance of climate literacy
Authors: Santin Selvaggia , Buonocore Mauro , Carlon Ottavia , Glauda Agnese
Published: February 2023

Climate literacy means making individuals aware of the daily interactions we all have with the world around us and, consequently, supporting them in making responsible and informed decisions on how to make such interactions sustainable and not harmful to the environment. The idea behind climate literacy is not only to educate people on such principles but also to provide learners with practical applications and equip them with tools they can use to become active change agents in their communities. CMCC is actively taking part in this ambitious challenge through an innovative, interactive platform in which climate change information, tools and data are narrated in a new, multidisciplinary way to help people understand what climate literacy is and what is the meaning of successful adaptation to climate change - and how to practically do it.
Focused on the Adriatic area, the multimedia platform collects a series of nine success stories taking place in the context of the Italy-Croatia Interreg AdriaClim project, which involves local authorities, experts, scientists and citizens in a common effort to adapt to climate change impacts in coastal areas.
The nine stories are presented through the use of new - or different - words, images,  unheard voices and multimedia contents to provide a new narration for innovative solutions. We simplify scientific jargon, giving new life to the words of climate science and sharing information that appeals to facts, and data but also emotions. We dived into the heart of the climate change discourse to extract the most useful keywords to talk about adaptation: we collected and organised them in a simpler, non-canonical dictionary, with practical examples, general context scenarios, differentiated sources and more. Images represent reality but can also be used as access points to knowledge, and impactful visual narratives to explain and illustrate complex concepts and phenomena. Getting in touch with experts and institutional representatives who are at the forefront of the adaptation activities carried out in their areas gives life to a peer-to-peer process that can be an inspiration for different stakeholders. 
Our Climate Literacy platform narrates stories that are born within science but are able to reach non-experts and citizens and help them understand and act about the challenges and solutions of coastal adaptation. Through a multimedia and interdisciplinary dialogue, the platform provides a unique hub for the contamination of knowledge and ideas to act in the face of future impacts.
 
­­­HPC implementation and algorithm of the Thermal Lattice Boltzmann Method for geodynamics simulations in 2D and 3D
Authors: Mora Peter , Morra Gabriele , Yuen Dave
Published: February 2023

The Thermal Lattice Boltzmann Method (TLBM) is a powerful numerical method for thermally driven fluid flow simulations that is starting to be applied to geodynamics research. It is based on solving the Boltzmann equations on a discrete lattice and involves two steps of movement and collision of particle number densities carrying mass density and energy density on a discrete lattice. The collision step is achieved by relaxing the distributions to the equilibrium distribution where the relaxation times relate to the kinematic viscosity and thermal diffusivity of the fluid. We present the TLBM algorithm and an optimized HPC implementation of the TLBM where the main code is written in python using MPI for python, and this code calls highly optimized c functions for the kernels which do the heavy computational work. The same code works in 2D or 3D and we calculate the optimal 2D or 3D domain decomposition at the start of each run. Edges of domains are sent and received using optimal unblocking MPI requests, with the send and receive requests and buffers initialized at the start of a run to further optimize the communication costs. We present performance results which show near linear speedup to thousands of cores provided the domain size is not too small. We achieve of order 2-3 Gflops per core which is typically over 50% of peak performance. We show 2D runs using a highly nonlinear rheology which promotes the formation of plate-tectonic like dynamics with upwelling and downwelling plumes with the horizontal motion tending to be constrained to the upper 100km of the model. We also show 2D and 3D runs with temperature dependent viscosities and power law thermal boundary layer scaling with Nusselt number. And we show runs of simulations with high Rayleigh numbers up to 10**12 and Prandtl numbers up to 10**4. The TLBM offers a means to study the effect of highly nonlinear rheologies on geodynamical processes, and may eventually lead to a more complete simulation capability for studies of planet and exoplanet evolution.
Risks and benefits of stratospheric solid particle injection for climate intervention
Authors: Vattioni Sandro , Weber Rahel , Klaus Oliver , Luo Beiping , Dykema John , Stenke Andrea , Feinberg Aryehe , Döbeli Max , Vockenhuber Christof , Kreiger Ulrich , Weers Uwe , Artiglia Luca , Yang Huanyu , Longetti Luca , Gabathuler Jerome , Ammann Markus , Keutsch Frank , Peter Thomas , Chiodo Gabriel
Published: February 2023

