bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulating Evapotranspiration in Green roofs using a Multifractal approach
Authors: Ramanathan S Arun , Versini Pierre-Antoine , Schertzer Daniel , Tchiguirinskaia Ioulia , Perrin Remi , Sindt Lionel
Published: February 2023

AbstractSeveral equations and their simplified versions already exist for estimating evapotranspiration. Still, the practical difficulty in using them is that they contain too many variables and empirical parameters including some non-atmospheric vegetation-based ones which may not be appropriate for all plant types. Therefore, a simple empirical equation is suggested here to approximately estimate evapotranspiration loss in a deterministic manner as a function of the green roof’s water content, ambient air temperature, wind speed, relative humidity, and total net radiation flux. For nonlinear processes such as evapotranspiration clearly, such deterministic estimates are not representative of the extreme values observed in evapotranspiration losses. Therefore, a universal multifractal-based simulation procedure is proposed here to improve such deterministic estimates, so that the simulated evapotranspiration loss has realistic intermittency and temporal scaling behaviour, while preserving its diurnal variability. KeywordsMultifractals, Non-linear geophysical systems, Cascade dynamics, Scaling, Hydrology, Meteorology. 
CO2 net ecosystem flux in Krakow, Poland
Authors: Jasek-Kaminska Alina , Zimnoch Miroslaw , Chmura Lukasz , Bartyzel Jakub
Published: February 2023

Urban areas, with dynamically changing, varied sources and sinks in highly heterogeneous terrain, are one of the most complicated ecosystems to explore. Being also a significant CO2 net source, they contribute largely to uncertainty in local and global carbon balance calculations. Experimental data are required to verify existing CO2 emission inventories and to become a reliable input to climate models.Since 2021 an eddy covariance site has operated in Krakow, southern Poland. Site neighborhood includes various anthropogenic sources and sinks such as traffic, household heating, mainly with natural gas, and people themselves. On the other hand, a significant part of the source area is covered in green, with a municipal park and a number of home gardens.We are presenting a data record from the beginning of the measurements in February 2021 up to the present. As expected, the area is a net CO2 source, emitting on average around 7 kg of CO2 per square meter yearly. Clear diurnal and seasonal patterns of CO2 net flux were observed: morning and evening traffic peaks and negative values during the day due to active photosynthesis; also higher diurnal amplitude during the warm season but on average higher net CO2 emission in winter. Directional flux analysis reveals that 1) the highest emissions come from the area where individual households as well as busy traffic lanes are located; and 2) urban green areas have a potential to become a net CO2 sink during the day in all seasons except winter, however, mean diurnal emission on average remains positive.This project has been partially supported by the European Union’s Horizon 2020 research and innovation program CoCO2 under grant agreement No. 958927, "Excellence Initiative - Research University" program at AGH University of Science and Technology, and the subsidy of the Ministry of Education and Science.
Upper Arctic Ocean properties and water mass pathways during the year-round MOSAiC expedition in the context of historical observations
Authors: Vredenborg Myriel , Körtke Wiebke , Rabe Benjamin , Walter Maren , Tippenhauer Sandra , Huhn Oliver
Published: February 2023

The Arctic Ocean is characterized by complex processes coupling the atmosphere, cryosphere, ocean and land, and undergoes remarkable environmental changes due to global warming. To better understand this system of physical, biogeochemical and ecosystem processes, as well as recent changes was the aim of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) ice drift conducted year-round from autumn 2019 to autumn 2020. Here, we focus on the properties and circulation pathways of upper Arctic Ocean water masses that have been found to change in recent decades, likely in response to changes in sea ice, surface fluxes, and advection of air masses under Arctic amplification.We use hundreds of hydrographic profiles obtained with two Conductivity Temperature Depth (CTD) systems mounted to rosette water samplers from the drifting ship and at a remote location on the ice to investigate the properties of the polar mixed layer, halocline waters and warm water of Atlantic origin (“Atlantic Water”) in the Eurasian Arctic during the MOSAiC campaign. Additionally, we analyse chemical tracers (noble gases and anthropogenic tracers CFC-12 and SF6) measured from water samples taken with both CTD/Rosette systems to identify pathways of the water masses. We compare these observations with a comprehensive dataset of historical hydrographic data from the region to put our findings into a long-term context.We find a shoaling and thickening of the Atlantic-Water layer compared to historical observations, as well as signatures of interleaving at the core of the warm Atlantic Water that slowly get eroded during the drift. Along the MOSAiC track the hydrographic data show convective lower halocline waters that are typically formed north of Fram Strait and further downstream, as well as advective-convective lower halocline waters typically formed in the Barents Sea. We see a change in lower halocline properties in the eastern Amundsen Basin compared to historical observations, that could either be caused by local formation or a change in circulation. Further, we use the chemical tracers to investigate possible pathways and formation regions of the observed water masses.
Assessing the impact of marine and atmospheric heatwaves on droughts and fire activity in the Mediterranean region
Authors: Santos Raquel , Russo Ana , Gouveia Célia M.
Published: February 2023

