bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of LDAPS Snow information by MERRA-2 and ASOS over the South Korea
Authors: Jeon Hyunho , Jeong Jaehwan , Lee Yangwon , Choi Minha
Published: February 2023

In the past decade, heavy snow has recorded the third-highest disaster damage in Korea after typhoons and heavy rain. In addition, snowfall is one of the important factors in the water cycle, and it directly affects hydrological factors such as evapotranspiration and soil moisture. Due to the topographical features of Korea, snowfall occurs heterogeneously, so it has limitations to use only in-situ data for snow monitoring. Although grid data such as remote sensing and model simulated data has been suggested as an alternative to this, it is also difficult to use only grid data due to the characteristics of snow that influence spectral behavior depending on grain size, age, etc. In this study, snow depth data was evaluated using model simulated data and ground observation data over the South Korea. For data, Local Data Assimilation and Prediction System [LDAPS] (provided with 3 hours of temporal resolution and 1.5 km of spatial resolution), Modern-Era Retrospective analysis for Research and Applications, version 2 [MERRA-2] (provided with 1 hour of temporal resolution and 0.5° × 0.623° of spatial resolution) and Automated Synoptic Observing System [ASOS] (provided with 1 hour of temporal resolution) were used. The applicability of each data was evaluated with topographic data, and long-term trend of snow depth was analyzed. This study can help to predict snow information, with the combination of various reanalysis data and model simulated forecast dataset. Keywords: Snow Depth, LDAPS, MERRA-2, ASOS AcknowledgmentThis research was supported by the BK21 FOUR (Fostering Outstanding Universities for Research) funded by the Ministry of Education (MOE, Korea) and National Research Foundation of Korea (NRF-2021R1A6A3A01087645).
Convolutional Neural Networks for Automated ULF Wave Classification in Swarm Time Series
Authors: Antonopoulou Alexandra , Balasis Georgios , Papadimitriou Constantinos , Boutsi Adamantia Zoe , Daglis Ioannis A. , Giannakis Omiros
Published: February 2023

Ultra-low frequency (ULF) magnetospheric plasma waves play a key role in the dynamics of the Earth’s magnetosphere and, therefore, their importance in Space Weather phenomena is indisputable. Magnetic field measurements from recent multi-satellite missions (e.g., Cluster, THEMIS, Van Allen Probes and Swarm) are currently advancing our knowledge on the physics of ULF waves. In particular, Swarm satellites, one of the most successful missions for the study of the near-Earth electromagnetic environment, have contributed to the expansion of data availability in the topside ionosphere, stimulating much recent progress in this area. Coupled with the new successful developments in artificial intelligence (AI), we are now able to use more robust approaches devoted to automated ULF wave event identification and classification. The goal of this effort is to use a popular machine learning method, widely used in Earth Observation domain for classification of satellite images, to solve a Space Physics classification problem, namely to identify ULF wave events using magnetic field data from Swarm. We construct a Convolutional Neural Network (ConvNet) that takes as input the wavelet spectrum of the Earth’s magnetic field variations per track, as measured by Swarm, and whose building blocks consist of two alternating convolution and pooling layers, and one fully connected layer, aiming to classify ULF wave events within four different possible signal categories: (1) Pc3 wave events (i.e., frequency range 20–100 MHz), (2) background noise, (3) false positives, and (4) plasma instabilities. Our preliminary experiments show promising results, yielding successful identification of more than 97% accuracy. The same methodology can be easily applied to magnetometer data from other satellite missions and ground-based arrays.
Mapping soil organic carbon with hyperspectral spaceborne images
Authors: Ward Kathrin , Foerster Saskia , Chabrillat Sabine
Published: February 2023

Monitoring of soil quality and its degradation is essential to face the big challenges of food security and climate change. One of the main soil parameters to observe is the content of soil organic carbon (SOC) which is linked to soil fertility and other ecosystem services. We investigate the potential of spaceborne hyperspectral images to estimate the content of SOC in the uppermost soil layer. Therefore, we use the spectral information of bare soil pixels in multiple PRISMA images together with chemically analyzed SOC contents of a range of local soil samples and a large-scale soil spectral library. The study site is located in the North-East of Germany within the long-term observatory of TERENO-NE and near the village of Demmin. We compare different machine learning and regression algorithms (Partial Least Squares Regression, Random Forest, Gaussian Process Regression, spectral SOC indices) for each of the images separately and for a synthetic multitemporal image. The best performing models are applied to all bare soil pixels to produce SOC content maps. The preliminary results show medium to high quality models for most cases. With an increasing number of hyperspectral satellites in orbit the outcomes of this case study can provide valuable information for future SOC mapping and monitoring.
Selection of hyetograph shapes for generating synthetic hydrographs in a bivariate analysis for hydrological dam safety assessment.
Authors: Carril-Rojas Daniel , Mediero Luis
Published: February 2023

