bluuebunny/crossref_metadata_2025 huggingface dataset:
Forecasting UK site level air quality with a Kalman filtering approach
Authors: Duncan Rachael , Young Paul , Nemeth Chris
Published: March 2021

Despite efforts to reduce pollutant emissions in the UK, between 28,000 and 36,000 deaths a year are attributable to poor air quality and ambient air pollution is considered the UK’s biggest environmental threat to health. Characterising, quantifying and understanding air quality variability and the importance of different drivers is essential to guide policies to address the issue and its risks, for both the short and long term. Here we investigate a statistical modelling approach to characterise air quality variability and its key drivers, using Kalman filters. Kalman filters are a commonly used tool in air quality modelling but are seldom used in a statistic framework that accounts for uncertainty in a principled way. Kalman filtering allows us to take data which is noisy or partially recorded, such as air quality data, and help reveal the true underlying trends and dynamics of the data. This allows us to combine measurement information with the statistical model to obtain an air quality forecast, using the measurement information to reduce the statistical model errors and improve model results. We explore this approach using air quality monitoring data from the UK Automatic Urban and Rural Network (AURN), which consists of 150 sites focussed mainly in populated areas, leaving large areas unmonitored. AURN is primarily used for compliance reporting against national and European air quality standards and targets. Eventually, our aim is to provide short-term forecasts of pollutant levels from AURN, comparing this against process model forecasts and ultimately providing an optimised combination of process model, statistical model and measurement.   
Investigation of Land Subsidence in Eastern Thrace (Turkey) using Multi Temporal InSAR
Authors: Nozadkhalil Tohid , Ergintav Semih , Cakir Ziyadin , Dogan Ugur , R. Walter Thomas
Published: March 2021

Westward migration of M>7 earthquakes along North Anatolian fault with the latest one, Izmit 1999 event, led focus of studies to the seismic gap in the main Marmara fault. For this purpose, the coastal ranges of the Marmara Sea, mainly Istanbul megacity, are renowned for earthquake and ground motion hazards, associated with faulting, landslides and sediment compaction processes. Ground motion associated with man-made activities, however, have been barely studied. The Thrace region of Turkey, some 50 km to the North of the Marmara Sea, expresses pronounced ground motions affecting large areas. We use the Persistent InSAR technique to monitor the Marmara region using Sentinel-1 satellites’ TOPSAR data between 2014 and 2020. Results for both ascending (T131 and T58) and descending (T36) tracks reveals 10 mm/yr rate of subsidence in the Thrace region of Turkey, affecting an area ~15400km² with dimensions of ~110 km by ~140 km. There are two plausible mechanisms for this deformation; (1) excessive pumping of groundwater for agricultural purposes, or (2) natural gas extraction activities taking place in the region. To better understand the observed deformation source, as a first step, we model potential gas extraction by volume change. No piezometric data are available for this region for the time being. Thick sediments including sandstone, reefal carbonates, amongst others, are aimed for gas exploration in the Thrace basin for more than half century. Depth of gas extraction wells and sediment thickness is compiled from previous studies to compare the subsided area with sediment and well depth variations. 

We use  the Poly3D boundary element method to model the surface. Poly3D uses planar triangular elements of constant model to model displacement’s source. Using triangular elements provides models with complex and smooth 3D surfaces avoiding overlaps or gaps, and hence allowing one to construct realistic models. Poly3dinv inverse model applies a fast non-negative/non-positive least squares solver to optimize the solution. We construct a surface enveloping tips of the wells and use it to produce deformation at surface due by allowing opening on it. Small residuals between the observation and model based on opening suggests that deformation is likely caused by natural gas extraction.
Prediction of near-surface temperatures using a non-linear machine learning post-processing model
Authors: Alerskans Emy , Nyborg Joachim , Birk Morten , Kaas Eigil
Published: March 2021