Heatwave events have been increasing in frequency, duration, and intensity along the past decades, leading to severe impacts on ecosystems, human health and basic resources. These events are projected to continue increasing associated to anthropogenic activity. Moreover, droughts have also been more recurrent and intense, which can significantly impact agriculture and reservoirs’ water level and quality.Events of high temperature can occur both in the atmosphere and the seas. These warmer conditions, together with extremely dry episodes, have been affecting southern Europe and the Mediterranean region, which appear to be very sensitive to climate change. Additionally, the co-occurrence of droughts and heatwaves increases meteorological fire danger, rising the probability of wildfire occurrence and severity and resulting in economic, ecological, and even human losses.In this sense, it becomes fundamental to pay special attention to the role of compound events and synergies in fueling extreme fire outbreaks. Therefore, we propose to address this problem by analyzing the occurrence of both marine and atmospheric heatwaves and drought conditions over Southern Europe, East Atlantic and Mediterranean Sea (relying on ERA5 reanalysis), as well as the recorded wildfires (through MODIS burned area product).This work aims to address the occurrence of heatwaves (marine and atmospheric) and previous and contemporaneous drought episodes on a compound or cascading approach, estimating their contribution to the occurrence of extreme wildfires in the region in the last decades were analyzed on a seasonal scale. Acknowledgments: This study is partially supported by the European Union’s Horizon 2020 research project FirEUrisk (Grant Agreement no. 101003890) and by the Portuguese Fundação para a Ciência e a Tecnologia (FCT) I.P./MCTES through national funds (PIDDAC) – UIDB/50019/2020- IDL,  DHEFEUS - 2022.09185.PTDC
Why do seismic hazard models predict higher shaking than that observed historically?
Authors: Gallahue Molly , Salditch Leah , Lucas Madeleine , Neely James , Stein Seth , Abrahamson Norman , Hough Susan
Published: February 2023

Seismologists have recently begun assessing how well probabilistic earthquake hazard models and corresponding maps forecast shaking that actually occurs. Based on several metrics, we find the 2018 National Seismic Hazard Model for California appears to overpredict the level of high-frequency shaking shown by the California Historical Intensity Mapping Project (CHIMP) dataset of maximum observed shaking from the largest Californian earthquakes between 1857 and 2019. Understanding this overprediction, which is qualitatively similar to that observed in France, Italy, Japan, and Nepal, could lead to improved seismic hazard models for California and, by extension, worldwide.  There are three possible reasons for the discrepancy between observed and predicted shaking: hazard models may be biased high (examined here), historical data may be biased low, or misfit may arise by chance.

We examine several assumptions used in prior studies to determine if they cause the overprediction: 1) not considering site effects from variations in VS30 (time-averaged shear-wave velocity in the top 30m of soil), which could amplify or deamplify ground motions relative to the reference hazard model, 2) assuming the CHIMP data set is complete at magnitude 5 used as the minimum magnitude (MMin) in hazard calculations, and 3) the ground-motion to intensity conversion equation (GMICE) used to convert hazard model peak ground acceleration (PGA) measures to Modified Mercalli Intensity (MMI) values, consistent with the historic data, and 4) the use of mean versus median hazard. We show that incorporation of site-specific VS30 does not appreciably change the models and hence their consistency with CHIMP data, because at the short periods that control PGA and hence MMI, nonlinear deamplification due to increased soil damping largely offsets linear amplification due to low VS30.  Increasing MMin reduces but does not eliminate the discrepancy. Biases in current GMICE methodology appear to be major cause in the discrepancy. Mean hazard estimates, a modeling choice, predict higher ground motions than the median, which may reduce the discrepancy. We discuss the effects of each of these assumptions, which we expect to be consistent for other areas.
Remote sensing-based analysis for resilient agriculture in steep slope cultural landscapes
Authors: Straffelini Eugenio , Tarolli Paolo
Published: February 2023

