bluuebunny/crossref_metadata_2025 huggingface dataset:
Ozone profiles without blind area retrieved from MAX-DOAS observations: methodology, validations and applications
Authors: Ji Xiangguang , Liu Cheng , Wang Yang , Hu Qihou , Wagner Thomas
Published: February 2023

    Tropospheric ozone (O3) profiles, especially within the boundary layer, are essential for studying the vertical, temporal, spatial variations, as well as the formation sensitivity and regional transport of O3. However, it is rare to find continuous tropospheric O3 profiles with high temporal and spatial resolutions without blind areas using current remote sensing technologies, with issues such as low near-surface sensitivity or systematic blind areas from satellite and LiDAR observations, respectively, being encountered. Here, multi-source data including stratospheric O3 profiles from external datasets and local monthly dependent a priori profiles were fused in the retrieval algorithm, then vertical O3 profiles from the near-surface to the free troposphere were retrieved from multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements. This study mainly includes the following three points: First, with the aim of deriving a set of best practice recommendations for applying a profile inversion algorithm to long-term observations, we comprehensively investigated the influence of various settings on profile retrieval, with emphasis on the selection of a Fraunhofer reference spectrum and appropriate a priori profiles in the upper troposphere. Secondly, tropospheric O3 profiles were retrieved for operational MAX-DOAS observations in Beijing, and the results, especially for the boundary layer, were evaluated in detail with respect to well-established independent O3 datasets, including one-year ozonesonde profiles and tower-based in-situ measurements at different altitudes. A good level of agreement was found for both near-surface and elevated-altitude results, and the MAX-DOAS O3 profiles were able to reproduce the vertical distributions measured by ozonesonde. Then, the characteristics of ozone vertical temporal variations during the pollution episode were concluded. At the meanwhile, vertical ozone formation sensitivities across the Chinese metropolis, such as Beijing, Guangzhou, etc., were studied basing on the retrieval of O3, HCHO and NO2 from MAX-DOAS observations.
Inverting the Subsurface Fracture Density by Detecting the Phase Difference of Various Seismic wave with Machine Learning
Authors: Yu Ting-To , Peng Wen Fei
Published: February 2023

The fracture density of rock could create the applying shock waves phase difference at the laboratory scale. For using this technology in determining the stress status along the wave propagating path, removing unnecessary noise is the most crucial task. In this study, a machine learning method with Long short-term memory (LSTM) algorithm to retreat the signals from sophisticated seismograms is proposed. The primary analyzing target is data across the 2022 Taitung, Eastern Taiwan seismic event and another micro-seismic data set associated with a surface crack on a hill of Ping-Tong, southern Taiwan. It is found that there is no phase difference among vertical and horizontal components from the same record, when comparing the difference between two various records then the result is distinct. The detecting sub-surface crack density via phase difference has increased in some seismic data pairs of eastern Taiwan after the rupture of the 2022 Taitung earthquake. The machine learning method with LSTM helps to elevate the data retrieval accuracy which cannot be done by conventional Fast Fourier Transformation (FFT). Records from stations adjacent to the hypocenter offer better agreement in phase difference measurement, the higher signal possibly causes it to noise ratio (SNR) in the such neighborhood. Keywords: phase difference, machine learning, LSTM, crack density, stress field
The critical importance of mine waste- an Australian Perspective
Authors: Parbhakar-Fox Anita
Published: February 2023

Australia, whilst host to many greenfield exploration and new mining activities, also contains at least 50,000 abandoned or historic mine sites. These may not necessarily present immediate or long-term environmental risks (e.g., noxious dust or acid and metalliferous drainage (AMD) formation), but may still contain mine waste (e.g., tailings, waste rock, slag) ultimately requiring rehabilitation. Who is ultimately required to fund and complete rehabilitation may be controversial and/or contentious depending on the circumstances of mine closure. However, across Australia, there is a growing recognition that these sites may contain critical raw materials (CRMs), particularly those required for the energy transition leading to the birth of several research programs to investigate the secondary prospectivity of mine waste. In addition to individual mining companies, Geoscience Australia and the Queensland, New South Wales, Northern Territory and South Australian Governments have commissioned research to investigate the tenor and deportment of critical metals (as identified by the Australian Government) including cobalt, rare earth elements (REE), vanadium, indium, gallium, germanium, selenium, antimony, bismuth and manganese. Currently, over 40 sites have been sampled (targeting tailings, waste rock and metallurgical wastes including slag, phosphogypsum slimes, spent heap leach and coal combustion products) and assessed using an integrated geometallurgical testing program.Early results have identified REEs (lanthanum and cerium) in tailings and waste rock at the Mary Kathleen mine, Queensland. New metallurgical extraction methods are being developed to enable ‘greener’ recovery. In addition, cobalt has been identified in the waste associated with iron-oxide copper gold (IOCG) and sedimentary hosted copper deposits in the North West Minerals Province, Queensland encouraging operational mines to consider mineral processing plant modifications to recovery this battery metal. Distinct manganese enrichment has been observed in wastes associated with Broken Hill type deposits, whilst indium is associated with volcanic hosted-massive sulphide (VHMS) and greisen deposits. Ongoing research is focused on developing business cases for CRM extraction at fertile sites. Post extraction, additional valorisation opportunities are being sought (e.g., aggregates, sulphuric acid production, ore sands) for the residual waste, and those barren (in CRM terms). By considering mine waste in these terms, Australia has an opportunity to significantly establish and grow their circular economy and take steps towards meeting their ambitious economic targets (AUD $26 Billion by 2025).
Emirates Mars Mission - Hope Probe - in a Martian Year
Authors: Almatroushi Hessa , Deighan Justin , Holsclaw Greg , Edwards Christopher , Wolff Michael ,   EMM Science Team
Published: February 2023

