bluuebunny/crossref_metadata_2025 huggingface dataset:
Seasonal and Interhemispheric Effects on the Diurnal Evolution of EIA: Assessed by IGS TEC and IRI-2016 over Peruvian and Indian sectors
Authors: Wan Xin , Zhong Jiahao , Xiong Chao , Liu Yiwen
Published: March 2022

The global total electron content (TEC) map in 2013, retrieved from the International Global Navigation Satellite Systems (GNSS) Service (IGS), and the International Reference Ionosphere (IRI-2016) model are used to monitor the diurnal evolution of the equatorial ionization anomaly (EIA). The statistics are conducted during geomagnetic quiet periods in the Peruvian and Indian sectors, where the equatorial electrojet (EEJ) data and reliable TEC are available. The EEJ is used as a proxy to determine whether the EIA structure is fully developed. Most of the previous studies focused on the period in which the EIA is well developed, while the period before EIA emergence is usually neglected. To characterize dynamics accounting for the full development of EIA, we defined and statistically analyzed the onset, first emergence, and the peaks of the northern crest and southern crest based on the proposed crest-to-trough difference (CTD) profiles. These time points extracted from IGS TEC show typical annual cycles in the Indian sector which can be summarized as winter hemispheric priority, i.e., the development of EIA in the winter hemisphere is ahead of that in the summer hemisphere. However, these same time points show abnormal semiannual cycles in the Peruvian sector, that is, EIA develops earlier during two equinoxes/solstices in the northern/southern hemisphere. We suggest that the onset of EIA is a consequence of the equilibrium between sunlight ionization and ambipolar diffusion. However, the latter term is not considered in modeling the topside ionosphere in IRI-2016, which results in a poor capacity in IRI to describe the diurnal evolution of EIA. Meridional neutral wind’s modulation on the ambipolar diffusion can explain the annual cycle observed in the Indian sector, while the semiannual variation seen in the Peruvian sector might be due to additional competing effects induced by the F region height changes
Forecasting the evolution and growth of glacial lakes
Authors: Saha Aniruddha , Jain Manoj , Schwanghart Wolfgang
Published: March 2022

The glaciers in the Himalayas are rapidly retreating. With the increasing loss of glacial mass, there is an increase in the number of glacial lakes and thereby, the potential threat of GLOF (Glacial Lake Outburst Flood) events. We aim to forecast the evolution and growth of proglacial lakes over Gangotri Glacier (Uttarakhand, India). Proglacial lakes are formed by damming action of a moraine, resulting due to retreat of melting glaciers. As the glacier melts and loses its mass, the glacier bed gets exposed, and any possible over-deepening, if available in “thereby exposed bed-topography”, shall act as a bedrock dam, to hold the meltwater, forming a moraine-dammed lake. As the glacier melts, more and more of such bedrock dams shall get exposed. The lakes shall not evolve to the full of its size at once, but slowly and gradually, as it loses the glacier mass above it. The present research aims to identify the potential sites for such glacial lake formation and forecast the growth of each of these lakes over time. This is done in two-fold steps. Firstly, identifying the potential sites of formation of glacial lakes, by preparing the glacier bed topography using the GlabTop2_IITB model. This model has a self-calibration feature, that could calibrate even in the absence of field measurements. Secondly, a glacier evolution model is operated using a simple parameterisation approach, i.e., an empirical glacier specific function is used for updating the glacier surface using the climate model datasets. The updated glacier surface data helps us forecast the evolution and growth of glacial lakes. The spatial distribution of ice thickness for Gangotri was found to be within a range of 19m to 343m for the year 2014, having a glacier volume of 13.49 km3. Fifty potential sites for glacial lake formation were identified using the bedrock topography modelling, having a total storage capacity of 37.04m3. Our results shall help determine the possibility of further expansion of the glacial lakes present and their maximum storage capacities. Having an idea of the formation and growth of lakes in future can help us forecast the: hazard potential of a lake, its flood peak, and the downstream effect of its dam break events as it evolves over time.  
The INCUS Mission
Authors: van den Heever Susan , Haddad Ziad , Tanelli Simone , Stephens Graeme , Posselt Derek , Kim Yunjin , Brown Shannon , Braun Scott , Grant Leah , Kollias Pavlos , Luo Zhengzhao Johnny , Mace Gerald , Marinescu Peter , Padmanabhan Sharmila , Partain Philip , Petersent Walter , Prasanth Sai , Rasmussen Kristen , Reising Steven , Schumacher Courtney ,   INCUS Mission team
Published: March 2022

The INvestigation of Convective UpdraftS (INCUS) is a recently selected NASA Earth Ventures Mission. The overarching goal of INCUS is to enhance our understanding of why, when and where tropical convective storms form, and why only some storms produce extreme weather. Life on Earth is bound to convective storms, from the fresh water they supply to the extreme weather they produce. Much of the vertical transport of water and air between Earth’s surface and the upper troposphere is facilitated by convective storms. This vertical transport of water and air, referred to as convective mass flux (CMF), plays a critical role in the weather and climate system through its influence on storm intensity, precipitation rates, upper tropospheric moistening, high cloud feedbacks, and the large-scale circulation. Recent studies have also suggested that CMF may change with changing climates. In spite of the critical role of this vertical transport of water and air within the weather and climate system, much is not understood regarding the way in which various environmental factors govern this mass transport, nor the subsequent impacts of CMF on high clouds and extreme weather. Representation of CMF is also a major source of error in weather and climate models, thereby limiting our ability to predict convective storms and their associated feedbacks on weather through climate timescales.

