bluuebunny/crossref_metadata_2025 huggingface dataset:
Mitigating the impact of dense vegetation on theSentinel-1 surface soil moisture over Europe
Authors: Massart Samuel , Vreugdenhil Mariette , Bauer-Marschallinger Bernhard , Navacchi Claudio , Raml Bernhard , Dostálová Alena , Wagner Wolfgang
Published: February 2023

The current generation of Synthetic Aperture Radars (SAR) has a high potential to retrieve surface soil moisture (SSM) at a kilometer-scale resolution. Research has shown that a change detection approach applied to the backscatter from the Sentinel-1 mission was able to yield a consistent kilometer-scale SSM product over Europe. This product is operational and available on the Copernicus Global Land Service (CGLS) website (https://land.copernicus.eu/global/). A known problem of the CGLS algorithm is its reduced performance over areas with dense vegetation. The combined influence of vegetation water content and geometry on the backscatter signal results in a lower sensitivity to SSM. This effect is especially observed over woody vegetation such as broadleaved or coniferous forests. In addition, a wet bias is detected in the CGLS SSM data during the growing season over land cover with seasonal variation of vegetation.This study utilizes the native resolution of Sentinel-1 in its interferometric wide swath mode (20x22m), resampled to a 20m pixel spacing, to assess three dense vegetation masks over Europe. The masks are derived from forest/tree cover maps based on Sentinel-1, Sentinel-2, or a combination of both. At 20m, the backscatter pixels are selectively filtered to discard the ones flagged as non-soil moisture sensitive. The masked backscatter at 20m sampling is then resampled to a kilometer scale and used as input for the CGLS change detection model algorithm. The resulting SSM product is compared to in-situ stations from the International Soil Moisture Network (ISMN) and with modeled soil moisture from ERA5-Land. The results sug gest that masking dense vegetation consistently improves the SSM signal over regions containing both forested areas, and croplands or grasslands.This study highlights the potential of masking non-soil moisture sensitive pixels at the native resolution of the Sentinel-1 backscatter. The results demonstrate the ability of high-resolution forest masking to mitigate the effect of dense vegetation on the CGLS SSM product.
Intercomparison of black carbon emissions from biomass burning using FLEXPART-WRF and ground-based observation in Alaska
Authors: Takigawa Masayuki , Taketani Fumikazu , Kanaya Yugo , Kobayashi Hideki , Kinase Takeshi , Zhu Chunmao , Kim Yongwon
Published: February 2023

Black carbon aerosols (BC) are emitted into the atmosphere by incomplete combustion processes of fossil fuels and biomass. Especially in the Arctic region, anthropogenic emissions from mid-latitudes (e.g., China) are transported by large-scale atmospheric circulation, and local emissions such as forest fires in boreal forests and gas flares are also considered to contribute significantly. In this study, we report on the result of intercomparison for Poker Flat, Alaska, especially focusing on the biomass burning emission inventories, which still show large differences among the inventories.Since April 2016, observations of BC and CO have been conducted at the Poker Flat Research Range (PFRR; 65.12°N, 147.49°W) in cooperation with the University of Alaska Fairbanks. The pathways of air parcels that were observed at PFRR were estimated using the Lagrangian particle diffusion model FLEXPART-WRF version 3.3. Backward calculations were performed for 20 days using 40,000 particles every 6 hours from April 2016 to December 2020. The meteorological field was calculated by a regional meteorological model (WRF) covering the Northern Hemisphere. The concentration and source attribution has been estimated using the residence time estimated by FLEXPART-WRF and emissions at each grid. ECLIPSEv6 and 6 different inventories (FINNv1,5 FINNv2.5(MODIS, MODIS+VIIRS), GFEDv4.1a, GFASv1.2, QFEDv2.5r1, FEERv1.0-G1.2) are used as the anthropogenic and biomass burning emissions, respectively.The concentration in the wintertime was generally well reproduced by the model, and it was estimated that anthropogenic emissions in Alaska (especially domestic and transport sectors in ECLIPSEv6) were dominant in that period. It was also found that there were very large differences in the contribution of biomass burning among inventories, especially in summer when the forest fires are active. Among them, GFEDv4.1 generally succeeded in capturing large fire events, especially in 2017 and 2019 (r=0.93). FINN inventories (version 1.5, version 2.5 with MODIS, and MODIS+VIIRS) tended to underestimate such eventual increases. In contrast, QFED sometimes overestimated concentrations at large events. If we assume the ‘event period’ as observed BC concentration exceeds the 95 percentiles for the whole period, the contribution of biomass burning was estimated to be higher at the event period (47%) than that during the non-event period (22%) in the simulation with GFEDv4.1.
What is Soil? – Addressing challenges due to interdisciplinary differences in the understanding of the word soil
Authors: Kurka Margit
Published: February 2023

