bluuebunny/crossref_metadata_2025 huggingface dataset:
Using line transect sampling to detect cetaceans and floating litter during vessel survey in western Black Sea
Authors: Paiu Romulus-Marian , Tonay Arda M. , Timofte Costin , Paiu Angelica , Mirea Candea Mihaela , Gheorghe Anca-Maria , Slabakova Violeta , Amaha Ozturk Ayaka , Murariu Dumitru
Published: March 2021

                The quality of the Black Sea ecosystem is partly but importantly dependent on the survival and sustainability of the top predator populations. It is difficult to foresee all consequences for the regional biodiversity if cetaceans disappear as it had happened with the Mediterranean monk seals in the past. During 7 days, between 30 September and 7 October, 2019, a joint oceanographical survey was made with a multipurpose R/V Mare Nigrum in offshore as well as deep sea locations, within the Romanian (RO), Bulgarian (BG) and western Turkish (TK) national waters of the Black Sea in the frame of ANEMONE project. The total track line was around 700 nautical miles and the sampled area covered 9754,58 km2. Observations were made of cetaceans and floating litter, following line transect sampling method, with a single platform (2 observers, on the left and right of the vessel bridge) over 380.44 km of transects. A total of 54 cetacean sightings and 81 floating litter items were recorded. All the three species, short-beaked common dolphin (Delphinus delphis ssp. ponticus), Black Sea bottlenose dolphin (Tursiops truncatus ssp. ponticus), and Black Sea harbour porpoise (Phocoena phocoena ssp. relicta), were registered with a similar density (individuals/km2), 0.012 for RO sector and 0.013 for BG-TK sector. The number of debris varied between 1 and 24 items, reaching 5.26± 5.93 items on average. Among the transects, 53% contained less than 5 items and only 13% were with more than 10 items. Based on these results, the average density of floating macro-litter in BG waters was found 2.43 ± 2.4 items/km2, 1.73 ± 1.24 items/km2 in the RO waters and 2.43±2.17 items/km2 in TR waters. This study was the first to make a joint and continuous survey effort for both cetaceans and litter simultaneously in the Black Sea.

Key words:  Black Sea, cetaceans, marine litter, joint cruise, ANEMONE project.
Representation of crop phenology and associated management practices in the SWAT+ model using global datasets for large scale hydrological applications
Authors: Nkwasa Albert , James Chawanda Celray , van Griensven Ann , Jägermeyr Jonas
Published: March 2021

Even though cropland cultivation covers over 40% of the planet’s ice free land surface, most regional and global hydrological models either ignore the representation of cropland or consider crop cultivation in a simplistic way or in abstract terms without any management practices. Yet, the water balance of cultivated areas is strongly influenced by applied management practices (e.g. planting, irrigation, fertilization, harvesting). For instance, the SWAT+ model represents agricultural land by default in a generic way where the timing of the cropping season is driven by accumulated heat units. However, this approach does not work for tropical and sub-tropical regions such as the sub-Saharan Africa where crop growth dynamics are mainly controlled by rainfall rather than temperature.

In this study, we present an approach on how to reasonably incorporate crop phenology using decision tables and global datasets of rainfed and irrigated croplands with the associated cropping calendar and fertilizer applications in a SWAT+ model for North Eastern Africa. We evaluate the influence of the crop phenology representation on simulations of Leaf Area Index (LAI) and Evapotranspiration (ET) using LAI remote sensing data derived from Proba-V satellite and WaPOR ET data respectively. Results show that a representation of crop phenology using global datasets leads to improved temporal patterns of LAI and ET simulations especially for regions with a single cropping cycle.  However, for regions with multiple cropping seasons, global phenology datasets need to be complemented with local data or remote sensing data to capture additional cropping seasons. We conclude that regional and global hydrological models can benefit from improved representations of crop phenology and the associated management practices. Future work regarding the incorporation of multiple cropping seasons in global phenology data is needed to better represent cropping cycles in global hydrological models.
Accretional soil formation in northern hemisphere loess regions - evidence from OSL-dating of the P/H climatic transition from China, Europe and North America
Authors: Constantin Daniela , Mason Joseph , Hambach Ulrich , Veres Daniel , Panaiotu Cristian , Zeeden Christian , Zhou Liping , Marković Slobodan , Gerasimenko Natalia , Avram Anca , Tecsa Viorica , Sacaciu-Groza Stefana Madalina , del Valle Villalonga Laura , Begy Robert , Timar-Gabor Alida
Published: March 2021