INCUS is a NASA class-D mission. Three RainCube-heritage Ka-band 5-beam scanning radars that are compatible with SmallSat platforms comprise the mission. The satellite platforms will be 30 and 90 seconds apart. Each SmallSat will carry one radar system each, and the middle SmallSat will house a single TEMPEST-D-heritage cross-track-scanning passive microwave radiometer with four channels between 150 and 190 GHz. Through its novel measurements of time-differenced profiles of radar reflectivity, INCUS is the first systematic investigation of the rapidly evolving CMF within tropical convective storms. The primary INCUS objectives are: (1) to determine the predominant environmental properties controlling CMF in tropical convective storms; (2) to determine the relationship between CMF and high anvil clouds; (3) to determine the relationship between CMF and the type and intensity of the extreme weather produced; and (4) to evaluate these relationships between CMF and environmental factors, high anvil clouds, and extreme weather within weather and climate models. The ground breaking observations of convective storms by INCUS are expected to significantly enhance our understanding and prediction of convective processes and extreme weather in current and future climates.
16,000 riverbank litter items – A data driven approach to optimizing riverine plastic monitoring
Authors: Begemann Finn , de Lange Sjoukje , Mellink Yvette , Vriend Paul , Tasseron Paolo , van Emmerik Tim
Published: March 2022

Macrolitter in aquatic environments is an emerging environmental risk, as it negatively impacts ecosystems, endangers aquatic species, and causes economic damage. One of the major reservoirs of macrolitter in aquatic environments are riverbanks. To effectively clean riverbanks and prevent future litter from accumulating in these reservoirs, robust monitoring techniques are needed that allow for quick, but reliable, assessments of the type, size and mass of macrolitter in these reservoirs. Here, we present a unique dataset of more than 16,000 anthropogenic litter items in the Dutch Rhine, Meuse and IJssel rivers. With this dataset, we facilitate making considered decisions for developing future monitoring strategies. Items were collected on 8 different riverbanks once per month for one year. Items were collected at upstream and downstream locations along the Dutch part of the rivers, and were categorized (river-OSPAR), weighed and measured. The dataset shows that the majority of the found items is plastic, especially fragments of foam, soft plastics (foils), and hard plastics. The composition of litter type varies more in space than in time, indicating that the spatial resolution of a future monitoring campaign outweighs the importance of the temporal resolution. We performed a Monte Carlo analysis to determine sample size requirements to calculate a representative number of average item mass. Up until 8,900 items are needed for an accurate representation of average items mass, depending on item category uniformity. Finally, a method is proposed to determine on which item size should be focused. The presented dataset can be used in future research, modelling practices and development of management strategies. 
Developing a high resolution coupled ocean-atmospheric model to understand reef fish distribution in the Eastern Tropical Pacific in the present and future climate
Authors: De Falco Chiara , Mooney Priscilla , Tjiputra Jerry
Published: March 2022

In the last 20 years the anthropogenic pressure on the ocean and its ecosystems have been increasing, inducing considerable oceanographic and biogeochemical changes. The global warming impact is projected to increase further in the next decades. Consequently, changes in reef fish distribution, and the subsequent cascading effects on biodiversity, ecosystem function, reefs’ services, climate feedbacks, and socio-economic wellbeing are inevitable. To understand the extent and the impact of these changes, it is of fundamental importance to have reliable climate information at high spatio-temporal resolution, integrating interannual-to-long-term atmospheric-oceanic variability. Earth System Models are too coarse to fully resolve key features at the local scales. A challenge that can be overcome with dynamical downscaling, a powerful tool to increase our understanding of future changes in coastal regions. We use the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System to simulate the eastern tropical Pacific (ETP) circulation and biogeochemistry. The model includes an atmospheric component, the Weather Research and Forecast Model (WRF) and an oceanic component, the Regional Ocean Modeling System (ROMS) with a biogeochemistry module. Present (1995-2016) and future (2025-2050) years will be dynamically downscaled, at a 20 km and 4 km resolution, from global reanalysis and the Norwegian Earth System model NorESM. To investigate the variability and the extent of anthropogenic-induced climate change impact on the local ecosystem, two contrasting future scenarios, the “strong mitigation” (SSP1-2.6) and the “business-as-usual” (SSP5-8.5), will be simulated. The performance of the model, its reliability and improvements in projecting future changes are presented here. We thoughtfully validate the model output, by comparing present days results with reanalysis and satellite data to demonstrate its potential to deliver crucial information for investigating climate changes impacts on the distribution of reef fish throughout the ETP. 
The Fresnel Platform for increasing the Greater Paris resilience to spatio-temporal variability of local rainfall
Authors: Drouen Guillaume , Schertzer Daniel , Gires Auguste , Tchiguirinskaia Ioulia
Published: March 2022

Urban areas are at stake under the threat of climate change. To overcome this challenge it is necessary to deepen our understanding of heavier and particularly local rainfall to avoid flooding and build resilient cites that can become sustainable. The main difficulty is that geophysics and urban dynamics are strongly nonlinear with associated extreme variability over a wide range of space-time scales.

