bluuebunny/crossref_metadata_2025 huggingface dataset:
Towards spatio-temporal measurements in the mountain boundary layer with a fleet of UAS
Authors: Wildmann Norman , Wetz Tamino , Zink Josef
Published: March 2022

Exchange and transport processes in the atmospheric boundary layer (ABL) are driven by turbulence on a wide range of scales. Their adequate parameterization in numerical weather prediction (NWP) models is essential for a high predictive skill of forecasts. In heterogenous and complex terrain, the common simplification of turbulence to statistical models does not necessarily hold. Coherent structures such as convective cells, secondary circulations, gusts, slope and valley flows can be summarized to sub-mesoscale structures which are not well represented in models. A reason for the lack of understanding of these flow features is the challenge to adequately sample their three-dimensional, spatio-temporal structure and their contribution to the energy budget of the ABL.
We present a system to achieve simultaneous spatial measurements with a fleet of multirotor unmanned aircraft systems (UAS). The major benefit of this approach is, that true simultaneous measurements can be obtained without the need of expensive infrastructure such as masts or lidar instruments. In field campaigns with more than 1000 single flights at the Meteorological Observatory Lindenberg - Richard Aßmann-Observatory (MOL-RAO), the system was validated in 2020 and 2021 to provide reliable measurements of the horizontal wind vector. We showed that turbulent eddies can be resolved with a time resolution of up to 2~Hz, unless the overall TKE level is below the noise threshold of the UAS measurements, which can be the case in stable atmospheric stratification. Additionally to the wind vector estimation that is based only on avionic data from the autopilot, pressure, temperature and humidity sensors are carried by each UAS.
In future, within the project ESTABLIS-UAS, the fleet of UAS shall be expanded and capabilities for flights beyond visual line of sight and throughout the whole ABL shall be developed. The project includes a three-fold approach to validate single UAS measurements, fleet observations and methods to derive spatial averages and fluxes. Wind tunnel tests, field experiments and virtual measurements in numerical simulations will be performed to gain confidence in the achievable accuracy in a wide range of conditions. Also, measurement strategies are to be developed that allow the derivation of meaningful fluxes in the mountain boundary layer (MoBL). 
The UAS fleet is planned to be deployed in two campaigns in the framework of the TEAMx research programme. The ESTABLIS-UAS measurements will fill observational gaps in the sub-mesoscale. The analysis of the UAS fleet data in synthesis with continuous ground observations and remote sensing will provide unprecedented new insights into the complex MoBL flow. The results will foster the development of new and better parameterization of the ABL in complex terrain.
Imaging Fabry-Perot interferometer correlation spectroscopy - improving the accuracy of SO2 flux measurements
Authors: Heimann Jaro , Nies Alexander , Fuchs Christopher , Kuhn Jonas , Bobrowski Nicole , Platt Ulrich
Published: March 2022

Imaging of trace gases by optical remote sensing provides insight in the dynamics of physical and chemical processes within the atmosphere. Among the various sources for atmospheric trace gases, volcanoes pose additional challenges, as their highly variable emissions necessitate a high spatio-temporal resolution and their sometimes remote and inaccessible locations call for a robust and also portable measuring device.

We applied Fabry-Perot interferometer (FPI) correlation spectroscopy (IFPICS) that fulfils all of the above criteria. The periodic transmission of an FPI is matched to the periodicity of the vibronic narrowband absorption structure of the target trace gas absorption. The apparent absorptivity is then calculated from the difference of optical densities in two measurement settings whereas the FPI transmission coincides with the maxima of trace gas absorption in one setting and with the minima of the absorption in the second setting. Since the difference in wavelength between these two settings is only about 1nm, it is theorised that measurements with cloudy backgrounds become possible as their scattering properties aren't expected to differ much between the measurement settings and thus allow for cancellation. This is not the case for a conventional SO2-Cameras, as they rely on band-pass filters with transmission spectra that are about 20 nm apart.

We will show results of a first study on the influence of cloudy backgrounds on measurement results by determining the amount of SO2 caused by meteorological clouds in the field of view.

We also present measurements from July 2021 of SO2 fluxes at Mt. Etna with an IFPICS instrument with a detection limit of ≈ 5e17 molec/cm² at 4 Megapixel spatial resolution and 1 s temporal resolution and discuss uncertainties and challenges of the technique. 
Magnetic Signatures associated with Dust Impacts on Parker Solar Probe
Authors: Gasque Claire , Bale Stuart , Bowen Trevor , Dudok de Wit Thierry , Geotz Keith , Malaspina David , Pusack Anna , Szalay Jamey
Published: March 2022