Soil is defined in different ways, depending on the scientific discipline and a project’s scope. Understanding these differences is key to facilitate clear communication of subsurface conditions within interdisciplinary project teams and allow a comprehensive presentation of results towards a broader audience. The goal of herein presented research is to find differences and analogies in discipline-dependent definitions of soil, outline resulting challenges and suggest possible solutions.Definitions of the word soil were reviewed and analyzed in discipline-specific dictionaries of the Oxford reference dictionary series and international standards in regard to soil classifications (i. e. ISO and ASTM). Additionally, a survey was performed among professionals from different disciplines, including, but not limited to pedology, geology, engineering, geomorphology and chemistry. The survey aimed at finding out (i) how the word soil is defined by representatives of different disciplines, (ii) if there are divergent understandings between and within disciplines, (iii) if the various interpretations result in problems in interdisciplinary research and (iv) if and what kind of solutions are needed. The survey was filled out by sixty-two, mostly senior-level professionals from the private sector as well as universities and research institutions.Together with the results of the analysis of dictionaries and international standards, the answers to the survey showed that there are recognizable differences in the understanding of the word soil and that the majority of the survey participants sees a need to find solutions to how these can be addressed, especially for interdisciplinary projects. It was found that consense among the project team and a clear and comprehensive definition of soil, as it is understood within in a specific project, is required as a minimum from the on-start of a project. Additionally, based on the results of the definitions given in literature as well as in the survey, typical definitions of soil are categorized according to discipline (e. g. soil science, geology, engineering) and a comprehensive summary of terminology and vocabulary is presented in regard to possible synonyms for the word soil. Both approaches aim to assist in defining the word soil by providing a simple terminological framework, in which the project’s detailed definition can be integrated. This framework is flexible enough to be extended to other relevant disciplines (e. g. agricultural science, forestry, law).
Velocity dependent contact angle hysteresis of Rhamnolipid biosurfactant on peat
Authors: Duggireddy ReddyPrasanna , Arye Gilboa
Published: February 2023

Of all organic materials employed in soilless culture systems, peat is commonly employed as a substrate for crop production. However, the properties of peat may not provide optimal water availability and aeration conditions due to the development of substrates water repellency (WR). Although synthetic surfactants are used to ameliorate WR, their negative environmental impacts demand for an alternative approach. In the past decade, biosurfactants have drawn attention due to their low toxicity, biodegradability and, could potentially be used as an alternative. However, to the best of our knowledge, the rate and extent to which biosurfactant may reduce the contact angle (CA) form on peat surface is currently not investigated. The main objective is this study is to quantify the interplay between Rhamnolipid biosurfactant and WR peat. The study is involved with measurements of dynamic advancing and receding CA of aqueous biosurfactant on peat surface at different velocities and aqueous concentrations, using Wilhelmy plate method. For concentration ranged from 20 to 200 mg/l, the results clearly demonstrated a velocity dependence in the first cycle of advancing/receding CA, and significant reduction in CA hysteresis at higher velocities. In the four subsequent cycles, further reduction in CA and CA hysteresis could be observed for the Rhamnolipid demonstrating its aid to peat wettability. However, for water, higher advancing and receding CA was observed even after five consecutive cycles. In our presentation, the results of advancing and receding CA of Rhamnolipid and water on peat surface will presented and possible mechanism will be discussed.Keywords: Peat, water repellency, Biosurfactant, advancing and receding contact angle, velocity
Sensitivity analysis on synthetic 3D Deep ERT data for the example of Plombières, Belgium
Authors: Forth Yannick , Mreyen Anne-Sophie , Kemna Andreas , Hase Joost , Wellman Florian , Chudalla Nils , Nguyen Frédéric
Published: February 2023

The E-TEST project (Einstein Telescope EMR Site & Technology) investigates the feasibility of constructing a large Laser Interferometer (Einstein Telescope) in the Euregio Rhine Meuse. The aim of this instrument is to detect gravitational waves. To reach a sufficient noise attenuation the telescope will be built deep underground (more than 200 meters depth). The infrastructure consists of multiple tunnels and caverns spanning several kilometers. As with any large-scale infrastructure, the geological model, especially the existence and orientation of faults, is of large importance for hydrogeophysical and geotechnical characterization. At such depths, few near-surface geophysical methods are able to provide information with enough details. The application of large 3D Deep ERT surveys helps understanding the local geological settings and to identify important geological features but suffers from ambiguous interpretation. However, such imaging requires measuring dipoles independent of the injection system (such as the Fullwaver System by IRIS Instruments) in contrast to conventional ERT Systems, and due to the large covered area, coarsely spaced. This results in a drastic decrease in resolution when compared to classical ERT measurements.Here, we present a sensitivity analysis on a dataset based on the geologic setting in Plombières, Belgium to identify the impact of geology and survey setup on Deep 3D ERT surveys. The utilized geologic model was created with the Open-Source 3D structural geomodelling software GemPy and used as an input for forward modelling using the Open-Source modelling and inversion library pyGIMLi.
Quantifying the response of the Greenland ice sheet in a high-end scenario until 2300 from a coupled high-resolution regional climate and ice sheet model
Authors: Paice Chloë Marie , Fettweis Xavier , Huybrechts Philippe
Published: February 2023