In flood events, in order to evaluate the hydrological dam safety, it should be assessed the frequency curve of maximum reservoir water levels. For this purpose, a large set of inflow hydrographs are routed through the reservoir. In this approach, the result will depend on several variables, such as flood peak and hydrograph volume frequency curves and the dependence structure between variables. In addition, for this process several hydrometeorological simulations are performed in order to characterise the catchment response in flood events, obtaining hydrograph shapes that can be generated in the catchment. However, first, the hydrological model calibration requires, as input data, given hyetograph shapes.This study presents the application of a bivariate analyses to assess the hydrological safety of dams based on hydrometeorological simulations. The analysis is carried out in the Cuerda del Pozo Dam in central Spain. In this catchment, flood hydrographs associated with annual maximum peak flows are usually generated by storms with a duration of several days. Consequently, hyetographs of several days obtained from intensity-duration-frequency curves are required, in order to obtain the runoff volumes given by the univariate frequency curve of hydrograph volumes. However, hydrological simulations with such long hyetographs present different problems. If a small time step is considered in the design hyetographs of several days, sharp hydrographs will be generated with peak flows greater than required. Unreasonable model parameters would be used to smooth the concentration and diffusion processes, reducing simulated flood peaks. On the other hand, if a large time step is considered, smooth hydrographs could be obtained with flood peaks smaller than quantiles in the flood frequency curve. Therefore, a detailed analysis is carried out to calibrate both flood peaks and hydrograph volumes, obtaining an appropriate hyetograph shape that will lead to acceptable values of the hydrological model parameters.The calibrated rainfall-runoff model is used to generate a set of possible synthetic hydrograph shapes. A bivariate analysis is performed to generate random pairs of peak flow and hydrograph volume that fit the univariate frequency curves and keep the dependence structure between variables. A given synthetic hydrograph shape is assigned to each pair of peak flow and hydrograph volume. A long set of 500 000 inflow hydrographs is used. Hydrological safety of the Cuerda del Pozo Dam is assessed by using the frequency curve of maximum reservoir water levels.
Can radon measurements at tall towers provide information on atmospheric vertical mixing states?
Authors: Saba Mareya , Kikaj Dafina , Chung Edward , Manning Alistair , Karstens Ute , Rennick Chris , Ganesan Anita , Forster Grant , O'Doherty Simon , Wenger Angelina , Arnold Tim
Published: February 2023

The vertical mixing state of the atmosphere, as well as the atmospheric boundary layer (ABL) height, are important atmospheric transport model parameters for the accurate simulation of greenhouse gas concentrations. In order to use tall tower greenhouse gas measurements to quantify regional scale emissions (top-down, inverse estimates) an estimate of the atmospheric transport model uncertainty across the time series of study is needed. Several methods have been used to estimate this, often relying on arbitrary thresholds or a combination of parameters (such as vertical gradients if a gas is measured at multiple points). Here we study if radon has potential as an independent measurement to assess model uncertainty.Radon is a radioactive noble gas present in our atmosphere and is a good tracer of mixing processes in the ABL due to its properties. Hence, measurements of atmospheric radon concentration can provide useful insights into the vertical mixing state of the atmosphere, and in turn may help to calibrate and validate atmospheric dispersion models.In this study, we use high temporal resolution atmospheric measurements of radon and CH4 from four tall tower sites in the UK, which are part of the Deriving Emissions linked to Climate Change (DECC) network: Heathfield (HFD), Ridge Hill (RGH), Tacolneston (TAC) and Weybourne (WAO). At each site, CH4 is measured at two or three different heights, while radon is measured at one height.To determine a metric whereby single-height measurements of radon can provide a proxy for vertical mixing states, we compare the diurnal cycle of the measured radon concentration with the modelled radon (calculated by the Met Office Numerical Atmospheric Modelling Environment (NAME) dispersion model and radon flux maps). The largest uncertainties are shown to be before sunrise and after sunset right before the inversion layer was formed/destroyed. The diurnal CH4 vertical gradient at these times is also compared with the modelled CH4 vertical gradient.
Large-eddy simulation of air quality in Hong Kong
Authors: Wang Yuting , Ma Yong-Feng , Brasseur Guy , Wang Tao
Published: February 2023

