bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of Regional Climate Model IITM-RegCM4 for Kashmir Valley in India
Authors: Rashid Muhammed
Published: February 2023

Climate change caused by human activities is a major topic of discussion in today's world and is of great concern. Currently, India is experiencing several climate anomalies, including changes in the mean temperature and severe natural disasters due to climate change. Kashmir valley in Jammu and Kashmir, India, is considered one of the hotspots for such climate change risk due to its physiographic and geographic location. Therefore, it is essential to study the future trend in climate projections to take necessary mitigation and adaptation measures in this region. Currently, as part of the Coordinated Regional climate Downscaling Experiment (CORDEX), IITM Pune, uses a Regional Climate Model (RegCM4) to downscale global climate projection to a uniform 50 km resolution for the South Asia region. This RCM is driven by six global driving models, namely, CanESM2, CNRM-CM5, CSIRO-Mk3.6, IPSL-CM5A-LR, MPI-ESM-MR, and NOAA-GFDL-ESM2M. In the present study, the performance of the IITM-RegCM4 model coupled with their six driving models was evaluated for its capability to simulate the historical temperature projections over the Kashmir valley for the period of 29 years from 1977 to 2005. The outputs from six CORDEX model experiments of IITM, namely CanESM2-RegCM4, CNRM-RegCM4, CSIRO-RegCM4, IPSL-RegCM4, MPI-RegCM4, and NOAA-RegCM4, were compared with the IMD observational data for the region Srinagar and Qazigund. Comparative analysis of the projections from six models revealed that temperature projections from the CSIRO-RegCM4 model are more promising than all other climate model projections. Further, the future change in temperature in Kashmir Valley was estimated under the RCP 4.5 and 8.5 scenarios for the period 2011–2100. The results indicated an increasing trend in the mean maximum and mean minimum temperatures at both Srinagar and Qazigund stations under both scenarios compared to the base period (1977–2005). It was observed that under both scenarios, the annual mean maximum temperature is projected to increase from 1.6 °C to 1.7 °C during 2030s, 2.8 °C to 3.5 °C during 2060s, and 3.1 °C to 5.9 °C during 2090s. Similarly, the annual mean minimum temperature is projected to increase from 1.5 °C to 1.8 °C during 2030s, 3 °C to 3.9 °C during 2060s, and 3.4 °C to 6.1 °C during 2090s. The results and information generated from this study can be used for framing climate change adaptation and mitigation policies. The estimated variations in temperature can be used for adaptation planning in the Kashmir Valley.
Effect of agricultural measures on CO2-sequestration, N2O emissions and soil functions
Authors: Slier Thalisa , Westerik Dorien , Lesschen Jan Peter , Koopmans Chris , Schepens Jonas , Vervuurt Wieke , Velthof Gerard , van der Kolk Jennie
Published: February 2023

In light of the Paris Climate Agreement, the Dutch government has set mitigation targets for the emission of greenhouse gases (GHGs). One of the targets for the Dutch agricultural sector is to sequester an additional 0.5 Mton CO­2-equivalents per year on mineral agricultural soils, from 2030 onwards. Additionally, all Dutch agricultural soils should be sustainably managed by then. The research programme Smart Soil Use aims to determine to what extent it is possible to meet these goals. Since 2018, various projects and experiments investigated (sets of) measures or management practices that have the potential to store carbon (C). For 12 agricultural measures, C-sequestration potential was determined based on a combination of long-term field experiments in which soil C has been measured and C-modeling using the RothC model. Additionally, trade-offs of these measures with the GHG nitrous oxide (N2O) were monitored in the field experiments, using a static flux chamber setup. In addition, various soil parameters from the BLN (Soil Indicators for Dutch Agricultural Soils) were measured to assess the impact on other soil functions. Here, we present an integrative summary of the results, with for each measure, the C-sequestration potential, the possible trade-off with N2O emissions, and the consequences for soil functions, such as soil fertility and soil biodiversity. Based on the modelling results, it is possible to sequester an estimated 0.9 Mton CO2 yearly, using a combination of measures and assuming a maximum implementation of 100%. The first results show that certain measures increase N2O emissions, but that, overall, a possible trade-off to N2O emissions will not exceed the benefit of C-sequestration on the short term. Based on a qualitative analysis, most of the measures have a positive or neutral effect on soil functions.
Point-Cloud Class Separability: Identifying the Most Discriminative Features
Authors: Hess Max , Rheinwalt Aljoscha , Bookhagen Bodo
Published: February 2023