Here we investigate the timing of Pleistocene-Holocene climatic transition as reflected in nine luminescence dated loess-palaeosol sequences across the northern hemisphere, from the Chinese Loess Plateau, the southeastern European loess belt and the central Great Plains, Nebraska, USA.
First, logs of high-resolution magnetic susceptibility and its frequency dependence were used as palaeoclimatic proxies to define the environmental transition from the last glacial loess to the current interglacial soil. Second, the onset of increase in their values above typical loess values was used to assess the onset of, and developments during, the Pleistocene-Holocene climatic transition. The variability seen in the magnetic susceptibility records are interpreted based on high-resolution luminescence dating applied on multiple grain-sizes (4-11 µm, 63-90 µm, 90-125 µm) of quartz extracts from the same sample. In order to increase the overall precision of the luminescence based chronology we rely on weighted average ages. Based on these, Bayesian modeling allowed the determination of age-depth models and mean sedimentation rates for each investigated site.
The magnetic susceptibility signal shows a smooth and gradual increase for the majority of the sites from the typical low loess values to the interglacial ones. At all but one site, this increase, associated to the onset of the Pleistocene-Holocene boundary (ie., 11.7 ka) was dated to 14 ka or even earlier. Our results highlight the need of combining palaeoclimatic proxies (magnetic susceptibility) with absolute dating when placing the Pleistocene-Holocene climatic transition as reflected by the evolution of this proxy in order to avoid misinterpretations in loess-paleosol records caused by simple pattern correlation. These results indicate diverse environmental dynamics recorded in the different North Hemisphere loess regions during the major global climatic shift from the last glacial to the Holocene.
The detailed luminescence chronology coupled with magnetic susceptibility records indicate the formation of accretional Holocene soils in the sites investigated. Modeled accumulation rates for the Holocene soil are similar for European, Chinese and American loess sites investigated and vary from 0.02 m/ka to 0.09 m/ka.
Global mapping of the nonstationary M2 internal tide using Argo data
Authors: Geoffroy Gaspard , Nycander Jonas
Published: March 2021

Data from Argo floats equipped with Iridium communications are used to obtain a global map of the total amplitude (or variance) of the M2 internal tide. The results are confirmed by a comparison with the High Resolution Empirical Tide (HRET) model, based on satellite altimetry. While HRET only contains the stationary component, with a fixed phase difference to the astronomical tide, the present results capture the total amplitude, including the nonstationary component. The time scale over which the nonstationary component is decorrelated is also obtained. We estimate the global average ratio of total to stationary semidiurnal internal tide variance to be more than 10. In terms of the ratio of nonstationary to total semidiurnal internal tide variance, the semidiurnal nonstationary variance fraction (SNVF), this translates into a global average ratio of about 90%. The Argo in situ observations provide a valuable ground-truth for the geographical variability of the internal tides. The latter is key to predicting the magnitude and distribution of the mixing that ultimately results from the tides.
Modelling population displacement: both climate change and population growth heighten displacement risk due to river floods. 
Authors: Kam Pui Man
Published: March 2021

Disaster displacements create hardships, particularly for socio-economically vulnerable groups. Displaced people face heightened risks to their well-being, including their physical and mental health and personal security. Assisting displaced people is an important part of any humanitarian response to disasters.

Among weather-related disasters, river flooding is responsible for a large part of population displacement. River flood risk is expected to increase due to climate change and its effects on the hydrological cycle. At the same time, socioeconomic development scenarios indicate substantial increases of population in many regions that experience flood-induced displacement.

We have modelled projected changes to flood-driven population displacement in the 21st Century with the CLIMADA (CLIMate ADAptation) platform, in collaboration with the Internal Displacement Monitoring Centre.

We show that both climate and population change are projected to lead to an increase of relative global flood displacement risk by roughly 350% by the end of the century. If we keep the population fixed at present levels, we find a roughly 150% increase in relative global flood displacement risk by the end of the century, or a 50% increase of risk per degree of global warming. We model displacement probabilities as a function of population density, flood depth and flood fraction.

Although the resolution of the global model is limited, the effect of climate change is robust across greenhouse gas concentration scenarios, climate models and hydrological models. Our work potentially enables the creation of a displacement early warning system.
Strong aerosol effects on cloud amount based on long-term satellite observations over the East Coast of the United States
Authors: Cao Yang , Wang Minghuai , Rosenfeld Daniel , Zhu Yannian , Liang Yuan , Liu Zhoukun , Bai Heming
Published: March 2021

Here we use 16-year satellite and reanalysis data in combination with a multivariate regression model to investigate how aerosols affect cloud fraction (CF) over the East Coast of the United States. Cloud droplet number concentrations (Nd), cloud geometrical thickness, lower tropospheric stability, and relative humidity at 950 hPa (RH950) are identified as major cloud controlling parameters that explain 97% of the variability in CF. Nd is shown to play an important role in regulating the dependence of cloud fraction on RH950. The observed annual-mean CF shows no significant trend due to the cancelation from the opposite trends in Nd and RH950. The multivariate regression model revealed that the decline in Nd alone would lead to a about 20% relative decline in CF. Our results indicate the significant aerosol effects on CF and suggest the need to account for pollution-induced cloud changes in quantifying cloud feedback based on long-term observations.
Ensemble data assimilation for systems with different degrees of nonlinearity with a hybrid nonlinear-Kalman ensemble transform filter
Authors: Nerger Lars
Published: March 2021