As the closest humanmade object to the sun, the Parker Solar Probe (PSP) is uniquely positioned to study inner heliospheric dust. The PSP/FIELDS instrument suite detects dust via short voltage pulses generated by the plasma clouds formed during hypervelocity dust impacts on the spacecraft. Similar dust detection methods have been used on other missions, including Voyager 1 and 2, STEREO, Wind, Cassini, and Solar Orbiter. In addition to the voltage signatures, about 2% of dust impacts captured by Time Domain Sampler (TDS) burst data on PSP/FIELDS are shown to have magnetic signatures measured by the high-frequency winding of PSP's Search Coil Magnetometer (SCM). While magnetic signatures have previously been detected in laboratory hypervelocity impact experiments, they have not been previously reported in space. The signatures are brief (lasting less than 0.1ms), and are associated with high-amplitude voltage signatures. In this work, we present statistics and case studies of dust impacts with magnetic signatures on PSP. We will discuss the TDS calibration required to interpret the measurements physically, along with potential physical mechanisms for the magnetic signatures. We will also present early modeling efforts and implications for future hypervelocity impact studies.
The difficulty of finding conceptually correct yet practically feasible unsaturated hydraulic conductivity curves.
Authors: de Rooij Gerrit H.
Published: March 2022

In recent years, models for the unsaturated hydraulic conductivity have emerged that separate the soil hydraulic conductivity to constituting conductivities of water held in soil pores by capillary forces and of water adsorbed in films on the surface of soil grains. Some models include an equivalent hydraulic conductivity that accounts for diffusive movement of water vapor. The bulk soil hydraulic conductivity for a particular matric potential is the sum of these constituting conductivities.

The additivity attribute of the constituting conductivities relies on implicit assumptions regarding the configuration of the three domains: capillary water, water adsorbed in films, and the gas phase. These assumptions are not met in natural soils, and so alternatives to straight-forward addition are examined.

This examination unfortunately shows that any type of averaging of the constituting hydraulic conductivities leads to a non-monotonic hydraulic conductivity curve if the capillary water content reaches zero at a distinct matric potential above oven dryness. In fact, a correct expression for the hydraulic conductivity based on physically sound configurations of the domains can be shown to be realistically unattainable, leaving us without many alternatives for the additive model.

This being the case, an additive conductivity model and one alternative that is also unconditionally monotonic are introduced for a recently described parameterization of the soil water sigmoidal retention curve with a distinct air-entry value and a logarithmic dry branch terminating at a finite matric potential.
Unveiling Plant Community Shifts as a Consequence of Climate Change
Authors: Bergamo Thaisa , Ward Raymond , Joyce Christopher , Sepp Kalev
Published: March 2022

Coastal wetlands are considered valuable ecosystems for their biodiversity and the wide range of ecosystem services they supply. However, coastal wetlands worldwide are also subject to various impacts resulting from natural and anthropogenic drivers, such as urbanization and residential developments, conversion to agricultural land and climate change related impacts such as sea level rise, changes in precipitation, inundation, changes in salinity and erosion. The consequences of climate change over recent decades are evident in the Baltic Sea region, with modifications in sea water circulation, temperature and salinity. Due to the high importance of coastal wetlands and the impacts of climate change on this ecosystem, it is essential to determine how future conditions will influence coastal plant community functioning. In the Baltic Sea, both salinity and water levels have been shown to have a strong influence on coastal plant community composition. In order to assess the effects of climate change in coastal wetlands, an investigation of the influence of changes in water level and salinity on coastal wetland plant communities was undertaken. Future scenarios of Baltic coastal wetlands were evaluated using a three-year mesocosm experiment simulating altered environmental conditions. The response of three plant communities (Open Pioneer-OP, Lower Shore-LS and Upper Shore-US) were assessed in terms of changes in species composition over time. The experiment included 45 mesocosms, 15 per community with 5 treatments (3 replicates per treatment) with control, altered water level and salinity. In order to analyse the differences among treatments in plant communities through time, Permutational Multivariate analysis of variance (PERMANOVA) and species contribution were performed. Bray-Curtis dissimilarity was calculated from species importance values. Finally, a principal coordinate analysis (PCoA) based on Bray-Curtis dissimilarity was used to visualize the responses of the communities to treatments in each year. The results showed that all factors, year and treatment, influenced plant community composition. PCoA revealed plant community shifts in OP in the second year of experiment. Species were more clustered in LS and US communities compared to OP, but changes were still noted. The small spread of species throughout the years in ordination space in LS and US suggests a higher degree of similarity between communities across treatments. Based on these mesocosm experiments, it can be concluded that altered water level and salinity in Baltic coastal wetlands can have important consequences for species composition in plant communities, which support high diversity and are important for conservation.
Higher taxonomic diversity of protists, fungi and bacteria, but lower functional diversity in soils of agricultural ecosystems compared to a deciduous forest
Authors: Semenov Mikhail , Krasnov George , Ksenofontova Natalia , Nikitin Dmitry
Published: March 2022