The global availability of dense point-clouds provides the potential to better assess changes in our dynamic world, particularly environmental changes and natural hazards. A core step to make use of modern point-clouds is to have a reliable classification and identify features of importance for a successful classification. However,  the quality of classification is affected by both the classifier and the complexity of the features which describe the classes. To address the limitations of classification performance, we attempt to answer the question: To what extent can a classifier learn the separation into different classes based on the available features in a given training dataset?We compare several measures of class separability to assess the descriptive value of each feature. A ranked list is generated that includes all individual features as well as all possible combinations within specific groups. Selecting high-ranked features based on their descriptive value allows us to summarize datasets without losing essential information about the individual classes. This is an important step in processing existing training data or in setting priorities for future data collection.In our application experiments, we compare geometric and echo-based features of lidar point-clouds to obtain the most useful sets of features for separating ground and vegetation points into their respective classes. Different scenarios of suburban and natural areas are studied to collect various insights for different classification tasks. In addition, we group features based on various attributes such as acquisition or computational cost and evaluate the benefits of these efforts in terms of a possible better classification result.
Quantifying the effect of snow and sea ice interactions on SnowModel-LG snow depth and density product
Authors: Merkouriadi Ioanna , Liston Glen , Salilla Heidi
Published: February 2023

Snow is a crucial component of the Arctic sea ice system. It dominates the exchanges of heat and light between the atmosphere and the ocean, with important physical and biological implications. To address the imperative need for more realistic representation of snow on sea ice, recent efforts have focused on reanalysis-based snow depth and density reconstructions. However, none of the recent snow products account for snow losses due to snow and sea ice interactions.This study quantifies the snow loss in snow-ice formation, and its effect in SnowModel-LG snow depth and density product. We coupled SnowModel-LG, a snow modeling system adapted for snow depth and density reconstruction over sea ice, with HIGHTSI, a 1-D sea ice thermodynamic model, to simulate snow-ice and thermal ice growth: SnowModel-LG_HS. We assumed that all negative freeboard would result in snow-ice formation. Pan-Arctic model simulations were performed over the period 1 August 1980 through 31 July 2021, and they were guided by observations where available. In SnowModel-LG_HS, snow depth was lower (domain average: 18%), and snow density was higher (2.3%) compared to SnowModel-LG. The differences were much larger in the Atlantic sector. Our simulations suggest that when snow models do not account for snow and ice interactions, snow depth can be significantly overestimated. In this talk we will discuss the magnitude of this overestimation in relation to the sub-grid parameterization of sea ice dynamics and their effect in snow redistribution over the ice floes. Sea ice dynamics (e.g. deformed ice formation), are likely an additional important snow sink that is not yet accounted for in snow models.Finally, we use our snow depth and density results from SnowModel-LG_HS to obtain sea ice thickness retrievals from CryoSat-2. A validation of these retrievals against Airborne Electromagnetic Measurements shows that SnowModel-LG_HS performed better when compared to SnowModel-LG and snow climatologies.  
Quantification of tephra impact on the road network: the example of lava fountains at Etna volcano in 2021-22
Authors: Mereu Luigi , Stocchi Manuel , Garcia Alexander , Prestifilippo Michele , Sandri Laura , Bonadonna Costanza , Scollo Simona
Published: February 2023

During explosive eruptions a large amount of tephra is dispersed and deposited on the ground with the potential to cause a variety of damage and disruption to residential buildings and infrastructure, including road networks. The quantification of the tephra ground load is, therefore, of significant interest to reduce environmental and socioeconomic impact, and for managing crisis situations during volcanic eruptions. Tephra dispersal and deposition is a function of multiple factors, including mass eruption rate (MER), degree of magma fragmentation, vent geometry, top plume height (HTP), particle size distribution (PSD) and wind velocity and pattern.In this work we quantify the tephra load deposited on the road network of the eastern flank of Mt. Etna, in Italy, during the sequence of lava fountains occurred between February 2021 and 2022. In particular we analyse those events generating volcanic plumes mostly dispersed towards the east-southeast direction and focus our study on the main road networks of some municipalities which are found in this section of Mt. Etna as Milo, Santa Venerina, Fleri.We applied the volcanic ash radar retrieval (VARR) approach to a large dataset of short-lasting and intense lava fountains detected by the X-band weather radar, located at about 32 km from the Etna summit, to retrieve the eruption source parameters. When the radar data were unavailable, we analysed images of the SEVIRI satellite and of the visible calibrated camera images of the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo.Two numerical models (TEPHRA2 and FALL3D) were used to simulate tephra ground accumulation. The model calibration was performed using data collected during an eruptive event in 2021. Tephra load was calculated for areas of particular interest as e.g., building roofs, infrastructure and road networks, requiring clean-up.We compute a cumulative in time of deposited tephra on some locations of the road network obtaining values ranging from 40-140 kg/m2, and from 110-480 kg/m2 in function of model considered and selected location.As a result, we produce fast estimates of total tephra deposited on specific infrastructures (e.g., roads) during sequences of eruptive events; such information can be a valuable input for quick planning and management of the short-term tephra fall hazard.
The use of multivariate Gaussian process emulation in making projections of land ice contributions to sea level rise
Authors: Turner Fiona , Edwards Tamsin , Rougier Jonathan
Published: February 2023