Recent studies have suggested that injection of solid particles such as alumina (Al2O3) and calcite (CaCO3) instead of SO2 for stratospheric aerosol intervention could reduce some of the adverse side effects of SAI such as ozone depletion, stratospheric heating, and changes in diffuse radiation. However, the expected improvements from alteration of stratospheric chemistry are subject to large uncertainties. We constrain some of these uncertainties by experimental work on calcite particles using elastic recoil detection analysis (ERDA) and in-situ experiments using X-ray photoelectron spectroscopy (XPS). Subsequently, we use a global aerosol-chemistry climate model that, for the first time, interactively couples microphysical and chemical processes of solid calcite and alumina particles as well as liquid sulfuric acid aerosols with model radiation and transport. Notably, SAI by solid particles only leads to more effective radiative forcing per aerosol burden compared to sulfuric acid aerosols, not per injected mass. However, reduced stratospheric warming remains a major advantage of solid particles. Furthermore, different assumptions on the heterogeneous chemistry of solid particles, based on the available experimental data, result in drastically different impacts on stratospheric composition, in particular, ozone. For alumina particles, which are thought to not undergo chemical aging during their stratospheric residence time we present a sensitivity analysis for heterogenous reactions to quantify uncertainty. For the alkaline calcite particles, which are thought to undergo chemical aging in the stratosphere via reaction with acids (e.g., HCl, HNO3, H2SO4) we find even larger uncertainties due to unknown reaction pathways and highly uncertain rates under stratospheric conditions. The large uncertainty in predicted stratospheric ozone changes can only be reduced via substantial additional laboratory experiments under stratospheric conditions, i.e., partial pressures of relevant gases (e.g., HCl, HNO3, H2SO4), temperatures < 220 K, relative humidity < 1% and realistic UV irradiance. From the present perspective, sulfur-based SAI has significantly lower uncertainty than injection of solid particles, which have significantly reduced stratospheric heating but very large uncertainties in impacts on stratospheric composition.
Convective influence on UT/LS water vapor from in-situ measurements of water vapor isotopologues
Authors: Moyer Elisabeth , Clouser Benjamin , KleinStern Carly , Khaykin Sergey , Sarkozy Laszlo , Singer Clare , Lykov Alexey , Krämer Martina , Legras Bernard , Thornberry Troy , Stroh Fred
Published: February 2023

The isotopic composition of water vapor provides a novel source of information on the convective origins and life cycle of water in the UT/LS region.  The Chicago Water Isotope Instrument (ChiWIS) has now provided a deep catalog of measurements over both the North American and Asian summer monsoons, from both European and American high-altitude aircraft campaigns: StratoClim (Stratospheric and upper tropospheric processes for better climate predictions) in 2017, and ACCLIP (Asian summer monsoon Chemical and CLimate Impact Project in 2021-2022. Isotopic measurements show the importance of deep convection in carrying moisture as lofted ice, but also the strong distinction between the two monsoons, with higher convective influence and more complete sublimation over North America. Convective outflow remnants remain distinct for as long as two weeks and govern the locations of formations of in-situ ‘secondary cirrus’. We show the consistency and power of the complete dataset collected and examples highlighting the utility of isotopic measurements in understanding the life cycle of UT/LS water, including convective inputs, mixing, sedimentation, and sublimation.
Towards a Performance-Portable Finite-Volume Dynamical Core for Numerical Weather Prediction
Authors: Ubbiali Stefano , Ehrengruber Till , Krieger Nicolai , Kühnlein Christian , Papritz Lukas , Wernli Heini
Published: February 2023