The morphology of cultivated steep slopes is often the result of the layering of traditional agricultural practices. Their complexity and uniqueness result in high cultural-historical value, sometimes leading to the inclusion of landscapes on special protection lists (such as FAO-GIAHS or UNESCO). Agricultural terraces, adopted in different parts of the world for centuries, successfully combine cultivation needs with various valuable ecosystem services. However, cultivating in steep-slope areas is complex and requires a great effort in terms of human and economic resources (primary reasons for agricultural land abandonment). Moreover, their inherent complexity can become a problem during external disturbances. Heavy rainfall, increasingly frequent due to climate change, can generate surface runoff, soil erosion, terrace wall collapse, and landslides. Therefore, it is crucial to establish appropriate management plans to ensure the functionality of these cultural landscapes, guaranteeing agricultural production and territorial security. The advancement of new technologies in remote sensing, high-resolution mapping, and spatial analysis is opening new frontiers to support the management of such landscapes. A virtuous example is the SOiLUTION SYSTEM project (www.soilutionsystem.com; Rural Development Program for Veneto 2014-2020), carried out in the GIAHS site "Soave Traditional Vineyards" (Italy). It aims to develop innovative soil erosion risk mitigation solutions and improve vineyard management in hilly and mountainous landscapes. It involved high-resolution mapping of terraced landscapes based on low-cost methodologies (such as UAV-SfM photogrammetry) and identifying erosion-prone areas through specific algorithms. In addition, optimal soil management was researched to mitigate surface runoff and sediment production, including adopting biodiversity enhancement strategies. A modelling approach (validated by field measurements) was adopted for the analyses to maximize the reproducibility of the methodology in other contexts. An overview of the opportunities that remote sensing-based analysis can offer to steep-slope agricultural landscapes is proposed here. High-resolution mapping of hydroerosive processes is useful for preventing soil degradation, which, combined with sustainable management, helps to increase the resilience of such cultural and agricultural landscapes.
Sedimentation enhancing strategies for sustainable deltas: local adaptation to radical transformation
Authors: Dunn Frances E. , Cox Jana R. , Scown Murray , Du Haomiao , Triyanti Annisa , Middelkoop Hans , Minderhoud Philip S. J.
Published: February 2023

Coastal river deltas around the world are at risk of relative sea-level rise driven by global sea-level rise, human-induced compaction, and natural subsidence. Deltas naturally accumulate sediment when the accommodation space for aggradation is made available through relative sea-level rise, but this process is often prevented by human activities prohibiting flooding and therefore sediment deposition on delta land. Without sedimentation, deltas lose elevation relative to sea level, causing salinization and land loss. Sedimentation enhancing strategies aim to reduce or prevent these issues and improve delta sustainability by encouraging the natural delta-building process of sediment deposition, thereby combating relative sea-level rise by building new elevation.The implementation of sedimentation enhancing strategies presents both challenges and opportunities for delta system management from biophysical and societal perspectives. We explore the barriers to and enablers of sedimentation enhancing strategies from a transdisciplinary perspective to identify conditions for success. Key biophysical issues include rapid rates of relative sea-level rise, reduced fluvial sediment delivery, and lack of detailed knowledge about spatially and temporally variable sediment deposition, erosion, and coastal sediment delivery. From a societal perspective, conditions for successful sedimentation enhancing strategy implementation include social acceptance and local inclusion in decisions surrounding land use management, available finance including loss compensation, and institutional capacity, coordination, integration, and fit to the biophysical systems involved.We suggest that, while sedimentation enhancing strategies can be successfully employed at small scales to promote the achievement of sub-delta management goals, they can also be used as a springboard to transform delta management and environments to support long-term sustainability. This transformation requires re-integrating societal and biophysical systems rather than attempting to isolate and exclude them from each another. Delta-scale solutions will require imagination, engineering, and collaborative experimentation and learning to enhance resilience and reduce vulnerability in the face of environmental changes.
Evaluation of TROPOMI observations for estimating surface NO2 concentrations over Europe using XGBoost Model
Authors: Shetty Shobitha , Schneider Philipp , Stebel Kerstin , Kylling Arve , Koren Berntsen Terje , Hamer Paul
Published: February 2023

Nitrogen dioxide (NO2) is among the major air pollutants in Europe posing severe hazard to environmental and human health. The concentrations of surface NO2 are measured by ground monitoring stations which are fairly limited in representation and distribution. While NO2 estimates from chemical transport models are realistic, their complexity makes them computationally intensive. Satellite observations from instruments such as TROPOMI provide high spatiotemporal distribution of NO2. However, these instruments capture NO2 density only along the tropospheric column and not on the surface. Exploiting the availability of ground station measurements and spatially continuous information from TROPOMI, this study estimates surface NO2 concentrations over Europe at 1km spatial resolution for 2019-2021 using XGBoost machine learning model. While ground measurements are used as target reference features, satellite observations such as tropospheric column density of NO2 (from TROPOMI), night light radiance (from VIIRS), NDVI (from MODIS) and modelled meteorological parameters such as planetary boundary layer height, wind velocity, temperature are used as input features to the model. We find an overall mean absolute error of 7.87µg/m3, mean bias of -3.13µg/m3 and spearman correlation of 0.61 during model validation. We found that the performance of the model is influenced by NO2 concentration levels and is most reliable for predictions at concentration levels <40µg/m3 with a relative bias of <40%. The spatial error analysis also indicates the spatial robustness of the model across the study area. The importance of input features is evaluated using SHapley Additive exPlanations (SHAP), which shows TROPOMI NO2 being the most important source for the modelled NO2 predictions. Furthermore, SHAP values also highlight the role of VIIRS night light radiance in deriving finer detailed spatial patterns of surface NO2 estimates. Despite the complex non-linear relationship of the input features, the trained XGBoost model requires an average of 570 seconds to predict single day surface NO2 concentrations for the large study area of continental scale. Thus, this work evaluates the importance of TROPOMI data and reliability of machine learning models for estimating surface NO2 concentrations on a larger spatial scale.
Towards 2D flood forecasting with the HPC-enabled shallow water solver SERGHEI-SWE
Authors: Özgen-Xian Ilhan , Morales-Hernández Mario , Nones Michael , Caviedes-Voullième Daniel
Published: February 2023