Better understanding changes in the cryosphere is key to predicting future global sea level rise, as is being done in the PROTECT project (https://protect-slr.eu). There are large uncertainties around how these changes will present over the next few centuries, with the Antarctic ice sheet being the component with the most varied predictions of potential mass change; statistical methods are required in order to quantify this uncertainty and estimate more robust projections.
We present here results from a multivariate Gaussian process emulator (Rougier, 2008; Rougier et al., 2009) of an ensemble of ice sheet and glacier models. We build projec- tions of contributions to global sea level rise over several centuries from the Antarctic and Greenland ice sheets, and the world’s glaciers, emulating them individually in order to better understand the biases and internal variability each model contains. Our use of an outer-product emulator allows us to model multi-variate output, resulting in projections over several centuries rather than a single year at a time. We predict changes for differ- ent Shared Socioeconomic Pathways (SSPs) to show how different emissions scenarios will affect land ice contributions to sea level rise, and demonstrate the differing sensitivity to parameters and forcings of the ensemble of models used.
References
Rougier, J. (2008). Efficient emulators for multivariate deterministic functions. Journal of Computational and Graphical Statistics, 17(4):827–843.
Rougier, J., Guillas, S., Maute, A., and Richmond, A. D. (2009). Expert knowledge and multivariate emulation: The thermosphere–ionosphere electrodynamics general circula- tion model (tie-gcm). Technometrics, 51(4):414–424.
Persistent shallow microseismicity near a glacier in southwestern Switzerland (Arolla VS) revealed by enhanced earthquake catalogs
Authors: Mesimeri Maria , Diehl Tobias , Herwegh Marco , Clinton John , Wiemer Stefan
Published: February 2023

On October 05, 2021 an Mw4.0 earthquake struck 6 km south of the village of Arolla, near the tongue of the Arolla Glacier. Almost one year prior to this earthquake, an M3.5 event occurred on November 08, 2020 in the same location. Both earthquakes were followed by a few aftershocks that were detected and located by the Swiss Seismological Service (SED). The unusually shallow depth of 1-2 km of these earthquakes, indications for a mostly thrust-type mechanisms within a region characterized by a predominantly extensional stress regime, and unusual high CLVD (50-70%) components of SED’s routine moment tensor solutions raised questions regarding the triggering mechanism. To understand and explain the possible existence of shallow thrust earthquakes in the area, we perform a thorough seismotectonic analysis that is based on enhancing the existing earthquake catalog of the SED and complementary moment-tensor solutions computed by multiple algorithms. The original SED earthquake catalog contains 83 earthquakes that occur between January 01, 2020 and December 31, 2021 and locate ~5 km around the two mainshocks. Using a deep learning based algorithm (EQTransformer), we detect additionally 253 events, thus the new catalog contains 4 times more earthquakes than the original SED bulletin. Absolute locations for the additional earthquakes are obtained using the probabilistic NonLinLoc method in combination with a recently updated Vp and Vs crustal 3D velocity model. In addition, we compute local magnitudes (MLhc) using SED’s standard procedure, in order to compile a homogeneous catalog consistent with the SED bulletin. The enhanced catalog events are used as templates for a match filtering scheme, which increased the number of detections by at least one magnitude order. Last, we relocate the final catalog using the double difference method towards obtaining a high resolution enhanced earthquake catalog. Spatially, the main cluster shows an intense seismic activity, stretched in N-S direction that matches the strike of the fault planes derived from moment tensor inversion. An additional cluster, that is not present in the SED bulletin locations, is identified next to the area were the aftershock activity of the two main events locates. Furthermore, the enhanced catalog shows a smother temporal evolution with more background events than previously recorded. Overall, we explore the possibility of fluid driven microseismicity that might be related to the nearby glacier. With our study we emphasize the importance of enhanced earthquake catalogs using both machine learning pickers and template matching algorithms. These approaches lead to unravel prior unmapped structures and improve our understanding of the seismotectonic regime in the study area.
Using available and incoming data for reducing and updating seismic source ensembles for probabilistic tsunami forecasting (PTF) in early-warning and urgent computing
Authors: Cordrie Louise , Selva Jacopo , Bernardi Fabrizio , Tonini Roberto
Published: February 2023