We present the ongoing development of a Python implementation of a finite-volume non-hydrostatic dynamical core at ECMWF and its member state partners. The main drivers behind the model formulation are suitability for convective-scale resolutions and increasing multi-level parallelism. Sustainable software design with respect to emerging and future heterogeneous computing platforms is addressed by leveraging the GT4Py domain-specific framework. We further address aspects of implementing and coupling selected ECMWF model physical parametrizations using GT4Py. 
The enigma of a massive carbon imbalance – Two decades of cropland eddy flux measurements at Gebesee, Thuringia, Germany
Authors: Brümmer Christian , Schrader Frederik , Kolle Olaf , Herbst Mathias , Lucas-Moffat Antje , Kutsch Werner
Published: February 2023

Agriculture plays an important role in the land surface-atmosphere exchange of greenhouse gases and terrestrial carbon cycling. The determination of carbon budgets with varying system boundaries has been in the focus of environmental research, particularly at agricultural sites, which occupy roughly 50% of the global land surface. Accurate carbon balancing at crop sites is subjected to a number of uncertainties, for example through variations in vegetation cover development, carbon imports and exports by fertilization, harvest, and recurring disturbance by soil and plant management. Since 2001, continuous observations of CO2 and water vapour net ecosystem exchange, meteorological parameters, and field operations have been carried out at the ICOS Class-1 station Gebesee (DE-Geb), located in the Thuringian Basin, Germany, making it the longest operating agricultural eddy-covariance site in Europe. In this contribution, we present two decades of flux measurements under the given land management and bioclimatic conditions. We found two opposing trends between net ecosystem and net biome production, called NEP and NBP, respectively. While the net CO2 exchange resulted in an average annual ecosystem carbon gain of ca. 2.2 t C ha-1 (NEP), including lateral fluxes from harvest and fertilization turned the site into a substantial deficit, indicating a loss of ca. 1.6 t C ha-1 (NBP) per year. The mean values in repeated measurements of soil organic carbon (SOC) stocks in 2004 and 2019, however, did not show any significant changes in any of the soil horizons. Taking conservative uncertainty estimations from all components into account, the carbon loss revealed in the NBP trend over 21 years barely matched the outer ranges of the SOC uncertainty in the 0-60 cm layer. As the soil type at DE-Geb is a black earth with high carbonate content, we speculate that a certain amount of the emitted CO2 is of inorganic origin and may partly explain the site’s carbon imbalance. An additional experiment investigating the δ13C signature of the emitted CO2 to potentially prove this assumption is still ongoing. Our study highlights the importance of long-term continuous biosphere-atmosphere observations within research infrastructures like ICOS for understanding carbon cycling in agricultural landscapes, but also emphasizes the importance of site-specific knowledge to improve sustainable land management.
Attribution of seasonally-relevant climate indicators in Hungary
Authors: Szabó Péter , Bartholy Judit , Pongrácz Rita
Published: February 2023

Although anthropogenic global warming is well-described in the climate community, some socioeconomic groups are still skeptical about it due to various reasons, and they do not know how to associate local weather or climate events with global warming. It is our duty to raise awareness by conveying easily understandable yet scientifically sound and straightforward information and to explain how human activity contributes to climate impacts in front of our eyes, in our region. Although it is widely assessed now in Western Europe, in Hungary from September 2021 we began our comprehensive analyses and raised awareness in several social strata through our local attribution project.Within the project, we selected seasonally relevant and publicly well-known climate indicators (e.g., vegetation start in spring, heatwaves and forest aridity in summer, second summer in autumn, snow in winter), since they either have a fairly large public interest or have big impacts in our region. Dissemination is done mainly via a well-known online Hungarian platform with broad media coverage, while their social media network is also used with short messages. Results are published in each season at around an event occurrence or absence (e.g., when there is no snow in winter, when vegetation starts too early in spring).For the analysis, we used several state-of-the-art data sets consisting of global climate model simulations with both natural-only and historical forcings, an ensemble of regional climate model simulations with strong mitigation and non-mitigation future scenarios, and high-quality, gridded observations.
FORECASTING DEFORMATION TRIGGERED BY GROUNDWATER EXTRACTION USING PS-InSAR TIME SERIES. APPLYING MACHINE LEARNING AND STATISTICAL MODELS IN THE MADRID AQUIFER (SPAIN).
Authors: Rivera Rivera Jhonatan Steven , Aguilera Alonso Héctor , Arias Patiño Juliana , Guardiola Albert Carolina , Béjar Pizarro Marta
Published: February 2023