Numerical weather prediction (NWP) models are known to exhibit systematic errors, especially for near-surface variables such as air temperature. This is partly due to deficiencies in the physical formulation of the model dynamics and the inability of these models to successfully handle sub-grid phenomena. Forecasts that better match the locally observed weather can be obtained by post-processing NWP model output using local meteorological observations. Here, we have implemented a non-linear post-processing model based on machine learning techniques with the aim of post-processing near-surface air temperature forecasts from a global coarse-resolution model in order to produce localized forecasts. The model is trained on observational from a network of private weather stations and forecast data from the global coarse-resolution NWP model. Independent data is used to assess the performance of the model and the results are compared with the performance of the raw NWP model output. Overall, the non-linear machine learning post-processing method reduces the bias and the standard deviation compared to the raw NWP forecast and produces a forecast that better match the locally observed weather.
Options and extensions for the stochastic shallow convection scheme in ICON
Authors: Ahlgrimm Maike , Klocke Daniel , de Lozar Alberto , Machulskaya Ekaterina , Sakradzija Mirjana , Seifert Axel
Published: March 2021

The Icosahedral Model (ICON) of the German Weather Service (Deutscher Wetterdienst, DWD) is used for numerical weather prediction at global and regional scales. In the limited area mode, resolution is typically on the order of a few kilometers horizontal grid spacing. Deep convective transport is partially resolved at these scales, but shallow convection remains poorly represented without a parameterization.

A stochastic shallow convection scheme was developed in collaboration with the Max Planck Institute for Meteorology, and is now being implemented in ICON with a view towards operational use. The scheme is scale-adaptive and renders resolution-dependent tuning of the convection parameterization unnecessary. Mass flux limiters essential for the stable operation of the unaltered convection scheme can be removed when the stochastic perturbations are introduced.

Alongside the original, explicit stochastic scheme an approximation using stochastic differential equations (SDE) has been developed. The advantage of the SDE version is a lower computational and memory cost, and the ability to save and restart the model‘s stochastic cloud state easily.

Equivalence of the two versions can be demonstrated by running one version interactively, the other passively (“piggy-backing”). While the SDE approximation is computationally more efficient, the explicit version of the scheme can be easily extended to keep track of additional properties of the shallow cloud ensemble. For example, the convective updraft core fraction can be calculated for use in the diagnostic subgrid cloud scheme. Or knowledge of individual clouds’ depth can be used to derive a more realistic lateral detrainment profile than is currently in use.

We demonstrate the performance of the scheme and illustrate options and applications in single column mode, case studies and month-long hindcasts.
Observations of California forest fire aerosol in Potenza (Italy) by the multi-wavelength Raman lidar MUSA
Authors: De Rosa Benedetto , Mona Lucia , Amodeo Aldo , Summa Donato
Published: March 2021

Smoke aerosols play an important role in the atmospheric chemistry in terms of direct and indirect radiative forcing. Despite this, their properties in free troposphere and stratosphere are still insufficiently studied. When the smoke reaches these altitudes can be transported over transcontinental distances. During the transport of particles important transforming processes, such as coagulation, condensation, and gas-to-particle conversion occur, thus affecting environment and climate. The optical properties of smoke plumes have been usually analyzed by ground-based radiometers and satellite. However, these techniques cannot characterize accurately the high variability of the vertical structure of smoke aerosol. Raman lidar systems  are characterized by high temporal and vertical resolutions and have demonstrated a strong capability to study long-range transport, optical properties and vertical structure of forest fire smoke. 

In the 2020 California’s fire season was exceptionally catastrophic. 23rd October, the immense Sonoma fire, in few days scorched 31000 hectares. The deep convection lifted the smoke from these fires to great heights. After reaching the free troposphere and stratosphere, the forest fire smoke was transported over great distances and reached the south of Italy, as evinced by the map of biomass burning aerosol optical depth at 550 nm, provided by the Copernicus Atmosphere Monitoring Service (CAMS).

This work reports measurements carried out in the frame of the project CAMS21b by the Raman lidar system MUSA deployed at CNR-IMAA Atmospheric Observatory (CIAO) in Potenza. CAMS21b aims to design, test and set up the provisioning to CAMS of ACTRIS/EARLINET products in real time and near real time. 