The second-order exact particle filter NETF (nonlinear ensemble transform filter) is combined with local ensemble transform Kalman filter (LETKF) to build a hybrid filter scheme (LKNETF). The filter combines the stability of the LETKF with the nonlinear properties of the NETF to obtain improved assimilation results for smaller ensembles. Both filter components are localized in a consistent way so that the filter can be applied with high-dimensional models. The degree of filter nonlinearity is defined by a hybrid weight, which shifts the analysis between the LETKF and NETF. Since the NETF is more sensitive to sampling errors than the LETKF, the latter filter should be preferred in linear cases. It is discussed how an adaptive hybrid weight can be defined based on the nonlinearity of the system so that the adaptivity yields a good filter performance in linear and nonlinear situations. The filter behavior is exemplified based on experiments with the chaotic Lorenz-63 and Lorenz-96 models, in which the nonlinearity can be controlled by the length of the forecast phase.
Assessment of the impact of large changes in the ratio of photolysis rate of nitrate to that of gas nitric acid on HONO concentrations simulated by a 3-D chemical transport model
Authors: Guo Yitian , An Junling , Zhang Jingwei
Published: March 2021

Some studies show that photolysis of nitrate and deposited nitrate and gas nitric acid (HNO3) on the ground surface is much faster than that of HNO3. The former mechanism has been considered as a possible daytime HONO source and discussed in many laboratory and field studies. Although this mechanism is also coupled into some three-dimensional chemical transport models, the effect of large changes in the ratio of photolysis rate of nitrate to that of HNO3 (RAT) on HONO concentrations has not been assessed and will be discussed here by using the updated WRF-Chem model. Simulations indicate that in the morning, this mechanism only resulted in a HONO increase of a few ppt, while the heterogeneous reaction of NO2 enhanced HONO by about 150 ppt; in the afternoon, however, this mechanism led to a significant HONO increase, with its contribution to HONO concentrations being close to the contribution of the heterogeneous reaction of NO2. In some heavily nitrate-polluted areas, this mechanism contributed more than 80% of HONO concentrations during the afternoon. Large changes in RAT produced a substantial impact on HONO concentrations. When RAT was altered from 15 to 100, increase of HONO concentrations was enhanced by about 6 times. Our results suggest that more laboratory and field studies on the photolysis rates of nitrate and deposited nitrate and HNO3 on the ground surface are still needed.
The role of the Pacific Decadal Oscillation and ocean-atmosphere interactions in driving United States heatwaves
Authors: Vijverberg Sem , Coumou Dim
Published: March 2021

Heatwaves can have devastating impact on society and reliable early warnings at several weeks lead time are needed. Heatwaves are often associated with quasi-stationary Rossby waves, which interact with sea surface temperature (SST). Previous studies showed that north-Pacific SST can provide long-lead predictability for eastern U.S. temperature, moderated by an atmospheric Rossby wave. The exact mechanisms, however, are not well understood. Here we analyze Rossby waves associated with heatwaves in western and eastern US. Causal inference analyses reveal that both waves are characterized by positive ocean-atmosphere feedbacks at synoptic timescales, amplifying the waves. However, this positive feedback on short timescales is not the causal mechanism that leads to a long-lead SST signal. Only the eastern US shows a long-lead causal link from SSTs to the Rossby wave. We show that the long-lead SST signal derives from low-frequency PDO variability, providing the source of eastern US temperature predictability. We use this improved physical understanding to identify more reliable long-lead predictions. When, at the onset of summer, the Pacific is in a pronounced PDO phase, the SST signal is expected to persist throughout summer. These summers are characterized by a stronger ocean-boundary forcing, thereby more than doubling the eastern US temperature forecast skill, providing a temporary window of enhanced predictability.
Role of the internal climate variability in the atmospheric response to a sudden summer Arctic sea ice loss
Authors: Delhaye Steve , Fichefet Thierry , Massonnet François , Docquier David , Roberts Christopher , Keeley Sarah , Senan Retish , Msadek Rym , Chripko Svenya , García-Serrano Javier , Bretonnière Pierre-Antoine
Published: March 2021

The retreat of Arctic sea ice for the last four decades is a primary manifestation of the climate system response to increasing atmospheric greenhouse gas concentrations. This retreat is frequently considered as a possible driver of atmospheric circulation anomalies at mid-latitudes. However, the year-to-year evolution of the Arctic sea ice cover is also characterized by significant fluctuations attributed to internal climate variability. It is unclear how the atmosphere will respond to a near-total retreat of summer Arctic sea ice, a reality that might occur in the foreseeable future. This study uses sensitivity experiments  with higher and lower horizontal resolution configurations of three global coupled climate models to investigate the local and remote atmospheric responses to a reduction in Arctic sea ice cover during the preceding summer. Recognizing that these responses likely depend on the model itself and on its horizontal resolution, and that the model’s internally-generated climate variability may obscure the atmospheric response, we design a protocol to compare each source separately. After imposing a 15-month albedo perturbation resulting in a sudden summer Arctic sea ice loss, the remote mid-latitude climate response has a very low signal-to-noise ratio such that internal climate variability dominates the uncertainty of the response, regardless of the atmospheric variable. Indeed, more than 28, 165 and 210 members are needed to detect a robust response in surface air temperature, precipitation and sea level pressure to sea ice loss in Europe, respectively. Finally, we find that horizontal resolution plays a secondary role in the uncertainty of the atmospheric response to substantial perturbation of Arctic sea ice. These findings suggest that even with higher resolution model configurations, it is important to have large ensemble sizes to increase the signal to noise ratio for the mid-latitude atmospheric response to sea ice changes.
Combining multi-GNSS phase bias products for improved undifferenced ambiguity resolution
Authors: Geng Jianghui , Pan Yuanxin , Yang Songfeng , Li Pan
Published: March 2021