In April 2023, the Emirates Mars Mission (EMM) completes its primary science mission observing the Martian atmosphere with global coverage examining the diurnal and seasonal variations throughout one full Martian year. The mission has disseminated publicly more than 1 TB of scientific data combined from three scientific instruments studying the atmosphere of Mars from ultraviolet, visible, and infrared bands. The measurements are taken from a highly elliptical orbit (20,000 km periapse and 43,000 km apoapse) providing unprecedented local and seasonal time coverage over most of the planet. Here we summarize the discoveries and key results from the primary science mission of EMM revealing atmospheric behavior and connections that challenge existing models and assumptions that we have of the Martian atmosphere and form new global perspective of the planet. We will also highlight the status of the mission and recent updates on its extended science phase.
IMERG Run Deep: Can we produce a low-latency IMERG Final run product with a deep learning based prediction model?
Authors: Hung Ho Tin , Wang Li-Pen
Published: February 2023

IMERG is a global satellite-based precipitation dataset, produced by NASA. It has provided valuable rainfall information to facilitate the design or the operation of the disaster and risk management worldwide. In operation, NASA offers three types of IMERG Level 3 (L3) products, with different levels of trade-offs in terms of time latency and accuracy. These are Early run (4-hour latency), Late run (14-hour latency) and Final run(3.5-month latency). The final-run product integrates multi-sensor retrievals and provides the highest-quality precipitation estimates among three IMERG products. It however suffers from a long processing latency, which hinders its applicability to near real-time applications. In the past 10 years, deep learning techniques have made significant breakthroughs in various scientific fields, including short-term rainfall forecasting. Deep learning models have shown to have the potential to learn the complex variations in weather systems and to outperform the Numerical Weather Prediction (NWP) in terms of short lead-time predictability and the required computational resources for operation. In this research, we would like to explore the potential of deep learning (DL) in generating high-quality satellite-based precipitation product with low latency. More specifically, we investigate if DL models can learn the difference between Final- and Early-run products, and thus predict a Final-run-like product using Early-run product as input. Low-latency yet high-quality IMERG precipitation product can be therefore obtained. Various DL techniques are being tested in this work, including Auto-Encoder(AE), ConvLSTM and Deep Generative model. IMERG data between 2018 and 2020 over a rectangular area centred in the UK is used for model training and testing, and ground rain gauge records will be used to evaluate the performance of the original and predicted products. This pilot includes both ocean and land regions, which enables the comparison of the model performance between two different surface conditions. Preliminary analysis suggests that given patterns do exist in the differences between Early- and Final-run products, and the capacity of the selected DL models to learn the differences will be further investigated. The proposed work is of great potential to improve the applicability of IMERG products in an operational context.
Oxidative potential and chemical characterization of PM2.5 in a medium-sized residential city of South Korea.
Authors: Park Sung-Won , Han Youngj-Ji , Jeon Ji-Won , Hong Jin-Hyuk , Lee Hyo-Won , Hong Se-in , Koo Ji-Hyeon , Kim Young-Kyu
Published: February 2023