In the case study of 26 October 2020, from to 10:13 to 13:45 UTC, measurements of particle backscattering coefficient at 355, 532 nm and 1064 and of the particle extinction coefficient at 355 nm and 532nm, show the presence of two distinct aerosol layers. A lower one extending from 6 km to 8 km and an upper one extending from 10 km to 12 km. The back-trajectory analysis reveals that the air masses originated over California, overpassed the Atlantic sea before reaching the measurement site.

The values of the particle depolarization ratio are similar to those found in literature for smoke aerosols. In the first layer, values lower than 0.05 are indicative for small and spherical smoke particles. The moderately increased depolarization ratios in the second layer indicate the possible presence of partly coated smoke particles.

More results from this measurement effort will be reported and discussed at the Conference.
Dynamics of upper and lower mantle subduction and its effects on the amplitude and pattern of mantle convection.
Authors: van der Wiel Erik , Thieulot Cedric , Spakman Wim , van Hinsbergen Douwe
Published: March 2021

Long-lived, Mesozoic-Cenozoic subduction zones such as the Pacific slab under the Americas and the Tethyan slab under Eurasia consumed thousands of kms of lithosphere of which remnants are detected in today’s mantle by seismic tomography. Major differences, however, in subduction zone evolution occurred between these systems which include strong variations in subduction rate, slab morphological evolution, and trench motion, which all appear mostly to be accommodated in the upper 1000 km of the mantle (van der Meer et al. 2018). Furthermore, sinking rates of slabs below this zone tend to be similar for different subduction systems and an order of magnitude smaller than their plate/subduction velocities. Working from the premise that the mantle rheology that accommodated these subduction systems is basically similar, although still poorly constrained, we test the hypothesis that the contrasting evolution of these subduction systems is primarily tied in with the global plate tectonic forcing of subduction.

It is generally accepted that plate motion is primarily driven by slab pull with contributions from ridge push, rather than the drag of the underlying mantle. If correct, numerical subduction models should be able to obtain upper as well as lower mantle subduction velocities and sinking rates similar to those reconstructed from geological records. We are at the start of this investigation and will present the numerical model setup, modeling strategy, and preliminary results of a 2-D subduction modelling experiment. We implement a 2D-cylindrical model setup for solving the conservation of momentum, mass and energy with the open-source geodynamics code ASPECT (Kronbichler et al. 2012) using a nonlinear visco-plastic rheology and including the major phase changes. Our focus is on the possible role of the absolute motion of the subducting and overriding plates in concert with slab pull variation reconstructed from plate tectonic evolution models, while in both subduction cases the same (partly nonlinear) mantle rheological processes are required to accommodate slab morphology change and slab sinking. Kinematic modelling constraints are derived from global plate tectonic evolution models, while the tomographically inferred present-day stage provides the end-stage geometry of slabs.

van der Meer, D. G., Van Hinsbergen, D. J., & Spakman, W. (2018). Atlas of the underworld: Slab remnants in the mantle, their sinking history, and a new outlook on lower mantle viscosity. Tectonophysics, 723, 309-448.

Kronbichler, M., Heister, T., & Bangerth, W. (2012). High accuracy mantle convection simulation through modern numerical methods. Geophysical Journal International, 191(1), 12-29.
Identifying dominant drivers of northern European wildfires
Authors: Bakke Sigrid Joergensen , Wanders Niko , van der Wiel Karin , Ionita Monica , Tallaksen Lena Merete
Published: March 2021