The rapid development of multi-GNSS constellations, e.g., Galileo and BeiDou, is catalyzing innovations in high-precision applications. Precise point positioning ambiguity resolution (PPP-AR) has been essential to achieving the highest positioning precision using multi-GNSS data in wide areas. In recent years, several International GNSS Service analysis centers (IGS ACs such as CNES, CODE, WHU) have been providing phase bias products to enable PPP-AR, but whether these AC-specific multi-GNSS (e.g., GPS/Galileo/BeiDou-2/3) products are compatible with each other and whether they can be reconciled for an IGS combination product are pending. In this study, we combined phase bias products from four organizations for GPS/Galileo/BeiDou-2/3 in 2020. All phase bias products are first converted to observable-specific representation and then reconciled with satellite clocks before the combination; their capability of recovering integer undifferenced ambiguities has been always kept after properly addressing inter-system biases and satellite attitude discrepancies. It is found that the RMS of clock alignment residuals are around 6.8, 7.1, 14.9 and 14.6 ps for GPS, Galileo BeiDou-2 and BeiDou-3, respectively. BeiDou products perform worse due largely to sparse tracking networks and deficient orbit models. In a kinematic PPP experiment with 151 global MGEX (Multi-GNSS Experiment) stations, the combined phase bias products provide better or at least equivalent positioning results as opposed to AC specific products. Compared with ambiguity-float solutions, ambiguity-fixed PPP solutions can improve the positioning precision by 29-50% in the east component. With combined phase bias products, the positioning precision of GPS/Galileo/BDS-2/3 PPP-AR solutions can achieve 0.62, 0.64 and 1.90 cm in the east, north and up components, respectively, in contrast to 0.87, 0.88 and 2.60 cm for GPS only PPP-AR solutions.
Numerical study of fault sliding under fluid injection
Authors: Riga Vasily , Sergey Turuntaev
Published: March 2021

Seismicity associated with fluid injection into the subsurface is one of the most important issues worldwide. Fluid injection into or near a fault could lead to the fault sliding and to moderate or even hazardous seismic events. In the presented research, we study the single fault behavior under action of a single well injection near the fault. Various cases of initial conditions, system geometry, and friction properties of the fault are considered. To describe the friction on the fault we use two-parameter rate-and-state law. The fault has zones characterized by velocity-weakening and velocity-strengthening friction behavior. We analyze how location and size of the velocity-weakening zone and parameters of the friction law influence the fault sliding dynamics. We also consider how the fault sliding is changed when taking into account the rock poroelastic effects. As the result, we get conditions that are favorable for the occurrence of noticeable seismicity.
Novel MCMC methods for Bayesian inference of spatial parameter fields
Authors: Reuschen Sebastian , Xu Teng , Jobst Fabian , Nowak Wolfgang
Published: March 2021

Geostatistical inference (or inversion) methods are commonly used to estimate the spatial distribution of heterogeneous soil properties (e.g., hydraulic conductivity) from indirect measurements (e.g., piezometric heads). One approach is to use Bayesian inversion to combine prior assumptions (prior models) with indirect measurements to predict soil parameters and their uncertainty, which can be expressed in form of a posterior parameter distribution. This approach is mathematically rigorous and elegant, but has a disadvantage. In realistic settings, analytical solutions do not exist, and numerical evaluation via Markov chain Monte Carlo (MCMC) methods can become computationally prohibitive. Especially when treating spatially distributed parameters for heterogeneous materials, constructing efficient MCMC methods is a major challenge.

Here, we present two novel MCMC methods that extend and combine existing MCMC algorithms to speed up convergence for spatial parameter fields. First, we present the sequential pCN-MCMC, which is a combination of the sequential Gibbs sampler, and the pCN-MCMC. This sequential pCN-MCMC is more efficient (faster convergence) than existing methods. It can be used for Bayesian inversion of multi-Gaussian prior models, often used in single-facies systems. Second, we present the parallel-tempering sequential Gibbs MCMC. This MCMC variant enables realistic inversion of multi-facies systems. By this, we mean systems with several facies in which we model the spatial position of facies (via training images and multiple point geostatistics) and the internal heterogeneity per facies (via multi-Gaussian fields). The proposed MCMC version is the first efficient method to find the posterior parameter distribution for such multi-facies systems with internal heterogeneities.