To better connect theoretical and experimental research on these topics, an advanced urban hydro-meteorological observatory with associated SaaS (Software as a Service) developments, the Fresnel platform of the Co-Innovation Lab of the École des Ponts ParisTech, has been purposely set-up. The mission of the Fresnel platform is to facilitate synergies between research and innovation in the pursuit of upstream research and the development of innovative downstream applications. With profiled access for specialized services, it provides the concerned communities with the necessary high resolution measurements in real time and in replay form, that easily yield Big Data.

The Fresnel platform unites several components. One of them, the RadX SaaS platform, provides online tools to study rainfall data over the greater Paris area (i.e., about 50 km radius and more). It provides an easy access to various products based on precipitation measurements performed by the ENPC polarimetric X-band radar at the pixel scale of 125 m. It broadcasts these measurements in free access and in real-time (https://radx.enpc.fr) together with a point measured environmental parameters provided by another component of Fresnel, namely the exTreme and multi-scAle RAiNdrop parIS observatory (Taranis) observatory, containing several, a 3D sonic anemometer and a meteorological station.

The RadX platform was developed in participatory co-creation, and in scientific collaboration with the world industrial leader in water management. As the need for data accessibility, fast and reliable infrastructure were major challenges, the platform was constructed as a cloud-based solution. The components that make up this platform are designed to be configurable for specific case studies using an adjustable visual interface. Depending on a case study, specific components can be integrated to meet particular needs using maps, other visual tools and forecasting systems, eventually from third parties.

Developments are still in progress, with a constant loop of requests and feedback from the scientific and professional world.
Determination of eruption source parameters of the 2011-2013 and February 2021 Etna’s paroxysms using multi-sensor strategies.
Authors: Freret-Lorgeril Valentin , Bonadonna Costanza , Carbone Daniele , Corradini Stefano , Donnadieu Franck , Guerrieri Lorenzo , Gurioli Lucia , Lacanna Giorgio , Lemus Jonathan , Marzano Frank Silvio , Mereu Luigi , Merucci Luca , Passarelli Luigi , Ripepe Maurizio , Rossi Eduardo , Scollo Simona , Stelitano Dario
Published: March 2022

The determination of Eruptive Source Parameters (ESPs) is crucial especially for very active volcanoes whose eruptive intensity can vary significantly. In this aim, new strategies are being developed to determine in near real time the total erupted mass (TEM), total grain-size distribution (TGSD) and plume height from ground sampling and remote sensing methods. Since 2011, Etna volcano has produced about 100 paroxysmal episodes characterized by the emission of fountain-fed tephra plumes whose heights reached up to 15 km (above sea level). In this work, we present multi-sensor strategies based on data acquired by the complementary set of remote sensing systems available at Etna. In fact, multi-sensor strategies may help to refine and assess the uncertainty of ESP estimates made by individual sensors, which can present various limitations such as narrow field of views (e.g., visible imagery) and/or low temporal resolution (e.g., satellite-based infrared). First, we show how the combination between tephra-fallout deposit and satellite-based estimates, along with numerical modelling, can help to refine estimates of TEM and TGSD, especially for weak explosive eruption such as the 29 August 2011 paroxysm. We use the model TEPHRA2 and compute synthetic data of ground accumulation to successfully fill significant sampling gaps in the tephra-fallout deposits. Moreover, we find that the Rosin-Rammler equation can be used to inform on missing part of the TGSD, including the tail of very fine ash also detected by satellite-based platforms. Additionally, we compare all estimates of Mass Eruption Rates, Plume height and grain-size distributions made by all available methods including Doppler radar detection, visible and infrared imagery, infrasound arrays, gravimetric signals and tephra-fallout deposit sampling. Accordingly, based on each sensor limitation and capacities, we obtain new constraints on ESP estimates acquired during several paroxysms between 2011-2013 and February 2021. We also bring new insights into the differences and complementarities that exist between the available remote sensing methods, especially in the case of future eruptive events at Mount Etna.
Numerical simulation of large drop falling on the water surface in strong winds
Authors: Zotova Anna , Troitskaya Yuliya , Kandaurov Alexander , Sergeev Daniil
Published: March 2022

Processes of sea spray formation play important role in the interaction of ocean and atmosphere under strong winds. Among other factors, the formation of small droplets is caused by the falling of previously generated larger drops onto the sea surface. Using the Basilisk software package [1] numerical simulation of fall of a large drop with a substantial horizontal velocity on a water surface was carried out. The problem of the following configuration was considered: a cubic domain was half filled with water, and air was in the upper half. At the initial time, at a height of h = 2 cm above the water surface, there was a drop with a diameter of 2 mm, the horizontal projection of the drop velocity was v0x = 3 m/s, the vertical projection of the drop velocity v0y = 1.25 m/s was obtained from the calculation that at a height of 10 cm above the water surface, the vertical component of the droplet velocity was equal to zero. Boundary conditions along the x coordinate were periodic. The coordinates and volume of each individual water body (including each drop) were recorded over time.