Ground deformation caused by groundwater exploitation leads to significant socio-economic losses worldwide. Driving factors such as population growth and climate change will increase these losses, especially in arid regions where droughts are becoming more intense, longer lasting, and frequent. Therefore, there is a need to generate models capable of forecasting ground deformation. However, few studies have analyzed deformation time series (DTS) to identify and characterize subsidence phenomena.Our research aims to predict the ground deformation associated with groundwater abstractions in 18 wells of the Madrid Detrital Aquifer (ATDM) using statistical models and shallow and deep Machine Learning (ML) algorithms. We generated a database with 18 monthly time series (one for each well) between 1992 and 2010, with data for two variables: a binary variable indicating extraction-recovery cycles of the aquifer and a continuous variable representing the average deformation for the area of influence of each well. DTS generated from Persistent Scatter Interferometry (PSI) of ERS-1/2 and ENVISAT radar images were used to calculate the average deformation. Finally, we applied six different methods for forecasting DTS: two statistical models, Autoregressive Integrated Moving Average (ARIMA) and Prophet (P), one ensemble shallow ML algorithm, Random Forest (RF), one hybrid method, Neural Prophet (NP), and two Deep Learning (DL) techniques 1D Convolutional Neural Networks (CNN1D), and Long Short-Term Memory (LSTM).The analysis of DTS allowed us to differentiate two zones with different hydrological behavior: a zone of higher permeability (north zone) and another of lower permeability (south zone). We found that establishing the architectures of ML and DL algorithms based on hydrological zones improves the prediction of ground deformation. ML and DL algorithms provide better forecasts compared to statistical and hybrid models. Specifically, LSTM and RF offer the best results. Our results show the potential of LSTM algorithms and the previous grouping of DTS in predicting ground deformation associated with groundwater exploitation.This work has been developed thanks to the pre-doctoral grant for the Training of Research Personnel (PRE2021-100044) funded by MCIN/AEI/10.13039/501100011033 and by "FSE invests in your future" within the framework of the SARAI project "Towards a smart exploitation of land displacement data for the prevention and mitigation of geological-geotechnical risks" PID2020-116540RB-C22 funded by MCIN/AEI/10.13039/501100011033.
Individual versus combined effects of elevated CO2, warming and drought on grassland productivity and stoichiometry
Authors: Bahn Michael , Reinthaler David , Piepho Hans-Peter , Pötsch Erich , Schaumberger Andreas , Herndl Markus , Meeran Kathiravan , Kaufmann Rüdiger , Radolinski Jesse , Tissink Maud ,   ClimGrass-Team
Published: February 2023

In a future world, ecosystems will be affected by a concomitant increase in atmospheric CO2 concentrations, temperature and drought events. While the individual effects of elevated CO2, warming and drought on plant and ecosystem productivity are comparatively well understood, there is a major lack of experimental studies testing for their interactive effects. In a multifactor experiment (ClimGrass) established in 2013 on a managed montane grassland in Central Austria we tested how elevated CO2 (eCO2), warming (eT) and drought individually and interactively affect productivity and tissue stoichiometry.Treatment effects varied and amplified across the eight treatment years, partly related to shifts in species composition. Above-ground net primary productivity (ANPP) was generally increased when eT and eCO2 were combined, while it was not consistently affected by the individual treatments. Drought and drought recovery effects on ANPP, gross primary productivity (GPP) and belowground carbon allocation were amplified when drought was combined with eT and eCO2. Both under current and future (eT, eCO2) scenarios drought altered tissue stoichiometry by decreasing phosphorus concentrations during drought and increasing nitrogen and potassium concentrations post-drought. Overall, our study suggests that in the temperate grassland studied drought had an overriding effect on productivity and tissue stoichiometry, which was amplified by warming, but only weakly altered by elevated CO2. 
Assessing cloud sensitivity to shipping aerosol across large emissions ranges
Authors: Manshausen Peter , Watson-Parris Duncan , Christensen Matthew  W , Jalkanen Jukka-Pekka , Stier Philip
Published: February 2023