We demonstrate the applicability and efficiency of the two proposed methods on hydro-geological synthetic test problems and show that they outperform existing state of the art MCMC methods. With the two proposed MCMCs, we enable modellers to perform (1) faster Bayesian inversion of multi-Gaussian random fields for single-facies systems and (2) Bayesian inversion of more realistic fields for multi-facies systems with internal heterogeneity at affordable computational effort.
Aerosols and their impacts on future Arctic climate change under different emission projections in the GISS-E2.1 Earth system model
Authors: Im Ulas , Tsigaridis Kostas , Faluvegi Gregory  S. , Langen Peter L. , French Joshua P. , Mahmood Rashed , Manu Thomas , von Salzen Knut , Thomas Daniel C. , Whaley Cynthia H. , Klimont Zbigniew , Skov Henrik , Brandt Jørgen
Published: March 2021

In order to study the future aerosol burdens and their radiative and climate impacts over the Arctic (>60 °N), future (2015-2050) simulations have been carried out using the GISS-E2.1 Earth system model. Different future anthrpogenic emission projections have been used from the Eclipse V6b and the Coupled Model Intercomparison Project Phase 6 (CMIP6) databases. Results showed that Arctic BC, OC and SO42- burdens decrease significantly in all simulations following the emission projections, with the CMIP6 ensemble showing larger reductions in Arctic aerosol burdens compared to the Eclipse ensemble. For the 2030-2050 period, both the Eclipse Current Legislation (CLE) and the Maximum Feasible Reduction (MFR) ensembles simulated an aerosol top of the atmosphere (TOA) forcing of -0.39±0.01 W m-2, of which -0.24±0.01 W m-2 were attributed to the anthropogenic aerosols. The CMIP6 SSP3-7.0 scenario simulated a TOA aerosol forcing of -0.35 W m-2 for the same period, while SSP1-2.6 and SSP2-4.5 scenarios simulated a slightly more negative TOA forcing (-0.40 W m-2), of which the anthropogenic aerosols accounted for -0.26 W m-2. The 2030-2050 mean surface air temperatures are projected to increase by 2.1 °C and 2.4 °C compared to the 1990-2010 mean temperature according to the Eclipse CLE and MFR ensembles, respectively, while the CMIP6 simulation calculated an increase of 1.9 °C (SSP1-2.6) to 2.2 °C (SSP3-7.0). Overall, results show that even the scenarios with largest emission reductions lead to similar impact on the future Arctic surface air temperatures compared to scenarios with smaller emission reductions, while scenarios with no or little mitigation leads to much larger sea-ice loss, implying that even though the magnitude of aerosol reductions lead to similar responses in surface air temperatures, high mitigation of aerosols are still necessary to limit sea-ice loss. 
Calibrating microcharcoal in recent marine sediments: implications to reconstruct paleofire regimes on African continent
Authors: Haliuc Aritina , Daniau Anne-Laure , team members Braise
Published: March 2021

Fire is a worldwide terrestrial process and has shaped the ecosystems and life on Earth over millions of years. Today, fire regime metrics such as burned area, intensity and frequency, depend on a set of climatic and environmental variables, but under anticipated climate warming scenarios, it is projected that fire characteristics will change, posing great threats to the environment and society. Large uncertainties remain in better understanding this complex process, integrating it in Earth system global models and better forecasting the response of fire to future climate changes.

Paleofire records from marine sediments capture information about regional-scale relative changes in biomass burning over long timescale and can help understanding the relationships between climate change and fire activity. We still lack, though, what a change in biomass burning in the paleorecord means in terms of fire regimes.

The present study aims at exploring the link between charcoal accumulation in marine surface sediment samples of modern ages from about 150 sites across the African coast and fire regimes on land. It is based on an integrated approach using fire proxy, climate, environmental and historical information, and satellite data. Exploratory in character, this study is designed to investigate this link among different biomes, describing latitudinal and longitudinal transects, and to test the influence of different physical site-specific variables (climate, vegetation, size of the source area etc.) on land and transport-deposition processes into the marine realm.

This study aims to provide a novel sediment-based proxy for a key physical parameter unlocking specific technical and theoretical problems related to fire research; it may also help to better understand local to regional processes controlling the fire signal and contextualize current and past environmental changes.
Quantification of erosion rate in crop field gullies from point clouds with two different methods  : the case study of Savigny crop field (North of Lausanne, Switzerland) 
Authors: Charlotte Wolff , Tiggi Choanji , Marc-Henri Derron , Li Fei , Michel Jaboyedoff
Published: March 2021

The spreading use of remote techniques is in our daily life benefits to ease and/or speed up the acquisition and analysis of geographical data that can be meaningful for risk assessment or for taking decisions for prevention measures.

Here is presented one of the possible applications for the Unmanned Aerial Vehicle (UAV) acquisition, to evaluate the volume of eroded soils in a crop field due to washout after heavy rains. The case study is located North of Lausanne (Switzerland), in the village of Savigny. It is a crop field with a gentle slope where we can clearly see washout gullies appearing after rainfalls. A great number of small water streams disappeared for more intense agriculture which is the case here : According to topographical maps, a small stream was flowing in the past but disappeared  after 2004. It is interesting to see that after important rainfalls, gullies appear that could correspond to old small stream patterns. 

The data acquisition survey of October 30th, 2020 was done by means of a DJI Phantom 4 RTK flying at an altitude of about 20m and the Pix4d Capture planning mission application. To process the obtained 800 images, the new Pix4D Matic software was tested to get a fast dense point cloud with GSD ~1 cm accuracy, a DEM and an orthophoto. The dense point cloud was then analyzed with two compared methods to estimate the washout volumes, which are (1) inverse Sloping Local Base Level; and (2) Point cloud segmentation based on normal vectors and curvatures.