PM2.5, defined as particulate matter less than 2.5 μm, is derived from a variety of natural and anthropogenic sources. Studies have shown that PM2.5 adversely affects human health, causing various respiratory and cardiovascular diseases. One of the methods to assess the potential health impacts of PM2.5 is to measure its oxidative potential, which refers to the ability of the particles to generate reactive oxygen species when inhaled into the lungs. In this study, antioxidants including ascorbic acid (AA) and reduced glutathione (GSH) as well as dithiothreitol (DTT) were used to measure the oxidative potential of PM2.5 collected in Chuncheon, a medium-sized residential city of South Korea. The degree of oxidation of antioxidants and DTT were measured using a spectrophotometric assay. In addition, a detailed PM2.5 compositions including NO3-, SO42-, NH4+, organic carbon (OC), elemental carbon (EC), metallic elements, and individual organic substances were measured to identify the characteristics of high PM2.5 concentration episodes (HCE) and to determine the association between chemical components with oxidative potential.PM2.5 concentrations were generally higher in fall than in summer, and OC was the biggest contributor to PM2.5 mass. Among organic matters, sugar compounds, the marker species of biomass burning, were prominent while dicarboxylic acids, predominantly secondarily formed in atmosphere, were important in summer. For HCEs, NO3- and dicarboxylic acids increased the most among PM2.5 components, suggesting that secondary formation was important to enhance PM2.5 concentration. Nitrogen oxidation ratio (NOR) also increased during HCEs, and there was statistically significant correlation between NO2 and NO3-, possibly indicating that in situ oxidation of NO2 and/or gas-aerosol partitioning for HNO3 and NO3- occurred. Average OP measured by depletion of AA (OPAA), GSH (OPGSH), and DTT (OPDTT) were 4.5 ± 1.1, 4.9 ± 1.3, and 17.7 ± 5.9 pmol min-1 mg-1, respectively, during summer. All three OPs were especially low for the sample obtained when Asian dust event occurred. PM2.5 mass concentration was successfully reconstructed by EC, ∑n-Alkane, Ca2+, SO42–, and OC from multiple linear regression while oxidative burden by GSH (OBGSH) was explained by EC and ∑PAHs. These different results between PM2.5 mass and OP suggest that the PM2.5 concentration alone is not sufficient to explain the association with health effects.
Impact of Turbulence Energy Cascade Process and Eddy Intermittency on Suspended Sediment Particle in Open Channel Flow
Authors: Lin Shi-Wei , Tasi Christina W.
Published: February 2023

Turbulence is chaotic and full of different spatial and temporal scales of eddies in its energy cascade process (Richardson, 1922). Moreover, it is observed that erratic behavior occurs in turbulent properties, such as flow velocity (Townsend, 1949) might result in the intermittency of turbulent eddy occurrences. As we know, the movement of sediment particles is not only influenced by flow advection but also by turbulent eddies. For turbulence, particle diffusivity is a coefficient used to measure the impact of turbulence on particles. This study attempts to build a linkage between turbulent eddies and particle diffusivity. On the other hand, turbulent eddies are an intermittent process, which will be further considered in this study. To consider the chaotic property of turbulence on particle motion, Man and Tsai (2007) proposed the stochastic diffusion particle tracking model (SD-PTM) based on the mass conservation and the Langevin equation of particle displacement to simulate the suspended particle in open channel flow. Their model regards suspended particle movements as a stochastic process and uses Brownian motion to describe particle irregular trajectories caused by turbulence. To investigate the impact of the energy cascade process and eddy intermittency on particles, we aim to develop a modified stochastic diffusion particle tracking model (MSD-PTM) that incorporates the effect of the energy cascade process and turbulent intermittency. In the proposed model, an additional stochastic term will be considered to simulate the impact of the turbulence energy cascade process. In addition, a physical parameter will be used to represent the intermittency effect of eddies. The MSD-PTM will be compared with SD-PTM for statistical properties of particle movement such as the ensemble statistics of particle trajectory and concentration profile. The sensitive analysis will be used to evaluate the degree of impact of the turbulent energy cascade and eddy intermittency on suspended sediment particles.  
Evaluating the L-MEB forward radiative transfer model for the assimilation of SMOS observations
Authors: Jamei Mozhdeh , Asadi Oskouei Ebrahim
Published: February 2023

Satellite observations play an important role in providing the initial conditions for the Numerical Weather Prediction (NWP) models. Satellite data are assimilated into the first estimate provided by NWP models using a radiative transfer model. The impact of satellite observations significantly depends on the accuracy of the simulation performed by the radiative transfer (RT) models. In recent years, there have been significant advances in RT modeling for microwave and infrared observations, which are not sensitive to the surface. However, in the case of sensitive surface observations such as Soil Moisture and Ocean Salinity (SMOS) satellite observations, the assimilation has been limited by inaccuracy in the forward calculations. This study investigates the accuracy of the L-band Microwave Emission of the Biosphere (L-MEB) RT model for SMOS frequencies using high-quality in-situ observations as input. The L-MEB model is the forward RT model used in the SMOS L2 algorithm, specifically developed to simulate brightness temperature (TB) over the land surfaces at different incidence angles (between 0° and 60°). The L-MEB model simulated the SMOS TB data with the horizontal (H) and vertical (V) polarization at the lowest SMOS incidence angles at the meteorological stations over Iran.The land cover at these stations is either bare soil or low vegetation. The comparison between simulated TB and the SMOS TB products showed a suitable RMSE and a relatively low bias for horizontally and vertically polarized channels. The relatively low bias can justify the assimilation of SMOS observations into the data assimilation systems. However, cross-comparison of the RT models used at the NWP centers and the RT models such as L-MEB, which were mainly developed to work with the SMOS data, is required to ensure that the operational RT models used at the NWP centers meet the same accuracy. 
Long-term sensor drift of pressure gauges characterized by a pressure balance
Authors: Matsumoto Hiroyuki , Kajikawa Hiroaki , Araki Eiichiro
Published: February 2023