This work was supported by the RFBR grant 21-55-52005 and RSF grant 21-19-00755.

[1] Popinet, S. The Basilisk code: http://basilisk.fr.
Grain-size distribution of sediments in Lake Munozero (Baltic Sea drainage basin)
Authors: Myasnikova Nadezda
Published: March 2022

Bottom sediments have archived a continuum of information about past and recent natural events. Seeking to learn more about the deglaciation process in the Onega ice lake basin, we studied bottom sediments from Lake Munozero situated in North-west Russia (Republic of Karelia). The lake has a tectonic basin; the water surface area is 0.144 km2, the elevation above sea level is 79 m. Three sediment cores up to 4.80 m thick were exposed and their lithostratigraphy was described. Visually, the sediment column in the studied 6.00-9.00 m core can be divided into two intervals: sediment in the 6.00-8.86 m interval, made up of beige, greenish-brown gyttja formed during the Holocene; sediment in the 8.86-9.00 interval – greenish-gray clayey silt formed during the Pleistocene.

Analysis of the grain-size distribution in sediments in the 8.00-9.00 m interval revealed the paleohydrodynamic environment for sedimentation in Lake Munozero during deglaciation. Studies have demonstrated that the water dynamic regimes changed at least twice during the transition from a nival to a humid climate. In the 8.00-8.30 m depth interval the sand fraction prevails with 81% to 87%, while the silt fraction contributes 13% to 19%; at the 8.46-8.66 m depth the sand fraction constitutes 87% and 88%, and the silt fraction 12% and 13%; in the 8.80-9.00 m layer the sand fraction declines from 63% to 11%, while the silt fraction grows from 36% to 78%. The share of the clay fraction at 8.00-9.00 m depth is minor, 3% on average. The highest clay content is found in the 8.88-8.90 m interval (13%).

The research was funded from the federal budget under state assignment to KarRC RAS (Northern Water Problems Institute KarRC RAS) and partially funded by RSF grant #18-17-00176.
Use of near real-time cloud-free MODIS snow cover data from DLR’s Global SnowPack for the early forecast of extreme hydrological events
Authors: Roessler Sebastian , Dietz Andreas
Published: March 2022

The MODIS sensor on the NOAA Terra satellite has been providing daily information on global snow cover with a nominal spatial resolution of 500 m since February 2000. Since July 2022, this sensor is also located on NOAA's Aqua Satellite in orbit. The daily snow cover product of both platforms constitutes the basis for the DLR Global SnowPack (GSP) processor.

In the course of the GSP processing, the daily data of both MODIS sensors are merged and data gaps (e.g., clouds or polar night) are interpolated over 3 days. From a digital elevation model, the snow height (elevation above which only snow occurs), as well as the snow-free height (elevation below which no snow occurs) are determined. Heights above or below these thresholds are filled accordingly. Finally, remaining gaps are gradually filled by the values of preceding days. Since the year 2022, the daily cloud free GSP data has been made available in near real time (3 days delay due to the preprocessing of the NSIDC) via the GeoService Portal of the Earth Observation Center (EOC).

The rapid provision of the information on global snow coverage allows completely new applications of time-critical questions. These include hydrological estimates to what extent the snow conditions in the catchment area influence the drainage behavior. In addition to the satellite data, meteorological and hydrological data of the past 20 years are used to estimate the impact of a changing snow cover on the runoff. In the course of climate change, a delayed onset of snow cover and an earlier snowmelt is likely. Warmer winters also increase the risk of Rain-on-Snow events, which cause a strong increase in the outflow and have more dramatic ecological effects.

We will present results for selected river catchment areas with a special focus on hydrological extreme events (droughts and floods), and when their occurrence has been shown early in the development of seasonal snow coverage. Our goal is to provide an automatic early warning system based on near real time GSP for large river catchments with nival-influenced drainage regimes.
Prominent discords in climate data through matrix profile techniques: detecting emerging long term pattern changes and anomalous events  
Authors: El Khansa Hussein , Gervet Carmen , Brouillet Audrey
Published: March 2022

Outliers detection generally aims at identifying extreme events and insightful changes in climate behavior. One important type of outlier is pattern outlier also called discord, where the outlier pattern detected covers a time interval instead of a single point in the time series. Machine learning contributes many algorithms and methods in this field especially unsupervised algorithms for different types of data time series. In a first submitted paper, we have investigated discord detection applied to climate-related impact observations. We have introduced the prominent discord notion, a contextual concept that derives a set of insightful discords by identifying dependencies among variable length discords, and which is ordered based on the number of discords they subsume. 