As a result, these two methods gave a first estimation of the eroded volume of around 15m3 over a surface of 9 hectares which corresponds to an erosion rate of 1,7m3/hectare. These remote and non-destructive techniques are fast and easy compared to conventional field surveys, and the data acquisition and processing could be automated. In conclusion, these techniques provide a relatively low-cost time-series datasets processing to monitor and quantify the ongoing gully erosion. 

Further investigation would be to keep recording the volume and erosion rate estimations after important rainfalls, when clear new gullies appear and to record in the meanwhile the rainfall intensity. This could help assess in a second step the relationship between the erosion rate and the rainfall intensity and control if this relation follows a power-law function. Such a study could also give some clues about the possible impact of climate changes on erosions in crop fields. 
Evaluation of the Chemical Explosions Impact using Infrasound and InSAR Analysis
Authors: Hamama Islam , Yamamoto Masa-yuki , Medhat Noha Ismail
Published: March 2021

Chemical explosions generate shockwaves which can be recorded at far distant with infrasound sensors. Infrasound propagation and energy of the explosion are main factors which control the infrasonic wave arrivals. In this study, a China explosion which happened on 22 March 2019, Biuret explosion on 4 August 2020, and the explosion of MOMO-2 rocket failure during the launching process will be investigated. The infrasound data sets of these explosions are extracted from IMS infrasound stations and KUT infrasound sensors which are distributed all over Japan.

The explosions had different propagation conditions which can be simulated using ray tracing and parabolic equation numerical methods, furthermore the transmission losses can be estimated in order to determine the yield energy in TNT-equivalent of each explosion, moreover the severe surface damages were identified by using InSAR techniques which can be classified according to the interferometric coherency.

In conclusion, the integration between the infrasound technique and InSAR showed the safety zone which should be taken in account for any chemical factories or rocket launch sites.
Unsupervised classification of Mercury’S Visible–Near-Infrared MASCS/MESSENGER reflectance spectra for automated surface mapping.
Authors: D'Amore Mario , Helbert Jörn , Alessandro Maturilli , Indhu Varatharajan
Published: March 2021

The surface of Mercury has been mapped in the 400–1145 nm wavelength range by the Mercury Atmospheric and Surface Composition Spectrometer (MASCS) instrument during orbital observations by the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft.

Under the hypothesis that surface compositional information can be efficiently derived from spectral reflectance measurements with the use of machine learning techniques, we have conducted unsupervised hierarchical clustering analyses to identify and characterize spectral units from MASCS observations.

We apply our analysis on the latest MESENGER data delivery to PDS including the new spectral photometric correction , finding result consistent with our previous analysis based on our custom photometric effect removal.

The input is a global hyperspectral data cube image of normalized MASCS visible (VIS) detector spectra, from the first Earth year of the orbital mission. Data coverage varies from region to region, but global maps at 1 degree/pixel can be obtained with a high signal-to-noise ratio (SNR). The resultant hyperspectral map was then visually inspected to search for anomalies that originated mainly in regions of low coverage or from high levels of spectral variation within a single pixel.

Our approach consist of several steps:
1.  Data cleaning step: remove data artifact.
2.  Independent Component Analysis (ICA): features compression and undelyng signal demixing.
3.  Manifold learning : embedding of data in a low dimensional space via UMAP.
4.  Hierarchical clustering : creation of spectrally similar partition and projection on the surface with comparison to existing human generated classifications.

We  found the existence of two large and spectrally distinct regions, which we call the polar spectral unit (PSU) and the equatorial spectral unit (ESU).
The spatial extent of the polar unit in the northern hemisphere generally correlates well with that of the northern volcanic plains.
Further analysis indicates the presence of smaller sub-units that lie near the boundaries of these large regions and may be transitional areas of intermediate spectral characters.
Automatic swarm analyzer based on matched filtering algorithms: El Hierro 2011 and Torreperogil 2012-2013
Authors: Díaz Suárez Eduardo Andrés , Domínguez Cerdeña Itahiza Francisco , Del Fresno Rodríguez-Portugal Carmen , Cantavella Nadal Juan Vicente , Barco De La Torre Jaime
Published: March 2021

Dense seismic swarms usually show a high number of earthquakes per hour, the events may overlap and in most of the cases seismic records are characterized by a low signal-to-noise ratio. As a result, the manual characterization performed by seismic and volcanic observatories can become very complicated or impossible to perform. In order to solve this problem, we have developed a set of algorithms whose purpose is to detect the events, pick their phases and give a location (in an absolute and relative way) of the earthquakes associated with a known swarm. 

 

These algorithms have been tested in two different tectonic environments: the volcano-tectonic pre-eruptive swarm of El Hierro, Spain (2011) and the tectonic seismic series of Torreperogil, Spain (2012-2013).  Both crises mainly differ in the distances from the seismic stations to the hypocentres of the swarms: in the case of El Hierro,  data corresponds to local epicentral distances (5-20Km) while the case of Torreperogil seismic series deals with regional distances (10-180km). Otherwise, both series present a similar evolution of the seismic network: as the number of earthquakes increased, more stations were deployed and the network became denser. 