The Greenland ice sheet comprises a volume of 7.4 m sea level equivalent and is losing mass rapidly as a result of global warming. It is widely thought that the ice sheet will exhibit tipping behaviour in a warmer climate. In other words, due to ice sheet – climate feedbacks (some of) its contribution to sea level rise may become irreversible once critical thresholds are crossed. This would severely affect the increasing number of people living in low-lying coastal areas worldwide. However, the current understanding of such thresholds and tipping behaviour is very limited, because most modelling studies up to date do not include (local) interactions or feedbacks between the ice sheet (topography and ice extent) and other climate system components (surface mass balance and atmosphere).To investigate the irreversibility of Greenland’s ice mass loss and the associated processes, we coupled our high-resolution Greenland Ice Sheet Model (GISM) with a renowned high-resolution regional climate model, the Modèle Atmosphérique Régional (MAR). The two-way coupling between both models provides a (more) realistic representation of (local) ice sheet – climate interactions for future ice sheet simulations.Like all regional climate models, MAR needs 6 hourly atmospheric forcing from a global climate model (GCM). Several coupled model runs with forcing from different GCMs are envisioned over the coming months and years. As they are computationally intensive, simulations up to the end of the century and beyond take several weeks to a few months to complete.The poster will present the preliminary results from our first coupled model run in an envisioned series of experiments: a two-way coupled MAR-GISM run forced by the IPSL-CM6 6 hourly output, which is available up to 2300. For this timescale, our coupled models can still be run in fully interactive mode, which means the information (surface mass balance and ice sheet extent/topography) between both models can be exchanged on a yearly basis. In addition to its long duration, the IPSL forcing is of particular interest as it is on the high end of the CMIP6 model ensemble projections regarding warming over Greenland. We thus expect the experiment to provide valuable insights regarding Greenland’s potential contribution to future sea-level rise and the associated ice sheet – climate interactions or feedbacks.  
Inversion of irrigation from satellite soil moisture data with a model based on PrISM (Precipitation Inferred from Soil Moisture)
Authors: Paolini Giovanni , Pellarin Thierry , Escorihuela Maria jose , Merlin Olivier , Bellvert Joaquim , Altes Victor , Villar Josep Maria , Petit Xavier
Published: February 2023

Accurate irrigation water management is crucial for maximizing crop yield and minimizing water waste. Remote sensing technology offers a promising solution for efficiently estimating irrigation water use at the field scale.In this study, we adapted the PrISM (Precipitation inferred from Soil Moisture) methodology to detect and estimate irrigation events from soil moisture remotely sensed data. PrISM is a well-known approach to correct precipitation estimates using soil moisture data. Its main application is to provide a near real-time corrected precipitation product. PrISM employs an antecedent precipitation index (API) formula coupled with a particle filter assimilation scheme for soil moisture.In this study, we adapted the PrISM methodology to estimate irrigation amounts from soil moisture. The methodology uses initial precipitation estimates and soil moisture profile to detect whenever water excess is present in the soil (not caused by precipitation) and estimates its amount, together with its uncertainty. The methodology does not need extensive calibration and it is adaptable to different spatial and temporal scales. A synthetic study was performed to investigate the effect of a degraded soil moisture signal in terms of temporal resolution (lowering the temporal sampling of the soil moisture time-series), spatial resolution (lowering the percentage of irrigated area in a pixel), and random noise (increasing RMSE values). Results from this study suggested that high spatial resolution is critical in order to avoid underestimation of irrigation amounts. Ideally, a field-level soil moisture (with more than 75% of the pixel irrigated) and a product with low RMSE (0.02 m3/m3) is required for precise estimations (in order to keep the error of annual cumulative irrigation below 20%). Temporal resolution has a lower impact, especially when an assumption on the frequency of irrigation events (deduced from the system of irrigation used at the field-level) is included in the algorithm.Consequently, the developed algorithm was applied to actual satellite soil moisture products at different spatial scales over the same area. Validation was performed using in situ data at the district level of Algerri-Balaguer from the study area in Catalunya, Spain, where ground-based irrigation amounts were available for various years. Additional validation was performed at the field-level at the Segarra-Garrigues irrigation district using in-situ data from a few fields where soil moisture profiles and irrigation amounts were continuously monitored. Our results suggest that PrISM can be used effectively to estimate irrigation from soil moisture remote sensing data and that this methodology could be potentially applied on a large scale, with the only limitation being the quality and spatial resolution of the satellite soil moisture product.
Identifying weather stress events from power system optimisation outputs
Authors: Grochowicz Aleksander , van Greevenbroek Koen , Bloomfield Hannah
Published: February 2023