It is postulated that a pressure gauge has potential for detection of vertical crustal deformation associated with plate convergence since the measurement resolution is higher than the expected deformation. However, it has been long known that the sensor drift being a few of hPa (cm) per year or larger rate is identified in the long-term pressure observation at the seafloor. We have investigated the sensor drift of pressure gauges pressurized by a pressure balance in the laboratory. Two types of pressure gauges were examined; one is quartz resonant pressure gauges which are traditionally used for in-situ pressure observations and the other is silicon resonant pressure gauges which can be used for oceanographic observations in the future. Full scale of all pressure gauges examined in the present experiment is 70 MPa. Pressure calibration curves were obtained by applying the standard pressure from zero to full scale to characterize hysteresis and repeatability of pressure gauges. Comparing pressure calibration curves under the different temperature condition, only zero offset is changed for the tested quartz pressure gauges, whereas both zero offset and span are changed for some silicon pressure gauges. Then, static pressure of 20 MPa equivalent to 2000 m water depth is applied to the pressure gauges simultaneously for a period of approximately 100 days under the low temperature condition. Some silicon pressure gauges were pressurized under the normal temperature condition. Pressure calibrations were conducted about 50 times repeatedly by providing the standard pressure of 20 MPa using the pressure balance during the experiment. Differences between the standard pressure and the sensor’s output over time were calculated to evaluate the sensor drift. The results suggest that the lower ambient temperature can contribute to the shorter relaxation time (i.e., the elapsed time to disappear initial abrupt change) and the smaller sensor drift (i.e., the linear trend) in the both types of pressure gauges. The sensor drift between the quartz and the silicon pressure gauges were comparable except for the specific silicon pressure gauges. It is noted that the quartz pressure gauges are more sensitive to temperature than the silicon pressure gauges in the present experiment.
Investigation of optimal probability distribution of Standard Precipitation Index for daily precipitation time series in Southern Korean Peninsula
Authors: Lee Chaelim , Seo Jiyu , Won Jeongeun , Kim Sangdan
Published: February 2023

The Standardized Precipitation Index (SPI) is applied worldwide for drought assessment. In general, in many studies, SPI was estimated from a two-parameter gamma distribution. However, in other climatic regions, there are also studies that suggest that distributions other than the Gamma distribution are more suitable. In addition, as the frequency of drought events increases, the need for daily SPI calculated with relatively short time-scales for immediate drought response is increasing. In this study, the optimal probability distribution for estimating SPI using daily precipitation in the southern part of the Korean Peninsula was explored. Gumbel, Gamma, GEV, Loglogistic, Lognormal, and Weibull are applied as candidate distributions, and optimal distributions for each season, region, and time-scale are investigated. The Chi-square test was applied to investigate the probability distribution function appropriate to the cumulative daily precipitation time series for various time-scales. In the process of calculating the SPI, when the cumulative daily precipitation has a value of 0, the cumulative probability value was calculated by reflecting the probability of having a value of 0. Then, by applying the candidate distribution, it was verified whether the estimated SPI conformed to the standard normal distribution. Finally, a more precise drought assessment could be performed by determining the optimal probability distribution for each region, season, and time-scale. It is also expected to increase the applicability of daily SPI by reducing problems that occur in a short time-scale. 
Acknowledgement
This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. NRF-2022R1A2B5B01001750).
Slow rupture propagation and large stress drop during the 2020 Mw6.4 Petrinja earthquake
Authors: Lončar Iva , Causse Mathieu , Vallée Martin , Markušić Snježana
Published: February 2023

Seismological data from almost 100 broadband stations (70 < Δ < 420 km) from Croatia, Slovenia, Hungary, Italy, Austria, Bosnia and Hercegovina, Montenegro, and Slovakia have been used in the rupture analysis of the Petrinja (Croatia) MW6.4 earthquake, that occurred on the 29th of December 2020. Several foreshocks and aftershocks have been used as empirical Green’s function (EGF) to isolate source effects from propagation and local soil effects. First, P-wave mainshock seismograms are deconvolved from the EGF seismograms in the frequency domain to obtain the corner frequency (fc). Assuming Brune’s source model, the spectral analysis results in a large stress drop of 25 MPa. Second, using time-domain deconvolution of the Love wave time windows, apparent source time functions (ASTFs) have been computed and indicate an average source duration of 5 seconds. No significant directivity effects can be seen in both the fc values and source durations, whose weak variability suggests a bilateral rupture. Lastly, physical rupture parameters, such as rupture velocity, rupture dimensions, slip model and rise time, have been extracted from the ASTFs by two different techniques: (1) the Bayesian inversion method (Causse et al. 2017) and (2) the backprojection of the ASTFs on the isochrones (Király‐Proag et al. 2019). Both techniques indicate a slow rupture velocity (about 50% of the shear-wave velocity) and a rather short rupture length for an MW6.4 event (about 8 km), consistent with the obtained large seismological stress drop. Such features may be explained by the relatively complex and segmented fault system, typical of immature fault contexts. References:Causse, M., Cultrera, G., Moreau, L., Herrero, A., Schiappapietra, E. and Courboulex, F., 2017. Bayesian rupture imaging in a complex medium: The 29 May 2012 Emilia, Northern Italy, earthquake. Geophysical Research Letters, 44(15), pp.7783-7792.Király‐Proag, E., Satriano, C., Bernard, P. and Wiemer, S., 2019. Rupture process of the M w 3.3 earthquake in the St. Gallen 2013 geothermal reservoir, Switzerland. Geophysical Research Letters, 46(14), pp.7990-7999.
The rate of information transfer as a measure of ocean-atmosphere interactions
Authors: Docquier David , Vannitsem Stéphane , Bellucci Alessio , Frankignoul Claude
Published: February 2023