Great advancement has been achieved in the last decade in 2D shallow water solvers for flood modelling. However, their application to physically-based flood forecasting continues to be experimental and not widespread. One of the central challenges towards operational flood forecasting with 2D solvers is their computational cost, which needs to be reconciled with the required lead times for forecasts to be of use. Nonetheless, these solvers have great potential to improve flood forecasting predictions, especially when it comes to flash floods, for which the established 1D and conceptual models may be significantly less applicable.The shallow water solver SERGHEI-SWE leverages on robust and efficient numerical techniques and is implemented for High Performance Computing (HPC), allowing its use in supercomputers and opening new opportunities in 2D flood forecasting. In this contribution, we present proof-of-concept simulations of several flood events in different catchment and river systems. We show that, with SERGHEI-SWE, it is possible to run very high resolution flood simulations for large hydrological systems with runtimes significantly lower than the event duration. This property is essential to enable operational forecasting with useful lead times.We run simulations on three river reaches, in the Italian river Po (125 km reach between Boretto and Pontelagoscuro) and in one of its tributaries, the river Secchia (20 km reach), and a meandering reach of the Ebro river through the city of Zaragoza. We also perform flash flood simulations on a 5 km2 district of Nice (France), and in a 50 km2 agricultural catchment in Jaén (Spain). The focus of the exercise is on the computational performance aspect and not on the model performance. The results show that high resolution simulations can be done with runtimes in the order of 100 times faster than real time, potentially allowing a very good forecast lead time. We also explore different combinations of computational resources, model resolution and ensemble size to explore the flexibility of the modelling approach under different computational systems, which may be available for flood forecasting.
In-situ trace-gas measurements from the ground to the stratosphere by an OF-CEAS balloon-borne instrument
Authors: Catoire Valery , Xue Chaoyang , Krysztofiak Gisèle , Jacquet Patrick , Chartier Michel , Robert Claude
Published: February 2023

Monitoring climate change and stratospheric ozone budget requires accurate knowledge of the abundances of greenhouse gases and ozone depleting substances from the lower troposphere to the stratosphere. An infrared laser absorption spectrometer called SPECIES (acronym for SPECtromètre Infrarouge à lasErs in Situ) has been developed for balloon-borne trace gases measurements.The complete instrument has been validated on the occasion of a flight in August 2021 in the polar region (Kiruna, Sweden) within the frame of the “KLIMAT 2021” campaign managed by CNES for the “MAGIC” project using concomitant balloon and aircraft flights. Results of this flight concerning CH4 and CO2 will be presented.
Intra-annual variability of carbon signature and transport in the North Atlantic Ocean
Authors: Bajon Raphaël , Carracedo Lidia , Mercier Herlé , Pérez Fiz F. , Velo Anton , Asselot Rémy , Thierry Virginie
Published: February 2023

The ocean is the largest carbon reservoir on Earth, and a major sink for the excess of CO2 (anthropogenic carbon) emitted to the atmosphere by human activities. Having removed about a quater of these emissions since the beginning of the industrial era, ocean’s key role in climate is particularty outstanding in the North Atlantic (NA). A combination of physical and biological processes makes the NA a key-role region for the natural and anthropogenic carbon uptake and storage, and hence for the global carbon cycle. Traditionally, the seasonal carbon cycle has been assumed to respond to natural variability, unnafected by the ongoing anthropogenic increase of atmospheric CO2. Recent model projections, however, point otherwise, yet observational evidence to verify these predictions is still missing. Here we examine seasonal cycle in dissolved inorganic carbon (DIC) and its (surface-2000 dbar) transport, estimated using in-situ data and neural networks, across the OVIDE (GO-SHIP A25) section, from 1993 to 2021 at a monthly resolution. Our results highlight that changes in temperature, dissolved oxygen and ocean circulation are key components driving the seasonal DIC variability. DIC concentrations are higher in years with strong winter mixing regimes (which bring more nutrient-rich waters to the surface, favouring photosynthesis, and more (remineralized) carbon back to the surface). Seasonal DIC transport fluctuations are found significant compared to the mean (e.g. +/- 25% in the upper branch of the meridional overturning circulation), putting into relevance that caution is needed if assuming that single-cruise occupations are representative of the annual state. We also observe a yearly variant seasonal imbalance, with a significant reduction over the past two decades in the upper branch of the meridional overturning circulation. These results underscore the importance of considering intra-annual variability in the North Atlantic's carbon cycle when addressing climate change.

