bluuebunny/crossref_metadata_2025 huggingface dataset:
Sentinel-2 mission Contribution for Supporting Bathymetric layers of SAFAGA coastal zone, Egypt
Authors: Saeed Ramez , Abdelrahman Saad , Scozari Andrea , Negm Abdelazim
Published: March 2021

ABSTRACT

With the fast and highly growing demand for all possible ways of remote work as a result of COVID19 pandemic, new technologies using Satellite data were highly encouraged for multidisciplinary applications in different fields such as; agriculture, climate change, environment, coastal management, maritime, security and Blue Economy.

This work supports applying Satellite Derived Bathymetry (SDB) with the available low-cost multispectral satellite imagery applications, instruments and readily accessible data for different areas with only their benthic parameters, water characteristics and atmospheric conditions.  The main goal of this work is to derive bathymetric data needed for different hydrographic applications, such as: nautical charting, coastal engineering, water quality monitoring, sediment movement monitoring and supporting both green carbon and marine data science.  Also, this work proposes and assesses a SDB procedure that makes use of publicly-available multispectral satellite images (Sentinel2 MSI) and applies algorithms available in the SNAP software package for extracting bathymetry and supporting bathymetric layers against highly expensive traditional in-situ hydrographic surveys. The procedure was applied at SAFAGA harbor area, located south of Hurghada at (26°44′N, 33°56′E), on the Egyptian Red Sea coast.  SAFAGA controls important maritime traffic line in Red Sea such as (Safaga – Deba, Saudi Arabia) maritime cruises.  SAFAGA depths change between 6 m to 22m surrounded by many shoal batches and confined waters that largely affect maritime safety of navigation.  Therefore, there is always a high demand for updated nautical charts which this work supports.  The outcome of this work provides and fulfils those demands with bathymetric layers data for the approach channel and harbour usage bands electronic nautical chart of SAFAGA with reasonable accuracies.  The coefficient of determination (R2) differs between 0.42 to 0.71 after applying water column correction by Lyzenga algorithm and deriving bathymetric data depending on reflectance /radiance of optical imagery collected by sentinel2 missions with in-situ depth data values relationship by Stumpf equation.  The adopted approach proved to give  highly reasonable results that could be used in nautical charts compilation. Similar methodologies could be applied to inland water bodies.  This study is part of the MSc Thesis of the first author and is in the framework of a bilateral project between ASRT of Egypt and CNR of Italy which is still running.

Keywords: Algorithm, Bathymetry, Sentinel 2, nautical charting, Safaga port, satellite imagery, water depth, Egypt.
What determines the position of the transition zone between alpha and beta regions in the ocean? A model study.
Authors: Caneill Romain , Roquet Fabien , Madec Gurvan , Nycander Jonas
Published: March 2021

The stratification is primarily controlled by the temperature in subtropical regions (alpha ocean), and by salinity in subpolar regions (beta ocean). Between these two regions lies a transition zone where intense frontal systems are usually found, either in the Southern Ocean or in the North Atlantic and North Pacific basins. Transition zones are often characterized by deep mixed layers in winter responsible for the ventilation of intermediate layers. Here we want to investigate what determines the latitudinal position of the transition zone. It is generally assumed that this position is set by the wind stress pattern forcing Ekman downwelling, however the position of the transition zone does not match so well the wind stress convergence zone in the observations. Another possibility would be that it is controlled by the distribution of air-sea fluxes. The equation of state (EOS) for seawater determines the relative impact of heat and freshwater forcing on the buoyancy forcing. A key property of seawater is that the density becomes less sensitive to temperature at low temperatures (caused by an important nonlinearity of the EOS), increasing the effect of salinity on the stratification in polar region. We hypothesize that the decreasing of the relative influence of temperature on density is a major component in setting the position of the transition zone. To test this hypothesis, we developed an idealized triple-gyre configuration with the ocean global circulation model NEMO (Nucleus for European Modelling of the Ocean). A range of simplified EOS have been ran to test the effect of the buoyancy forcing on the position of the transition zone and the convective area. Under restoring conditions for the temperature and the salinity, augmenting or reducing the sensitivity of the density to the temperature is used as a way to modify the relative contribution of temperature and salinity to the buoyancy forcing. We show that the position of the convective area corresponds to a surface density maximum and is not directly related to the Ekman pumping zone. Moreover, alpha - beta ocean distinction becomes possible because the EOS is nonlinear. The first order influence of the forcing evolution on setting the localization of the transition zone and the associated deep water formation challenges the classical theories of thermocline ventilation by Ekman pumping.
Ionospheric Scintillation observed by LOFAR PL610 station
Authors: Pożoga Mariusz , Matyjasiak Barbara , Rothkaehl Hanna , Ciechowska Helena , Grzesiak Marcin , Wronowski Roman , Budzińska Katarzyna , Tomasik Łukasz
Published: March 2021

Due to their low intensity, ionospheric scintillations in the middle latitude region are difficult to observe. However, scintillations intensity increases at lower frequencies. Those below 90 MHz, covered by LOFAR, enable scintillation measurements in mid-latitude region. Long-term observations, with the use of PL610 station, allow the study of weak scintillation climatology, unavailable for measurement led with other methods. The developement of functional tool for the scintillation parameters analysis described in the paper enabled the study of scintillations in the mid-latitude region and future application to the data collected by LOFAR.