Aerosol-cloud interactions remain a large source of uncertainty in anthropogenic climate forcing. One of the reasons for this uncertainty is the confounding role of meteorology, influencing both aerosols and cloud properties. To untangle these variables, ship tracks, the clouds polluted by shipping emissions, have been widely studied. Recently, the use of shipping emissions locations and amounts, combined with reanalysis winds, has allowed us to study polluted clouds by following ship emissions to the locations they are advected to by the time of a satellite measurement of clouds. This is possible even when no visible tracks appear in satellite images. Here, we additionally use emission amounts data and investigate their effect on key cloud characteristics like droplet numbers and liquid water. This per-ship emissions data is valuable as it allows us to investigate cloud property changes stratified by region or meteorology. Between the ships with the lowest and highest emissions, droplet number anomalies increase by an order of magnitude from 0.25% to 2.5%, but the effect saturates at high emissions. We furthermore present evidence that increases of liquid water are insensitive to the amount of aerosol increases. Crossing data with a set of machine-learning detected ship tracks, we show that emissions amount has a similarly saturating effect on the formation of visible tracks as on droplet number, increasing roughly linearly for a large range of emissions before saturating (and even declining) at high emissions. The saturation of cloud responses at relatively high emissions could indicate that clouds react strongly to reductions in aerosol emissions. 
Information-based approach for quantifying uncertainty in precipitation estimates from commercial microwave links
Authors: Špačková Anna , Fencl Martin , Bareš Vojtěch
Published: February 2023

Opportunistic sensors have great potential for rainfall monitoring, as the density of their networks can outperform standard rainfall monitoring networks. The commercial microwave link (CML) network enables indirect monitoring of path-averaged rainfall intensity. It is retrieved from signal attenuation caused by raindrops, which can be related to rainfall intensity by a simple power law. Quantitative precipitation estimates from CMLs are, however, affected by uncertainty, which is still challenging to estimate.This study proposes, for the first time, to use information theory methods to quantify uncertainty in CML QPEs. This method enables measuring the firmness of relationships between different variables using discrete probability distributions and also estimates the uncertainty. The advantage resides also in the fact that it allows any type of data to be used. This approach was recently applied by Neuper and Ehret (2019) to evaluate quantitative precipitation estimates with weather radar.Data from non-winter periods of 2014 – 2016 are used at a temporal resolution of 15 min. The target (reference) data are the rain gauge adjusted radar observation. The CML data (signal attenuation and its processing) from the Prague network and its hardware characteristics are used as predictors. Additionally, other predictors, e.g., temperature and synoptic types, are used as further predictors. First, the information content of individual predictors of the target rain gauge adjusted radar data is measured. Specifically, we tested how different combinations of predictors reduce uncertainty. Second, the effect of the sample size on uncertainty is investigated. Different sizes of random samples are selected from the dataset and their information content for the target is quantified.Depending on the choice of the predictor(s), their abilities to estimate the target variable can be compared. Their predictive uncertainties are different, which results in a ranking of suitability of available predictors and their combinations. ReferencesNeuper, M. and Ehret, U. (2019) Quantitative precipitation estimation with weather radar using a data- and information-based approach, Hydrol. Earth Syst. Sci., 23, 3711–3733, https://doi.org/10.5194/hess-23-3711-2019. This study is supported by the Student Grant Competition grant of Czech Technical University in Prague no. SGS22/045/OHK1/1T/11.
An Artificial Intelligence-based platform for volcanic hazard monitoring
Authors: Del Negro Ciro , Amato Eleonora , Cariello Simona , Corradino Claudia , Torrisi Federica , Zago Vito
Published: February 2023