Wildfires are recurrent natural hazards that affect terrestrial ecosystems, the carbon cycle, climate and society. An ignition can lead to a wildfire when there is biomass available for burning, typically in combination with dry and windy conditions. Wildfires are regarded as compound events defined as “an extreme impact that depends on multiple statistically dependent variables or events” [1], and dominant drivers include a combination of various meteorological, hydrological and biological conditions. More specifically, wildfires can be regarded preconditioned hazards [2] because the combination of drivers can cause the hazard only in the presence of available and burnable biomass (precondition). The availability of burnable biomass is itself driven by conditions such as soil moisture, temperature, humidity, precipitation, etc. Identifying a selection of dominant controls and their statistical dependence, can ultimately improve predictions and projections of wildfires in both current and future climate. In this study, we apply a data-driven bottom-up statistical learning approach (including random forest and logistic regression) to identify dominant factors determining burned area over northern Europe. Potential explanatory variables include temperature, precipitation, wind, soil moisture and vegetation cover, as well as meteorological drought, soil moisture drought and greenness indices. A monthly 2001-2020 burned area product derived from satellite observations is used as target variable, and multiple hydrometeorological and vegetation metrics stemming from the ERA5 reanalysis and observational datasets (e.g. EOBS) are tested as potential predictors. The derived relationships between wildfires and its compound drivers will further be used to assess the potential changes in such a combination of factors under different climate scenarios using large-ensemble global climate simulations and hydrological models. This new framework will allow us to better quantify the changes in potential wildfire risk in a changing climate using a combination of data driven and physically based models.

[1] Leonard et al., 2014: https://doi.org/10.1002/wcc.252
[2] Zscheischler et al., 2020: https://doi.org/10.1038/s43017-020-0060-z
Colloidal Transport of Heavy Metals in Natural Subsurface Sediments
Authors: Sengor Sema Sevinc
Published: March 2021

Colloid particles are widely distributed in the environment. These colloids have recently been gaining significant attention due to their unique characteristics in environmental remediation pertaining to degradation, transformation and immobilization of contaminants in soils and aquifers. On the other hand, once mobilized by subsurface water flow, colloids may pose risks to surface water and groundwater quality as they are effective ‘‘carriers’’ of a variety of common contaminants found in water and soils. Therefore, understanding the transport mechanisms of the colloids and incorporation of colloidal transport processes in reactive transport models are crucial for successful applications of many remediation efforts in the subsurface. Fe (hydr)oxide colloidal compounds have large surface areas and high reactivity, which can lead to spontaneous adsorption of many pollutants. For the successful stabilization of pollutants, it is vital to understand the associated biogeochemical processes, and competitive effects of contaminant sorption onto these colloidal phases. This work focuses on the development of a mechanistic Fe(hydr)oxide based colloid-facilitated reactive transport model which identifies the impact of Fe(hydr)oxide colloids on the stability and mobility of heavy metals (Zn and Pb) in example subsurface sediments of Lake Coeur d’Alene (LCdA), USA. Key reactions include the mobilization of heavy metals initially sorbed onto the colloidal Fe(hydr)oxide minerals through microbial reductive dissolution. Precipitation of metal sulfides at depth as a result of biogenic sulfide production is also captured. The simulations compare the biogeochemical cycling of metals considering colloidal vs. immobile phases of Fe(hydr)oxide minerals in the lake sediments.
Balloon-borne GLORIA hyperspectral Limb and Nadir imager in the LWIR
Authors: Kretschmer Erik , Friedl-Vallon Felix , Gulde Thomas , Höpfner Michael , Johansson Sören , Kleinert Anne , Maucher Guido , Neubert Tom , Nordmeyer Hans , Piesch Christof , Preusse Peter , Riese Martin , Schardt Georg , Schönfeld Axel , Ungermann Jörn , Wetzel Gerald
Published: March 2021

The GLORIA-B (Gimballed Limb Observer for Radiance Imaging of the Atmosphere - Balloon) instrument is an adaptation of the very successful GLORIA-AB imaging Fourier transform spectrometer (iFTS) flown on the research aircrafts HALO and M55 Geophysica. The high spectral resolution in the LWIR (Long Wave Infrared) allows for the retrieval of temperature and of a broad range of atmospheric trace gases, with the goal to retrieve O3, H2O, HNO3, C2H6, C2H2, HCOOH, CCl4, PAN, ClONO2, CFC-11, CFC-12, SF6, OCS, NH3, HCN, BrONO2, HO2NO2, N2O5 and NO2. The radiometric sensitivity of the Balloon instrument is further increased in comparison with the GLORIA-AB instrument by having two detector channels on the same focal plane array, while keeping the same concept of a cooled optical system. This system improvement was achieved with minimal adaptation of the existing optical system.