LOFAR PL610 station in Borowiec (23E,50N) regularly observes ionospheric scintillation using signals from the 4 strongest radio sources, members of LOFAR A-team: Cas A, Cyg A, Vir A and Tau A. The measurements are taken by LBA antennas at frequencies in the range of 10-90 MHz. Since 2018 we have collected more than 8000 hours of observations. In this work research, we present the results of the automatic s4 calculation system based on our observations. The observations are led in 4-bit mode, for 4 independent sources, with sampling of 10 Hz at 244 subbands. Sources are selected automatically depending on their visibility. Due to the fact that natural radio sources are relatively weak and beamforming is not ideal, the data are noisy. In order to improve the quality of data, the measured amplitudes are filtered and S4 index is computed for each beamlet. All processed data are stored in a database and enable in-depth analysis of scintillation behavior in the mid-latitude region.

We look at the intrinsic features of the observation: dependence on the geometry of the measurement, impact of RFI depending on the strength of the radiosource, the observation frequency then show the dependence of scintillation on the global conditions caused by space weather.
Variability in Sea Ice Melt Onset in the Arctic Northeast Passage: Seesaw of the Laptev Sea vs. the East Siberian Sea
Authors: Liang Hongjie , Su Jie
Published: March 2021

The ice/snow melt onset (MO) is a critical triggering signal for ice-albedo positive feedback in the Arctic. Concerning the Northeast Passage (NEP), for 1979-1998, the MO in the East Siberian Sea (ESS) occurred generally earlier than that in the Laptev Sea (LS). However, for 1999-2018, the LS experienced significantly earlier MO than did the ESS in several years. This phenomenon is identified as the MO Seesaw (MOS), i.e., the MO difference between the LS and ESS. For the positive MOS, storm tracks in May tend to cover the ESS rather than the LS and easterly wind prevails and shifts slightly to a northerly wind in the ESS, resulting in higher surface air temperature (SAT) and total-column water vapor (TWV) and earlier MO in the ESS. For the negative MOS, storm tracks are much stronger in the LS than in the ESS and prominent southerly/southwesterly wind brings warm air from coastal land towards the LS. The effect of the Barents Oscillation (BO) on the MOS could be dated back to April. When the Barents Sea is centered with a low SLP in April, sea ice in the LS would be driven away from the coasts, leading to a lower sea ice area (SIA), which increases the surface latent heat flux and humidifies the overlying atmosphere. Along with an enhanced downward sensible heat flux, earlier regional average MO occurs in the LS. For 1999-2018, the MOS was more closely related to both the local variables and the large-scale atmospheric circulation indices.
Quantification of N2O fluxes and EF values in a pasture using chamber and eddy-covariance technique
Authors: Barczyk Lena , Kuntu-Blankson Kate , Calanca Pierluigi , Six Johan , Ammann Christof
Published: March 2021

In grassland ecosystems nitrogen (N) inputs are mainly attributed to fertilizer applications for increasing  herbage productivity and to excreta of grazing animals. Cattle, for instance, excrete 75-95 % of the N intake. Accordingly, dung and urine patches of grazing animals form hotspots of nitrate leaching and gaseous N emissions as ammonia (NH3) or the important greenhouse gas nitrous oxide (N2O). Global default emission factor (EF) values for N2O, 2.0 % for grazing based nitrogen inputs (EF3) and 1.0 % for nitrogen inputs via fertilizer applications (EF1) have been suggested by IPCC. However, some countries like New Zealand, Canada or the Netherlands have established country-specific EFs showing considerable regional differences.

In the present research study, we examine N2O emissions of a pasture field in Switzerland in relation to possible drivers. Field scale emissions by eddy covariance are measured in parallel to patch-scale N2O fluxes from controlled applications of urine, dung and fertilizer. The patch-scale fluxes are measured by a manually operated chamber ('fast-box') connected to an online gas analyzer. Besides estimating EF values on annual and seasonal basis, relevant factors that might control N2O fluxes like environmental conditions (weather parameters, soil moisture, soil temperature), vegetation characteristics (height, composition, nitrogen and carbon content) and pasture management (patch age, grazing, fertilization, cut events, interactive effects) are analyzed. 