Following this study, here we propose a ranking function based on the length of the first subsumed discord and the total length of the prominent discord, and make use of the powerful matrix profile technique. Preliminary results show that our approach, applied to monthly runoff timeseries between 1902 and 2005 over West Africa, detects both the emergence of long term change with the associated former climate regime, and the regional driest decade (1982-1992) of the 20th century (i.e. climate extreme event). In order to demonstrate the genericity and multiple insights gained by our method, we go further by evaluating the approach on other impact (e.g. crop data, fires, water storage) and climate (precipitation and temperature) observations, to provide similar results on different variables, extract relationships among them and identify what constitutes a prominent discord in such cases. A further step will consist in evaluating our methodology on climate and impact historical simulations, to determine if prominent discords highlighted in observations can be captured in climate and impact models.
Hydroxyl group of libethenite Cu2(OH)PO4 – olivenite Cu2(OH)AsO4 solid solution series - vibrational spectroscopic study
Authors: Waluś Edyta , Manecki Maciej
Published: March 2022

Libethenite and olivenite present itself as a particularly interesting candidates for a photocatalyst due to its unique structure. One of the features of copper hydroxy- phosphates and -arseniates is the presence of bridging hydroxyl (OH) groups shared between neighboring Cu atoms. In materials used in photoelectrochemical applications, the role of surface OH groups and OH-related defects is often variable and depends on the material system and reaction of interest. For instance, OH groups can improve photocatalytic activity by forming OH radicals or act as an important intermediate in the catalytic reaction. As such, the presence of the OH group inherent in the crystal structure of the material may lead to potentially interesting behavior. Seven compounds of the libethenite Cu2(OH)PO4 – olivenite Cu2(OH)AsO4  solid solution series were synthesized at 70 °C from aqueous solutions and characterized using XRD, SEM–EDS and FTIR and Raman. The substitution effect of [PO4]3- anions by [AsO4]3- on systematic changes in lattice parameters and spectral properties has been explained based on correlation between chemical composition and the peak positions. The substitution results in systematic linear increase in unit cell parameters and unit cell volume. Isomorphic substitutions are apparent in IR and Raman as a change in the position and intensity of bands derived from phosphates, arsenates and hydroxyl ions. Isomorphic substitutions of As for P in the solid solution series change the bond length and geometry. Investigation into materials that contain intrinsic OH groups may lead to better understanding of these processes and impact for photocatalytic properties. These studies will help determine the potential of libethenite Cu2(OH)PO4 – olivenite Cu2(OH)AsO4 isomorphic series as photocatalysts.
Dealing with climate data uncertainty for agricultural impact assessments in West Africa
Authors: Aschenbrenner Paula , Gleixner Stephanie , Gornott Christoph
Published: March 2022

West Africa is characterized by high variability in climate, has a fast growing population, and is home to a population strongly reliant on rainfed agriculture. The largely weather-dependent agricultural production is now further at risk under increasing climate change. To adequately address climate risks and avoid further pressure on food security, evidence-based information on climate impacts and guidance on the suitability of adaptation measures is required. Simulations of regional impacts of climate change on crop production are strongly influenced by the climate data used as input. The selection of climate forcing data is most influential in regions with high uncertainties in past climate data and where the agricultural production varies greatly under climate variability (Ruane et al., 2021). Both is the case in West Africa, calling for an improved understanding of past and future climate data for its use in agricultural modelling over the region. 

In this session we want to contribute to an increased understanding on the usability of different past and future climate data sets for agricultural impact models over West Africa. In a recent study, we compared ten CMIP6 (Coupled Model Inter-comparison Project Phase 6) models and their respective bias-adjusted ISIMIP3b (Inter-Sectoral Impact Model Intercomparison Project Phase 3b) versions against different observational and reanalysis data sets. Focusing on their use for agricultural impact assessments we centred the analysis on climate indicators highly influencing agricultural production and their representation in the different climate data sets.

Results show that the ten CMIP6 models contain regional and model dependent biases with similar systematic biases as have been observed in earlier CMIP versions. Although the bias-adjusted version of this data aligns overall well with observations, we could detect some regional strong deviations from observations in agroclimatic variables like length of dry spells and rainy season onset. The use of the multi-model ensemble mean has resulted in an improved agreement of CMIP6 and the bias-adjusted ISIMIP3b data with observations. Choosing a subensemble of bias-adjusted models could only improve the performance of the ensemble mean locally but not over the whole region. The results of this study can support agricultural impact modelling in quantifying climate risk hotspots as well as suggesting suitable adaptation measures to increase the resilience of the agricultural sector in West Africa.
Triggered Earthquakes Reveal Hydraulic Properties of the Subsurface
Authors: Delorey Andrew , Ma Xioafei , Chen Ting
Published: March 2022