 

 

 
European Petrophysics Consortium's Contributions to IODP
Authors: van Peer Tim , McIntyre Andrew , Rydzy Marisa , Le Ber Erwan , Team Members European Petrophysics Consortium
Published: February 2023

The European Petrophysics Consortium (EPC) is part of the ECORD Science Operator (ESO). EPC comprises the University of Leicester and Géosciences Montpellier and provides petrophysics staff scientists and petrophysicists, as well as expertise in downhole logging and core petrophysics programmes. The EPC has dedicated equipment for core logging and discrete measurements and is involved in data calibration, quality control, evaluation and interpretation of these data. The EPC is also involved in post-expedition activities, the preparation of upcoming expeditions, capability development, and training for IODP MSP expeditions and other key activities, including education and training.Over the past pandemic years, EPC has been active within expeditions and the community. EPC recognizes the importance of scientific drilling to palaeoclimate studies amongst other key topics, which is also reflected in our new science and operations roadmap: i) hired new staff members with a paleoclimate background; ii) developed a system for knowledge exchange between petrophysics and climate scientists, for instance via the ECORD summer schools; iii) renewed focus to include the development of measurement protocols and data analysis techniques to better serve the IODP community.EPC also has a website (http://www.le.ac.uk/epc) and will host the next ECORD Summer School Downhole Logging for IODP Science in person in Leicester in summer 2023. *European Petrophysics Consortium Team Members:Sarah Davies, Simon Draper, Tim van Peer, Andrew McIntyre, Marisa Rydzy (University of Leicester).Philippe Pezard, Johanna Lofi, Erwan Le Ber, Laurent Brun (University of Montpellier).
Iron Heating Across a Shock Observed by Solar Orbiter's Heavy Ion Sensor
Authors: Alterman Benjamin L. , Livi Stefano , Owen Christopher , Louarn Philippe , Bruno Roberto , D'Amicis Raffaella , Raines Jim , Lepri Susan , Spitzer Sarah , Dewey Ryan M. , Bert Christopher M. , Kistler Lynn , Galvin Antoinette , Rivera Yeimy , Horbury Tim , Trotta Domenico , Hietala Heli , Fauchon-Jones Ed , Gershkovich Irena , Verscharen Daniel ,   SWA and MAG Teams
Published: February 2023

Ion mass-per-charge and shock geometry determine both shock injection and the number of times a charged particle is reflected across a shock. As such, they govern charged particle acceleration and heating at shock. Solar Obiter’s Heavy Ion Sensor (HIS) observed a quasi-parallel CME-driven shock on March 11, 2022. HIS has sufficient time, mass, and charge resolution that it measured individual distributions of iron 8+ through 12+ on the variable timescale of 2 to 5 minutes. Using these 1D velocity distribution functions (VDFs), we report that the thermal portion of the Fe distribution heats across the shock, that this heating increases with Q/M, and the heating increases with distance downstream from the shock.
Carbon and nitrogen isotope stratigraphy of the Cambrian SPICE record in the UK
Authors: Warren Francesca , Gröcke Darren R. , Smith Martin , Sinnesael Matthias
Published: February 2023

Carbon isotope fluctuations have been determined globally within the late Cambrian with particular focus on the Steptoean Positive Carbon Isotope Excursion (SPICE) and the negative Hellnmaria-Red Tops Boundary/Top of the Cambrian Excursion (HERB/TOCE). These events correspond to global anoxia/euxinia, increased global weathering of organic rich material and a shift in dissolved inorganic carbon availability. We have extended our knowledge of SPICE and HERB/TOCE in the UK by conducting coupled carbon and nitrogen isotope analysis of cores (Merevale 1, 3) and quarry samples from Warwickshire (Oldbury Quarry). Our organic δ13C record replicates the changes previously published for SPICE in other global records. The bulk sediment δ15N record reveals a rapid positive excursion at the start of SPICE followed by a gradual decline through the remaining SPICE interval. We interpret the δ15N record as reflecting expansion of the oxygen minimum zone into the upper water column and replacing nitrification with denitrification processes. Denitrification is also supported during the SPICE interval from previously published iron-speciation data from the same cores. The negative δ13C HERB/TOCE record is coupled with a more subtle δ15N positive excursion. There is a paucity of organic carbon isotope records through this time interval, and hence a lack of global comparability is possible. The shift in δ13C and δ15N, coupled with changes in redox conditions in Cambrian oceans may also reflect biological shifts between red and green phytoplankton superfamilies making up the upper water column community. Additional research on organic carbon, nitrogen and redox proxies are required to ascertain the link between phytoplankton superfamily dominance, species richness, diversity and/or the onset of the Phytoplankton Revolution and the Great Ordovician Biodiversity Event.
Distributed right-lateral faults accommodating strain at the northern boundary of the Quito-Latacunga microblock of the Northern Andean Sliver
Authors: Harrichhausen Nicolas , Marconato Léo , Audin Laurence , Baize Stephane , Jomard Hervé , Lacan Pierre , Saqui Diana , Alvarado Alexandra , Mothes Patricia , Rolandone Frédérique , Ortiz Iván , Arcila Mónica
Published: February 2023