Microbial taxonomic diversity is considered as one of the crucial factors responsible for the sustainable functioning of soil systems. However, it is still unclear to what extent microbial taxonomic diversity reflects its functional diversity. In this study, we compared taxonomic and functional diversity of the soil microbiome in a few natural and agricultural ecosystems.
Soil samples were collected three times (April, July, and October) from grassland, deciduous forest, and three agricultural ecosystems (no fertilizers, NPK, cattle manure). We applied high-throughput sequencing on the Illumina MiSeq platform using a combination of multiple DNA metabarcoding markers and characterized soil prokaryotic (16S rRNA gene: bacteria and archaea) and eukaryotic (ITS2 to target fungi; 18S rRNA gene to target protists) communities. Community-level physiological profiles of the soil microbiomes were analyzed using Biolog Ecoplates to assess functional diversity of heterotrophic microorganisms.
All five soils differed significantly from each other in the taxonomic composition of the bacteriome, the mycobiome, and the protistome. The forest soil microbiome was characterized by the higher relative abundances of Verrucomicrobia, Agaricomycetes, Apicomplexa, and Mesomycetozoa. Proteobacteria, Acidobacteria, Sordariomyces, Cercozoa, and Ochrophyta were the dominant taxa in the agricultural soils. Surprisingly, taxonomic diversity of the bacteriome, the mycobiome, and the protistome in forest soil was significantly lower compared to the agricultural soils (except the NPK treatment). Differences in microbial physiological profiles between distinct ecosystems were much lower than those in taxonomic diversity. The forest soil microbiome was characterized by the highest physiological activity and plasticity, especially for amines and phenolic compounds. Our findings suggest that lower microbial taxonomic diversity does not necessarily result in lower functional diversity of the soil microbiome.

This research was supported by the Russian Science Foundation, Project No 21-76-10025.
New features, broader accessibility, and improved performance of the Hector v3 simple carbon/climate model
Authors: Dorheim Kalyn , Bond-Lamberty Ben , Pressburger Leeya , Woodard Dawn , Gering Skylar , Shiklomanov Alexey
Published: March 2022

Hector is a carbon/climate model capable of emulating Earth System Model outputs at the global scale and is able to reproduce historical observations well. Like other participating models of the Reduced Complexity Model Intercomparison Project, Hector is a computationally efficient source of climate projections and thus has a wide range of applications such as scenario generation, coupling with integrated assessment models, outreach, education, and policy making. Hector version 3 includes a number of new features: carbon tracking, permafrost, improved land-ocean warming contrast, and a web browser-accessible interface. Here we summarize these developments and discuss how they improve the model’s performance and broaden its potential user base. 
High-resolution Poynting fluxes derived from the ESA Swarm mission: How much are we underestimating?
Authors: Billett Daniel , McWilliams Kathryn
Published: March 2022

The ESA Swarm constellation of satellites have been measuring the ionospheric electric and perturbation magnetic fields since 2013. Recently, the entire dataset of Swarm electric fields has been reprocessed into a 16Hz data product, allowing the analysis of ionospheric dynamics on sub-kilometre scales.

In combination with the on-board magnetometer data, the Swarm satellites can use the electric field measurements to determine the total electromagnetic energy into and out of the ionosphere, the Poynting flux. The 16Hz dataset allows for the capturing of much smaller scale sizes than previously considered, thus presenting the opportunity to study how much Poynting flux is missed when utilizing data across typically monitored scales (usually on the order of tens to hundreds of kilometres).

We present a statistical analysis of the Swarm A and B derived 16Hz Poynting flux, utilising various low-pass filters on the electric and magnetic field data to simulate smoothing the data to larger scale sizes. We find that by increasing the width of the low-pass filters, measured Poynting flux decreases significantly and quickly. Our results show that there is an over 50% underestimation in the total hemisphere integrated Poynting flux when observing it on scale sizes of a few hundred kilometres, compared to the raw 16Hz measurements that correspond to scales of around 0.5km. Under certain circumstances, as much as a 10% underestimation in the Poynting flux is observed by increasing scale size to only 5km. These results stress the importance observing small-scale electric and magnetic fields, as they may account for a large proportion of the ionosphere-thermosphere energy budget.
The IMF BZ Dependence of Cusp-Aligned Arcs
Authors: Thor Simon , Kullen Anita , Cai Lei
Published: March 2022

Occasionally, the auroral oval is filled with arcs pointing from the night side towards the cusp. These aurorae are known as cusp-aligned arcs. While there have been some theoretical predictions about their origins, the cause of these arcs remains unknown. For this study, we have identified both cusp-aligned arcs and regular transpolar arcs from DMSP satellite data. We investigate the correlation between the appearance of cusp-aligned arcs and various solar wind parameters, with a focus on IMF BZ and solar wind velocity. These results are then compared to the occurrence of regular transpolar arcs with respect to the same parameters. We see that cusp-aligned arcs appear almost exclusively when the IMF is northward for a long period of time, contrary to regular transpolar arcs which can have a varying, but typically northward on average, IMF. This result is in agreement with previous studies. No clear correlation between the solar wind velocity and cusp-aligned arc occurrence frequency can be seen. The results indicate that cusp-aligned arcs might be caused by Kelvin-Helmholtz instabilities at the flanks, as has been previously suggested. We also discuss other potential causes and models of cusp-aligned arcs in further detail. Additionally, we investigate the conjugacy of cusp-aligned arcs, based on DMSP data.
A simple and realistic aerosol emission approach for use in a double moment aerosol-aware microphysics scheme in the NOAA UFS Weather Model 
Authors: Li Haiqin , Barnes Hannah , Grell Georg , Zhang Li , Ahmadov Ravan , Sun Shan , Schnell Jordan
Published: March 2022