To perform realistic high-resolution air quality modeling in a polluted urban area, the WRF (Weather Research and Forecasting) model was used with an embedded large-eddy simulation (LES) module and with online chemistry. As an illustration, the numerical experiment was conducted in the polluted megacity of Hong Kong, which is characterized by multi-type pollution sources as well as complex topography. The multi-resolution simulations from mesoscale to LES scales were evaluated by comparing the calculated fields with ozone sounding profiles and with the observations at surface monitoring stations. The comparison shows that both mesoscale and LES simulations reproduced well the mean concentrations of the chemical species and their diurnal variations at the background sites; however, the mesoscale simulations largely underestimated the NOXconcentrations and overestimated O3 near roadside stations due to the coarse representation of the traffic emissions. The LES simulations improved the agreements with the measurements near the road traffic, and the LES with highest spatial resolution (33 m) provided the best results. The LES simulations showed more detailed structures of the spatial distributions of chemical species than the mesoscale simulations, indicating the capability of LES of resolving high-resolution photochemical transformations in urban areas like Hong Kong. The LES simulations showed similar trends with the mesoscale model in the evolution of the profiles of the chemical species with the development of the boundary layer over a diurnal cycle. The vertical fluxes of the chemical species are stronger in the 33 m LES than the 100 m LES, because the high-resolution LES can better resolve the turbulent eddies.
Impact of incorporating SPIRE CubeSat GPS observations in a global GPS network solution
Authors: Kobel Cyril , Arnold Daniel , Jäggi Adrian
Published: February 2023

Precise orbit determination (POD) of low earth orbiters (LEO) using data of the Global Positioning System (GPS) and the computation of GPS network solutions are usually performed in separate processes. Typically, orbits and clock corrections of GPS satellites, which have been previously determined as part of a network solution, are introduced as fixed in a LEO POD. However, various studies have shown that the inclusion of GPS observations of LEOs in a global network solution can be advantageous, particularly in terms of the quality of resulting GPS products and certain geodetic parameters, such as the Earth’s center of mass coordinates. Since a few years more and more GPS data from LEO CubeSats are available, such as from the SPIRE satellites which are equipped with dual-frequency GPS receivers and may be used as part of specific scientific investigations. The SPIRE satellite constellation is a group of remote sensing satellites that are used to measure and map the earth's surface and atmosphere.In the present study, we aim to determine the impact of GPS observation data from specific SPIRE satellites when they are included in the computation of a global network solution. Code and phase observations received by GPS receivers on board of selected SPIRE satellites, along with those from ground stations of the International GNSS Service (IGS), are processed together in a joint least-squares adjustment process to obtain a combined GPS-LEO solution. This determines orbit parameters of the SPIRE satellites together with GPS orbit parameters and geodetic parameters, such as station coordinates, Earth rotation parameters, and the Earth's center of mass coordinates. To assess the influence of the SPIRE LEOs more closely, various solutions are analyzed in which GPS observations from different SPIRE satellites and from scientific LEO missions are included. Given the different orbit characteristics of the selected SPIRE satellites, specifically the orbital inclinations, it is also possible to examine the impact of this on the resulting solution. The global solutions are compared to each other and to a solution using only data from terrestrial GPS stations. Quality characteristics are analyzed to assess the quality of the combined GPS-LEO solution, which are the resulting GPS orbit solutions in terms of orbit overlaps at arc boundaries, the quality of geodetic parameters, and the determined formal errors of the estimated parameters. The resulting SPIRE orbits of the combined solutions are also compared to those of a separate POD.
Deformation in carbonates and its contribution to fold & thrust belt architecture
Authors: Boianju Inga , Faber Carly , Rowe Christie
Published: February 2023

Fold and thrust belts are frequent structures that form under a compressive regime. They record a variety of deformation that guides earthquake ruptures and controls seismic hazard. The Naukluft mountains of Namibia with their extraordinary exposure, present a unique opportunity to study carbonate fault rocks. Through linked field investigations and microstructural analysis, we aim to map how changes in fault strength contributed to larger scale architectural evolution of a fold and thrust belt. Mineralogical assemblage of the stacked nappes show units of carbonate and shale in the lower to upper greenschist facies, correlating to the seismological depth for carbonate rocks. Cross cutting relations prove that the Naukluft Nappe Complex (NNC), previously thought to form through gravity sliding, is a foreword-propagating fold and thrust belt, stacking Neo Proterozoic sedimentary nappes on top of each other, and on top of the cambrian Nama fore-rift group. Most thrusts separating the stacked nappes are made of 20-150 meters of calc mylonites, except for the youngest two brittle thrust faults, including the basal thrust. Brittle deformation is recorded by localized brecciation and the development of discrete faults. The brittle faults follow the same orientation as the overall transport direction of the nappe complex. Ductile shearing is facilitated by crystal plastic deformation, leading to grain size reduction, and grain boundary sliding. Both ductile mylonite units and the younger brittle faults are also overprinted by later brittle faults, and between the ductile and brittle behavior, we map a unit of a block-in-matrix. We found no clear correlation between the temporal evolution of the nappe complex and the thickness of ductile shear zones. We show evidence for embrittlement through exhumation of a carbonate terrane, and suggest that it may be important to consider the effects of deeper ductile behavior in “Coulomb wedge” descriptions of thin-skinned thrust belts.
Build and evaluate climate change adaptation with a parsimonious integrated agro-hydrological model over a catchment in northeastern France
Authors: Soutif-Bellenger Myriam , Thirel Guillaume , Fernandez Sara , Dorchies David
Published: February 2023