We present initial remote sensing and field data that suggest active distributed right-lateral faulting at the northern edge of the Quito-Latacunga tectonic block in northern Ecuador and southern Colombia. In this region, oblique subduction of the Nazca Plate beneath the South America plate induces northward migration of the Northern Andean Sliver (NAS), with respect to stable South America. Recent geodetic studies now suggest that this sliver is composed of several independent tectonic blocks, and the boundaries of these blocks are locations where we hypothesize crustal strain is accommodated. One of these blocks, the Quito-Latacunga block, is located in the densely populated Interandean valley of northern Ecuador and southern Colombia, and geodetic modelling predicts approximately 3 mm/yr of right-lateral strain at its northern boundary. A shallow July 25, 2022, MW 5.6 earthquake and damaging historical earthquakes along the northern boundary have illustrated the importance of understanding where this strain is being accommodated. We use available digital surface models (DSMs), local DSMs derived from Pleiades and SPOT satellite stereo-imagery, Interferometric Synthetic Aperture Radar (InSAR), Google Earth imagery, and a field survey to show that this boundary is distributed across several parallel northeast striking right-lateral faults. InSAR shows the July 25 event resulted in right-lateral surface displacement of > 20 cm along an east-northeast striking, steeply dipping fault. Offset volcanic soils and glacial moraines indicate recent earthquakes on two faults north of and subparallel with this rupture. Both faults overlap with the proposed area for the August 15, 1868, M 6.4–6.8 El Angel earthquake, suggesting either fault could be associated with this event. As the DSMs reveal a number of parallel strike-slip faults to the north in Colombia, further paleoseismic studies are needed in this region to delineate active faults and help define regional seismic hazard.
Combining geostationary and polar-orbiting satellite observations for studying the effect of INP on cold clouds
Authors: Alexandri Fani , Mueller Felix , Seelig Torsten , Tesche Matthias
Published: February 2023

Aerosol particles play a key role on Earth’s radiation budget and indirectly affect climate due to aerosol-cloud interactions (ACI), by acting as ice nucleating particles (INP) during the phase change in mixed-phased clouds. The forcing associated with the modification of cloud optical properties due to aerosol is yet insufficiently understood and represents a large uncertainty in future climate projections. Spaceborne remote sensing is a promising technique for quantifying ACI at a global scale and improving the performance of climate models.Height-resolved measurements of aerosol optical properties from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite are used to estimate the vertical distributions of INP concentrations. Individually tracked clouds from geostationary observations are then matched with the aforementioned concentrations in the vicinity of those clouds. Hence, a bottom-up data set of cold clouds is formed that can be stratified according to different aerosol and cloud properties to investigate the INP effects on ice-containing clouds.
Modeling the Impact of Global Warming on the Phenology of the Olive Tree in the Mediterranean region
Authors: Moumni Aicha , Abouseir Iman , Lahrouni Abderrahman
Published: February 2023

Nowadays, there is observable evidence from all continents and most oceans that many natural systems have been affected by regional climate changes, particularly by the increase in temperature. This increase has also influenced the phenology of plants. As the olive tree is a plant characterizing the Mediterranean area, it is obvious that its phenology could serve as an indicator of the impact of global warming on this area. In this study, we will use the PMP model and observations of the tree phenology to predict its flowering date, which is the most remarkable and easiest to observe development phase. On the other hand, we will study by simulation the impact of climate change on the flowering of the olive tree under the conditions of Haouz of Marrakech according to three contrasting scenarios of a possible climate change. The PMP software is a tool that facilitates the development of mechanistic phenological models. It is based on thermal time calculations. In the present work, we chose to test three thermal time models: the ForcTT model, the TT model and the UniForc unified forcing model. The first two models are two versions of Growing Degree Days (GDD) which corresponds to a linear relationship of forcing rate from the initial date t0 and a threshold temperature Tb. The third UniForc model is a sigmoidal function of temperature with the initial time t0 as an unknown. The tests were carried out using two databases, the first recorded in the meteorological stations of the Haouz region covering the period 1985 - 2012 and the second observed on the phenology of the olive tree in the Tassaout area for the periods 1986 - 1991 and 1997 - 2012. The first result obtained shows that the UniForc is the most robust model, it is therefore retained for the study of the impact of global warming on the olive tree.In the second part of this work we have chosen three scenarios of greenhouse gas emissions, SRES (Special Report on Emissions Scenarios), which explore future development paths (demographic, economic and technological). Each of the three scenarios chosen is based on a degree of temperature increase according to the imagined development pathway: the more optimistic B1 scenario (increase of 1.1°C), the medium degree A1B scenario (increase of 2.8°C) and the more pessimistic A1F1 scenario (increase of 6.4°C). All the simulations carried out according to the chosen SRES scenarios confirm that the increase in temperature leads to the advancement (earliness) of the flowering date, this advancement varies between 0.3 and 27.3 days. The higher the temperature increase, the earlier the flowering date. Thus, the flowering date of the olive tree is univocally linked to the type of greenhouse gas emission scenario chosen. Our results therefore confirm that this agronomic variable is a good indicator of the severity of global warming that could occur in the region.
Quantification of soil water balance components based on lysimeter measurements
Authors: Incze Dóra , Barcza Zoltán , Fodor Nándor
Published: February 2023