Seismicity both at The Geysers geothermal field (northern California) and in north-central Oklahoma is heavily influenced by industrial activities related to energy production, though the mechanism in which earthquakes are induced or triggered is different. At The Geysers, much of the seismicity is linked to thermoelastic stresses caused by injecting cold water into hot rocks, while in Oklahoma the seismicity is linked to a reduction of confining stress on faults due to increasing pore pressure resulting from wastewater injections. Here we show that these contrasting conditions are also evident in tidally-triggered earthquakes. At The Geysers, earthquakes preferentially occur during maximum extensional strain, which does not occur at the same time as maximum shear strain on optimally oriented faults in the regional stress field. In Oklahoma, earthquakes preferentially occur during maximum shear strain on optimally oriented faults, rather than maximum extensional strain. The magnitude of tidal extensional strain is naturally much greater than tidal shear strain. However, in a fluid saturated environment, pore pressure responds to changes in volume, which can counteract or reduce the effect of the applied stress. The difference in behavior at these two sites is indicative of the level of coupling between applied stress and pore pressure, corresponding to unsaturated conditions at The Geysers and high pore pressure in Oklahoma.
Control of North Atlantic cyclone variability and impacts by the large-scale atmospheric flow
Authors: Li Camille , Madonna Erica , Hes Gabriel , Michel Clio , Siew Peter Y.F.
Published: March 2022

Extratropical cyclones are key players in the poleward transport of moisture and heat. This study investigates wintertime cyclone variability to better understand the large-scale controls on their frequency, path and impacts at higher latitudes. One of the main corridors for Arctic-bound cyclones is through the North Atlantic to the Barents Sea, a region that has experienced the greatest retreat of winter sea ice during the past decades. Large-scale atmospheric conditions are found to be decisive, with the strongest surface warming from cyclones originating south of 60N in the North Atlantic and steered northeastward by the upper-level flow. Atmospheric conditions also control cyclone variability in the Arctic proper: months with many cyclones are characterized by an absence of high-latitude blocking and enhanced local baroclinicity, due to the presence of strong upper-level winds and a southwest-northeast tilted jet stream more than changes in sea ice. Due to the large interannual variability in the number of Arctic-bound cyclones, no robust trends are observed over the last 40 years. Our results highlight the importance of accounting for internal variability of the large-scale atmospheric circulation in studies of long-term changes in extratropical cyclones.
Space-Enabled Modeling of the Niger River to Enhance RegionalWater Resources Management
Authors: Bruscolini Margherita , Ogunwumi Taiwo , Schumann Guy
Published: March 2022

The Niger River and floodplain landscape is experiencing a constant change as a result of natural and human processes thereby contributing to the yearly occurrence of flooding. The increasing flood frequency and intensity causes loss of life, destruction of assets and disrupts the livelihood of a large proportion of the population. Due to the current data challenges and lack of hydrological information we are developing a 2-D flood inundation model showing the spatially distributed dynamics of water surface elevation and future flood extent of Niger river and its surroundings. We considered the following parameters such as floodplain topography, river channel widths, banks heights, model parameters, and hydrology information to develop our final output which is an interactive web visualization map showing the inundated extent. Our developed 2D flood prediction model can be extended to other parts of the Niger River Basin which will contribute to a positive regional economic and environmental impact. It will also help the relevant ministries, emergency institutions, local partners and national government of Niger to build safe and resilient communities through effective risk communication and contribute to the achievement of the Sustainable Development Goal (SDG) 11 and 13.
Statistical Study of Decameter Scale Plasma Irregularities in the Polar Ionosphere
Authors: Jin Yaqi , Clausen Lasse , Spicher Andres , Ivarsen Magnus , Zhang Yongliang , Miloch Wojciech , Moen Joran
Published: March 2022

The polar ionosphere is often highly irregular and turbulent with significant plasma structures. As a result, the satellite-based navigation and communication systems that rely on trans-ionospheric radio signals can be severely disrupted. In this study, we take advantage of the high-resolution (1 kHz) electron density observations of a polar orbiting satellite (NorSat-1) to address plasma structures at several 10s of meters that are responsible for scattering of High Frequency (HF) radar signals. The in-situ electron density data are taken from the winter season of 2017-2018. Though the solar activity is very low, NorSat-1 frequently observes significant plasma irregularities from several 10s km down to several decameter. These are often observed near the dayside cusp and dawnside auroral zone. The decameter-scale irregularities are positively correlated with intermediate-scale (10 km) density gradients, for both negative and positive gradients encountered by the satellite. The spatial distribution of electron density over two winter months in the Northern hemisphere along NorSat-1 orbits is constructed, which shows significant density increases in the cusp ionosphere (75º-80º MLAT) and in regions near the dawnside auroral oval. Intermediate scale density gradients and small-scale irregularities are clearly collocated with these density enhancements. These density enhancements and irregularities are likely induced by auroral particle precipitation/plasma dynamics. The power of decameter scale irregularities is also directly compared with the backscatter echo of HF radars.
Inferences from the comparison of two non-intrusive methods for estimation of bedload transport
Authors: Baranya Sándor , You Hojun , Muste Marian , Kim Dongsu , McAlpin Tate , Abraham David
Published: March 2022

Non-intrusive technologies for the in-situ measurement of river hydro-morphological features are increasingly popular in the scientific and practice communities due to their efficient and productive data acquisition. Our research team have successfully demonstrated through laboratory experiments and field measurements that, by combining acoustic mapping with image velocimetry concepts, we can characterize the planar dynamics of the bedform migration and eventually rates of bedload transport. The technique, labeled Acoustic Mapping Velocimetry (AMV), is currently transferred to field conditions using multiple-beam echo-sounders (MBES) and Acoustic-Doppler Current Profilers (ADCP) for producing acoustic maps and tracking the bedform dynamics.