The climate crisis and cost reductions in key technologies like solar, wind, and batteries are pushing an ambitious transition of power systems to renewables. This shift towards intermittent generation deepens the impact of weather and climate on the energy sector and can introduce new risks if not accounted for properly. Furthermore, as the ramifications of climate change are only to become even more noticeable, extreme events are expected to increase both in frequency and intensity. This in itself may lead to additional stress on renewable power systems, and recent research in energy meteorology relates these extreme weather events to so-called compound weather events, which are caused by more than one variable or component at the same time. However, compound events, their characteristics, and their risk for energy systems design are not yet well understood.In this work, we use outputs of a power system model to identify what meteorological drivers lead to difficult periods and stress in the European electricity system. For this we couple energy modelling and meteorology in an iterative process that can connect weather insights from a synoptic scale to features of a highly resolved representation of the European electricity network. We use the open energy system model PyPSA-Eur with four decades of reanalysis weather data to find cost-minimal solutions for a fully decarbonised European power system. Dual variables of these optima are used to identify difficult weather periods, understood as periods that drive system design and total cost. This use of dual variables of the optima - as opposed to studying weather data in isolation - allows for a more accurate identification of difficult periods, tailored to the energy system at hand. We then characterise the underlying weather conditions during those periods and assess their effects on the power system and energy variables. Due to the level of integration, some of these spread across the entire continent, whereas other phenomena remain local; they can be of varied intensity and persist on different time scales.Bringing an enhanced understanding of which weather events are difficult for energy systems, this approach can help to find obstacles for a transition to a fully renewable European power network, and inform how certain risks can be avoided or resilience strengthened.
Investigating transport and deposition of plant seeds in an alpine braided floodplain
Authors: Caponi Francesco , Conde Daniel A. S. , Vetsch David F.
Published: February 2023

Fluvial seed dispersal is a key mechanism controlling riparian vegetation dynamics along rivers. Riparian plant species produce a large number of lightweight seeds that are well adapted to be transported by wind and water over long distances both along channels and across floodplains. Water-mediated dispersal (hydrochory) is particularly sensitive on how water flows into secondary channels, low-flow velocity areas where seeds can land and eventually germinate. River-floodplain connectivity is thus a key factor to understand the spatial and temporal distribution of riparian vegetation and its modifications due to morphological changes.Despite our general understanding of hydrochory, the specific relationship between water discharge, river morphology and seed dispersal at the reach scale remains largely unexplored. To quantify this relationship, we investigated the transport and deposition mechanisms of plant seeds in a 1 km long reach of the Moesa river, Switzerland. The reach is characterized by a relative wide gravel bed floodplain that has been activated by multiple flood events in the past years. Vegetation patches and wood debris are sparsely located across the floodplain, creating a mosaic of morphological structures. We combine field experiments with mimics and numerical modelling to understand the influence of such structures and discharge variability on plant seed dispersal.We will show how specific river planform structures, such as confluences, riffles, pools, and log jams affect particles travel times, long-distance dispersal, and deposition patterns. We will be able to show how daily and seasonal fluctuations in the water discharge may influence these processes, considering some key seed morphological traits. Our results will be analyzed with connectivity metrics applied at the reach scale but at different temporal scales to disentangle the role of each underlying process. Overall, this study is expected to aid river managers to mitigate impacts of flow discontinuities such as dams and physical barriers on riparian vegetation dynamics and design better e-flows regulations favoring plant biodiversity and ecosystem resilience in the face of climate change.
Air Pollution knowledge Assessments (APnA) City Program in Asia and Africa
Authors: Guttikunda Sarath , Jawahar Puja , Dammalapati Sai Krishna
Published: February 2023

Representative emissions and pollution data is a critical requirement for supporting clean air action plans for cities. The data can be used for both long-term policy assessments and short-term pollution alert systems via modeling at various scales. In a data sparse environment, several assumptions are made, and several data resources are accessed to construct a reliable emissions and pollution modeling framework to support public and policy dialogue. These assumptions include interpolation of observations from one zone to another, extrapolation of operational conditions from one country to another, and utilization all available source and emissions data, complemented with open satellite retrievals and global databases with information on population, topography, land use, urbanization level, road network, locations of commercial and other points of interest, to compile a city’s spatially and temporally representative dynamic emissions map. The urban airshed inventory is maintained at a spatial resolution of 0.01 degrees (~1km) and with monthly and hourly temporal modulation suitable for chemical transport modeling. Here, we will present examples from the Air Pollution knowledge Assessments (APnA) program implemented for 60 Indian cities and expansion of the program to Balkan, Central Asian, and African cities, while addressing data gaps using emerging technology and big data feeds, combined with traditional meteorological and chemical transport modeling (WRF-CAMx) systems. Where available validation of the model results against available monitoring data from reference-grade and sensor networks is also included in the study. All the methodologies and data resources are accessible @ https://www.urbanemissions.info
Monitoring of subsurface runoff using absolute gravimetry in Taiwan
Authors: Chen Kuanhung , Hwang Cheinway
Published: February 2023