Among other factors, water availability strongly influences the amount and quality of crop yield. International interest in sustainable management of limited freshwater supplies has resulted in increased demand for measurements and modeling methods of cropland water balance components. In order to ensure adequate and sustainable crop production, it is necessary to understand the full water cycle of crop production including evapotranspiration. The purpose of the presented research is to quantify the soil water balance components of arable lands based on an experimental platform that can provide reference data for understanding processes and for model validation. Measurements by large weighing lysimeters are commonly used to test different evapotranspiration estimation methods. The data used for the research is provided by a weighing lysimeter station that was installed in 2018 at Martonvásár in Hungary. The station consists of twelve scientific lysimeters with soil temperature, soil water content, soil water potential sensors installed at several depths in the 2 m deep undisturbed soil profiles, and an ancillary meteorological tower. Every year since 2018 different crop varieties have been grown in six lysimeters. The other six lysimeters are not cultivated and are maintained vegetation-free (bare soil). The measurements are made with high accuracy and fine time resolution (1 reading per minute). Despite our best efforts, several types of errors occurred due to various reasons. The quality assurance and quality control (QA/QC) procedures used in the research help to minimize these errors in processing lysimeter datasets. A web application also contributes to a better interpretation of the data. The poster presents the first results with case studies focusing on wheat evapotranspiration.
Theoretical damage characterization and failure precursor recognition of the rock under uniaxial compression using infrared radiation
Authors: Liu Wei , Jaboyedoff Michel
Published: February 2023

The propagation of micro-cracks will cause the change of rock infrared radiation (IR) information, which provides the possibility to study the rock damage behavior and failure precursor using IR. In this paper, a new quantitative characterization method of rock damage evolution using IR is proposed. Firstly, the maximum classes square error and median filter methods are used to separate the temperature increment caused by crack development in IR images. On this basis, a new index, Damage Infrared Energy Response (DIER), is proposed to describe the crack evolution state and recognize the failure precursor of rock. It is found that the change characteristics of DIER and Acoustic Emission (AE) count are consistent: the DIER remains at the level in the compaction and elastic stages, rises gradually in the stable crack propagation stage, and increases sharply in the unstable crack propagation stage and fluctuates with the appearance of AE count “peak”. The change characteristics of DIER in unstable crack propagation stages can be regarded as the failure precursors of rock, about 84.10% of peak stress. Then, according to the continuum damage mechanics theory, the DIER is used to establish a theoretical characterization of the damage variable for rock, which can accurately describe the damage evolution process of the rock under uniaxial compression. The research results can provide experimental and theoretical support for monitoring slope and rock engineering stability by IR.
Performance of quantitative precipitation estimates in the complex terrain of the Peruvian Andes. IMERG V06 and the development of user-driven downstream applications.
Authors: Mantas Vasco , Caro Claudia
Published: February 2023

Quantitative precipitation estimates obtained from satellite data are of critical importance to research and applications. Not only is precipitation a key component of important water and energy cycles, but the immediate societal benefits offered by reliable products are undeniable.The complex terrain of the Peruvian Andes creates significant challenges to precipitation retrievals from space and to the establishment of dense ground monitoring networks. Nonetheless, for the communities and authorities of the region (home to nearly one third of the Peruvian population), this information is vital.The performance of the quasi-global Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG) V06 was assessed in Peru as part of Project e-Andes. Data covering the period between 2011 and 2020 were compared against gauge data from 35 stations maintained by SENAMHI. The gauges are located in the Andes and arid Pacific coast. Mean Pearson correlation values ranged from 0.34 (Early, Daily), to 0.80 (Final, Monthly), showing a clear improvement with temporal aggregation and from Early to Final runs. The trend was also observed across other metrics including Bias, RMSE, and MAE. Challenges to the validation of IMERG Final in sparsely gauged regions is also discussed. The study was an important component of capacity-building efforts and the development of user networks. The information provides important guidance for the development of monitoring services that incorporate both IMERG and gauge networks to create estimates with reduced bias.
Learning model parameters from observations by combining data assimilation and machine learning
Authors: Janjic Tijana , Ruckstuhl Yvonne , Legler Stefanie
Published: February 2023