Exchanges of momentum, energy and mass between the ocean and atmosphere are of large importance in regulating the climate system. Here we apply the Liang-Kleeman rate of information transfer to quantify interactions between the upper ocean and lower atmosphere over the period 1988-2017 at monthly time scale in two different case studies. In the first case study, we investigate dynamical dependencies between sea-surface temperature (SST), SST tendency and turbulent heat flux in satellite observations. We find a strong two-way influence between SST or SST tendency and turbulent heat flux in many regions of the world, with largest values in eastern tropical Pacific and Atlantic oceans, as well as in western boundary currents. The total number of regions with a significant influence of turbulent heat flux on SST and SST tendency is reduced when considering the three variables, suggesting an overall stronger ocean influence compared to the atmosphere. In the second case study, we focus on the influence of ocean heat transport convergence (dynamical influence) and net surface heat flux (thermodynamical influence) on upper ocean heat content tendency in three global climate models with at least two different ocean resolutions. We find that low-resolution model configurations (1° in the ocean) show a much larger number of regions with a significant dynamical influence compared to high-resolution model configurations. The reason for the large difference in dynamical influence between low and high resolutions partly comes from the spatial distribution of ocean velocity field, which displays a larger spatial variability at high resolution.
Retrieval of tropospheric ozone using TANSO-FTS-2 on GOSAT-2: a regional trend analysis of metropolitan area in Japan
Authors: Li Arthur Ho Wang , Imasu Ryoichi
Published: February 2023

The Greenhouse gases Observing SATellite-2 (GOSAT-2, launched on October 29, 2018) has shown immense potential in CO2 and CH4 research, as a successor of GOSAT; however, the retrieval of tropospheric ozone is yet to be analyzed. Meanwhile, metropolitan areas are regarded as tropospheric ozone source for emission of ozone precursors (NOx and VOC) by anthropogenic activities. The extreme surface temperature due to urban heat island effect can potentially modify the averaging kernel (AK) of satellite retrieval; this effect, "thermal contrast", is expected to favor the analysis of ozone in urban areas.

In the paper, we aim at providing the first results of 3-year tropospheric ozone retrieval using thermal infrared (TIR) band from the nadir-looking instrument Thermal And Near infrared Sensor for carbon Observation – Fourier Transform Spectrometer-2 (TANSO-FTS-2), which is onboard GOSAT-2. The retrieval is focused on the urban area of Tokyo, Japan by the targeting mode of FTS-2 with around 40×40 km2 domain. In the retrieval process, we basically apply the optimal estimation and the Line-By-Line Radiative Transfer Model (LBLRTM) as the forward model, with the spectroscopic line parameters from HITRAN 2016 database. The climatological mean of the tropospheric ozone in Tokyo is applied as the a priori profile. For validation, we use ozonesonde data in Tsukuba, Japan (36.06° N, 140.13° E) with averaging kernel smoothing method. The results are also compared with ground measurements obtained from Atmospheric Environmental Regional Observation System (AEROS) of Japan. The performance of retrieval is evaluated by the degree of freedom of signal (DOFS), root-mean square error (RMSE) and mean bias (BIAS), in comparison with previous satellite missions such as TES and IASI.

Our results present day-to-day and seasonal variation of tropospheric ozone in metropolitan area, while elucidating the urban heat island effect on the sensitivity of satellite retrieval and the characteristics of retrieved ozone episodes in view of meteorological conditions. Our results facilitate the assessment of urban tropospheric ozone trend and lead to better understanding of ozone chemistry using new satellite observations. Global validation and analysis of GOSAT-2 retrieval will be presented in a subsequent paper.
Earthquakes illuminate the incipient collision and subduction of Loyalty Ridge at Vanuatu subduction zone
Authors: Passarelli Luigi , Cesca Simone , Nooshiri Nima , Jónsson Sigurjón
Published: February 2023

Bathymetric highs resist subduction producing large- to small-scale change in the morphology of the subduction zone: Increase of the outer-rise curvature, trench indentation and large-scale slides and slumps in the fore-arc region. At the plate interface, bathymetric highs induce geometrical and frictional changes that can produce increase or decrease of the local coupling, and thus having an effect on the likelihood of occurrence of large megathrust earthquakes. Numerical models predict complex strain and stress patterns arising from subduction of such relief mainly driven by the size and relative geometry of trench and subducted high. However, the collision and subduction of bathymetric highs is investigated mainly via geophysical and geological surveys since seismic sequences have rarely illuminated the subduction of seafloor relief. Here, we report of a year-long and very energetic earthquake activity (10 Mw 6.5-7.5) at the Loyalty Ridge – Vanuatu trench at both the plate interface and in the outer-rise region. The spatio-temporal and magnitude of the earthquakes revealed complex release of the accrued flexural strain along the outer-rise and a pronounced segmentation of the interface with repeating M7 earthquakes, low aftershock activity and a large “aseismic” zone. The collision and subduction of the Loyalty Ridge along the Vanuatu trench seem to indicate a frictionally segmented interface where large megathrust earthquakes are unlikely to occur.
An efficient poroelastic wave simulation based on discontinuous grid and nonuniform time step
Authors: Zhang Heng , Ren Hengxin , Sun Yao-Chong , Li Mingbo , Wang Tao , Fang Changjiang
Published: February 2023