A constant preoccupation of the research team during this transfer has been the validation of the AMV in field conditions. Such validation requires the use of identical input data and the availability of a similar capability measurement system in terms of measurement output, spatial and temporal coverage for the measurement. Fortunately, there is a similar system for estimation of bedload transport labeled Integrated Section Surface Difference Over Time (ISSDOT).  The latter method has been developed and extensively tested by a research group of US Corps of Engineers. While the data inputs (acoustic maps) and the underlying principle (i.e., dune tracking) are the same as for AMV, ISSDOT is based on purely geometrical estimation of the bedload transports rates. The present paper described a comparison between AMV and ISSDOT applied to a set of repeated maps acquired in the Mississippi River. In the absence of a third measurement alternative to be used as benchmark, the paper draws inferences from the comparisons of the two instruments.
Effect of diverse microwave link characteristics on rainfall retrieval errors
Authors: Fencl Martin , Spackova Anna , Bares Vojtech
Published: March 2022

Commercial microwave links (CMLs), point-to-point radio connections forming the backbone of cellular networks, can be used as opportunistic rainfall sensors and provide rain rate at high temporal resolution. The CML rainfall retrieval methods have been mostly developed for devices operating between 13 – 40 GHz where attenuation-rainfall relation is relatively insensitive to drop size distribution. New deployments have, however, an extensive share of E-band CMLs operating at 71 – 81 GHz frequency where drop size distribution (DSD) represents a major source of errors (Fencl et al., 2020). This study investigates for the first time the joint use of 13-40 GHz and 71-86 GHz CMLs with focus on evaluating different sources of errors.

Rainfall retrieved from 250 CMLs located in the city of Prague and its vicinity are compared to the quantitative precipitation estimates from C-band weather radar adjusted to the local network of 23 municipal rain gauges. Diverse path-lengths and frequencies of CMLs enable us to distinguish between different sources of errors. Shorter CMLs operated at lower frequencies are dominantly disturbed by errors related to antenna wetting whereas E-band CMLs are significantly more affected by DSD variability and non-uniform distribution of rain rates along the CML path. Moreover, longer E-band CMLs suffer from outages during heavy rainfalls. In general, E-band CMLs are more sensitive to low rain rates and thus suitable for retrieving light rainfalls whereas CMLs operating at lower frequencies are more accurate during heavy rainfalls.

Diverse characteristics of CMLs typically occurring in real-world cellular networks pose a challenge as each CML is affected by the instrumental errors in a different manner. On the other hand, the diversity in CML characteristics can be also exploited to quantify and possibly reduce these errors, especially in cities, where CML networks are usually dense and thus often provide collocated (redundant) rain rate measurements.

References:

Fencl, M., Dohnal, M., Valtr, P., Grabner, M., and Bareš, V.: Atmospheric observations with E-band microwave links – challenges and opportunities, 13, 6559–6578, https://doi.org/10.5194/amt-13-6559-2020, 2020.

Acknowledgements: This study was conducted within SpraiLINK project (20-14151J) and supported by Czech Science Foundation.
Energetic Electron lensing of Ganymede’s Magnetic Field observed by the Juno Spacecraft’s Advanced Stellar Compass
Authors: Herceg Matija , Jørgensen John Leif , Merayo Jose M. G. , Denver Troelz , Jørgensen Peter S. , Benn Mathias , Kotsiaros Stavros , Connerney Jack E. P.
Published: March 2022

The micro Advanced Stellar Compass (µASC), an attitude reference for the Juno Magnetic Field investigation, also continuously monitors high energy particle fluxes in Jupiter’s magnetosphere. The µASC camera head unit (CHU) shielding is sufficient to stop electrons with energy <15MeV. By recording the number of particles that penetrate µASC CHU shielding and deposit energy in the CCD sensor, the µASC functions as an energetic particle sensor with a detection threshold well above that of the Juno Energetic Particle Detector Instrument (JEDI) flown for that purpose. Radiation data gathered by the µASC is used to monitor the radiation environment of Jupiter and mapping of the trapped high energy particles. Comparison of the particle population around Jupiter with individual perijove particle observations reveals disturbances when Juno is traversing Ganymede’s M-shell. We present highly energetic electrons interaction with Ganymede’s magnetic field, magnitude and extend of the particle depletion associated with the Ganymede interaction.
Time series compositional insights into magmatic evolution during the 2021 Cumbre Vieja eruption, La Palma, Canary Islands, Spain
Authors: Scarrow Jane H. , Chamberlain Katy J. , Pankhurst Matthew J. , Barbee Olivia A. , Coldwell Beverley C. , Hickey James , Neave David A. , Morgan Daniel J. , Martín-Lorenzo Alba , Rodríguez Fátima , Rollinson Gavyn K. , Hernández William , Hernández Pedro A. , Pérez Nemesio M.
Published: March 2022