We present and discuss results of the first measurement year 2020. Three artificial urine applications during summer and autumn were performed. They show peak N2O fluxes of 279-1718 μg m-2 h-1 directly after application that decrease to near-background fluxes within 19-43 days. Using a simple linear interpolation of measured N2O fluxes, EF values of artificial urine patches vary between 0.57 and 2.44 % indicating a seasonal variability of N2O fluxes.
BioDiv-Support: scenario-based decision support tool for policy planning and adaptation to future challenges in biodiversity and ecosystem services 
Authors: Andersson Camilla ,   BioDiv-Support research team
Published: March 2021

Biodiversity includes any type of living variation, from the ecosystem level to genetic variation within organisms. The greatest threats to biodiversity is climate change, destruction of habitats and other human activities. High-altitude mountain regions are pristine environments, with historically small impacts from air pollution, but at risk of being disproportionately impacted by climate change. We focus on three mountainous regions: the Scandinavian Mountains, the Guadarrama Mountains in Spain, and the Pyrenees in France, Andorra and Spain. We study the impact of drivers of change of biodiversity such as future climate change, increased incidences of wild fires, emissions from new shipping routes in the Arctic as ice sheets are melting, human impacts on land use and management practices (such as reindeer grazing) and air pollution.

We simulate future climate change using WRF and a convective permitting climate model, HARMONIE-Climate, with a spatial resolution of 3km. The high resolution strongly improves the representation of precipitation compared to coarser scale simulations (Lind et al., 2020). We use these simulations to develop future scenarios of air pollution load, using two well established chemistry transport models (MATCH and CHIMERE; Marécal et al., 2015). These climate and air pollution scenarios are subsequently used, together with management scenarios, to develop scenarios for biodiversity and ecosystem services. These scenarios are developed applying a process-based dynamic vegetation and biogeochemistry model, LPJ-GUESS (Smith et al., 2014). 

The scenarios, representing mid-21st century, will be made available through a web-based planning tool, where local stakeholders in each region can explore the project results to understand how scenarios of climate change, air pollution and policy development will affect these ecosystems. Local stakeholders are involved throughout the project, such as reindeer herder communities, regional county boards and national authorities, and in a time of changing climate and a global pandemic we have learned the necessity for flexibility in such interactions.

 

References

Lind et al. 2020., Climate Dynamics 55, 1893-1912.

Marécal et al., 2015. Geosci. Mod. Dev. 8, 2777-2813.

Smith et al. 2014 Biogeosciences 11, 2027-2054.
A new methodology to detect changes in displacement rates of slow-moving landslides using InSAR time series
Authors: Urgilez Vinueza Alexandra , Handwerger Alexander , Bakker Mark , Bogaard Thom
Published: March 2021

Regional-scale landslide deformation can be measured using satellite-based synthetic aperture radar interferometry (InSAR). Our study focuses on the quantification of displacements of slow-moving landslides that impact a hydropower dam and reservoir in the tropical Ecuadorian Andes. We constructed ground surface deformation time series using data from the Copernicus Sentinel-1 A/B satellites between 2016 and 2020. We developed a new approach to automatically detect the onset of accelerations and/or decelerations within each active landslide. Our approach approximates the movement of a pixel as a piecewise linear function. Multiple linear segments are fitted to the cumulative deformation time series of each pixel. Each linear segment represents a constant movement. The point where one linear segment is connected to another linear segment represents the time when the pixel’s rate of movement has changed from one value to another value and is referred to as a breakpoint. As such, the breakpoints represent moments of acceleration or deceleration. Three criteria are used to determine the number of breakpoints: the timing and uncertainty of the breakpoints, the confidence intervals of the fitted segments’ slopes, and the Akaike Information Criterion (AIC). The suitable number of breakpoints for each pixel (i.e., the number of accelerations or decelerations) is determined by finding the largest number of breakpoints that complies with the three listed criteria. The application of this approach to landslides results in a wealth of information on the surface displacement of a slope and an objective way to identify changes in displacement rates. The displacement rates, their spatial variation, and the timing of acceleration and deceleration can further be used to study the physical behavior of a slow-moving slope or for (regional) hazard assessment linking the onset of change in displacement rate to causal and triggering factors.
How not to study fossil biomolecules
Authors: Alleon Julien , Gueriau Pierre
Published: March 2021

The search for fossil biomolecules often requires combining many techniques to properly characterize their chemical composition. Recently, it was suggested in 6 papers that conventional Raman spectroscopy (i.e., equipped with a 532 nm laser as the excitation source under continuous illumination) can be used alone to identify diverse remnants or derivatives of biomolecules in animal fossils, with important implications for both evolutionary events and fossilization processes. Unfortunately, the reported claims are not supported by the spectroscopy data provided, which actually result from instrumental artefacts and data processing. Here, we outline the limitations of Raman spectroscopy with respect to the identification of biomolecules in fossil materials, and then describe in detail the origin of the misinterpreted signal. Conventional Raman spectroscopy alone cannot be used to identify fossil biomolecules. Instead, non-conventional Raman spectroscopy, mass spectrometry and infrared and X-ray absorption spectroscopy techniques, are successfully used by paleontologists to identify fossil biomolecules that help understanding both the history of life and the mechanisms of fossilization.
Implications of Climate Change on Erosion Dynamics and Sediment Connectivity in Semi-arid Ecosystem
Authors: Yetemen Omer
Published: March 2021