Aerosols play a significant role in the atmospheric precipitation physics of microphysics and convection. A physics suite, which includes the aerosol-aware double momentum Thompson microphysics scheme (Thompson MP), and the scale-aware and aerosol-aware Grell-Freitas (GF) convection scheme, was developed at NOAA Global System Laboratory (GSL).  In the Thompson MP, the hygroscopic aerosol is referred as a “water friendly” aerosol (WFA), and the non-hygroscopic ice-nucleating aerosol is referred as “ice friendly” aerosol (IFA). For usual Thompson applications, WFA and IFA are derived using climatologies from NASA’s Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. The Common Community Physics Package (CCPP), which is designed to facilitate a host-model agnostic implementation of physics parameterizations, is a community development and is used by many model developers. All physics parameterizations in the NOAA Unified Forecast System (UFS) Weather Model must be CCPP-compliant. Here we embedded sea-salt, dust emission, and biomass burning and plumerise emission modules as well as anthropogenic aerosol emissions into the UFS by using CCPP. These aerosol modules are directly called within the physics package. The prognostic emission of sea-salt, sulfate, and organic carbon are combined to represent the WFA emission, while the prognostic emission of dust is used to represent IFA emission. Wet-scavenging is included in both, resolved and non-resolved precipitation physics. Dry deposition is also parameterized. Subgrid scale transport is included in PBL and convection. There are no additional tracer variables introduced in this simple approach. In the global forecast with C768 (~13km) horizontal resolution and 128 vertical levels, the initial results are promising.
Predictability of the Indian Ocean and North Atlantic European circulation anomalies during early winter
Authors: Abid Muhammad Adnan , Kucharski Fred , Molteni Franco
Published: March 2022

In the current study, we analyzed the predictability of the tropical Indian Ocean precipitation anomalies and the North Atlantic European (NAE) circulation anomalies during the boreal early winter season using the ECMWF System-5 seasonal (SEAS5) prediction dataset. The observational analysis show that the boreal Autumn Indian Ocean dipole (IOD) conditions are the pre-courser for the early winter precipitation anomalies in the Tropical Western-Central Indian Ocean (TWCIO) region, which is well represented in the ECMWF-SEAS5 prediction system. Moreover, the ECMWF-SEAS5 skillfully predicts the Indian Ocean (IO) precipitation anomalies with some biases during the early winter. These biases tend to weaken the IO teleconnections to the NAE Region during the boreal early winter, mimicking the prediction skill of the NAE circulation anomalies. Furthermore, the positive TWCIO heating anomalies tend to favor the above normal Surface Air temperature (SAT) conditions over the NAE region, indicating to the mild early winter conditions over the region. The ECMWF-SEAS5 system shows a significant prediction skill of the surface temperature anomalies over the NAE region.
DAS Data Management Challenges and Needs
Authors: Mellors Rob , Trabant Chad ,   DAS RCN Data Management Working Group
Published: March 2022

Distributed Acoustic Sensing (DAS) is a relatively recent technology that has the capability to collect seismic (and other data) time series data using optical fiber as sensors. These optical fibers may be custom deployments or re-purposed telecommunication fibers. The range of applications is increasing rapidly, and recent studies include subsurface monitoring, earthquake hazard, geotechnical engineering, and ice flow. As the number of uses and studies increase, it is expected that the need for archiving of the datasets will also increase. Archiving of DAS faces multiple challenges at present. These include the need for large amounts (100’s TB) of storage, associated data transport and processing, and a standardized metadata format. As part of the DAS Research Coordination Network (RCN), a DAS data management working group is constructing a metadata model for DAS data that will address these needs. The objective is to develop a common metadata standard for archival purposes and guide data collection at experiments. The metadata requirements include: 1) accommodation of most use cases (data collection scenarios); 2) permitting of cloud-based processing; 3) allowing of pre-processing; and 4) reduction of the burden of data transport. Standard metadata principles, such as findability, accessibility, interoperability, reusability (FAIR), and machine-readability, will be adhered to. The purpose of this presentation is to inform potential users of these efforts, encourage adoption of the proposed standard, and invite community input.
Creating a database of electrical resistivity tomography surveys of permafrost in Canada and establishing best practices for data processing and sharing
Authors: Herring Teddi , Lewkowicz Antoni
Published: March 2022

Electrical resistivity tomography (ERT) is a geophysical method that produces an estimate of subsurface resistivity distribution, which can be used to infer the presence and extent of frozen ground. Repeated ERT surveys indicate how subsurface temperature and ground ice conditions are changing over time, which is particularly important for evaluating the changes and risks associated with climate change. However, there is no existing framework for sharing ERT data and datasets are rarely published, making it difficult to find and use historical data to assess subsurface changes. To facilitate data sharing, we are developing a Canadian database for ERT surveys of permafrost.