Tsunami urgent computing procedures quantify the potential hazard due to an earthquake right after its occurrence, that is within a few hours. The hazard is quantified by simulating the propagation of the tsunami waves in the sea, accounting for the uncertainty due to the scarce knowledge of the source parameters and wave modelling uncertainty.In the context of the European project eflows4HPC, a workflow is currently in development for tsunamis hazard urgent computing, which consists of the following steps: 1) Retrieval of information about the tsunamigenic seismic event (magnitude, hypocentre and their uncertainties); 2) Definition of an ensemble of seismic sources; 3) Simulation of seismic/tsunamigenic waves propagation for each scenario in the ensemble; 4) Results aggregation to produce an estimate of seismic and tsunami hazard, which also incorporates a basic treatment of modelling uncertainty. The ensembles cover the uncertainty on source characteristics and may consequently be very large (generally 10,000 to 100,000 of scenarios; Selva et al., Nat. Comm.), requiring very high computational resources for the urgent computing context. It is thus necessary to reduce the size of these ensembles to limit the number of simulations and to converge faster towards stable results of hazard calculation.We developed and tested several sampling procedures aiming to reduce the number of scenarios in the ensemble and, at the same time, to integrate the new incoming information as they become available (e.g. solutions for focal mechanisms, seismic or tsunami records). When applied to several past earthquakes and tsunamis (e.g., the 2003 Boumerdes and the 2017 Kos-Bodrum earthquakes), our novel sampling strategies yielded a reduction of 1 or 2 order of magnitudes of the ensemble size, allowing a drastic reduction of the computational effort. Also, the update of the ensemble based on the incoming of new data, which strongly reduce the uncertainty, yields to an update of the probabilistic forecasts without compromising its accuracy. This may result very important for mitigating the risk far from the seismic source, as well as improving the risk management by better informing decision making in a frame of urgency.
Comparison between polar motion excitation functions estimated from different models of geophysical fluids
Authors: Wińska Małgorzata , Śliwińska Justyna , Nastula Jolanta
Published: February 2023

The motion of the Earth's pole is excited by processes internal to the Earth's system – continually changing mass distribution in the geophysical fluids, i.e., atmosphere, ocean, and land hydrology. The mass redistribution and its movements within the Earth system excite the Earth's rotational changes mainly at seasonal or shorter timescales. The importance of atmospheric and oceanic angular momentum (AAM, and OAM, respectively) signals for polar motion excitation at seasonal and interannual timescales is well known. However, previous studies showed that the AAM, computed from different models of atmospheric pressure changes and winds, slightly differ from each other, especially in ­χ1 component. The discrepancies between various representations of ocean bottom pressure and currents from different OAM models are apparent too.An essential technique for understanding Earth's rotational changes is comparing the sum of mass and motion terms of AAM and OAM based on different geophysical models.Up to now, studies of geophysical excitations of polar motion containing AAM, OAM, and hydrological angular momentum (HAM) have not achieved entire agreement between geophysical (sum of AAM, OAM, and HAM obtained from the models) and geodetic (GAM, geodetic angular momentum; obtained from geodetic measurements of polar motion) excitation. There are many geophysical models of the atmosphere, oceans, and land hydrology that can be used to compute polar motion excitation. However, these models are very complex and still suffer from uncertainties in the process descriptions, parametrization, and forcing.Until now, no studies have shown that selecting one particular combination of AAM+OAM models provides the best correlation with GAM. The choice of AAM and OAM time series is usually entirely arbitrary and the only criterion considered is that the AAM model should be combined with the OAM model in which the forcing data is taken from the  AAM model used. This analysis of the most recent AAM and OAM series highlights that hydrological signals in polar motion differ significantly. The main goal of this presentation is to demonstrate that using different combinations of mass and motion terms of both AAM and OAM may have a considerable influence on the geophysical excitation of polar motion and its consistency with GAM. In this study, we extend the present understanding of the problem of inconsistency of mass and especially motion terms of different AAM and OAM models at seasonal and non-seasonal time scales.
Projected Changes in Türkiye's Wind Energy Potential Using Next-Generation Climate Models and Scenarios
Authors: Demiralay Zekican , Turp M. Tufan , An Nazan , Kurnaz M. Levent
Published: February 2023

Renewable energy is a cornerstone in reducing greenhouse gas emissions and, accordingly, mitigating changes in the global climate system. Wind energy is becoming more common among all renewable energy sources used for electricity generation in terms of generation capacity, rapid growth and technological maturity. The share of wind energy in Türkiye's total electricity production, whose installed capacity has been increasing in recent years, has nearly tripled in the last decade. However, given that wind energy potential varies with wind speed, even small changes in future wind patterns and characteristics can strongly affect future wind power generation dependent on projections. For this purpose, in this study, Türkiye's mid-future (2031-2060) wind energy potential is examined under optimistic (SSP2-4.5) and pessimistic (SSP3-7.0) scenarios. In the study, 0.25° x 0.25° spatial resolution CMIP6 models from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) dataset were used. The results point to regional differences in Turkey's mid-future (2031-2060) wind energy potential.Acknowledgement: This research was supported by DaVinci Energy Investments and Consulting Industry and Trade Inc.
Moho and LAB below the Western Alps from P and S Receiver Function analysis and joint inversion
Authors: Montuori Caterina , Monna Stephen , Frugoni Francesco , Piromallo Claudia , Vinnik Lev , Working Group AlpArray
Published: February 2023