Satellite remote sensing data are suitable to monitor global scale volcanic hazards in an efficient and timely manner. The development of monitoring systems which automatically collect and process satellite data is crucial during a volcanic crisis. The huge amount of multispectral satellite data available requires new approaches capable of processing them automatically and artificial intelligence (AI) addresses these needs. Machine learning, a type of AI in which computers learn from data, is gaining importance in volcanology. The combination of ML algorithms and satellite remote sensing in volcano monitoring has the potential of analyzing global data in near real-time for mapping and monitoring purposes. Here, an AI-based platform was developed to monitor in near real-time the volcanic activity from space. AI algorithms are used to retrieve information about the ongoing volcanic activity. Under this perspective, a key role is played by ML since it overcomes the issues related to hard coded/explicit rules by implicitly learning them from historical satellite data. Volcanic eruptions are then fully characterized in terms of their energy release, e.g. volcanic radiative power (VRP), effusive rate, quantification of the erupted products, i.e. volume, spatial extension, volcanic cloud composition. This task is achieved by combining a variety of freely available satellite datasets, i.e. infrared (IR) data with different spatial, temporal and spectral features.  In particular, both a geostationary satellite sensor, i.e. SEVIRI (Spinning Enhanced Visible and InfraRed Imager, on board Meteosat satellites), and several mid-high spatial resolution polar satellite sensors, e.g. MODIS (Moderate Resolution Imaging Spectroradiometer, on board Terra and Aqua satellites), VIIRS (Visible Infrared Imaging Radiometer Suite, on board the Suomi-NPP and NOAA-20 satellites), SLSTR (Sea and Land Surface Temperature Radiometer, on board Sentinel-3A and Sentinel-3B satellites), MSI (MultiSpectral Instrument, on board Sentinel-2), are adopted. We demonstrate the potential of this web-based satellite-data-driven platform during the recent eruptive events on Stromboli and Etna. 
Towards teaching multi agent system the concept of risks and safety for actionable climate decisions
Authors: Hoang Lan , Smyrnakis Michail
Published: February 2023

Climate change is posing challenges for operating and designing critical infrastructure. Increasingly, AI has been used to enhance these decision making process. Reinforcement Learning has shown its advantages in dealing with difficult sequential decision making in games. When scaling to real life applications, their complexity and heterogenous nature potentially will require Multi Agent Reinforcement Learning (MARL) to provide adaptive capacity in a distributed manner. However, the human system is also characterised by the diverse belief of each individuals and groups - a feature that was captured in agent based models. AI/agent systems are evolving to work with human and become ubiquitous in real life/applications critical to society (such as health and transport). We argue that allowing belief transfer and full interactions across MARL actors in a three-layer model capturing data uncertainty, logical model and belief will help create a heterogeneous MARL system for better human-AI interaction that better aligns with human thoughts/values for actionable climate decisions.
A revised Database of CME characteristics from in-situ and remote observations
Authors: Mugatwala Ronish , Francisco Gregoire , Chierichini Simone , Napoletano Gianluca , Foldes Raffaello , Del Moro Dario , Erdelyi Robertus , Giovannelli Luca , de Gasperis Giancarlo , Camporeale Enrico
Published: February 2023

One of the goals of Space Weather studies is to achieve a better understanding of impulsive phenomena, such asCoronal Mass Ejections (CMEs), in order to improve our ability to forecast them and reduce the risk to ourtechnologically driven society. To do this, it is crucial to assess the application of theoretical models or even tocreate models that are entirely data-driven. The quality and availability of suitable data are of paramountimportance. We have already merged public data about CMEs from both in-situ and remote instrumentation inorder to build a database (DB) of CME properties. To evaluate the accuracy of such a DB and confirm therelationship between in-situ and remote observations, we have employed the drag-based model (DBM). DBM is ananalytical model that assumes the aerodynamic drag caused by the surrounding solar wind to be the primary factorin the interplanetary propagation of CMEs. Here, we explore the parameter space for the drag parameter and solarwind speed using a Monte Carlo approach to analyse how well the DBM described the propagation of CMEs. Withthis method, we validate and/or correct the initial hypotheses about solar wind speed, and also yield additionalinformation about CMEs. Using a data-driven approach, this procedure allows us to present a homogeneous,reliable, and robust dataset for the investigation of CME propagation.
Magma ascent in Australian intraplate basaltic volcanic provinces
Authors: Handley Heather , Cas Ray , England Thomas , Didonna Rosa
Published: February 2023