In semi-arid ecosystems, basin elevation and hillslope aspect play an important role in the distribution of plant type and density. In general, north-facing aspects host mesic and denser vegetation than south-facing aspects where host xeric plants. Beside aspect, elevation plays a dominant role in vegetation distribution. The Upper Rio Salado Basin, in central New Mexico, hosts shrublands and grasslands at lower elevations and forests at higher elevations. The geomorphometric analysis shows that forest areas are steeper than the grasslands and shrublands. Shrub encroachment in the region and the increase in global temperatures may lead to the replacement of forests by shrublands and the transition from a resource-conserving ecosystem to a leaky (non-conserving) ecosystem on the north-facing aspects which is similar to current south-facing aspects. The preliminary results show these transitions will lead to emerging hotspot areas in erosion. These erosion­-prone zones should be monitored in future for sustainable management.

This study has been produced benefiting from the 2232 International Fellowship for Outstanding Researchers Program of the Scientific and Technological Research Council of Turkey (TUBITAK) through grant 118C329. The financial support received from TUBITAK does not mean that the content of the publication is approved in a scientific sense by TUBITAK.
Supervised and unsupervised machine-learning for automated quality control of environmental sensor data
Authors: Polz Julius , Schmidt Lennart , Glawion Luca , Graf Maximilian , Werner Christian , Chwala Christian , Mollenhauer Hannes , Rebmann Corinna , Kunstmann Harald , Bumberger Jan
Published: March 2021

We can observe a global decrease of well maintained weather stations by meteorological services and governmental institutes. At the same time, environmental sensor data is increasing through the use of opportunistic or remote sensing approaches. Overall, the trend for environmental sensor networks is strongly going towards automated routines, especially for quality-control (QC) to provide usable data in near real-time. A common QC scenario is that data is being flagged manually using expert knowledge and visual inspection by humans. To reduce this tedious process and to enable near-real time data provision, machine-learning (ML) algorithms exhibit a high potential as they can be designed to imitate the experts actions. 

Here we address these three common challenges when applying ML for QC: 1) Robustness to missing values in the input data. 2) Availability of training data, i.e. manual quality flags that mark erroneous data points. And 3) Generalization of the model regarding non-stationary behavior of one  experimental system or changes in the experimental setup when applied to a different study area. We approach the QC problem and the related issues both as a supervised and an unsupervised learning problem using deep neural networks on the one hand and dimensionality reduction combined with clustering algorithms on the other.

We compare the different ML algorithms on two time-series datasets to test their applicability across scales and domains. One dataset consists of signal levels of 4000 commercial microwave links distributed all over Germany that can be used to monitor precipitation. The second dataset contains time-series of soil moisture and temperature from 120 sensors deployed at a small-scale measurement plot at the TERENO site “Hohes Holz”.

First results show that supervised ML provides an optimized performance for QC for an experimental system not subject to change and at the cost of a laborious preparation of the training data. The unsupervised approach is also able to separate valid from erroneous data at reasonable accuracy. However, it provides the additional benefit that it does not require manual flags and can thus be retrained more easily in case the system is subject to significant changes. 

In this presentation, we discuss the performance, advantages and drawbacks of the proposed ML routines to tackle the aforementioned challenges. Thus, we aim to provide a starting point for researchers in the promising field of ML application for automated QC of environmental sensor data.
Pre-treating GNSS time series using a recurrent neural network to improve the automated detection of jump discontinuities
Authors: Tavasci Luca , Cascarano Pasquale , Gandolfi Stefano
Published: March 2021

Ground motion monitoring is one of the main goals in the geoscientist community and at the time it is mainly performed by analyzing time series of data. Our capability of describing the most significant features characterizing the time evolution of a point-position is affected by the presence of undetected discontinuities in the time series. One of the most critical aspects in the automated time series analysis, which is quite necessary since the amount of data is increasing more and more, is still the detection of discontinuities and in particular the definition of their epoch. A number of algorithms have already been developed and proposed to the community in the last years, following different statistical approaches and different hypotheses on the coordinates behavior. In this work, we have chosen to analyze GNSS time series and to use an already published algorithm (STARS) for jump detection as a benchmark to test our approach, consisting of pre-treating the time series to be analyzed using a neural network. In particular, we chose a Long Short Term Memory (LSTM) neural network belonging to the class of the Recurrent Neural Networks (RNNs), ad hoc modified for the GNSS time series analysis. We focused both on the training algorithm and the testing one. The latter has been the object of a parametric test to find out the number of predicted data that mostly emphasize our capability of detecting jump discontinuities. Results will be presented considering several GNSS time series of daily positions. Finally, a discussion on the possible integration of machine learning approaches and classical deterministic approaches will be done.
Assessing Surface water- alluvial aquifer water exchange using a multitracer approach and modelling
Authors: Texier Jérôme , Gonçalves Julio , Stieglitz Thomas , Vallet-Coulomb Christine
Published: March 2021