We used the data from the dense, broadband AlpArray Seismic Network to derive a set of Receiver Function (RF) measurements on the Moho and Lithosphere-Asthenosphere Boundary (LAB) for a broad region encompassing the Western Alps and including the Ivrea Geophysical Body (IGB), a fragment of mantle emplaced in the lower continental crust. Our analysis fills an information gap since, in spite of numerous active and passive seismological investigations on the Alpine orogen, many of the observations focus on the Moho or the deeper part of the mantle, while reliable information on the LAB below the Alps is scarce. Moreover, our findings provide an additional contribution to resolving the debated topic of the existence of continuous or interrupted continental subduction below the Western Alps.We derive seismic velocity profiles of the crust-uppermost mantle below each of the 50 analyzed stations down to about 250 km depth, through the joint inversion of P and S RFs. We constrain the lateral variations of the Moho and LAB topographies across the colliding plates, and quantify the errors related to our measurements. Our observations allow us to considerably expand the published data of the Moho depth and to add a unique set of new measurements of the LAB (Monna et al., 2022). Our results yield a comparable thickness (on average 90–100 km) of the Eurasia and Adria lithospheres, which are colliding below the IGB; Eurasia is not presently subducting below Adria with vertical continuity. These findings suggest that there is a gap between the superficial (continental) European lithosphere and the deep (oceanic) lithosphere, confirming the discontinuous structure imaged by some seismic tomography models.the AlpArray Working Group: list on http://www.alparray.ethz.ch/home/Monna, S., Montuori, C., Frugoni, F., Piromallo, C., Vinnik, L., & AlpArray Working Group (2022). Moho and LAB across the Western Alps (Europe) from P and S receiver function analysis. Journal of Geophysical Research: Solid Earth, 127, e2022JB025141. https://doi.org/10.1029/2022JB02514
Thermodynamic assessment of simulations of the last deglaciation with an Earth system model of intermediate complexity
Authors: Racky Muriel , Trombini Irene , Pfeilsticker Klaus , Weitzel Nils , Rehfeld Kira
Published: February 2023

As we observe and expect severe changes in the Earth’ climate, the analyses of past climate state transitions is of major value for improving our Earth system understanding. Under this objective, the last deglaciation (~ 21 ka to 9 ka before present), the transition from the Last Glacial Maximum (LGM) to the Holocene, is an ideal case study. During this transition, the orbital configuration gradually changed and greenhouse gases have risen, which caused a sharp decline in northern hemisphere ice sheets and an increase in the global mean surface temperature.We create an ensemble of deglaciation simulations with a modified version of the Planet Simulator, an Earth system model of intermediate complexity (EMIC). We produce single and combined forcing simulations for further investigation from a thermodynamic perspective. The response to the transiently changing radiative forcing is investigated in terms of energy and entropy budgets of the atmosphere. Here, we focus on the deglacial evolution of the material entropy production (MEP). Its contributions represent the strength of major climate features such as the kinetic energy generation rate, vertical and horizontal heat transport and the hydrological cycle. Preliminary results show an increase of the global mean MEP from the LGM to the Holocene because of a strengthening of the hydrological contribution. In contrast, the relative importance of kinetic energy dissipation and turbulent heat diffusion in the boundary layer decrease. Our work can provide the basis for investigating the MEP as a diagnostic quantity with other models and for other climate state transitions.
An Exploratory Study on the Methodology for the Analysis of Urban Environmental Characteristics in Seoul City based on S-Dot Sensor Data
Authors: Kim Daehwan , Kim Kwanchul , Lee Dasom , Yang Jae-Hoon , Kim Seong-min , Park Jeong-Min
Published: February 2023

This paper identifies the aspects of living environment elements (PM2.5, PM10, Noise) throughout Seoul and the urban planning characteristics that affect them by utilizing the big data of the S-Dot sensor in Seoul, which has recently become a hot topic. In other words, it proposes a big data-based research methodology and research direction to confirm the relationship between urban characteristics and environmental sectors that directly affect citizens.  The temporal range is from 2020 to 2022, which is the available range of time series data for S-Dot sensors, and the spatial range is throughout Seoul by 500m*500m GRID. First of all, as part of analyzing specific living environment patterns, simple trends through EDA are identified, and cluster analysis is conducted based on the trends. After that, in order to derive specific urban planning characteristics of each cluster, basic statistical analysis such as ANOA and OLS, and MNL analysis were conducted to confirm more specific characteristics. As a result of this study, cluster patterns of PM2.5, PM10, noise and urban planning characteristics that affect them are identified, and there are areas with relatively high or low long-term living environment values compared to other regions. The results of this study are believed to be a reference for urban planning management measures for vulnerable areas of living environment, and it is expected to be an exploratory study that can provide directions to studies related to data in various fields related to environmental data in the future.
Simulating snow drift in WRF – First results and future plans of a novel module
Authors: Saigger Manuel , Mölg Thomas , Schmid Christina , Sauter Tobias
Published: February 2023