Calibration of subsurface runoff models in a catchment scale requires lots of observation sites/wells due to their scale difference. An observation site could fail to receive the required data due to variations in flow paths in rainfall events.  Therefore, establishing an effective monitoring site for subsurface runoff is a challenging task in hydrology studies. An alternative choice of monitoring equipment for subsurface runoff is using a terrestrial gravimeter. A terrestrial gravimeter has a broader sensible region than a monitoring well or several ERT (Electrical Resistivity Tomography) profiles. In addition, it takes the water(mass) itself as a tracer rather than using biogeochemical proxies and thus the quantity of runoff is estimated through observed gravity changes accordingly. Due to such advantages, in this presentation, we demonstrate the possibility of using gravimetry to monitor subsurface runoff in Taiwan. In one of the study sites at a proximal fan, our studies cover hourly, daily, weekly and monthly time spans, which encounter different intensities of rainfall over 1.5 years. The infiltration coefficient and percolation rate over 30 m length around our study site were determined in a severe rain event. In another study where we placed an absolute gravimeter in land subsidence regions, we estimated water storage changes at different sites after a wet season and rank their capability for being an artificial recharge pond. This presentation demonstrates the possibility of terrain gravimetry used in calibrating subsurface runoff models. We can picture that when quantum gravimeters are well-developed, high-temporal gravity measurements can assist to build a more accurate subsurface runoff model.
Novel investigative techniques on calcareous red algae build-ups: photogrammetry and CT-scan on Coralligenous from Marzamemi (Sicily)
Authors: Bazzicalupo Pietro , Bracchi Valentina Alice , Varzi Andrea Giulia , Fallati Luca , Savini Alessandra , Rosso Antonietta , Sanfilippo Rossana , Guido Adriano , Cipriani Mara , Basso Daniela Maria
Published: February 2023

Crustose coralline algae (CCA) form Coralligenous build-ups, which are ranked among the most important ecosystems in the Mediterranean shelf. Their skeletal framework hosts a variety of epi- and infaunal communities, which compete for space, contributing to the reef growth, or weaken the structure throughout bio-erosive activities. Investigating the relationship between the algal framework and these hosted communities is of extreme importance for ecological and palaeoecological purposes and monitoring goals. In this frame, the Italian project “CRESCIBLUREEF - Grown in the blue: new technologies for the knowledge and conservation of the Mediterranean reefs”, is aimed at investigating coralligenous reefs present in the  area off the Marzamemi village (South-East Sicily). Two build-ups have been collected: the first one at 37 m depth, from an area rich in coralligenous cover, and the second one at 36 m depth, from a submarine channel with sparsely distributed build-ups. We present here two new investigative techniques, so far seldom applied for the characterization of the Coralligenous. The first approach involved the quantification of the surficial cover, with the use of an image analysis software, both before and after the removal of their ephemeral canopy of unmineralized organisms.These models were then analysed using Object-Based Image Analysis (OBIA) algorithms that allowed the quantification of the surficial cover. Moreover, the analysis allowed the identification and categorisation of the organisms and materials on the external part of the build-ups, confirming the primary role of CCA as the major component of the samples. Afterwards, a Computed-Tomography (CT) scan was used - for the first time with Coralligenous - to reconstruct the inner structure of the build-ups and, together with radiocarbon dating, to infer the build-ups age and growth rate. CT analysis divided the framework into four main categories based on their density (Low, Medium, High and Ultra High). The structure’s cavities, either primary or developed through taphonomic processes, have been measured as porosity. The overall highly-resolved analysis points to a complex and nonlinear growth of the build-ups. The understanding of the structural density, porosity, growth rate, and surficial cover of the build-ups is shedding some light on the Coralligenous inception and growth. 
Report on our hybrid online/on-site field trip: Reconstructing Earth’s past climate from the sedimentary record.
Authors: Toy Virginia , Hawemann Friedrich , Kirilova Martina , Fenske Selina , Thomann Jan
Published: February 2023

In August 2022, we organized a hybrid course within the European Universities “FORTHEM” Alliance, which integrated virtual and on-site teaching techniques, testing various didactic concepts that allowed simultaneous, collaborative work by groups of on-line and on-site students.The field area is located in Molinos, Teruel province of eastern Spain, where a spectacular fossil-rich Jurassic-Cretaceous sedimentary sequence is exposed. The record mainly comprises marine units, which reveal changes in depositional environment that reflect paleoclimate changes. However, the area is extensively folded and faulted, and thus the tectonic deformation needs to be unraveled in order to determine the original depositional sequences.The two groups of students worked on the same challenges but on different scales. The exchange of field and digital observations between students facilitated a holistic understanding of the local geology. The on-site participants performed traditional geological mapping, focusing on definition of units with different sedimentological characteristics and fossil assemblages, definition of a stratigraphic sequence and characterization of the geological structures that affect its continuity. In the field, these students learned how to use a geologic database (StraboSpot) on their phones or tablets for easy exchange of data, and were given a short introduction in the use of UAVs and photogrammetry.On-line participants examined 3D models of outcrops and macrofossils, some constructed by the on-site participants, and carried out digital geological mapping with the aid of satellite images. They were able to provide a broader context for the outcrop-scale observations made by the on-site students, and carry out literature review for interpretation of the observed geological unit characteristics.The two groups met in a hybrid classroom by video conference from 8-10pm daily, to share the outcomes of their days’ work and obtain instructions for the next day. The greatest challenges were logistical, related to establishing and maintaining a classroom environment in a region of poor internet reception. This required large time input from the teaching staff. Nevertheless, in general, the blended learning approach yielded more significant outcomes than would have been possible with only one of the participant groups. Acknowledgements: PlaneSight Online: Phillip Seelos, Steffen Abe, Hagen Deckert. V3Geo models: Simon Buckley, Conor Lewis. Molinos geology: Till Sachau, Paul Bons, Carlos Martinez-Perez, Sonia Ros-French, Fabrizio Pepe.  
Predictability of moist convection through ensemble-based convective-scale data assimilation
Authors: Minamide Masashi , Posselt Derek
Published: February 2023