Considering the emergency to adapt agriculture to climate change, it seems essential to develop generic tools to build and evaluate potential solutions. We combine here a prospective based on stakeholders’ interviews and an integrated agro-hydrological model to evaluate the impacts of scenarios on the Seille catchment in 2050. The prospective and stakeholders’ interviews aim at understanding agriculture and water management drivers on the modelled catchment and designing appropriate inputs for future scenarios modelling. The model simulates flows at a daily time step with GR rainfall-runoff models, and simulates daily irrigation demand thanks the to single Kc method of FAO, allowing estimating hydrological and agronomic impacts of climate change and scenarios. The integration of the two models is made thanks to the airGRiwrm package. Depending of the research advancement, results of simulations in a climate change context and conclusions about climate change impacts for designed scenarios will be presented.
Modeling extreme meteorological droughts from paleo-climatic reconstructions using a metastatistical framework
Authors: Caruso Maria Francesca , Peres David Johnny , Cancelliere Antonino , Marani Marco
Published: February 2023

The vulnerability of large areas to drought events emphasizes the importance of a reliable probability analysis of drought events. A drought is notoriously considered as one of the most complex natural phenomenon, which, more than other natural hazards, remains difficult to quantitatively model due to the difficulty of sampling a sufficient number of events in the historical record. In fact, due to the persistence and often long interarrival times between droughts, occurring on time scales of years to decades or more, very long observational time series are necessary to study their statistical properties. It is indeed rare that such a large amount of observational information, at appropriate space-time resolutions and consistency, are available in practical applications.One possible approach to overcome this problem relies on the use of proxy climatic data to extend the instrumental record. Additionally, since relatively few drought events occur even within records of several hundred years, techniques which optimally use available information, such as the metastatistical framework, may be highly beneficial in these analyses.Motivated by the above considerations, this work exploits a publicly available tree-ring based Old World Drought Atlas (OWDA; Cook et., 2015), a reconstruction of the June–August self-calibrating Palmer Drought Severity Index (sc-PDSI), to model the stochastic nature of the drought characteristics. To gain a quantitative understanding of how well tree ring-based data capture drought occurrences, we compare the sc-PDSI computed with direct observations of precipitation and temperature, with those obtained from tree-ring proxies. Furthermore, we characterize drought events and their properties using the statistical “theory of runs”. We then explore the potential of the Metastatistical Extreme Value Distribution (MEVD) to estimate the probability of occurrence of drought events and compare its performance with that obtained by the use of traditional approaches. A cross-validation scheme, dividing the available data into independent calibration and test sub-sample, is used to quantify the estimation uncertainty associated with different sample sizes and estimation methods.The analysis of extreme droughts in two case studies in Italy suggests that the MEVD-based formulations are more robust and flexible approaches with respect to traditional ones. The comparative analysis of the predictive estimation uncertainty is site-specific, but MEVD estimates outperform, in terms of bias and uncertainty, traditional GEV estimates.The analyses also (1) confirm the usefulness of the paleoclimate reconstructions for improving the robustness of the statistical study of extreme droughts, and (2) highlight that the metastatistical formulations allow estimations of probability of intense droughts even when observational length is too short to apply traditional methods.
Detection and characterization of seismic sequences in the normal fault system of the Irpinia region, Southern Italy
Authors: Scotto di Uccio Francesco , Festa Gaetano , Michele Maddalena , Beroza Gregory C. , Chiaraluce Lauro , Picozzi Matteo , Scala Antonio , Supino Mariano
Published: February 2023

Understanding mechanical processes occurring on faults and catching the preparation phase of large magnitude events require a detailed characterization of the microseismicity, which can be enhanced today using advanced techniques for earthquake detection. These techniques decrease the detection threshold of seismic networks and provide augmented catalogs, which enable improved statistical analysis associated with event occurrence and size. However, seismic events recorded at the level of the noise typically emerge only at a few stations, making earthquake characterization challenging. This issue is further complicated in areas where seismicity occurs deep in the crust, as happens in the normal fault system of the Irpinia region, Southern Italy, where earthquakes occur at depths between 8 and 15 km.In this work we focus on the detection and characterization of seismic sequences occurring in the Irpinia region featuring low magnitude mainshocks (Ml∼3), using data from the Irpinia Near Fault Observatory.Event detection for the sequences is performed through the integration of a machine learning based detector (EQTransformer, Mousavi et al., 2020) and a template matching technique (Chamberlain et al., 2018), with the former providing a wider set of templates for the similarity search. This strategy outperforms auto-similarity techniques based on fingerprints (FAST, Yoon et al., 2015) and template matching grounded in manual catalogs. On average, the final catalog of the analyzed sequences increases the manually revised network bulletin by a factor 7. We compared P- and S- arrival time estimates, grounded in the machine learning phase picking and cross-correlation for template matching, using manual identifications to assess the reliability of automatic picks; the mean residual between manual and automatic values is ~0 for both P- and S-waves, with a larger residuals standard deviation for the latter.We apply a double-difference location technique using both catalog and cross-correlation differential travel times for locating the events, with the goal of resolving and highlighting fault structures where seismicity takes place. We finally track the spatio-temporal evolution of the seismicity, and apply a mechanical model based on static stress, to discriminate whether sequences in the area are mainly triggered by static stress change, dynamic stressing, or aseismic mechanisms such as fluid diffusion.
When four or more (tracers) are better than one and why you should ski (to sample)
Authors: Ceperley Natalie , Michelon Anthony , Beria Harsh , Larsen Joshua , Vennemann Torsten , Schaefli Bettina
Published: February 2023