Alluvial aquifers are generally highly productive in terms of groundwater and are therefore particularly exploited. The study site is a drinking water production facility located on the alluvial plain of the Rhône river, France. This site consists of several pumping wells and observation piezometers organized along the riverbank. The site is continuously supplying water to neighboring agglomerations with intermittent pumping. In this situation, the pumping produces a piezometric depression allowing leading to a water exchange from the river to the aquifer which is a common feature in the case of alluvial aquifer exploitation along a riverside.

The four pumping wells and five piezometers were equipped with continuous automatic temperature and water level measurement probes, the river stage is monitored as well. These data are used to determine the exchange (direction and magnitude) between the aquifer and the river. Although pumping is intermittent, it does not allow a sufficient recovering of the natural piezometric level, i.e. the aquifer is permanently below the river stage.

In addition to the automatic probes, additional data acquisition campaigns were carried out. During these campaigns different tracers were used such as conductivity, stable isotopes of water and radon activity. Together with the continuously measured temperature, these various tracers were used to identify hydrodynamic variables and parameters, such as Darcy’s velocity, dispersivity, transit times. A MODFLOW model was developed, integrating the site geometry and hydrodynamic context, with the Rhone River at the western boundary and the Ouveze river at the eastern boundary. Model calibration was performed using the study site piezometric records and the optimization package PEST. The flow was reproduced at the site for two situations, a natural situation without groundwater pumping, and the exploitation situation with the groundwater withdrawals. Finally, the tracer’s data were integrated into the model to reproduce the transport of different tracers, in order to quantify the exchanges and the water fractions coming from the different hydraulic boundaries.
Gaussianization for Multivariate, High-dimensional Earth Observation data Analysis
Authors: Johnson J. Emmanuel , Piles Maria , Laparra Valero , Camps-Valls Gustau
Published: March 2021

Long-standing questions in multivariate statistics, information theory and machine learning reduce to estimating multivariate densities. However, this is still an unresolved problem and one of the biggest challenge in general, and for Earth system data analysis in particular, due to the high dimensionality (spatial, temporal and/or spectral) of the data streams. Gaussianization is a class of generative models (normalizing flows) that is effective in computing density estimates by using  a sequence of composite invertible transformations which transform data from its original domain to a multivariate Gaussian distribution. The methodology in turn allows us to estimate information theory measures (ITMs), which are relevant for the analysis and characterization of Earth system data superseding the mean, variance and correlation, as higher order measures, thereby capturing more complexity and providing more insight into various problems. We show that our Rotation-Based Iterative Gaussianization (RBIG) method allows us to compute ITMs from multivariate (spatio-spectral-temporal) Earth data efficiently in both computation and memory terms, directly from the Gaussianizing transformation, while being robust to data dimensionality . We demonstrate how Gaussianization is useful in various Earth observation data analysis problems, from hyperspectral image analysis to drought detection in data cubes.
Approaches to improve the robustness of the Comparison Model Method for the inverse problem of groundwater hydrology
Authors: Comunian Alessandro , Giudici Mauro
Published: March 2021

Indirect inversion approaches are widely used in Geosciences, and in particular also for the identification of the hydraulic properties of aquifers. Nevertheless, their application requires a substantial number of model evaluation (forward problem) runs, a task that for complex problems can be computationally intensive. Reducing this computational burden is an active research topic, and many solutions, including the use of hybrid optimization methods, the use of physical proxies or again machine-learning tools allow to avoid considering the full physics of the problem when running a numerical implementation of the forward problem.

Direct inversion approaches represent computationally frugal alternatives to indirect approaches, because in general they require a smaller number of runs of the forward problem. The classical drawbacks of these methods can be alleviated by some implementation approaches and in particular by using multiple sets of data, when available.

This work is an effort to improve the robustness of the Comparison Model Method (CMM), a direct inversion approach aimed at the identification of the hydraulic transmissivity of a confined aquifer. The robustness of the CMM is here ameliorated by (i) improving the parameterization required to handle small hydraulic gradients; (ii) investigating the role of different criteria aimed at merging multiple data-sets corresponding to different flow conditions.

On a synthetic case study, it is demonstrated that correcting a small percentage of the small hydraulic gradients (about 10%) allows to obtain reliable results, and that a criteria based on the geometric mean is adequate to merge the results coming from multiple data-sets. In addition, the use of multiple-data sets allows to noticeably improve the robustness of the CMM when the input data are affected by noise.