The development of atmospheric deep moist convection has been a challenging topic for numerical weather prediction, due to its chaotic nature of the development with multi-scale physical interactions. We recently found that greater than 20-km scale (as commonly known as meso-α (2000-200 km) and meso-β (200-20 km) scales) initial features helped to constrain the general location of convective activity with a few hours of lead time, but meso-γ (20-2 km) or even smaller scale features with less than 30-minute lead time were identified to be essential for capturing the spatiotemporal features of individual convection. To examine the potentials of ensemble-based data assimilation in capturing the individual convective development, as well as the subsequent development of severe weather events, we have conducted large ensemble convection-permitting data assimilation experiments with all-sky infrared satellite radiances from the latest-generation geostationary satellites. We found that the greater number of ensembles more effectively suppressed the spurious correlation for convective-scale data assimilation. However, the exact signals of convective development were not clearly captured in covariances even with thousands of ensemble members. These results suggest the potential limitation of the traditional “Eulerian” (i.e. physical grid-based) ensemble approach in convective-scale data assimilation.
Atmospheric Surface-Science Solar Simulator: An artificial solar irradiator for atmospheric photochemistry
Authors: Abdelmonem Ahmed , Fawey Mohammed H.
Published: February 2023

Solar simulators are indispensable tools and are usually linked to industrial applications, e.g. for determining the precise characteristics of solar cells. In photochemistry, usually UV light is used to stimulate the photo-interactions without particular attention to the spectral distribution. However, the spectral distribution has a non-negligible effect on the photoreaction pathways. To address photochemistry under atmospheric conditions, it is necessary to use an irradiation source that emits light equivalent to the solar light. Solar simulator based on LED technology is the best candidate for irradiating natural photo-interactive substances at specific wavelength and intensity. We have devolved a homemade compact light source that is based on LED technology, and emits light with wavelength starts from 275 nm with tuneable intensity, selectable wavelength, homogenous illumination, compact size and light weight. In this presentation we present the design and characteristics of our homemade solar simulator and demonstrate potential application in atmospheric surface-chemistry.
Labile substrate availability shapes interactions in a synthetic chitin-degrading soil bacterial community
Authors: Mohrlok Moritz , Alteio Lauren , Guseva Ksenia , Mor Galvez Julia , Salas Hernández Erika , Kaiser Christina
Published: February 2023

Chitin decomposition involves different extracellular enzymes and intermediate products, giving rise to complex social dynamics within chitin-degrading communities. These communities are therefore an ideal model system to investigate how complex organic matter is decomposed in soil, and what effect microbial interactions have on the decomposition process. We used a synthetic consortium consisting of three unrelated, potentially chitin-degrading soil bacterial strains (Paenibacillus alginolyticus, Paraburkholderia xenovorans and Solirubrobacter soli) to investigate how their interactions affect the decomposition of chitin, and how the availability of labile carbon influences these interactions.The strains were grown in monoculture and in all possible combinations on three different substrates (2% chitin, 2% n-acetylglucosamine (NAG, the monomer of chitin) and a mixture of 1% chitin and 1% NAG). Cumulative respiration as a community performance metric was measured over the course of two weeks using the MicroResptm system. We measured the concentration of chitin oligomers (chitobiose and chitotriose) at the endpoint using PMP-derivatisation and UPLC-Orbitrap MS. The final microbial community composition was assessed via 16s Amplicon sequencing and the 16s gene copy number was measured with droplet-digital PCR.Depending on the substrate, each strain showed distinct respiration patterns in monoculture, indicating different functionalities. We found both competitive and synergistic interactions in the strain combinations, depending on the involved species and available substrate. P. xenovorans dominated the other strains whenever the labile substrate (NAG) was added. The relative abundance of the less competitive strains (P. alginolyticus and S. soli) was however increased in the treatment containing only chitin compared to the NAG-treatments. Chitin was degraded a lot more when all three strains were included, as shown by both the maximum respiration and chitobiose concentration. All three strains were still detectable in this treatment, which was not the case when NAG was present from the beginning.Based on these results we assume that energy limitation forces synergistic interactions in this model community, increasing the chitin decomposition efficiency. Adding labile substrate alters these interactions, leading to the exclusion of less competitive strains. Our results emphasize how interacting bacteria of different functional groups can result in increased decomposition of complex soil organic matter and how the relationships between different species in a microbial community at a soil microsite might change based on the available substrate.
Estimation of geostationary satellite-based hourly daytime and nighttime AOD using machine learning
Authors: Song Sanghyeon , Kang Yoojin , Im Jungho
Published: February 2023