We present a new framework to simulate snow drift in the Weather Research and Forecasting (WRF) model. Here, we show the basic structure of the module, first results of several test applications as well as our future plans with the model.In past studies, wind-driven redistribution of snow has been shown to greatly influence the spatial structure of snow accumulation. Additionally, sublimation from blowing snow particles can - depending on the atmospheric conditions - act as an important process for mass loss of snow. Hence, to improve our understanding of snow accumulation an accurate representation of snow drift in our models is needed.Our new module calculates snow drift inside WRF which allows for a more direct coupling to the fields of wind and turbulence. Additionally, with our approach drifting snow sublimation can also feed back into the model’s fields of temperature and moisture and consequently the wind field.The model has been tested extensively both in idealized and realistic settings in the Alps and provided physically reasonable results consistent with our basic understanding of drifting snow.With the model we intend to get a deeper understanding on the role of snow drift for glacier mass balance. Our future plans with the model are twofold. For specific case studies high-resolution simulations of drifting snow events will be carried out. Apart from that we plan to expand the evaluation to a (multi-)seasonal perspective. In order to keep a high degree of complexity while staying computationally feasible (also with regard to climatological time scales), we plan to train a deep-learning model on the WRF-simulated fields of snow drift. We intend to use this trained model to reconstruct high-resolution seasonal snow accumulation including drifting snow.
Recent heavy metal pollution from the territory of the former Soviet Union (FSU) – ice core records and emission estimates
Authors: Eichler Anja , Nalivaika Petr , Jenk Theo , Singer Thomas , Kakareka Sergey , Kukharchyk Tamara , Eyrikh Stella , Papina Tatjana , Plach Andreas , Schwikowski Margit
Published: February 2023

Atmospheric heavy metal pollution caused by metal smelting, mining, waste incineration and fossil fuel combustion presents a significant issue for human health and the environment. Anthropogenic emissions from the territory of the former Soviet Union (FSU) considerably influenced atmospheric concentrations of heavy metals. However, due to scarce monitoring data and fragmentary reporting, emissions quantities from this region are not well-known and it is even unclear if emissions decreased or increased after collapse of the Soviet Union. This is underlined by the fact that existing ice-core records and emission estimates based on national inventories for the FSU reveal an opposing trend for the most recent ~30 years. Here we present new records of post-Soviet Union anthropogenic heavy metal  emissions (Bi, Cd, Cu, Pb, Sb, Zn) derived from three ice cores; from the Mongolian Altai (Tsambagarav ice core, period 1710-2009 AD) and the Siberian Altai (two Belukha ice cores, period 1680-2018 AD), covering a large regional footprint of emissions. The major source region of air pollution arriving at the Altai is primarily the territory of the FSU except for the eastern-most Siberian parts. Heavy metal concentrations at ultra-trace levels in the studied ice cores were analysed using inductively coupled plasma sector-field mass spectrometry (ICP-SF-MS). These records were complemented with new heavy metal emission estimates based on the available inventory data (1975-2015 AD) to derive a robust reconstruction of recent FSU heavy metal emissions. Consistent with the emission estimates, ice-core concentrations of Cd, Cu, Pb, Sb, Zn during the 2010s correspond to 20-40% of the maximum values in the 1970s and are comparable to their 1940s-1950s levels. A similar magnitude was also estimated for the decrease in Bi between 1975 and 2015, however, ice-core concentrations do not show a substantial downward trend.
Magnetotelluric data across Ciomadul volcano and the Perşani Volcanic Field — constrains on the nature and structure of the magma storage system
Authors: Comeau Matthew Joseph , Hill Graham J. , Kovacikova Svetlana , Kamm Jochen , Lukács Réka , Seghedi Ioan , Szabolcs Harangi
Published: February 2023

Ciomadul volcano, located at the south-eastern terminus of the Carpathian volcanic arc (Romania), is the youngest volcano in eastern-central Europe, with the last eruption occurring at 32 ka. Petrological and geophysical constraints indicate a melt-bearing silicic crystal mush body beneath Ciomadul, approximately 5–20 km below surface. This suggests that long-dormant or seemingly inactive volcanoes may have potentially active magma storage systems. However, the geometry and size of the magma storage region is unknown. Understanding the nature and structure of the volcanic plumbing system is crucial to understanding the evolution of the system, as well as to assess the hazard potential.In this presentation, we will report on 41 new magnetotelluric measurements acquired in 2022. The survey design consists of an irregular grid with dimensions of approximately 75 km by 75 km, centered around Ciomadul in the corner of the south-eastern Carpathian Mountains. This makes an array suitable for three-dimensional modelling. A 100 km long NW-SE transect across the array has a measurement spacing of less than 15 km.The newly acquired data complement previous measurements (recorded in 2010) near Ciomadul and Băile Tuşnad within an area of approximately 5 km by 10 km. The new data extend westward to the Perşani volcanic field (Racoș, Homorod), about 40 km west of Ciomadul, towards the Transylvanian Basin, and to the south-east to the edge of the seismically active Vrancea zone, often attributed to the descent of a slab, more than 50 km south-east of Ciomadul, towards the Focșani Basin. Both regions are targets for future measurement campaigns.Recordings were carried out at each location for approximately 1–5 days. The data typically had reliable periods of up to 1,000–4,000 s. The data are not homogenous and have characteristics of three-dimensionality. At some locations, cultural electromagnetic noise contaminated the signals and degraded the data; thus choosing appropriate locations for measurement was critical. Estimating local and inter-station transfer functions required special care, such as applying data pre-selection schemes and manual time windows, in addition to standard approaches including using robust statistics and the remote reference method. Overall, the preliminary analysis is encouraging and the results show that it is possible to obtain usable magnetotelluric data in this region.
Aeolian sand transport and beach morphology influenced by temporal beach grain size variability in a microtidal environment
Authors: Lamy Antoine , Robin Nicolas , Hesp Patrick , Smyth Thomas A.G. , René Camille , Feyssat Pierre , Hebert Berthil
Published: February 2023