All the tests are performed by using open source and widely used tools like the USGS Modflow6 and its Python interface flopy to foster the application of the CMM. The scripts and corresponding package, named cmmpy, is available on the Python Package Index (PyPI) and on bitbucket at the following address: https://bitbucket.org/alecomunian/cmmpy.
Application of GSMaP for the analysis of upper tropospheric radiative cooling over the Asian summer monsoon region
Authors: Terao Toru , Murata Fumie , Yamane Yusuke , Kiguchi Masashi , Fukushima Azusa , Masahiro Tanoue , Kamimera Hideyuki , Hayashi Taiichi
Published: March 2021

The Asian summer monsoon system is the strongest monsoon circulation on the Earth. A huge reversal of meridional temperature gradient develops over the area covering the hemispheric region due to strong diabatic heating associated with convective activities. Vigorous conventions reach the upper troposphere providing a great amount of high potential temperature airmass. This high potential temperature air mass originates from the high equivalent potential temperature airmass accumulated in the lower troposphere over the Asian monsoon region. The highest potential temperature tropospheric air mass is observed only over the Asian summer monsoon region. To get a total view of the Asian summer monsoon circulation system, we focused on the mass budget of the upper-tropospheric air mass with a potential temperature between 355K to 370K. The non-conservative change of the air mass corresponds with the diabatic heating due to the convective activities, and the diabatic cooling due to the radiative process. To analyze the radiative cooling process that takes place in the upper troposphere, we utilized hourly GSMaP pixel values to detect rain-free pixels of the ERA5 dataset. We calculated the non-conservative air mass tendency over the rain-free pixels on a daily and 0.5 degrees spatio-temporal scale. We found the radiative equilibrium amount of high potential temperature air mass and the Newtonian cooling process with a relaxation time scale of 6 to 7 days. We will show the quantitative estimates of the total convective process of the Asian summer monsoon system associated with the convective clouds and radiative processes, through the mass budget of 355K-370K potential temperature air mass. We will further show results of the evaluation of the accuracy of TRMM and GPM products using our high-resolution tipping bucket raingauge network distributed over the Northeastern Indian subcontinent.
Quantifying the erosion of the world’s largest impact crater using cosmogenic nuclides: the Vredefort Dome, South Africa.
Authors: Khosa Rivoningo , Tooth Stephen , Kramers Jan , Mbele Vela , Corbett Lee , Bierman Paul
Published: March 2021

The world’s largest meteorite impact crater, the Vredefort Dome, has been the subject of extensive studies relating to its age, geology and geomorphology. However, there are no studies pertaining to the rate at which the rocks in the crater remnant are eroding, which can provide insight into the development of the landform over time. This study used the cosmogenic nuclides 10Be and 26Al, extracted from purified quartz samples, to investigate erosion rates along the Vaal River as it traverses the impact crater. The Vaal River flows in mixed bedrock-alluvial terrain through the dome, crossing two different bedrock lithologies. The river is multi-channelled (anabranching) atop the granitoids exposed in the core of the dome, then downstream flows as a single channel through a narrow canyon cut into the quartzites that form the rim of the dome. We collected 14 samples from the two rock types to assess lithologic controls on erosion rate and determine landscape erosion history. Results from the analysis of both isotopes were in close agreement; here, we report outcrop erosion rates based on the 10Be. The average 10Be-determined erosion rates (± 1 SD) along the active river channel for the quartzite (n = 4) and granitoid (n = 6) regions are 1.90 ± 0.12 and 2.19 ± 0.14 m/Ma respectively.  Additional samples from older, now elevated (>5 m) strath terraces developed atop quartzite (n = 4) indicate slightly lower average apparent erosion rates of 1.65 (± 0.09) m/Ma.  The data demonstrate that the erosion rates along the active river channel are similar between the two lithologies despite differences in rock hardness.  The resistant, slowing eroding quartzites serve as the local base level for the river upstream, promoting the development of anabranching, which disperses bedrock erosion over a wider area of the crater. We infer that both bedrock hardness and channel characteristics are important controls on erosion rates along the river.  Collectively, the dataset further illustrates the low bedrock erosion rates that prevail across large areas of the southern African interior.
Forest management practices in reduction of damage caused by Pine weevil (Hylobius abietis L.) and Cervidae animals in newly planted Scots pine forests.
Authors: Dūmiņš Kārlis , Timma Sigita , Lazdiņa Dagnija
Published: March 2021