The existence of slow P wave, in addition to fast P wave and S wave, makes it tricky for grid-based numerical simulation methods to conduct poroelastic wave modeling. The grid spacing has to be fine enough to capture the slow P wave since the velocity of slow P wave is much smaller than that of the other two waves. Dense space and time steps significantly increase the computation cost. In this study, we propose a poroelastic finite-difference simulation method that combines discontinuous curvilinear collocated-grid and non-uniform time step Runge-Kutta scheme. Only the space and time steps for the areas near interfaces, where the contribution of slow P wave is non-negligible, are refined in an effort to speed up the computation. The refined space step is determined by the velocity of slow P wave, while the coarse space step is determined by the velocity of shear wave. The coarse and refined time steps are set according to the non-uniform time step Runge-Kutta scheme, which is derived with Taylor expansion and avoids interpolation or extrapolation for communication between different time levels. This scheme helps maintain fourth-order accuracy in the whole domain. The accuracy and efficiency of the proposed method are verified by numerical tests. Compared with the conventional curvilinear collocated-grid finite-difference method that uses a uniform space grid as well as a uniform time step, the computation efficiency is improved significantly and the computation time can be saved by more than 80%.
Preliminary evaluation of the ECMWF 6th generation ocean and sea-ice reanalysis system (ORAS6)
Authors: de Boisseson Eric , Zuo Hao , Browne Philip , Chrust Marcin , Balmaseda Magdalena , de Rosnay Patricia , Balan Sarojini Beena
Published: February 2023

Ocean and sea-ice reanalyses are reconstructions of historical ocean and sea-ice states by ingesting observations into simulated model states through data assimilation methods. Reanalysis provides invaluable information for climate monitoring and is an essential component in long-term prediction such as seasonal to decadal forecasts. The Ocean ReAnalysis System-6 (ORAS6) is the 6th generation of ocean and sea-ice reanalysis system developed at ECMWF. Compared with the current ECMWF operational system-5 (ORAS5), the ocean and sea-ice model has been upgraded and is now driven by hourly atmospheric forcing. A new Ensemble-based variational ocean Data Assimilation (EDA) system has been developed. This new EDA system is constructed with a hybrid covariance model that provides flow-dependent background error variances and correlation scales, both of which are critical for better assimilation of sea surface observations.Direct assimilation of L4 SST observations with ORAS6 EDA system greatly reduces SST biases, especially in critical regions around the Gulf Stream separation. Assimilation of L3 sea-ice concentration data within a multi-category sea ice model has been implemented as well and shows promising results in terms of sea ice spatial distribution and concentration. ORAS6 also includes a new freshwater budget closure scheme which allows to constrain the atmosphere-ocean freshwater fluxes using an external product.This presentation will feature results from a prototype ORAS6 reanalysis with a focus on performance evaluation against its predecessor ORAS5 and potential impacts on coupled ECMWF forecasts.
Assessment of sediment and nutrient sources and their influence on eutrophication: case study from the Czech Republic
Authors: Krasa Josef , Borovec Jakub , Jáchymová Barbora , Bauer Miroslav , Dostál Tomáš
Published: February 2023

The purpose of a three-year project QK22020179 is to build a methodology to assess the importance of the impact of sediments deposited in the tributary parts of reservoirs on water quality. The project should describe the dynamics of phosphorus release or capture in sediments in relation not only to the environment of the reservoir, but also to the source basin, the mineralogical composition of the sediment, its granularity and chemistry, and the method of its supply to the reservoirs.In 2022, the solution was concentrated in the catchment areas of the Bojkovice, Boskovice, Hamry, Seč, Stanovice and Lučina reservoirs. Sediment traps were installed in the inflow reservoirs, continuous models of sediment transport from the catchment were also compiled for the reservoirs, and key parts of the catchment area were defined as potential main sources of sediment. By analyzing the mineralogy and chemistry of the listed source areas, especially on the basis of data from agrochemical analysis of agricultural soils, potential links are now being created between the sediment properties in the inlet parts of the reservoirs and the source areas defined by the model.The paper will present the current results and the overall methodology with the aim of obtaining feedback in the discussion, because the methodology of potential "fingerprinting" of sediment in catchments and defining the importance of its properties for the behavior of reservoirs in terms of eutrophication has not yet been developed in the Czech Republic, let alone successfully solved.Research has been supported by projects QK22020179 and SS03010332.
An 8-year time series of mesozooplankton fluxes in Kongsfjorden, Svalbard
Authors: Giordano Patrizia , D'Angelo Alessandra , Mayers Kyle , Renz Jasmin , Conese Ilaria , Miserocchi Stefano , Giglio Federico , Langone Leonardo
Published: February 2023