Atmospheric aerosols not only scatter or absorb solar radiation and affect the Earth’s radiation balance, which plays an important role in climate change, but also react with air pollutants and affect public health. In East Asia, due to naturally occurring Asian dust and anthropogenic air pollution resulting from urbanization and industrialization, continuous aerosol monitoring is crucial. Atmospheric aerosols are quantified by satellite- or model-derived Aerosol Optical Depth (AOD), which is defined as the extinction of solar radiation due to aerosols integrated over the atmospheric columns. In this study, machine learning-based models were developed to estimate daytime and nighttime AODs in East Asia using a geostationary satellite Geo-KOMPSAT-2A (GK-2A). Two machine learning approaches, random forest (RF) and light gradient boosting machine (LightGBM), were used in this study. Top-of-atmosphere (TOA) reflectance and brightness temperature (BT) from visible and infrared channels of GK-2A, meteorological data, geographical information, and auxiliary variables were used as input features to the machine learning models. The estimated AOD by the model was evaluated with ground-based AOD data from Aerosol Robotic Network (AERONET) by 10-fold cross-validation methods. To consider the model continuity of day and night and the model performance, two schemes using different combinations of input variables from GK-2A were examined: scheme 1 uses the same composition of input variables of BT for both daytime and nighttime for day-and-night continuity, and scheme 2 additionally uses TOA reflectance only during the daytime based on scheme 1 for high model performance. The LightGBM model (R2 = 0.78, RMSE = 0.1099 for scheme 1, R2 = 0.82, RMSE = 0.0993 for scheme 2) showed higher performance than RF model (R2 = 0.76, RMSE = 0.1213 for scheme 1, R2 = 0.76, RMSE = 0.1214 for scheme 2). Especially in LightGBM model, scheme 2 showed higher performance than scheme 1, and it is supported by the SHapley Additive exPlanations (SHAP) feature importance showing that TOA reflectance of visible and NIR channels of daytime of scheme 2 played an important influence on the model result. The estimated AOD from machine learning-based models were compared with GK-2A level 2 AOD and Copernicus Atmosphere Monitoring Service (CAMS) AOD forecast products. The spatiotemporal distribution in East Asia and time series trend at ground-based stations of estimated AOD show similar patterns to CAMS AOD forecast product, and generally agreed well with AERONET AOD. In conclusion, using the machine learning-based models proposed in this study, it is expected to contribute to continuous satellite-based aerosol and air quality monitoring over a specific region including nighttime, when geostationary satellite-based AOD retrieval is not available. 
Fire Weather Compromises Large Scale Afforestation Scenarios
Authors: Jäger Felix , Quilcaille Yann , Schwaab Jonas , Windisch Michael , Humpenöder Florian , Popp Alexander , Doelman Jonathan , van Vuuren Detlef , Frank Stefan , Lessa Derci Augustynczik Andrey , Havlik Petr , Narayan Kanishka Balu , Seneviratne Sonia Isabelle
Published: February 2023

Ambitious climate change mitigation scenarios typically include substantial amounts of carbon dioxide removal. Such negative emissions are projected by integrated assessment models (IAMs) to be partly provided by afforestation and reforestation. At present, only few IAMs incorporate climate information or natural forest disturbances of any kind on forest dynamics. In this study we show how exposed to fire weather the afforestation areas in the IAM projections are. We illustrate that IAM mitigation scenarios lack climate information to arrive at more realistic projections of carbon stocks in forests, more reliable land use distributions and more realistic forestation costs. In this work we combine forest fractional cover from IAM land use projections and fire weather index (FWI) from multi-model climate projections, based on the latest simulations assessed in the 6th assessment report of the IPCC. With this metric we show how forests and afforestation areas are and will be affected by fire weather. We find a strong upward trend of forest mean fire weather under a 2 °C warming scenario (SSP1-2.6 for both land use and climate, roughly compatible with 2.6 W/m² climate forcing) driven by afforestation more than by fire weather intensification, increasing exposure by 27 % by the end of the century. We argue that climate information, especially climate forcing of forest disturbances (fires, hot droughts, etc.) needs to be included in the modelling framework of IAMs. Such developments would enhance the consistency between emission and climate projections. While such efforts are underway, IAM scenarios currently available likely underestimate management cost of large scale afforestation or overestimate the effectiveness and hence the remaining carbon budget for positive emissions.
Fault Geometry Evolution During Hyper-Extension: Formation of Sub-horizontal Reflectors and Allochthons
Authors: Kusznir Nick , Gómez-Romeu Júlia
Published: February 2023