Australia hosts at least two active continental basaltic volcanic fields with Holocene eruption ages yet little is understood about magma ascent and mantle to surface ascent pathways and timescales in these regions. In this study we use textural and chemical information stored within minerals from two of the youngest volcanic eruptions in northeast and southeast Australia to investigate magmatic plumbing systems and magma ascent in Australia’s intra-plate volcanic fields. Volcanic rock samples from the three main eruptive phases at Mt Schank volcano in the Newer Volcanics Province, South Australia, reveal textural and mineralogical differences throughout the evolution of the eruption that correspond to variations in eruption style and the availability of external water. Crustal xenoliths (e.g., quartz and limestone) are abundant in the middle, maar-forming phase of the eruption. The lack of mantle-derived xenoliths and xenocrysts throughout the eruption, olivine compositions and sector and oscillatory zoned, euhedral clinopyroxene suggest a more stalled ascent pathway of magma compared to the mantle xenolith-bearing volcanoes in parts of the Victorian sector of the province. Skeletal olivine crystals and dendritic clinopyroxene microlites indicate moderate degrees of undercooling at Mt Schank during magma ascent. In northeast Queensland, interaction of magma with mantle xenolith’s are used to determine magma ascent dynamics. Disequilibrium and quench textures and chemical zoning patterns in olivine, clinopyroxene, orthopyroxene and spinel on xenolith margins and within host glass reveal a detailed and complex history of magma ascent.
The differentiation of pharmaceutical concentrations at two river bank filtration sites located in Warta River valley (Poland) - preliminary results
Authors: Dragon Krzysztof , Kruć-Fijałkowska Roksana , Drożdżyński Dariusz , Górski Józef
Published: February 2023

Emerging contaminants (e.g. pharmaceuticals, personal care products, drugs or pesticides) are increasingly detected in aquatic environments. The most apparent contamination source of river water pollution by pharmaceuticals are sewage treatment plant stations that discharge treated sewage effluent to the rivers. The river bank filtration systems (RBF) can effectively remove these contaminants from polluted river waters. The two RBF sites were examined for pharmaceuticals occurrence that are located in the Warta River valley (Poland): Śrem waterworks located upstream and Gorzów waterworks located downstream from Poznan city. The water samples for pharmaceuticals investigation (114 substances in total) were taken from the river and from four continuously pumped wells in each site. Two wells at a close distance from the river were chosen at each site (40-50 m) and two wells located at a greater distance from the river (70 m in Śrem and 110 m in Gorzów). A visible increase in pharmaceutical concentration was observed in the river water. The sum of pharmaceuticals concentration is 8151 ng/l in the Śrem location, while in the Gorzów location, the sum of pharmaceuticals concentration is 9142 ng/l. Most probably, this increase is caused by the influence of treated sewage effluent from Poznań city and towns and villages located along the river. A considerable differentiation in pharmaceuticals removal rate was observed. In the Śrem site the sum of pharmaceuticals concentration in wells is between 657 ng/l and 3290 ng/l, while in the Gorzów site despite the higher concentrations of pharmaceuticals in the river, the pharmaceuticals were detected only in one well located at a close distance from the river (two substances at a total concentration of 92 ng/l). The research presented proves a very different rate of pharmaceuticals removal even on sites located at similar hydrogeological conditions and demonstrates the necessity of its monitoring, especially in groundwater that is strongly influenced by river water contamination (like RBF sites). This work has received funding from the National Science Centre of Poland (grant no. 2021/41/B/ST10/00094).