We measured a combination of natural tracers of water at a high frequency, including stable isotope compositions (δ2H, δ17O, δ18O), electrical conductivity, and water and soil temperature to characterize hydrological processes in a snow-dominated Alpine catchment and to understand the diversity of streamflow sources and flow paths. Previous work metabarcoding eDNA from stream samples led us to suppose that subsurface connectivity was a primary driver of genetic richness in the water of an alpine catchment, however our process understanding was limited.   By diving into temperature measurements in soil and water, electrical conductivity, and stable isotopes, we start to weave together the complexity of this subsurface connectivity.  Of particular interest in this alpine catchment is the seasonality of connectivity, which is mainly, in different forms, in melt periods occurring in spring and during rain-fed runoff events in summer and rain-on-snow events in winter.   This is dramatically different than in non-mountain, low-elevation environments where connectivity is observed in the cold or winter season.  In this presentation, we will compare and contrast what we learn from each tracer and highlight findings that could only be learned by bringing them all together.  We will reveal how these tracers inform our understanding of the timing of snow presence and melt, the existence of sub-snowpack local flow, the magnitude of subsurface exchange, and the mixing of snowmelt with groundwater. These insights into the details of streamflow generation in such a dynamic environment were only possible due to the intense, year-round field work.
Observations of radiatively active halogenated species at MonteCImone WMO-GAW station and their use in inverse modelling techniques to derive emission estimates at the regional scale.
Authors: Arduini Jgor , Annadate Saurabh , Cesari Rita , Cristofanelli Paolo , Falasca Serena , Giostra Umberto , Maione Michela
Published: February 2023

Long term measurement activities carried out at the WMO GAW global station of Monte Cimone (CMN) provide a useful insight into the characterization of the composition of the Southern European atmosphere. Since 2003, ozone depleting substances (ODSs) and halogenated Greenhouse Gases (GHGs) have been measured at CMN in the frame of the AGAGE (Advanced Global Atmospheric Gases Experiment) programme, with the aim of tracking progress towards the implementation of the international treaties on stratospheric ozone depletion and climate, and getting a better understanding of emissions both in terms of magnitude and localisation at the regional (EU) scale. CMN is often influenced by the advection of polluted air masses from the Po basin, one of the most polluted areas in Europe, as well as by the transport from other highly anthropised regions in Central EU. However, during the cold months and at night-time in the warm season, the site is representative of the free troposphere.By providing high quality, high frequency, continuous -almost uninterrupted- observations of ODSs (chlorofluorocarbons and hydrochlorofluorocarbons) and their radiatively active substitutes (hydrofluorocarbons) to modellers, the monitoring activities at CMN  are crucial for improving the overall sensitivity of the inverse modelling techniques used to derive emissions through the so called “top-down” approach. Such approach represents an important quasi-independent cross-check of national GHG emission inventories submitted annually by the parties to the United Nations Framework Convention on Climate Change (UNFCCC). Here we will present results of the Bayesian inverse modelling technique used to derive emissions at the EU national scale based on the observations described above.
ESPRESSO: Earth Science Problems for the Evaluation of Strategies, Solvers and Optimizers
Authors: Valentine Andrew , He Jiawen , Hauser Juerg , Sambridge Malcolm
Published: February 2023