The geometry and evolution of extensional faults with large offsets during rifting leading to continental breakup is hotly debated. We examine, using flexural isostatic modelling, extensional fault geometry evolution within the hyperextended domain and the transition to exhumed mantle during magma-poor rifted margin formation. Flexural response modelling is used to predict the isostatic rotation and bending of the active fault plane and also the geometries of earlier faults within footwall and hanging-wall. Faults are assumed to have an initial steep dip of 60 at the surface. In the case of progressive in-sequence faulting, we show that sub-horizontal reflectors imaged on seismic reflection data, often interpreted as seismically active low angle faults, can be generated by the flexural isostatic rotation of faults with initially high angle geometry; modelling results show that there is no requirement for sub-horizontal active faulting. With increase in fault extension, flexural isostatic rotation results in the decrease in fault dip at the point of footwall emergence (i.e. the rolling hinge effect). The emergence angle  decreases to asymptotic values of ~ 30 , the precise value depending on Te and whether the initial fault geometry is listric or planar. Shallow emergent fault angles result in fault locking and the development of new high-angle short-cut fault segments within the hanging-wall. This results in the transfer and isostatic rotation of triangular pieces of hanging-wall onto exhumed fault footwall, forming extensional allochthons which our modelling predicts are typically limited to a few km in lateral extent and thickness. Our modelling results show that a sequence of extensional listric or planar faults with identical parameters (i.e. location, heave, surface dip, Te) produce very similar sea-bed bathymetric relief. This indicates that sea-bed relief cannot be used to distinguish listric from planar fault geometry. Listric and planar fault geometries do however produce distinct Moho and allochthon shapes. Extensional faulting and thinning of hyper-extended continental crust may eventually lead to mantle exhumation. Where extensional faulting is in-sequence, this results in a smooth bathymetric transition from thinned continental crust to exhumed mantle. In contrast out-of- sequence faulting results in a transition to exhumed mantle with bathymetric relief. We illustrate these model predictions with examples from seismic reflection data.
Response of Soil Moisture to Vegetation Restoration
Authors: Han Lei , Chang Yuqing , Liu Zhao
Published: February 2023

The effects of vegetation on soil water content are very complicated, and precipitation and evapotranspiration are the key contributing factors, which are more significant in spring (water conservation), summer (transpiration and infiltration), and autumn (infiltration). It is easy for irrational planting to result in soil water deficits in ecologically fragile arid regions because evapotranspiration is aggravated by leaves. Moreover, understanding the dynamic changes of soil water content is particularly important for the long-term sustainable development of re-gional ecology. Related research worldwide can be roughly divided into studies on vegetation, soil moisture, rainfall–erosion–infiltration, spatial variation, and climate change, which are car-ried out in typical regions around the world (such as Loess Plateau of China, the Mediterranean region and the United States). Dynamic climate changes, including variations in precipitation and surface temperature, should receive more scientific attention in further studies based on monitoring data in typical regions where climatic features are distinct.
Integrating MRI and modeling for Understanding Freeze-Thaw Processes in Saturated Soil and Sand
Authors: Snehota Michal , Sobotkova Martina , Princ Tomas , Sklenar Jan , Jex Martin , Benes Michal , Pohlmeier Andreas J
Published: February 2023

In this study, magnetic resonance imaging (MRI) was used to investigate the freezing and thawing process of a series of repacked samples of sand, soil, and sand-soil mixture. The samples were placed in a thermally insulated container inside a vertical bore MRI scanner and cooled by flowing cold gaseous nitrogen through a porous material at the top of the container. Temperatures were monitored in several points above the sample and at the sample surface, and a marker placed on the sample surface was used to measure sample deformation. A 4.7 T magnet was used for MRI and the Multiple-Slice Spin-Echo (MSME) and Zero Echo Time (ZTE) pulse sequences were employed to obtain the images. The contrast between the frozen and unfrozen water in the samples was given by the substantial difference in T1 and T2 relaxation times between the two states. The hydrogen in the frozen water does not produce any signal for both pulse sequences, thus all the signal represent the liquid/unfrozen water. The time-lapse three-dimensional (3D) imaging was performed during the entire course of the experiment with alternating use of the MSME and ZTE imaging techniques. Once the freezing front reached near the bottom of the sample, the thawing process was initiated by switching the inflow of cooling gas to the inflow of nitrogen at room temperature. The small changes in sand structure as a consequence of volumetric ice-water changes were studied using spatiotemporal analysis of the freezing front advancement and frozen water volume. The study detected interesting patterns of preferential thawing on the onset of thawing process in the case of sand. The MSME pulse sequence was successfully used to image the process in the sand, whereas the ZTE was capable of detecting water in the finer soil material. The data obtained in the study were used to develop two-phase ice-water simulation models to interpret the experimental results and better understand the freezing and thawing phenomena.