In Arctic regions, the food availability for epi-pelagic fauna is strictly influenced by environmental stressors, such as solar radiation, ice cover, glacial and watershed runoffs. This study presents an 8-year time-series (2010-2018) of mesozooplankton collected from an automatic sediment trap in the inner part of Kongsfjorden, Svalbard, at ~87m depth. The aim of this study is to observe the temporal variability in the abundance of epipelagic mesozooplankton species, collected as active flux (swimmers). Reference meteorological and hydrological data are also presented as environmental stressors, to evaluate possible relationships with zooplankton populations. A principal component analysis (PCA) applied to the dataset revealed that the physical and chemical characteristics of seawater affected the mesozooplankton abundance and composition. Collectively, this result highlighted the role of the thermohaline characteristics of the water column on the Copepods behavior, and the correlation between siliceous phytoplankton and Amphipods. Overall, the zooplankton within inner Kongsfjorden did not show a clear seasonal trend, suggesting their high adaptivity to extreme environmental conditions. Although the swimmer fluxes have decreased from 2013 onwards, an increase in community diversity has nevertheless been observed, probably due to copepods decline and subsequent higher food availability. Despite the decreasing magnitude of the zooplanktonic community over time, we recorded the intrusion of subarctic boreal species, such as Limacina retroversa, since 2016. The uniqueness of this dataset is an 8-year uninterrupted time series, which provides correlations between environmental and biological parameters in a poorly studied region. Under a warming Kongsfjorden scenario, with increasing submarine and watershed runoff, and the rapid Atlantification of the fjord, major changes in mesozooplankton communities are expected in the medium to long-term due to their adaptation to environmental changes and the introduction of alien species.
Inferences on the shear wave velocity structure below the Reykjanes peninsula (SW Iceland) from transdimensional ambient-noise surface wave tomography
Authors: Weemstra Cornelis , Rahimi Dalkhani Amin , Ágústsdóttir Þorbjörg , Árni Guðnason Egil , Páll Hersir Gylfi , Zhang Xin
Published: February 2023

We report on a Bayesian (i.e., probabilistic) inversion for the shear-wave velocity structure of the Reykjanes peninsula, SW Iceland. Travel times of Rayleigh waves traversing the peninsula served as input to the probabilistic algorithm. These Rayleigh waves were retrieved through the application of seismic interferometry to yearlong recordings of ambient seismic noise. The Reykjanes peninsula is well placed for this technique because it is surrounded by ocean, which implies a relatively uniform seismic noise illumination; the latter being a condition for accurate interferometric surface wave retrieval. The Bayesian algorithm uses a variable model parametrization by employing Voronoi cells in conjunction with a reversible jump Markov chain Monte Carlo sampler. The algorithm is entirely data-driven, meaning that, contrary to conventional deterministic tomographic inversions, the user does not need to define any regularization or parameterization parameters to solve the inverse problem.
 
The geology in the area of interest is characterized by four NE-SW trending volcanic systems, orientated oblique to the divergent plate boundary cutting across the Reykjanes Peninsula. These are from west to east; Reykjanes, Svartsengi, Fagradalsfjall and Krýsuvík, of which all except Fagradalsfjall host a known high-temperature geothermal field. We observe relatively high shear wave velocity patches close to the Earth’s surface (top two kilometers) at the location of these known high-temperature fields. These high velocity anomalies invert to relatively low shear wave velocities (in comparison to shear wave velocities in the same horizontal plane) at depths greater than 3 km. The latter low-velocity anomalies are relatively small below Reykjanes and Svartsengi. At depths of 5 to 8 km, a low-velocity anomaly extends horizontally below Reykjanes and Svartsengi, correlating relatively well with the inferred brittle-ductile transition below the high-temperature fields at 4-5 km depth. The low-velocity anomaly below Krýsuvík is much larger and coincides with a deep-seated low electrical resistivity anomaly. Horizontally, it coincides with the center of an inflation source at 4–5 km depth. For example, in 2010 this resulted in an uplift exceeding 50 mm/year, but several periods of alternating uplift and subsidence associated with increased seismicity have been observed in Krýsuvík since 2009. Our results both confirm and add details to previous models obtained in the area. Our study demonstrates the potential of Bayesian surface wave inversion as a complementary geophysical tool for geothermal exploration.