Many Earth systems cannot be observed directly, or in isolation. Instead, we must infer their properties and characteristics from their signature in one or more datasets, using a variety of techniques (including those based on optimization, statistical methods, or machine learning). Development of these techniques is an area of focus for many geoscience researchers, and methodological advances can be instrumental in enhancing our understanding of the Earth.         In our experience, progress is substantially hindered by the absence of infrastructure facilitating communication between sub-disciplines. Researchers tend to focus on one area of the earth sciences — such as seismology, hydrology or oceanography — with only slow percolation of ideas and innovations from one area to another. Indeed, silos often exist even within these subfields. Testing new ideas on new problems is challenging as it requires the acquisition of domain knowledge, an often difficult and time-consuming endeavour with uncertain returns. Key questions that arise include: What is a relevant field data set, and how has it been processed? Which simulation package is most appropriate to predict the data? What would a 'good' model look like and what should it be able to resolve? What is the current best practice?To address this, we introduce the ESPRESSO project — a collection of Earth Science Problems for the Evaluation of Strategies, Solvers and Optimisers. It aims to provide  access to a suite of ‘test problems’, spanning a wide range of inference and inversion scenarios. Each test problem defines appropriate dataset(s) and simulation routines, accessible within a standardised Python interface. This will allow researchers to rapidly test new techniques across a spectrum of problems, share domain-specific inference problems and ultimately identify areas where there may be potential for fruitful collaboration and development. ESPRESSO is envisaged as an open, community-sourced project, and we invite contributions from across the geosciences.
A multi-center exercise on the sensitivity of PAZ GNSS Polarimetric RO for NWP modeling
Authors: Padullés Ramon , Cardellach Estel , Paz Antía , Turk F. Joe , Ao Chi O. , Wang Kuo Nung , de la Torre Juárez Manuel , Murphy Michael J. , Haase Jennifer S. , Lonitz Katrin , Hotta Daisuke
Published: February 2023

A better understanding of the thermodynamics of heavy precipitation events is necessary towards improving weather and climate models and quantifying the impact of climate variability on precipitation. However, there are limited observations available to assess the thermodynamics model structure within heavy precipitation conditions.In 2009, the Earth Observation Group at ICE-CSIC/IEEC conceived the polarimetric radio occultations (GNSS-PRO) technique with the aim to obtain simultaneous measurements of the vertical structure of precipitation and its associated thermodynamic state. Based on the standard GNSS radio occultation technique (GNSS-RO), polarimetric RO consists of an identical instrument working at two orthogonal linear polarizations (H,V) instead of the conventional circularly polarized antenna. This allows us to measure the differential phase delay at both ports, hypothesized to be positive in the presence of asymmetric hydrometeors (large raindrops, snowflakes, ice aggregates). This technique is being tested for the first time on the proof-of-concept mission Radio Occultations and Heavy Precipitation (ROHP) aboard PAZ satellite, operating since 2018. The results of the first 4 years of PRO observations already showed sensitivity to heavy precipitation and its associated cloud structures.Such technique provides high quality thermodynamic observations of water vapor, temperature and pressure with high vertical resolution, along with the vertical measurements of the phase delay linked to the precipitation structure. This study focuses on comparing these observations with the simulations based on the outputs of several operational models and reanalysis for a set of selected cases. The main objectives of the study are: (1) To check if the models reproduce the main features of the actual data; (2) to assess whether different models/schemes result in different GNSS PRO observables, and whether these differences are larger than the measurement uncertainty; and (3) to examine the utility of PAZ GNSS PRO observations for model validation and diagnosis.This effort provides insight on future methods to assimilate the PRO profile alongside other conventional (non-polarimetric) RO data, including work towards building a forward operator. The exercise includes comparisons with ECWMF operational model, ERA-5 reanalysis, the operational NWP at the Japan Meteorological Agency, and a near-real-time implementation of the WRF regional model over the northeastern Pacific produced at the Center for Western Weather and Water Extremes (CW3E) called West WRF, forced with ECMWF and GFS.
Flooded area monitoring using SAR image-based water body detection technique
Authors: Kim Wanyub , Lee Seulchan , Choi Minha
Published: February 2023

Flood is one of main water disasters and causes damage to human life and property. The spatial and temporal disproportion of precipitation due to recent climate change causes flood worldwide every year. As the severity of flood rises, accurate monitoring of flooded areas is being essential for preparation and adaptation. Due to the wide area-occurring characteristics of flood, the use of remote sensing is effective for detecting of flooded areas. In a SAR image, surface of water body appears smooth, so the backscattering coefficient value is generally low. Conversely, surface of non-water body is rough, so the backscattering coefficient value is high. It is possible to divide water body and non-water body by using the characteristics of the backscattering coefficient and specific threshold value. However, the histogram of the backscattering coefficients around rivers where flood occurs most often has a multi-modal distribution, so there is a limit in detecting water bodies using a threshold value only. In this study, a histogram-based multi-threshold method, an AI-based K-means clustering method, and an object segmentation-based Chan-Vese method were used to detect water bodies before and after floods in Sentinel-1 SAR images. The water/non-water body classification image from the Sentinel-2 optical image was used for validation. If SAR images with high spatial and temporal resolution will be available, it is expected that efficient water disaster management will be possible through near real-time detection of flooded areas. 
Significant changes in pH and saturation state of calcium carbonate in coastal ocean waters in Korea
Authors: Park Geun-Ha , Lee Seon-Eun
Published: February 2023