On 19 September 2021, Cumbre Vieja volcano, La Palma, Canary Islands erupted after 50 years of quiescence. The eruption lasted 85 days through to 13 December. Cone building that initiated from the main fissure vent resolved into discrete emission centres dominated by ash plumes and lava fountains that fed flows that coursed to the west and west-southwest. The lava flow field covers over 1000 hectares and is up to 3.5 km wide and ~6.2 km long. Tephra fall covers over 5,500 hectares with volcanic plume heights reaching up to 6000 m depositing material mainly in the eastern part of the island but, on occasion, reaching other Canary islands: El Hierro, La Gomera, Tenerife and Gran Canaria.

Significantly, uncertainties exist regarding how such eruptions initiate, evolve and ultimately cease, e.g. changes in magma composition and volume. Here we show time series whole-rock and mineral chemistry variations throughout the eruption from initiation to paroxysm and finally cessation. Bulk chemical trends of erupted products in the first week together with textural and mineralogical observations made within a few weeks of samples’ eruption provide an initial benchmark for understanding the evolution of the eruption. Petrographically, the lavas are hypocrystalline, porphyritic and vesicular. Clinopyroxene is the most common coarse mineral with olivine and amphibole also present. Whole-rock XRF and ICP-MS analyses show that samples have restricted, primitive, metaluminous, alkaline whole-rock compositions; geochemically, lavas plot as basanite-tephrites, but mineralogical observations, for example the absence of feldspathoids, classify them as alkali basalts.

Time-resolved whole-rock analyses through the eruption show increasing MgO contents and decreasing incompatible element contents, which may reflect changes in melting dynamics or crystal cargos. A jump in whole-rock major and trace element compositions on day 7 to 8 of the eruption coincides with the disappearance of resorbed amphibole crystals in the thin sections, and also the amphibole peak in XRD spectra, as well as transition to the eruption of less viscous lava flows. The whole-rock compositional changes also correlate with variations in geophysical monitoring records of real-time seismic amplitude measurements.

Our new data has potential to be applied to eruption forecasting, as well as evaluation of volcanic hazards and associated risks for activity in the Canary Islands and other comparable ocean island systems.
A multivariate convolutional autoencoder to reconstruct satellite data with an error estimate based on non-gridded observations: application to sea surface height
Authors: Barth Alexander , Alvera-Azcárate Aida , Troupin Charles , Beckers Jean-Marie
Published: March 2022

DINCAE (Data INterpolating Convolutional Auto-Encoder) is a neural network to reconstruct missing data (e.g. obscured by clouds or gaps between tracks) in satellite data. Contrary to standard image reconstruction (in-painting) with neural networks, this application requires a method to handle missing data (or data with variable accuracy) already in the training phase. Instead of using a cost function based on the mean square error, the neural network (U-Net type of network) is optimized by minimizing the negative log likelihood assuming a Gaussian distribution (characterized by a mean and a variance). As a consequence, the neural network also provides an expected error variance of the reconstructed field (per pixel and per time instance).

 

In this updated version DINCAE 2.0, the code was rewritten in Julia and a new type of skip connection has been implemented which showed superior performance with respect to the previous version. The method has also been extended to handle multivariate data (an example will be shown with sea-surface temperature, chlorophyll concentration and wind fields). The improvement of this network is demonstrated in the Adriatic Sea. 

 

Convolutional networks work usually with gridded data as input. This is however a limitation for some data types used in oceanography and in Earth Sciences in general, where observations are often irregularly sampled.  The first layer of the neural network and the cost function have been modified so that unstructured data can also be used as inputs to obtain gridded fields as output. To demonstrate this, the neural network is applied to along-track altimetry data in the Mediterranean Sea. Results from a 20-year reconstruction are presented and validated. Hyperparameters are determined using Bayesian optimization and minimizing the error relative to a development dataset.
Evaluation of temperature extremes over central Europe and their links to atmospheric circulation in CORDEX RCMs
Authors: Stryhal Jan , Plavcová Eva , Lhotka Ondřej
Published: March 2022

Automated classifications of atmospheric circulation are routinely used to link synoptic-scale circulation with temperature variability. Though powerful in general, classifications have considerable limitations regarding their skill to capture synoptic links to temperature extremes.

We evaluate and optimize several parameters of the popular method of self-organizing maps, in order to make the method better suited for studying central European temperature extremes. Furthermore, two methods of discretizing Sammon projections of atmospheric circulation have been developed to complement the image obtained by SOMs, and all methods have been used to analyse ERA5 SLP fields in relation to winter extremes.

Here, we plan to apply the new optimized classifications to daily winter and summer SLP fields from the outputs of evaluation and historical runs by CORDEX RCMs to study the skill of the methods to identify RCM biases in simulated circulation and their links to biases in temperature extremes. Furthermore, we plan to utilize various indices of low-frequency large-scale circulation to assess to what extent the eventual biases propagate from the driving (reanalysis, GCM) data.