 
Accurate information is power
Authors: Jagurinoska Ruzhica
Published: February 2023

 As secondary High school,, Orde Copela ”- Prilep, from Macedonia, we are part of The Global Learning and Observation to Benefit the Environment (GLOBE) program since 2008.  This worldwide science and education program with Pedosphere protocols was the base for my  program that additionally increases my students' knowledge about soil, named Pedosphere.  It was approved by center for secondary vocational education of Macedonia and is applied in my school as an additional subject. For two years I and my students have gain, networked and let data be compared with other countries in GLOBE program all around the world. Responsible research was the goal and that led to the awareness of the harm that climate change develop for the soil.Soil is not an isolated element, it’s a dynamic living system.We walk on the soil, we live on the soil and we feed from the soil, but soil importance  is often taken for granted. For agriculture production in my country, soil is the most important medium.  On the world level, the health of the soil is under great pressure by climate change extremes. Deforestation, erosion, overgrazed grasslands, pollution, population growth, migration and urbanization are additional massive stress factors. Soil as a part of pedosphere forms very slowly, for decades and even centuries, and requires regeneration longer than one human lifetime. It is imperative that our students recognize soil not just as a dirt, but as a resource of global priority for sustainable agriculture and food production. “Be the change that you wish to see in the world,” said Mahatma Gandhi.We started there, by improving our knowledge about soil and it’s properties and increasing awareness about soil importance. Making continuous measurements of soil temperatures , structure, consistency, fertility, pH environment, taking soil samples by ,,Star method’’ by GLOBE protocols for water content in the soil, and entry data into the GLOBE network is wonderful experience for the students that increase their knowledge and awareness.  Presenting protocols for data collecting and comparing them with others schools around the globe encourages students understanding  climate change and it’s effect of soil health. Continuous research and collecting data about soil characteristics and soil degradation on their own, augment students awareness about achieved data results, gain knowledge and eagerness for next research.I am sure that this can be one good way to protect and rebuild our soil systems.
The potential of automotive perception sensors for local snow avalanche monitoring
Authors: Muckenhuber Stefan , Goelles Thomas , Schlager Birgit , Kapper Kathrin Lisa , Prokop Alexander , Schöner Wolfgang
Published: February 2023

Monitoring of local snow avalanche releases are indispensable for many use cases. Existing lidar and radar technologies for monitoring local avalanche activity are costly and require closed source commercial software. These systems are often inflexible for exploring new use cases and too expensive for large scale applications, e.g., 100-1000 slopes. Therefore, developing reliable and inexpensive measurement and monitoring techniques with cutting- edge lidar and radar technology are highly required. Today, the automotive industry is a leading technology driver for lidar and radar sensors, because the largest challenge for achieving the next level of vehicle automation is to improve the reliability of its perception system. Automotive lidar sensors record high-resolution point clouds with very high acquisition frequencies of 10-20Hz and a range of up to 400m. High costs of mechanically spinning lidars (5-20kEUR) are still a limiting factor, but prices have already dropped significantly during the last decade and are expected to drop by another order of magnitude in the upcoming years. Modern automotive radar sensors operate at 24GHz and 77GHz, have a range of up to 300m, and provide raw data formats that allow the development of algorithms for detecting changes in the backscatter caused by avalanches. To exploit the potential of these newly emerging, cost- effective technologies for geoscientific applications, a stand-alone, modular sensor system called MOLISENS (MObile LIdar SENsor System) was developed in a cooperation between Virtual Vehicle Research Center and University of Graz. MOLISENS allows the modular incorporation of cutting-edge radar and lidar sensors. The open-source python package ‘pointcloudset’ was developed for handling, analyzing, and visualizing large datasets that consist of multiple point clouds recorded over time. This python package is designed to enable the development of new point cloud algorithms, and it is planned to extend the functionality to radar cluster data. Based on MOLISENS and pointcloudset, a strategy for their operational use in local avalanche monitoring is being developed.
Comparison of Standardized Precipitation Index (SPI) and Standardized Potential Evapotranspiration Index (SPEI) applicability for drought assessment during the maize growing period between Bărăgan (Romania) and Prekmurje (Slovenia) regions (199
Authors: Kobulniczky Bela , Holobâcă Iulian-Horea , Črepinšek Zalika , Pogačar Tjaša , Jiman Andrei-Marius , Žnidaršič Zala
Published: February 2023

In recent years, drought has become an increasing problem in agricultural production in many places where these problems did not exist in the past. The frequency and intensity of agricultural droughts are increasing, so it is very important to detect temporal and spatial variability of drought. This study analyzed the properties of agricultural drought (duration and intensity) in Bărăgan region (Romania) and Prekmurje region (Slovenia) between 1991-2020 based on the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) at different time scales. The reasons for comparing the two regions are similar climatic conditions, the importance of maize cultivation for food security, and repeated droughts in the recent period in these regions. The meteorological data for Romania were provided from ROCADA database, and for Slovenia from SLOCLIM database. Furthermore, relationships between drought-sensitive phenological stages of maize (germination, formation of the first 2 leaves, and flowering), growing season length, thermal time above threshold 10 °C, standardized yields, and calculated drought indicators were calculated. Based on our analysis, we expect to be able to evaluate whether SPI and SPEI can be used to monitor conditions on a variety of time scales and to provide indicators at regional scales on the likely occurrence of drought during critical phenological phases of maize, as well as the differences and similarities between the two regions will be discussed.