The high spatial and temporal resolution of the instrument is ensured by the imaging capability of the Fourier transform spectrometer while stabilizing the line-of-sight in elevation with the instrument and in azimuth with the balloon gondola. In a single measurement lasting 13 seconds, the atmosphere can be sounded from mid-troposphere up to flight altitude, typically 30 km, with a vertical resolution always better than 1 km for most retrieved species; a spatial resolution up to 0.3 km can be achieved in favourable conditions. Temperature retrieval precision between 0.1 and 0.2 K is expected. A spectral sampling up to 0.0625 cm-1 can be achieved.

The first flight of GLORIA-B shall take place during the late-summer polar jet turn-around at Kiruna/ESRANGE. This flight is organised in the frame of the HEMERA project and was scheduled for summer 2020, but was ultimately postponed to summer 2021. Beyond qualification of the first balloon-borne iFTS, the scientific goals of the flight are, among others, the quantification of the stratospheric bromine budget and its diurnal evolution by measuring vertical profiles of BrONO2 in combination with BrO observations by the DOAS instrument of University Heidelberg on the same platform.
Seafloor sediment classification of the Sylt Outer Reef, German Bight from 2016 -2018 using ensemble modelling 
Authors: Galvez Daphnie , Papenmeier Svenja , Bartholomä Alexander , Wiltshire Karen Helen
Published: March 2021

Recent studies on seafloor mapping have presented different modelling methods to map and classify marine sediment distribution. However, are these methods classify different sediment classes the same way? And how do we choose the right model for a certain set of sediment classes? In this study, we aim to address these issues by using ensemble modelling to map the distribution of different sediment class on a dynamic, shallow continental shelf. Our data were derived from side-scan mosaics and multibeam data repeatedly collected from 2016 to 2018 in the Sylt Outer Reef (German Bight). We used a probabilistic approach for each class separately and then compared the predicted probability for each class, to see which class is more likely to be assigned to the location. Each sediment class was predicted using a combination of different classification modelling techniques, and then the result of these models was ensembled to produced one final prediction. This approach avoids selecting one single method, limits model selection bias and can provide information on the trends and variation across models.  Furthermore, we also looked on the temporal changes in sediment distributions by comparing the sediment class predictions from 2016 to 2018.

Our analysis suggest that combining different modelling techniques  (i.e. random forest, boosting regression trees etc.) provide higher predictive accuracy than using one single modelling method. The resulting sediment distribution maps are more objective and are produced faster than manual delineated maps often considered by stakeholders. We also identify some limitations in having small sample size and we proposed that by combining certain models and choosing the proper amount of pseudo-absence or background data can address this issue.
Afforestation projects in Qinghai Province: what are the benefits of ecosystem services?
Authors: Hou Yanzhen , Zhao Wenwu
Published: March 2021

Qinghai is a pivotal area for protection and ecological restoration, which is a unique plateau ecosystem composed of tundra, grasslands, Gobi, and the source of rivers. In response to afforestation projects, the government has successfully implemented the Sloping Land Conversion Program (SLCP), Natural Forest Conservation Program (NFCP), and Three-North Shelter Forest Program (TNSFP), etc. However, the ecological benefits after the implementation of the restoration project lack quantitative evaluation. In this study, we extracted farmland (slope> 25°) and wasteland as appropriate afforestation areas based on the ecological niche of tree species simulated by MaxEnt. Then, ecosystem services are selected as indicators to measure the benefits of restoration, with supply services and recreation services as direct benefits, and regulating services and supporting services as indirect benefits. We compared the impact of afforestation on ecosystem services, highlighting the benefits of ecological engineering. Under the assumption that all afforestation tree species survive, the appropriate afforestation areas are 549.25hm2, mainly distributed in the northeast of Qinghai. Regulating services, supporting services and the attractiveness of recreation services have improved, while crop supply and the accessibility of recreation services have decreased. Our findings can enrich theoretical and empirical research on ecosystem services and have implications for afforestation management in similar areas.
Risk Assessment and Disaster Prevention and Mitigation Strategies for Large-Scale Sediment Disasters
Authors: Lee Shin-Ping , Tsai Yuan-Jung , Tsang Yun-Chung , Tsai Ching-Ya , Wang Shang-Ming , Fu Kui-Lin , Tsai Zheng-Xiu , Chen Wei-Di
Published: March 2021