Onshore wind is the primary driver of sediment transport allowing the construction of coastal dunes. In contrast, offshore winds result in the seaward export of sediment inducing a loss of the terrestrial beach sedimentary budget. Many parameters limit aeolian sand transport such as moisture, beach slope, beach length, vegetation and sediment characteristics. Although the impact of grain size on wind transport is well known, few studies have focused on its temporal variability. The temporal evolution of grain size characteristics is particularly important in microtidal environments where the relatively small tidal range minimises the mixing of the beach sand and winds have a strong impact on grain size sorting, resulting in the coarsening of the beach grain size. Leucate beach (SE, France) is a wave-dominated microtidal environment, subject to a strong offshore wind (72 % of the annual time and 17.5 % over 10m/s) which made this site suitable to this study. During the 19 months of meteorological surveys, 5 field measurements campaigns of 1 to 3 days were conducted. For this purpose, wind processes (intensity and direction); aeolian sand transport (24 runs), morphological variations of the beach-dune system and also many sub-surface sediment samples were collected.The results show a large temporal variability in beach grain size ranging from medium to very coarse sand in relation to wind and wave conditions. Aeolian processes produce a coarser beach grain size at days/months scale, whereas short marine storms (day) induce a mixing and finer  beach grain size, resulting  in very different  aeolian sediment transport values for  similar incident wind conditions. For example, with a wind speed of 10 to 14 m/s the measured sediment flux ranged from10 kg/m/h (coarse beach grain size) to 50 to 150 kg/m/h (medium beach grain size). Morphological variations of the upper beach surface are not significant when the sand is coarse but can cause lower by the upper beach surface by 0.5 m when the sand is composed of medium-sized. The time scale of the temporal beach grain size variations is closely related to the frequency and intensity of marine and wind storms. This study quantifies the effect of the beach grain size variability on the aeolian sand transport and thus the morphological changes of the beach. We conclude that because of their importance in the temporal variability of sediment size and the inherited sedimentological framework of the beach, it is crucial to take into account marine and aeolian processes to refine the predictions of wind transport rates. This confirms the need in a microtidal environment, to obtain beach grain size temporal data to better understand the aeolian sediment transport rates affecting a study site and not underestimated its impact when calculating transport rates with empirical formulas and numeric models.
Numerical model of multi-phase porous, mush, and suspension flows in magmatic systems
Authors: Keller Tobias , Wong Ying-Qi
Published: February 2023

Magmatic systems in the Earth's mantle and crust can range from melt-poor partially molten rock to trans-crustal magma mushes with ephemeral lenses of melt-rich suspensions. Most process-based models of magmatic systems, however, are limited to two-phase porous flow at low melt fractions (<20%) or suspension flow at high melt fractions (>60%). A lack of formal extensions to intermediate phase fractions has long hindered investigations into the dynamics of mush flows. To address this knowledge gap and unify two-phase magma flow models, we present a two-dimensional system-scale numerical model of the fluid mechanics of an n-phase system valid at all phase fractions. The numerical implementation uses a finite-difference staggered-grid approach with a dampened pseudo-transient iterative algorithm and is verified using the Method of Manufactured Solutions. Numerical experiments replicate known limits of two-phase flow including rank-ordered porosity wave trains in 1D and porosity wave breakup in 2D in the porous flow regime, as well as particle concentration waves in 1D and mixture convection in 2D in the suspension flow regime. In the mush regime, numerical experiments show strong liquid localisation into pockets and stress-aligned bands. A tentative application to a three-phase, solid-liquid-vapour system demonstrates the broad utility of the n-phase general model and its numerical implementation. The model code is available open source at github.com/kellertobs/pantarhei.
Two decades (2003-2021) of storage changes in the soil water and groundwater of CONUS
Authors: mehrnegar nooshin , Schumacher Maike , Jagdhuber Thomas , Forootan Ehsan
Published: February 2023