Parametrization of microphysics as well as parametrization of processes in the surface and boundary layers typically contain several tunable parameters. The parameters are not observed and are only crudely known. Traditionally, the numerical values of these model parameters are chosen by manual model tuning, leading to model errors in convection permitting numerical weather prediction models. More objectively, parameters can be estimated from observations by the augmented state approach during the data assimilation or by combing data assimilation with machine learning (ML).If the parameters are updated objectively according to observations, they are flexible to adjust to recent conditions, their uncertainty is considered, and therefore the uncertainty of the model output is more accurate. To illustrate benefits of online augmented state approach, Ruckstuhl and Janjic (2020) show in an operational convection-permitting configuration that the prediction of clouds and precipitation is improved if the two-dimensional roughness length parameter is estimated. This could lead to improved forecasts of up to 6 h of clouds and precipitation. However, when parameters are estimated by the augmented state approach, stochastic model for the parameters needs to be pre-specified to keep the spread in parameters. Alternatively, Legler and Janjic (2022) investigate a possibility of using data assimilation for the state estimation while using ML for parameter estimation in order to overcome this problem. We train two types of artificial neural networks as a function of the observations or analysis of the atmospheric state.  The test case uses perfect model experiments with the one-dimensional modified shallow-water model, which was designed to mimic important properties of convection. Through perfect model experiments we show that Bayesian neural networks (BNNs) and ensemble of point estimate neural networks (NNs) are able to estimate model parameters and their relevant statistics. The estimation of parameters combined with data assimilation for the state decreases the initial state errors even when assimilating sparse and noisy observations.
Ocean-Atmosphere Observations from Uncrewed Saildrones and Gliders during the 2022 Atlantic Hurricane Season
Authors: Foltz Gregory ,   2022 NOAA Saildrone Hurricane Observations Team
Published: February 2023

During the 2022 Atlantic hurricane season, uncrewed systems were used in an innovative and coordinated effort to measure the upper ocean and air-sea interface inside and outside of tropical cyclones. The main objectives were to advance understanding of air-sea interactions in and around tropical cyclones and aid forecaster situational awareness, with the ultimate goal of improving tropical cyclone intensity forecasts. The uncrewed systems included seven saildrones and five underwater gliders that operated in the western Atlantic Ocean, Caribbean Sea, and Gulf of Mexico. Nearly collocated and simultaneous measurements were acquired by an underwater glider and saildrone through the eye of Hurricane Fiona south of Puerto Rico in September. Another saildrone was directed through Fiona after it had intensified to a Category 4 Hurricane in the North Atlantic, measuring sustained winds of 35 m/s and significant wave height of 15 m. Two other saildrones obtained measurements in Fiona when it was a tropical storm east of the Caribbean and as a Category 1 hurricane north of Puerto Rico. Later in September, after Hurricane Ian made landfall in southwestern Florida and then re-intensified to a hurricane east of Florida, a saildrone was directed through its center, measuring winds of 29 m/s and an air-sea temperature difference of 8 deg. C near the Gulf Stream. This presentation gives an overview of the 2022 effort and the data acquired, discusses challenges and lessons learned, and looks toward the future of uncrewed systems observations in tropical cyclones.
Potential and limitations of silica encapsulated DNA particles for hydro(geo)logy
Authors: Foppen Jan Willem , Bogaard Thom
Published: February 2023

Artificial DNA as a tracer in environmental applications has received increased attention in environmental science. In the last few years, we have been looking at the transport of silica encapsulated DNA particles (SiDNA), which we injected instantaneously or as a function of time in various saturated groundwater and surface water laboratory set-ups. These included batches, columns, sand tanks, open pipes, trenches, flumes, etc. The overarching aim of all these experiments was to understand SiDNA transport behaviour, to quantify the mass balance and to assess tracer-like capabilities of SiDNA. Our work indicated that in most applications, the shape of the breakthrough curve in terms of time to rise and time to peak were similar to the breakthrough curve of a conservative tracer. Specifically, SiDNA could be used to quantify dispersion in surface water transport, and to determine aquifer parameters, like hydraulic conductivity and porosity in multi-tracer experiments. However, this was accompanied by some uncertainty as in most applications, injected mass recoveries were less than 100% due to losses as a result of settling, river bed interactions, interactions with particulate matter (in surface water applications), straining, kinetic attachment and detachment (in groundwater applications). We conclude that SiDNA can be used when mass balance issues are relatively unimportant, for instance in case of complex flow path analyses or source tracking applications, whereby encapsulated artificial DNA with different DNA strands can be injected in several locations or can be added to the source. Currently, we think large scale field applications of SiDNA are still limited, due to required specific knowledge and analytical infrastructure, relatively high costs and limited SiDNA production scale. Once these issues are tackled, a truly unique multi-tracer will enrich the toolbox of hydrologists.