Under climate change impact, the frequency of extreme hydrological events increases. The occurrence of extreme rainfall events may lead to large-scale flooding or sediment disasters resulting in serious property damage and casualties. Large-scale sediment disasters include large-scale landslides and debris flows which are the main types of disasters causing casualties. In Taiwan, during Typhoon Morakot in 2009, the long duration and high-intensity rainfall led to a large-scale sediment disaster resulting in heavy casualties. A disaster with certain magnitude and complexity cannot be coped with a single disaster management approach. In this study, a risk assessment method considering climate change impacts proposed by the Intergovernmental Panel on Climate Change (IPCC) was adopted. By analyzing hazard, exposure, and vulnerability indicators of large-scale sediment disasters in Xinfa catchment of Kaohsiung City, Taiwan, a disaster risk adaptation strategy was proposed based on the impact of disaster factors.

Two scenarios were applied for the catchment sediment hazards risk assessments including 50-year recurrence period (high frequency and low impact) and extreme scenario (low frequency and high impact). Multiple factors for hazard (impact area of landslides and debris flows), exposure (lifeline roads and land use intensity), and vulnerability (disaster prevention and relief resources and settlement population characteristics) assessments were considered. The correlation factor selection and weighting analysis was calibrated by the 2009 Typhoon Morakot event. All disaster-recorded locations were above moderate risk indicating that the risk assessment method was reasonable. A risk map for Xinfa catchment was completed based on the validated risk assessment model to identify the high-risk settlements. After analyzing the spatial characteristics and disaster risk impact factors of high-risk settlements, both software and hardware disaster prevention measures and adaptation strategies were suggested. According to the analyzed results, although the hardware measures were effective in reducing sediment hazards generally, under extreme hydrologic events, those measures could be ineffective due to limited protection capacity of the engineering facilities. Hence, reducing exposure and vulnerability is essential to deal with the impact of extreme events.

Keywords: Large-scale sediment disasters, Risk assessment, Adaptation strategies
Dynamical and thermodynamical drivers of variability in European summer heat extremes
Authors: Suarez-Gutierrez Laura , Li Chao , Müller Wolfgang A. , Marotzke Jochem
Published: March 2021

We use the 100-member Max Planck Institute Grand Ensemble (MPI-GE) to disentangle the contributions from colocated dynamic atmospheric conditions and local thermodynamic effects of moisture limitation as drivers of variability in European summer heat extremes. Using a novel extreme event definition, we find that heat extremes with respect to the evolving mean climate increase by 70% under a moderate warming scenario during the twenty-first century. With a multiple regression approach, we find that the dynamical mechanisms representing blocking and anticyclonic conditions are the main driver of variability in extreme European summer temperatures, both in past and future climates. By contrast, local thermodynamic drivers play a secondary role in explaining the total variability in extreme temperatures. We also find that considering both dynamical and thermodynamical sources of variability simultaneously is crucial. Assessing only one type of drivers leads to an overestimation of their effect on extreme temperatures, particularly when considering only thermodynamical drivers. Lastly, we find that although most past and future heat extremes occur under favorable dynamical atmospheric conditions; this occurs 10–40% less frequently over Central Europe in the twenty-first century. By contrast, heat extremes over Central Europe occur 40% more frequently under concurrent extreme moisture limitation in the twenty-first Century. Our findings highlight a new type of neutral-atmosphere, dryness-driven heat extremes, and confirm that the increase in European heat extremes and associated variability increase are dominated by the local thermodynamic effect of moisture limitation.
Electron beaming instabilities as sources of CME radio emissions
Authors: Lazar Marian , Lopez Rodrigo , Shaaaban Shaaban Mohammed , Poedts Stefaan , Fichtner Horst
Published: March 2021