A key component of this project is the development of an automated ERT data processing workflow to prepare datasets. Establishing best practices for data processing ensures that ERT results are optimized and standardized, which is essential so that changes in subsurface conditions can be reasonably interpreted. We also present our web-based data visualization tool that allows for targeted searching of surveys and plotting of selected results. By storing ERT data in a standardized and accessible way, our goal is to facilitate interpretations of permafrost change on a range of spatial and temporal scales and guide future research in permafrost science.
Quantifying microseismic noise generation from coastal reflection of gravity waves using DAS
Authors: Guerin Gauthier , Rivet Diane , van den Ende Martijn , Stutzmann Eléonore , Sladen Anthony , Ampuero Jean-Paul
Published: March 2022

Secondary microseisms are the most energetic noise in continuous seismometer recordings, and they are generated by interactions between ocean waves. Coastal reflections of ocean waves leading to coastal microseismic sources are hard to estimate in various global numerical wave models, and independent quantification of these coastal sources through direct measurements can therefore greatly improve these models. Here, we exploit a 40 km long submarine optical fiber cable located offshore Toulon, France using Distributed Acoustic Sensing (DAS). We record both the amplitude and frequency of ocean gravity waves, as well as secondary microseisms caused by the interaction of gravity waves incident and reflected from the coast. By leveraging the spatially distributed nature of DAS measurements, additional fundamental information are recovered such as the velocity and azimuth of the waves. On average, 30\% of the gravity waves are reflected at the shore and lead to the generation of local secondary microseisms that manifest as Scholte waves. These local sources can give way to other sources depending on the characteristics of the swell, such as its azimuth or its strength. These sources represent the most energetic contribution to the secondary microseism recorded along the optical fiber, as well as on an onshore broadband station. Furthermore, we estimate the coastal reflection coefficient R$^2$ to be constant at around 0.07 for our 5-day time series. The use of DAS in an underwater environment provides a wealth of information on coastal reflection sources, reflection of gravity waves and new constraints for numerical models of microseismic noise.
New opportunity of RS - variable rainfall simulator for plots variable plots area
Authors: Kavka Petr , Neumann Martin , Laburda Tomas , Devátý Jan , Dostal Tomas
Published: March 2022

Rainfall simulators are devices commonly used to study soil erosion in field and laboratory conditions. There is still an effort to develop equipment that will: not require a large number of workers, be easy to manipulate, have simple control systems, and automatically record data and parameters.

This paper shows a new variable rainfall simulator with many possibilities, it consists of four independent sections that can be joined into larger simulator. Each section can simulate rain on a 2x4m area. The rain is generated by swinging and pulse mechanisms. Soil sensors and rain gauges are integrated into the control unit.

The whole device is placed on a trailer that is moveable by car. On the trailer, there is also a 1m3 water reservoir, control unit based on WAGO control unit with electric switchboard, water pump, hydraulic system and valves. The device could be controlled by any laptop or smartphone with a wifi connection.

Each section (4 total) consists of a boom with 3 nozzles connected to a stepper motor for swinging. Each nozzle has a valve to interrupt the water supply to the nozzle. These sections can be connected linearly to increase the length of the rainfall area (to maximum 16 meters), or they can be used parallelly, thereby performing multiple replications at one time on multiple areas side by side. All these sections are computer-controlled and are independent of each other. Each section contains sensors for measuring soil moisture and tipping bucket rain gauges for continuous monitoring of actual soil properties and control of the rainfall. Remote control also allows for variable rainfall scenarios. The device allows the use of both pulsed and swinging rainfall formation or their combination and thus a large variability in the choice of nozzles according to the purpose of the experiment. Water is pumped by the gas water pump throughout the redistributions and pressure reducing valve, which can manage the required stable pressure. It also contains a datalogger so all measurements and parameters are collected in one device.

This study has been supported by the Grant Agency of the Czech Technical University in Prague, grant No. SGS20/156/OHK1/3T/11 and the Project QK1910029.
Transport of dynamically fragmented polystyrene (PS) microplastics through saturated porous media
Authors: Ameen Ahmad , Stevenson Margaret E. , Jakwerth Stefan , Blaschke A. Paul
Published: March 2022

Insufficient information is available about the transport of fragmented microplastics in groundwater systems. To understand the transport processes, lab-scale column experiments were performed using fragmented microplastics. To mimic realistic microplastics present in the environment, polystyrene (PS) microspheres of diameter 3 and 10 µm were crushed dynamically into fragmented microplastics for injection. We examined the impacts of key physiochemical factors like concentration, soil grain size, flow velocity, ionic strength and straining. The detection and quantification of fragmented microplastics was carried out using solid-phase cytometry (SPC). We observed a high breakthrough of microplastics in coarse soils, and in fine soils, a lesser breakthrough of microplastics was observed because of straining phenomena and wedging of microplastics. Other influencing factors were: (i) greater flow velocity caused detachment and resulted in low attachment efficiency and (ii) ionic strength was found to have a smaller impact on microplastics transport due to their strong negative charge. Results and conclusions from the study provide a baseline of valuable information in order to better understand the mobility of small-sized fragmented microplastics through the soil-aquifer system.
Atmospheric blocking and Arctic Amplification: climatology and associated impacts in ERA5 data
Authors: Cadau Marco , Gaetani Marco , Fosser Giorgia , Bordoni Simona
Published: March 2022