 

To analyze these series, we have used two sets of well relocated earthquakes of both swarms as masters, considering manually analyzed events by National Geographic Institute (IGN) with magnitude mbLg greater than 1.5. After the application of the new algorithms, we have increased the number of earthquakes of  the IGN seismic catalog by a factor of 4.5 for Torreperogil and 2.9 for El Hierro. Similarly, the number of picked phases for these two series has been increased by a factor of 4.5 and 3.5, respectively.
Multifractal analysis of spatial heterogeneity in Spanish arid rangelands
Authors: Sanz Sancho Ernesto , Saa-Requejo Antonio , Diaz-Ambrona Carlos G. , Ruiz-Ramos Margarita , Tarquis Ana M.
Published: March 2021

Rangeland and agricultural landscapes are complex and multifractal based on the interaction of biotic and abiotic factors such as soil, meteorology, and vegetation. The effects of land-uses on these areas modify their characteristics and dynamics.  The use of Normalized Difference Vegetation Index (NDVI) and NDVI anomalies (NDVIa) from satellite time series can effectively aid on understanding the differences among rangeland uses and types.

Multifractal detrended fluctuation analysis (MDFA) focuses on measuring variations of the moments of the absolute difference of their values at different scales. This allows us to use different multifractal exponent such as generalized Hurst exponent (H(q)), and the scaling exponent (ζ(q)) to characterize each area.

We collected the time series using satellite data of MODIS (MOD09Q1.006) from 2002 to 2019. Two areas from southeastern Spain (Murcia province) of 6.25 Km2 were selected. Each area has 132 pixels with a spatial resolution of 250 x 250 m2 and a temporal resolution of 8 days. The areas were selected to compare two types of arid rangeland. Area 1 (A1) is mainly covered by a mixed herbaceous cropland and grassland, Area 2 (A2) presents tree crops as well as a small patch of Mediterranean scrubland.

MDFA was used on every pixel of each area and H(q), and ζ(q) were plotted and compared. Our results report different exponent behaviours for diverse rangeland type or use. Within each area when different vegetation types are present MFDFA can allow us to distinguish among them such as in A2 where the pixels composing the river that crosses the area show less antipersistent character than the surrounding tree crops.
Comparing the scaling exponent of NDVI and NDVIa also suggest a difference of influence on the multifractal character of long-range correlations. This influence is much stronger in A4 than the three others, having their multifractal character due more heavily to probability density function.

We conclude that MDFA is a good tool to characterize arid rangelands spatial heterogeneity, particularly for rangeland with different vegetation types. It can be used to monitor and manage arid rangeland. It can be useful for policy-makers for short- and long-term solutions.

Acknowledgements: The authors acknowledge the support of Project No. PGC2018-093854-B-I00 of the Ministerio de Ciencia Innovación y Universidades of Spain, “Garantía Juvenil” scholarship from Comunidad de Madrid, and the financial support from Boosting Agricultural Insurance based on Earth Observation data - BEACON project under agreement Nº 821964, funded under H2020EU, DT-SPACE-01-EO-2018-2020.
Sources and transport of glacial meltwater in the Bellingshausen Sea, Antarctica
Authors: Sheehan Peter , Heywood Karen , Thompson Andrew , Flexas Mar
Published: March 2021

Quantifying meltwater content and describing transport pathways is important for understanding the impact of a warming, melting Antarctica on ocean circulation. Meltwater fluxes can affect density-driven, on-shelf flows around the continent, and the formation of the dense water masses that ventilate abyssal regions of the world ocean. We present observations collected from two ocean gliders that were deployed in the Bellingshausen Sea for a period of 10 weeks between January and March of 2020.  Using multiple high-resolution sections, we quantify both the distribution of meltwater concentrations and lateral meltwater fluxes within the Belgica Trough in the Bellingshausen Sea. We observe a cyclonic circulation in the trough, in agreement with previous studies. A meltwater flux of 0.46 mSv is observed flowing northwards in the  western limb of the cyclonic circulation. A newly identified meltwater re-circulation (0.88 mSv) is observed flowing back towards the ice front (i.e. southwards) with the eastern limb of the cyclonic circulation. In addition, 1.16 mSv of meltwater is observed flowing northeastward, parallel to the shelf break, with the northern limb of the cyclonic circulation. Peak meltwater is concentrated into two layers associated with different density surfaces: one approximately 150 m deep (27.4 kg m-3) and one approximately 200 m deep (27.6 kg m-3}). The deeper of these layers is characterised by an elevated optical backscatter, which indicates a more turbid water mass. The shallower layer is less turbid, and is more prominent closer to the shelf break and in the eastern part of the Belgica Trough. We hypothesise that the deeper, turbid meltwater layer originates locally from the Venables Ice Shelf, whereas the shallower, less turbid meltwater layer, comprises meltwater from ice shelves in the eastern Bellingshausen Sea. The broad distribution of meltwater from multiple sources suggests the potential for remote interactions and feedbacks between the various ice shelves that abut the Bellingshausen Sea.
Quantifying ambiguity in sea-level projections
Authors: Le Cozannet Goneri , Rohmer Jeremy , Manceau Jean-Charles , Durand Gael , Ritz Catherine , Melet Angélique , Meyssignac Benoit , Salas y Mélia David , Carson Mark , Slangen Aimée , Hinkel Jochen , Lambert Erwin , Thiéblemont Rémi , Le Bars Dewi , Stammer Detlef , Van De Wal Roderik , Nicholls Robert
Published: March 2021