Coastal ocean is more vulnerable to ocean acidification (OA) than open ocean due to high inputs of nutrients from land, large biological production, and various human activities. We started coastal acidification monitoring at three coastal (Busan, Jeju, and Ulleung) and one offshore (3km away from the Busan site) sites in Korea to examine long-term trends of the OA and their effects on coastal ocean environment. Discrete surface seawater samples for measurement of total dissolved inorganic carbon and total alkalinity were collected at the Busan, the Jeju and the Ulleung, and the offshore sites on a weekly, biweekly, and monthly basis, respectively. Here, we report changes in pH and saturation state of seawater with respect to aragonite (Ω) at the four sites for the period of 2019–2022. At the Busan and the Ulleung sites, both pH and Ω showed significant decreases, but there were no trends at the other two sites. The change rates of deseasonalized pH and Ω (-0.011 ± 0.005 yr-1 for pH and -0.049 ± 0.024 yr-1 for Ω) found at the Busan site were similar to those (-0.010 ± 0.005 yr-1 for pH and -0.058 ± 0.025 yr-1 for Ω) of the Ulleung site. These rates are about six times greater than the global long-term mean rates (-0.016 per decade for pH and -0.07 per decade for Ω). Sea surface temperature and salinity did not show any significant trends for the same period. Continuous monitoring of carbonate parameters at these sites is necessary to get robust long-term OA trends and understand coastal OA processes by finding their drivers.
Jovian synchrotron radiation multi-zonal parametric model: an update from Juno MWR observations
Authors: Adumitroaie Virgil , Levin Steven , Oyafuso Fabiano , MWR Team the Juno
Published: February 2023

The Microwave Radiometer (MWR), Juno’s remote-sensing experiment, captures the thermal and non-thermal radiation emitted by the atmosphere and the magnetosphere, which is present in the Jovian orbital environment. Other scientific instruments on the spacecraft record the signatures of space-charged particles and the planet’s magnetic field. To retrieve the atmospheric composition values from MWR’s low-frequency radiative observation, the contributions from three existing emission sources (the cosmic microwave background (CMB), the planet, and synchrotron radiation belts) must be untangled numerically. The multi-parameter, multi-zonal model of Levin et al. (2001) for synchrotron emission employs an empirical electron-energy distribution. Initially, this distribution has been adjusted exclusively from Very Large Array (VLA) observations made from Earth before the Juno mission.  This is a report on the recent model update based on a subset of MWR in-situ data. The approaches considered, challenges confronted, and the latest results are discussed here.
Influence of cap-rock on deformation during extrusion of salt diapir – a numerical study
Authors: Słotwiński Michał , Krýza Ondřej , Závada Prokop , Warsitzka Michael , Adineh Sadegh
Published: February 2023

Growth rate of salt diapirs usually oscillates depending on several factors. The growth can be arrested by depletion of the source layer or diapir burial, conversely, diapir reactivation occurs through erosion of the overburden and/or introduction of tectonic forces. Examples of reactivated diapirs can be observed in the Zagros Mountains in Iran. There, tectonic shortening responsible for development of the Zagros Fold and Thrust Belt simultaneously squeezes the diapirs, which extrude salt onto the surface. The top section of the diapir is usually affected by meteoric water, which dissolves the salt and leaves behind insoluble material embedded within the source layer, forming the so called caprock. This caprock can be assumed to be already present before the reactivation of the diapirs during shortening, hence it may play a role in the development of the salt extrusions. Geometry, composition and mechanical properties of the caprock can vary widely depending on factors such as original composition of diapiric material, dissolution and growth rates, etc. Additionally, exact mechanical properties of any caprock are difficult to determine and are currently largely unknown. Hence, we present a series of 2D numerical simulations utilising finite element method to investigate how different geometries and rheologies of the caprock affect the shape of the subaerial extrusions. The analysis was performed with three variable parameters (caprock viscosity, cohesion, and thickness) for three scenarios of diapirism (1 - purely shortening-based, with depleted source layer; 2 - purely buoyancy-based, with preserved source layer and no tectonic forces, and; 3) a combined scenario). We analysed the general deformation patterns as well as quantifiers such as velocities, displacements, strains, strain rates and ratios between vertical and horizontal components of the quantifiers. We investigated variability of averaged values of the quantifiers in time as well as detailed spatial distribution for the finite state of simulation. The simulations revealed the strong contrast between less (low cohesion and viscosity) and more competent rheologies in term of deformation patterns. The former tends to result in caprock material being thinly spread over the surface of the salt extrusion, whereas in the latter case the caprock fractures into “rafts” floating on top of the extrusion. The exact geometry of the rafts (size, spacing, distribution) is highly dependent on the geometry and type of diapirism. We also compare the resultant patterns to the quantifiers, especially velocities and their ratios, establishing clear ties between the patterns and deformation dynamics. 
Consistent atmospheric circulation responses due to Arctic sea ice loss between prescribed sea ice simulations and single long control simulations
Authors: Delhaye Steve , Massonnet François , Fichefet Thierry , Msadek Rym , Terray Laurent , Screen James
Published: February 2023