In the context of the accelerating global warming, surface air temperature in the Arctic region is increasing faster than the Northern Hemisphere or global average. This phenomenon is expression of the so-called Arctic Amplification (AA), and is related to the interaction of several processes, including the observed reduction in sea ice and the associated ice-albedo feedback. The AA potentially affects atmospheric circulation patterns in the Northern Hemisphere, namely by modifying the westerly jet stream dynamics and the occurrence of weather regimes. In particular, atmospheric blocking at mid-to-high latitudes may be subject to significant variations in formation, frequency, spatial patterns and intensity due to of the changes in the AA-induced changes in atmospheric circulation.

The objective of this study is to investigate the dynamics of atmospheric blocking in the Northern Hemisphere, by analysing the variability and frequency of the associated spatial patterns at decadal time scales. To this aim, the ERA5 reanalysis is used, and blocking events are detected based on geopotential height gradients between mid and high latitude regions.

Results highlight that blocking is associated with the occurrence of extreme events, in particular with increased likelihood of heatwaves and cold spells in the blocking high. Moreover, impacts are observed in the region adjacent to the blocking high, due to the persistent deflection of synoptic disturbances. The relationship between AA and blocking events is also analysed, to identify possible mechanisms controlling the variability of atmospheric blocking in the last decades.
A Neural Network-Based Model of the Relativistic Electrons Fluxes in the Outer Radiation Belt
Authors: Chu Xiangning , Ma Donglai , Bortnik Jacob , Tobiska W Kent , Cruz Alfredo , Bouwer S. Dave , Zhao Hong , Ma Qianli , Zhang Kun , Baker Daniel N. , Li Xinlin , Spence Harlan , Reeves Geoffrey D
Published: March 2022

We present a machine-learning-based model of relativistic electron fluxes >1.8 MeV using a neural network approach in the Earth's outer radiation belt. The Outer RadIation belt Electron Neural net model for Relativistic electrons (ORIENT-R) uses only solar wind conditions and geomagnetic indices as input. For the first time, we show that the state of the outer radiation belt can be determined using only solar wind conditions and geomagnetic indices, without any initial and boundary conditions. The most important features for determining outer radiation belt dynamics are found to be AL, solar wind flow speed and density, and SYM-H indices. ORIENT-R reproduces out-of-sample relativistic electron fluxes with a correlation coefficient of 0.95 and an uncertainty factor of ∼2. ORIENT-R reproduces radiation belt dynamics during an out-of-sample geomagnetic storm with good agreement to the observations. In addition, ORIENT-R was run for a completely out-of-sample period between March 2018 and October 2019 when the AL index ended and was replaced with the predicted AL index (lasp.colorado.edu/home/personnel/xinlin.li). It reproduces electron fluxes with a correlation coefficient of 0.92 and an out-of-sample uncertainty factor of ∼3. Furthermore, ORIENT-R captured the trend in the electron fluxes from low-earth-orbit (LEO) SAMPEX, which is a completely out-of-sample data set both temporally and spatially. In sum, the ORIENT-R model can reproduce transport, acceleration, decay, and dropouts of the outer radiation belt anywhere from short timescales (i.e., geomagnetic storms) and very long timescales (i.e., solar cycle) variations.
The EDI and ECS logos and female ratios of awards in geoscience academic societies of Japan
Authors: Hori, S. Rie , Oguchi, T Chiaki ,   Kazuyo Sakanoi (Chair)
Published: March 2022

The EDI (Equality, Diversity and Inclusion) and ECS (Early Career Scientist) logos has been introduced since the EGU General Assembly 2021 held in19th-39th April 2021. Following to this initiative, JpGU decided to introduce EDI logos on a trial basis starting with the Japan Geosicence UNion Meeting 2021 (JpGU 2021) held in 30th May to 6th June 2021to promote diversity in the session organization and to recognize the degree of diversity. The Geological Society of Japan (JGS), which is one of the oldest geoscience academic societies in Japan established in1893, also tried to introduce both EDI and ECS logos at the 128th Annual Meeting of the society (128th JGS) held in 4th ‒ 6th September 2021. Although there was some negative reaction from male JGS members about this pilot introduction, we got about 10% sessions awarded the EDI logos in the both meetings. The JpGU 2021 also awarded the EDI logo to about 10% sessions. The JpGU have already decided to introduce EDI logo officially in the next 2022 meeting, and 20 per 230 sessions got EDI logos at present for the next annual meeting.

There are problems on female ratios of award or prize among Japanese geoscience societies, such as, 1) the ratio of female awardees or prize holders to whole awardees is predominantly lower in average than female ratios (ex. JpGU:15-27%, JGS:10%) to whole members, 2) female ratio of JpGU fellows is 0-15%, 3) there are no female honorary members in the long history of the JGS until 2020.