Coastal impacts of climate change and the related mitigation and adaptation needs requires assessments of future sea-level changes. Following a common practice in coastal engineering, probabilistic sea-level projections have been proposed for at least 20 years. This requires a probability model to represent the uncertainties of future sea-level rise, which is not achievable because potential ice sheets mass losses remain poorly understood given the knowledge available today. Here, we apply the principles of extra-probabilistic theories of uncertainties to generate global and regional sea-level projections based on uncertain components. This approach assigns an imprecision to a probabilistic measure, in order to quantify lack of knowledge pertaining to probabilistic projections. This can serve to understand, analyze and communicate uncertainties due to the coexistence of different processes contributing to future sea-level rise, including ice-sheets. We show that the knowledge gained since the 5th Assessment report of the IPCC allows better quantification of how global and regional sea-level rise uncertainties can be reduced with lower greenhouse gas emissions. Furthermore, Europe and Northern America are among those profiting most from a policy limiting climate change to RCP 2.6 versus RCP 4.5 in terms of reducing uncertainties of sea-level rise.
Evaluation of the z-tilde vertical coordinate in a 1/4° global NEMO
Authors: Megann Alex , Chanut Jerome , Storkey Dave
Published: March 2021

The eddy-permitting 1/4° resolution in NEMO has been known to suffer from significant numerical diapycnal mixing. This arises from truncations in the advection scheme, which causes spurious mixing of tracers where there are transient vertical motions from internal tides and near-inertial waves, as well as from computational modes associated with partly-resolved mesoscale features. Suppressing the near-gridscale noise by increasing the viscosity has been shown to offer a useful reduction in that contribution to numerical mixing, but does not have a significant effect on tides and inertial waves.

The z~ scheme replaces eulerian vertical tracer advection across the vertical coordinate surfaces, on time scales less than a few days, with displacements of the coordinate surfaces themselves, in a manner more consistent with the nearly adiabatic nature of near-inertial gravity waves and tides. This has been shown to give substantial reduction in numerical mixing in an idealised configuration, but has yet to be fully evaluated in a global ocean domain. It is shown, using a new prototype eORCA025 global NEMO configuration, that z~ with the default filter timescales reduces the effective diapycnal diffusivity and temperature drifts by only about 10%. Preliminary results will be presented for the sensitivity of the numerical mixing to the z~ timescale and other parameters. The application of z~ to a tidally-forced simulation will also be discussed.
Hierarchical exploration of single station seismic data with unsupervised learning
Authors: Steinmann René , Seydoux Leonard , Campillo Michel
Published: March 2021

Seismic datasets contain an enormous amount of information and a large variety of signals with different origins. We usually observe signatures of earthquakes, volcanic and non-volcanic tremors, rockfalls, road and air traffic, atmospheric perturbations and many other acoustic emissions. More and more seismic sensors are deployed worldwide and record the seismic wavefield in a continuous fashion, generating massive volumes of data that cannot be analyzed manually in decent times. Therefore, identifying classes of signals in seismic data with automatic strategies is a crucial stage towards the understanding of the underlying physics of geological objects. For that reason seismologists have developed different tools to detect and classify certain types of signals. Recently, machine learning gained much attention due to its ability to recognize patterns. While supervised learning is a great tool for detecting and classifying signals within already-known classes, it cannot be used to infer new classes of signals, and can be strongly biased by the labels we impose. We here propose to overcome this limitation with unsupervised learning. In this study, we present a new way to explore single-station continuous seismic data with a dendrogram produced by agglomerative clustering. Our method is motivated by the idea that labels in a seismic data set follow a hierarchical order with different levels of details. For example earthquakes belong to the larger class of stationary signals and can be also divided into subclasses with different focal mechanism or magnitudes. We first use a scattering network (a convolutional neural network that makes use of wavelet filers) in order to extract a multi-scale representation of the continuous seismic waveforms. We then select the most meaningful features by means of independent component analysis, and apply an agglomerative clustering on this representation. We finally explore the dendrogram in a systematic way in order to explore the different signal classes revealed by the strategy. We illustrate our method on seismic data continuously recorded in the vicinity of the North-Anatolian fault, in Turkey. During this time period, a seismic crisis with more than 200 micro-earthquakes occurred, together with many other anthropogenic and meteorological events. By exploring the classes revealed by the dendrogram with a posteriori signal features (occurrence, within-class correlations, etc.) we show that the strategy is capable of retrieving the seismic crisis as well as signals related to anthropogenic and meteorogical activities.