Key words: forest regeneration, Conniflex, Trico, mechanical site preparation

Forest regeneration is crucial stage in commercial forest management because actions during this stage impact future forest productivity and value. Scots pine is one of the main tree species in forestry of the northern part of Europe. Foresters have to overcome different risk factors during regeneration process and two of them are seedling damage by Pine weevil (Hylobius abietis L) and browsing by herbivores of Cervidae family. Pine weevil is one of the main forest pests in Europe that damage regenerated coniferous stands. Damage caused by this pest can produce 70% mortality of planted seedlings. Another significant risk factor is browsing. With increase of deer (Cervidae) population the damaged forest area also increases to the extent that foresters choose other tree species for regeneration. The mitigation of these risks is possible with appliance of forest management practices.  There are used different repelents against Cervidae animals.  Regarding Pine weevil, due to restrictions on insecticide use in EU, different protective coating materials have been developed, and several studies show that soil preparation before planting reduce amount of damaged Pine seedlings and increase possibility of successful regeneration.  We evaluated if and how forest management methods - soil preparation techniques (spot mounding, disc trenching) in combination with different plant protection products (Conniflex, Trico) - affects the degree of damage caused by pine weevil and Cervidae animals to Scots pine seedlings one and two years after outplanting in four forest stands in Latvia. The results from this study shows that application of Conniflex reduce number of damaged trees by 16.8% first and 20.3% second year after outplanting compared to untreated seedlings. Soil preparation has significant impact on reduction of pine weevil damage. The best results have been achieved by planting with Conniflex treated seedlings on spot mounds (2.4% damaged trees compared to 48.9% in unprepared soil without treatment). Repellent Trico do not provide additional protection against Pine weevil and do not have long term protection effect against browsing. Overall conclusion is that combination of soil preparation and use of appropriate coating material (Conniflex) can provide sufficient protection without usage of insecticides, and Trico has to be applied before winter season to achieve effect of protection.
Turbulent wave attractors in large-aspect ratio domains.
Authors: Sibgatullin Ilias , Elistratov Stepan , Ermanyuk Eugeny
Published: March 2021

Ocean abyss is an example of a system with continuous stratification subject to large-scale tidal forcing. Owing to specific dispersion relation of internal waves, the domains bounded by sloping boundaries may support wave patterns with wave rays converging to closed trajectories (geometric attractors) as result of iterative focusing reflections. Previously the behavior of kinetic energy in wave attractors has been investigated in domains with comparable scales of depth and horizontal length. As the geometric aspect ratio of the domain increases, the dynamic pattern of energy focusing may significantly evolve both in laminar and turbulent regimes. The present paper shows that the energy density in domains with large aspect ratio can significantly increase. In numerical simulations the input forcing has been introduced at global scale by prescribing small-amplitude deformations of the upper bound of the liquid domain. The evolution of internal wave motion in such system has been computed numerically for different values of the forcing amplitude. The behavior of the large-aspect-ratio system has been compared to the well-studied case of the system with depth-to-length ratio of order unity.  A number of most typical situations has been analyzed in terms of behavior of integral mechanical quantities such as total dissipation, mean kinetic energy and energy fluctuations in laminar and turbulent cases. The relative mean kinetic energy (normalized by the kinetic energy of the liquid domain undergoing rigid-body oscillations with the amplitude of the wavemaker), may increase by order of magnitude as compared to low-aspect-ratio system.
It was shown previously, that in the case of aspect ratio close to unity, the transition to wave turbulence regime is associated with a cascade of triadic wave-wave interactions. Now it is shown that for large aspect ratios the energy cascade in the system is due to generation of superharmonic waves corresponding to integer (including zero) multiples of the forcing frequency. As forcing amplitude increases beyond certain value, an abrupt change is observed in behavior of relative mean kinetic energy and spectra, accompanied with appearance of additional harmonic components corresponding to half-integer (including 1/2) and integer multiples of the forcing frequency.  

 
Gaussian Process emulation of multi-model ice sheet and glacier projections
Authors: Edwards Tamsin ,   ISMIP6 and GlacierMIP projects and friends
Published: March 2021

The land ice contribution to global mean sea level rise has not yet been predicted with ice sheet and glacier models for the latest set of socio-economic scenarios (SSPs), nor with coordinated exploration of uncertainties arising from the various computer models involved. Two recent international projects (ISMIP6 and GlacierMIP) generated a large suite of projections using multiple models, but mostly used previous generation scenarios and climate models, and could not fully explore known uncertainties.

Here we estimate probability distributions for these projections for the SSPs using Gaussian Process emulation of the ice sheet and glacier model ensembles. We model the sea level contribution as a function of global mean surface air temperature forcing and (for the ice sheets) model parameters, with the 'nugget' allowing for multi-model structural uncertainty. Approximate independence of ice sheet and glacier models is assumed, because a given model responds very differently under different setups (such as initialisation).

We find that limiting global warming to 1.5°C would halve the land ice contribution to 21st century sea level rise, relative to current emissions pledges: the median decreases from 25 to 13 cm sea level equivalent (SLE) by 2100. However, the Antarctic contribution does not show a clear response to emissions scenario, due to competing processes of increasing ice loss and snowfall accumulation in a warming climate.