The climate change along with anthropogenic water use have been affecting the (re)distribution of water storage and water flux across the Continental United States (CONUS). Understanding these changes requires tools that provide a big picture of the processes that drive these changes. These processes are implemented in this study by combining remote sensing data with available modeling techniques, where the data contains a sample of hydro-climatological signals and models reflect our understanding of these processes. Time series of Terrestrial Water Storage Changes (TWSC) from the Gravity Recovery and Climate Experiment (GRACE, 2003-2017) and its Follow-on (GRACE-FO, 2018-2021) are integrated into the W3RA water balance model within CONUS, where the model is run at 9-km resolution using ERA5 forcing data. The gap in the GRACE and GRACE-FO TWSC products is filled following https://doi.org/10.3390/rs12101639. To achieve the best possible statistical combination, the Markov Chain Monte Carlo-based Data Assimilation (MCMC-DA) approach (https://doi.org/10.1016/j.scitotenv.2020.143579) is applied to use GRACE and GRACE-FO TWSC as a vertical integration constraint to update W3RA's individual water storage estimates. This approach rigorously accounts for the uncertainties of model and observations.The outputs of MCMC-DA are evaluated using in-situ USGS groundwater level data and the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture product. The results indicate changes in trend and seasonality of water storage variations, for example, in southwestern (California and Nevada), southeastern (including Florida, South and North Carolina, Virginia, and Georgia), and south-central CONUS (including Texas, New Mexico, Colorado, Kansas, and Oklahoma). MCMC-DA improves the estimation of soil water in regions with high forest intensity, where ESA CCI and models reveal difficulties in capturing the soil-vegetation-atmosphere continuum. The representation of El Nino Southern Oscillation (ENSO)-related variability in water storage are found to be considerably improved after integrating GRACE(-FO) into W3RA. This new hybrid approach is found efficient for understanding the linkage between the climate variability and large-scale hydrological processes.Keywords: CONU; Data Assimilation; Bayesian Method; MCMC; GRACE(-FO); W3RA; groundwater storage; soil water storage; USGS; ESA CCI.
Development of an operational seasonal forecast in Colombia and Peru by mean of statistical downscaling of the SEAS5-Copernicus data
Authors: Rea Gloria , Galuzzo Daniele , Formenton Marco
Published: February 2023

Enel, as most of the Energy Players, has an important exposure on weather risk due to the indirect effect of the power demand and to the direct effects on renewable production. A large component of such risk comes from the hydroelectric production, this is especially true in Southern America where, in some countries, it can represent up to 70% of the total production. We present a practical development of an operational chain to extract information from the seasonal forecasts produced by SEAS5. It works on some catchments in Colombia and Peru with the aim to provide an ensemble forecast of monthly precipitations at a high resolution from the fields at low resolution provided by Copernicus. To produce the high-resolution fields of precipitations we developed a procedure based on Lorenz et al. (2021); for our scope, the biases of the SEAS5 forecasts are corrected following a reference climatology obtained from the SEAS5 hindcasts that is calibrated over the cumulative distribution function calculated be mean of historical measurements of the IDEAM weather stations. The method and preliminary results as well as the validation will be shown in this work.
Depth of sudden velocity increases from multi-mode Rayleigh waves derived with three-component ambient noise beamforming
Authors: Finger Claudia , Löer Katrin
Published: February 2023

Surface wave dispersion curves derived from ambient noise recordings are frequently used to invert for subsurface velocity information. Rayleigh wave ellipticities and phase velocities are exploited, and sometimes jointly inverted, for the velocity structure beneath seismic arrays. Wavelengths of surface waves become large at low frequencies and are, thus, sensitive to great depths, but provide only very smooth velocity profiles. However, sudden velocity increases in the subsurface are of particular interest to delineate the extent of reservoirs, i.e., by sub-horizontal faults or detachments, or estimate the depth of sedimentary basins.Here, we report a new approach to estimate sudden velocity increases in vertical velocity profiles using Rayleigh wave ellipticities and phase velocities. Using Kepler’s law of motion on elliptical orbits, we can theoretically delineate the frequency-dependent half-height and half-width of the energy ellipse described by Rayleigh waves.In the presence of sudden velocity increases, fundamental and first higher mode Rayleigh waves have similar phase velocities at the so-called osculation frequency. This often leads to mode misidentification that biases inversion results. We show that this osculation frequency is close to the frequency where the Rayleigh ellipticity of the fundamental mode is one, i.e., motion is circular, and the ellipticity of the first higher mode has its maximum. At this frequency, our derived relation only requires the phase velocity of the first higher mode to estimate the half-height of the ellipse, which is a very good approximation of the depth of the sudden velocity increase.To derive phase velocities and ellipticities of Rayleigh waves for synthetic three-component waveforms and real-world datasets from three sites (Weisweiler in Germany, FORGE in Utah, USA and Groningen, the Netherlands), we use three-component beamforming, which provides velocity and polarization parameters of recorded waves in short ambient noise time windows and thus can distinguish wave types and modes. From identified Rayleigh waves, we pick the phase velocity of the first higher mode at the osculation frequency directly in the beamformer plots and estimate the depth of sudden velocity increases using our new relation. No inversion scheme is needed for this approach.This approach provides more accurate depth estimates of velocity jumps than other ambient noise methods. The depth sensitivity is only limited by the inter-station distances in the array configuration and the useable frequency range. The derived depths of sudden velocity increases can be used to constrain inversion schemes for more accurate velocity models or can be used directly to map structural changes in the subsurface.