This study investigates the differences in atmospheric responses to Arctic sea ice anomalies between simulations from six (atmospheric-only) models contributing to the Polar Amplification Model Intercomparison Project and one long control simulation (piControl from CMIP6) from the same six (coupled) models. We perform a composite analysis between years of low and high Arctic sea ice extent in the piControl and consider four different types of experiment in the PAMIP where only the sea ice concentration is changed (pdSST-futArcSIC, pdSST-futBKSeasSIC, pdSST-futOkhotskSIC and pdSST-pdArcSIC) to examine the associated atmospheric circulation changes owing to an Arctic sea ice loss. A negative change in the North Atlantic Oscillation (NAO) pattern emerges in winter, linked to the so-called stratospheric pathway, and is mainly due to the sea ice anomaly in the Barents-Kara Seas. The results in the PAMIP experiments support these findings, except that the intensity is lower than in the piControl composite analysis. This work highlights that the atmospheric circulation responses to Arctic sea ice loss in a long control simulation (CMIP6) show similarities with the responses of a coordinated set of numerical model experiments with prescribed sea ice (PAMIP). However, the atmospheric responses in the numerical models with prescribed sea ice display weaker changes than in CMIP6. The role of the atmosphere-ocean coupling and of the initial sea ice condition could be the main reasons for this difference in intensity.
Greenland’s lithospheric structure from integrated modelling of potential field data
Authors: Wansing Agnes , Ebbing Jörg , Moorkamp Max , Heincke Björn
Published: February 2023

Greenland’s tectonic history is complex, and the resulting lithospheric structure is, although extensively studied, not well constrained. Most models agree regarding the location of the North Atlantic Craton in South Greenland, and the most recent surface heat flow model also predicts a cold lithosphere for that area. However, the velocity anomaly from the regional tomography NAT2021 shows two additional cratonic blocks in North Greenland that are not included in geological maps and previous lithospheric models.  To resolve these differences, we built a lithospheric model for Greenland that is compatible with multiple observables and focuses on data integration. In the first step, a background model is set up that uses petrological information of the mantle to model coherent seismic velocities, densities, and temperatures down to a depth of 400 km. The lithospheric model is then adjusted to reproduce the seismic velocities from NAT2021, the gravity field from satellite data and the isostatic elevation. In a second step, we jointly inverted the residual gravity field data from the lithospheric background model together with airborne magnetic data to estimate the crustal density and susceptibility structure. Both rock properties are coupled with a variation of information coupling constraint that establishes a distinct parameter relationship. To assess the compatibility of the thermal structure of our model with the most recent geothermal heat flow model for Greenland, we perform a grid search for the crustal radiogenic heat production, which would be necessary to reproduce this recent geothermal heat flow map. Finally, the results from the different steps are combined by cluster analysis and compared with petrophysical data from a newly established database of Greenland.The iterative workflow provides novel insights into the sub-ice geology of Greenland. We can model three cratonic blocks with LAB depths greater than 200 km and simultaneously fit the gravity, magnetic and elevation data in Greenland and the most recent geothermal heat flow model. 
Seismic constraints on sediment budget for a mountainous catchment
Authors: Wu Zhen-Yu , Chao Wei-An , Hung Chi-Yao
Published: February 2023

In the steep mountain catchment, measuring the budget change of soil and sediment has always been a great challenge. Results of recent research have shown that the seismic station nearby river channels can capture seismic signals cause by different mechanisms such as water flow, sediment transport, and debris flow. Among them, river sediment transport and the debris flow have a more serious impact on the sediment mass distribution of river bed. This study site selected the Putanpunuas River in southern Taiwan where landslide occurred frequently, which could provide a stable source of sediment materials for this river. The temporals changes of erosion and deposition in the downstream alluvial fan can represent the income and expenditure of soil and sediment in the catchment area. Therefore, two broadband stations and one Geophone station were installed at downstream of the Putanpunuas River, and a broadband station was installed at the confluence of the Putanpunuas River and the Laonong River, which was named the Putanpunuas seismic array (PSA). By using a multi-temporal digital elevation model (DEM) of downstream alluvial fan, water level information captured by time-lapse images, time-frequency analysis of seismic signals, and the seismic physical models for different mechanisms (turbulent flow, bed saltation, debris flow), out study not only effectively monitor sediment transport but also provide better understanding on sediment budget in the catchment area. Temporal changes in erosion and deposition volume of the downstream alluvial fan was used to validate above seismology-based results.