Awareness and diversified readership are essential and effective to improve the status of EDI among geoscience academic societies in Japan. For example, after the first female vice-president of JpGU elected at 2020, JpGU fellows increased from 0-15% to 25% and the Nishida Prize, which honor internationally recognized Mid-career researchers under the age of 45, named after Prof. Atsuhiro Nishida (JpGU fellow), winners increased to 40% in 2021. This change in diversity is just beginning and ongoing. 

The improvements in EDI issues among geoscience societies in Japan are also the result of strong networking or collaboration between EGU, AGU, GSA, JpGU and other societies related to geoscience. It is essential for further progress to share good practice and to keep pointing out and improve problems through global collaboration.  
Examination of magnetic map variability and uncertainty: crustal magnetic anomalies in oceanic areas
Authors: Saltus Richard , Chulliat Arnaud , Meyer Brian , Bates Martin
Published: March 2022

To paraphrase a common model aphorism: “all magnetic maps are wrong, some are useful”. In other words, all maps of the Earth’s magnetic field are subject to uncertainty, both observationally and dynamically. Depending on the intended use of the map, this uncertainty will have varying implications. For those of us who build and use magnetic maps it is important to gain understanding of the uncertainty in these maps to ensure that they are clearly presented and suitable for a given use.

Uncertainty evaluation is a general challenge that affects all magnetic maps and models, but here we concentrate on maps of magnetic anomalies (i.e., perturbations of the Earth’s main field primarily due to variations in magnetic minerals in the crust and shallow mantle) in oceanic areas.

Magnetic anomaly maps for oceanic regions are typically representations of gridded data. The grids are built from available data which generally consists of marine trackline data with a range of ages, collection parameters and uncertainty in original observations. Data coverage and trackline geometries are highly variable around the world. For example, near-shore regions in the Northern Hemisphere tend to be well sampled, whereas open ocean portions of the Southern Hemisphere are poorly sampled.

Quantification of cell by cell uncertainty for magnetic anomaly grids can be subdivided into two regimes: cells containing data and cells without data. For cells containing data, factors such as point-wise observation uncertainty, number of observations, and spatial distribution of data, can be analysed to estimate grid value uncertainty. For interpolated cells, factors such as distance to nearest data cells, local field behavior, and uncertainty in surrounding cells are relevant.

Using NOAA/NCEI trackline marine data for portions of the Caribbean Sea and North Atlantic we are constructing and testing uncertainty models and methods for representing this uncertainty for a variety of magnetic map uses. For a marine magnetic anomaly grid of a portion of the North Atlantic at a 4 km grid interval (the same grid interval used by our global EMAG2 magnetic anomaly compilation), the calculated cell level uncertainty ranges from 20 nT to 150 nT with a mean value of 90 nT. This mean value is similar to the average grid uncertainty of 100 nT/cell that we estimated for marine areas of EMAG2v3. Different gridding approaches, including kriging or minimum curvature algorithms, yield variations in individual cell values, but these variations fall within our estimated uncertainty ranges. 
Machine learning tools for predicting multi-hazards caused by convective storms - the TAMIR project
Authors: Pulkkinen Seppo , Niemi Tero , von Lerber Annakaisa , Leinonen Miikka , Renlund Tiia
Published: March 2022

Convective storms and long-lasting mesoscale convective systems have the potential to cause heavy rainfall, flooding, hail, wind gusts and lightning that can result in significant damage to property and loss of lives. Accurate prediction of the location or severity of such storms (e.g. in the sub-kilometer resolution for the next hour) to assist the decision-making of civil protection authorities is beyond the capabilities of the current numerical weather prediction models. Thus, weather radar and machine learning-based methods provide an important tool to predict such events and their impacts in advance. Identifying a storm cell or system as an “object” from a radar image provides a natural way for associating different meteorological attributes of a storm with its impacts. In the TAMIR project funded by the EU Civil Protection Mechanism, we have implemented this by combining a cell tracking system with a machine learning model. The hazard levels of storms are estimated from their distance and time delay to the associated emergency reports obtained from the PRONTO database provided by the Finnish civil protection authorities. Using several meteorological attributes related to severe weather (e.g. lightning flash, hail and wind observations and indicators of convective potential), a random forest model was trained for predicting the storm hazard level. This was done by using a large sample of data during summer months between 2013-2020. The model for predicting the hazard level was verified by cross-validation. A Kalman filter-based methodology was applied for probabilistic nowcasting of future storm locations, which was combined with the model for hazard level prediction. Finally, the hazard nowcasts were combined with different exposure layers to translate them into prediction of impacts caused by convective storms. In the presentation, we demonstrate the added value of the implemented hazard and impact nowcast products with case studies. The products have also been evaluated by the Finnish civil protection authorities during the test period June-September 2021 with largely positive feedback. While the feasibility of the proposed methodology is demonstrated in Finland, discussion about its transferability to other parts of the world is also given.
Influence of the Asian Summer Monsoon on the Chemical Composition of the Upper Troposphere and Lower Stratosphere using the MUSICA Regionally Refined Chemistry Climate Model 
Authors: Kinnison Doug , Zhang Jun , Honomichl Shawn , Smith Warren , Pan Laura , Tilmes Simone , Zhu Yunqian , Emmons Louisa , Saiz-Lopez Alfonso
Published: March 2022