However, under risk-averse (pessimistic) assumptions for climate and Antarctic ice sheet model selection and ice sheet model parameter values, Antarctic ice loss could be five times higher, increasing the median land ice contribution to 42 cm SLE under current policies and pledges, with the 95th percentile exceeding half a metre even under 1.5°C warming.

Gaussian Process emulation can therefore be a powerful tool for estimating probability density functions from multi-model ensembles and testing the sensitivity of the results to assumptions.
Application of SpectralWeather to prediction of flood and extreme rain events in the Maritime Continent
Authors: Latos Beata , Lefort Thierry , Flatau Maria K. , Flatau Piotr J. , Baranowski Dariusz B. , Szkółka Wojciech , Peyrillé Philippe
Published: March 2021

Monitoring of equatorial wave activity and understanding their nature is of high priority for scientists, weather forecasters and policy makers because these waves and their interactions can serve as precursors for weather-driven natural hazards, such as extreme rain and flood events. We studied such precursors of the January 2019 heavy rain and deadly flood in the central Maritime Continent region of southwest Sulawesi, Indonesia. It is shown that a convectively coupled Kelvin wave (CCKW) and a convectively coupled equatorial Rossby wave (CCERW) embedded within the larger-scale envelope of the Madden-Julian Oscillation (MJO), contributed to the onset of a mesoscale convective system. The latest developed over the Java Sea and propagated onshore, resulting in extreme rain and devastating flood. 

For the analysis of the January 2019 flood, we explored large datasets and detected interesting features to find multivariate relationships through visualization. We used SpectralWeather – a new tool supporting tropical weather training, research and forecasting, easily accessible at https://www.spectralweather.com. Extending Cameron Beccario's earth.nullschool.net project, SpectralWeather focuses on spectral decomposition of meteorological and oceanic fields into equatorial waves – CCKW, MJO, CCERW and Mixed Rossby-Gravity waves. SpectralWeather uses ECMWF ERA5 reanalysis at several levels, NASA GPM rainfall datasets, OMI OLR index, NEMO SST, AVISO sea surface height, and OSCAR currents.

This new visualization tool can help to quantify and understand factors triggering natural hazards in the global tropics. We will discuss its interface and available features, based on the example of the January 2019 Sulawesi flood and other flood and extreme rain events in the Maritime Continent.   
Integration of multiple observed and model-derived hydrological variables in landslide initiation threshold models in Rwanda 
Authors: Uwihirwe Judith , Hrachowitz Markus , Bogaard Thom
Published: March 2021

This study was conducted using data collected from 3 catchments in North-Western region of Rwanda; Kivu, upper Nyabarongo and Mukungwa. We used two parsimonious  models, a transfer function noise time series model and a linear reservoir conceptual model, to simulate groundwater levels using rainfall and potential evapotranspiration as model inputs. The transfer function noise model was identified as the model with great explanatory predictive power to simulate groundwater levels as compared to the linear reservoir model. Hereafter, the modelled groundwater levels were used together with precipitation to explain the landslide occurrence in the studied catchments. These variables were categorized into landslide predisposing conditions which include the standardized groundwater level on the landslide day ht and prior to landslide triggering event ht-1 and landslide triggering conditions which include the rainfall event, event intensity and duration.  Receiver operating characteristics curve and area under the curve metrics were used to test the discriminatory power of each landslide explanatory variable. The maximum true skill statistics and the minimum radial distance were used to highlight the most informative hydrological and meteorological threshold levels above which landslide are high likely to occur in each catchment. We will discuss our results of incorporation of groundwater information in the landslide predictions and compare these results with landslide prediction capacity which solely use of precipitation thresholds.Here we focus on at the same time on the practicalities of data availability for day-to-day landslide hazard management, both in terms of missed and false alarms
Visual representation of CORDEX climate data by using QGIS
Authors: Yessimkhanova Kalamkas , Gede Mátyás
Published: March 2021

The majority of studies are dedicated to the analysis of climate change and climate models with no regard for data visualization part. Therefore, this research is aimed at highlighting challenges, with an emphasis on spatial referencing that can occur while visualizing CORDEX data. CORDEX data are stored in NetCDF file format, and sometimes georeferencing may be misconceived in QGIS software. For this reason, two techniques of georeferencing data are examined in this work. The first way of data georeferencing is re-projecting coordinates from original projection to an interpolated latitude/longitude grid. The second way is re-encrypting initial data file so that QGIS is able to interpret projection information. Preference of using QGIS explained by two reasons: it is open source GIS application and it has expanded visualization toolkit.

In addition, there are a great deal of climate models based on CORDEX data for some regions whereas there is a lack of climate projections for particular areas. In this regard, carrying out analysis for the region of Kazakhstan is beneficial. Outcomes of this research may stimulate spreading local climate models for Kazakhstan territory. Results are represented in the form of maps of Kazakhstan illustrating temperature change over 21st century time period.