The role of the Asian Summer Monsoon (ASM) on influencing the chemical composition of the upper troposphere and lower stratosphere (UTLS) will be examined using the recently developed three-dimensional MUlti-Scale Infrastructure for Chemistry & Aerosols (MUSICA) chemistry-climate model. MUSICA uses a Spectral Element dynamical core, with an ASM regional refinement (RR) option where the horizontal resolution is increased from ~1.0 º to ~0.25º and the vertical resolution is ~500m in the UTLS. For this study, the specified dynamics option is applied where the temperature, zonal and meridional winds from the NASA Goddard Earth Observing System version 5 (GEOS5) data assimilation model are used to drive the physical parameterization controlling boundary layer exchanges, advective and convective transport, and the hydrological cycle. MUSICA includes fully interactive chemistry with ~240 chemical species and over 500 chemical reactions along with the representation of sulfate, primary and aged black carbon, primary and secondary organic, sea salt, and dust aerosols. This model study will examine the magnitude and variability of ozone precursors (e.g., VOCs, NOx, and CO) and halogen ozone depleting substances in the ASM UTLS outflow region for the 2017 through 2021 boreal summer seasons. The interannual influences of the ASM chemical emissions on UTLS oxidizing capacity and odd-oxygen loss processes will be quantified. The results from this model study will address the main hypothesis of the Asian summer monsoon Chemical and Climate Impact Project (ACCLIP), namely that the western Pacific is a significant pathway for reactive chemical pollutants and climate-relevant emissions from the ASM to enter the global UTLS. ACCLIP is an NSF/NASA supported airborne mission that will based from Osan, South Korea in July/August 2022.
Long-term interannual changes in extreme winds and waves in the Black Sea
Authors: Staneva Joanna , Ricker Marcel , Akpinar Adem , Behrens Arno , Giesen Rianne , von Schuckmann Karina
Published: March 2022

This study aims to analyse long-term interannual changes in extreme winds and waves in the Black Sea. Severe wave conditions from 1979 to 2020 are detected using the 99th percentile of the significant wave height (SWH), based on the method proposed in (Weisse and Günther, 2007; Staneva et al., 2020a). Long-term spatial wave statistics of the Black Sea are then obtained based on the annual trend of 99th percentile SWH and the number, lifetime, and intensity of extreme events occurring between 1979 and 2020. In addition, the variability of these extreme event characteristics is demonstrated. Besides, wave reanalysis of the Black Sea is used to investigate intraannual variation and long-term wave energy potential change. Hence, wave power and wind statistics are shown for Black Sea CMEMS multiyear products to identify the most suitable areas for wave energy exploitation and offshore wind power potential and to determine the safe and efficient design, installation and operation of marine energy sector assets. The results reveal that the average number of storm events is the highest in the eastern basin. In contrast, the average lifetime reaches a maximum on the southwestern coast. Intensity peaks in the same region as the lifetime but is also high in the basin interior. Spatial mean extreme event analyses show a slight increase in event numbers and intensity, but decreasing trends for the event lifetime and maximum area of storm events. In regions where wave conditions are strong, there have been increases in extremes relative to normal conditions in recent years. This can significantly affect designs. In terms of wave energy, mean wave power peaks in the southwestern area of the Black Sea. The wave power trend follows a pattern similar to that of the SWH with a pronounced east–west difference; its variation is higher, resulting in a coefficient of variation (CoV) of ~2.5.

 
Interpretation of a thermal response test in a Bayesian framework to infer the hydraulic properties surrounding a standing column well
Authors: Jacques Louis , Pasquier Philippe
Published: March 2022

The main objective of a thermal response test is to identify the thermal properties near ground heat exchangers. In standing column wells, the groundwater acts as the heat carrier fluid, rending hydraulic and thermal responses strongly related. Consequently, the identification of hydraulic properties through thermal response test is possible. In this study, the Bayesian framework is employed to infer joint and marginal distributions of thermal and hydraulic properties based on the experimental data gather during a 160-hour thermal response test. This test was conducted on a standing column well constructed in a layered aquifer having locally high groundwater velocities. To simulate the thermal response test, a finite element numerical model is first used to generate a training dataset. Then, a neural network is trained to emulate the ground heat exchanger response in fractions of seconds. This strategy accelerates the computation of the Markov chain Monte Carlo slice sampling algorithm.  A closed-form expression of the likelihood that takes into account the temporal correlation of the data is also used to obtain additional speedup. Main results indicate an accurate estimation of the hydraulic properties in comparison to results found by complementary experimental pumping tests completed at the same site. In accordance with the high velocities observed while drilling at this particular site, high hydraulic conductivity is obtained at the bottom of the borehole. It was possible to draw robust statistical distributions of hydraulic properties with only a thermal response test, while also assessing the thermal properties and their uncertainties.