Radio emissions accompanying coronal mass ejections (CMEs) from their flaring sources (type III bursts) to interplanetary shocks (type II bursts) are believed to originate in the electrostatic (ES) wave instabilities, which are excited by the electrons beaming along the intense magnetic fields. Theoretically, radio emissions of fundamental (plasma) frequency $\omega_{p}$ or the second harmonic $2 \omega_{p}$ may result from non-linear three waves interaction of electrostatic Langmuir and ion sound fluctuations. However, it is not clear yet what kind of electron beams and specific CME plasma conditions can determine destabilization of Langmuir waves (ion sound waves may result from non-linear decay). Recent attempts to identify and characterize these unstable regimes suggest very critical and limited conditions for Langmuir instabilities to develop, which may undermine our current understanding of their implication in nonlinear generation of radio waves. Thus, even for a dominance of ES instabilities, conditioned by high beaming velocities, Langmuir waves appear to be in close competition with other ES growing modes (such as electron acoustic instabilities), while for less energetic beams the theory predicts a strong interplay with instabilities of different nature (electromagnetic or hybrid, and propagating obliquely to the magnetic field). 
Machine Learning Prediction of Precipitation in Metro Manila, Philippines
Authors: Noda Akira
Published: March 2021

It is difficult to predict the occurrence and rain volume of torrential rainfalls, such as guerrilla rain, rain band with typhoon and linear precipitation zone. As heavy rain area is spatially localized and the parent thunderstorm tends to develop within a short time, it makes difficult to accurately predict the occurrence location/time and rain volume. Recently, the machine learning technique is remarkably developed with the improved processing speed of computers and with a huge amount of the data. In addition to this, the application of the machine learning methods to the meteorological fields is intensively tried in the world. Since 2017, we started installing the automatic weather observation system (AWS) named as P-POTEKA in Metro Manila, the Philippines, which is one of the cities suffering from the torrential rainfall and related flood. So far, we installed 35-P-POTEKAs in Metro Manila and continue the weather observations (rain volume, temperature, air pressure, humidity, wind speed, wind direction and solar radiation) with the time resolution of 1 min. In this study, we used both P-POTEKA rain volume data and machine learning model (ConvLSTM: Convolutional Long-Short Term Memory) in order to predict the near future (< 1hour) rain volume and distribution. At the presentation, we will show the results derived from the machine learning prediction of the rain volume and distribution more in detail.
Gravity gliding and spreading in a compressional setting: the example of the Algerian margin
Authors: Travan Gaia , Gaullier Virginie , Vendeville Bruno , Déverchère Jacques , Raad Fadl , Lofi Johanna
Published: March 2021

The Algerian margin, located in the Western Mediterranean basin, is reactivated in compression since 8 My due to the convergence between Africa and Eurasia, and is nowadays subjected to a N45W compression of several mm/y (Jolivet et al., 1995; Noquet et Calais, 2004). While the reactivation is attested by GPS measurements and destructive seismic events, such as the earthquake of Boumerdes in 2003 (M 6.8), the visualization in the seismic data of the deep structures is made difficult by the presence of a thick Messinian salt layer. The seismic reflection profiles acquired on the Algerian margin during the “Maradja I” oceanographic survey (2003) highlighted the presence of north-verging thrusts offshore Algiers (Déverchère et al., 2005; Domzig et al., 2006), as well as the peculiar geometry of the Messinian salt layer (Lofi et al., 2011, Obone Zue Obame, 2011).

Between 2 and 4° East, the margin presents particularly complex salt structures, partly associated to the uplift of the plateau as a consequence of the crustal convergence (Déverchère et al., 2005; Domzig et al., 2006). One of the consequences of the uplift of the plateau is the dipping of the base salt horizon towards W to NNW. Moreover, from the analysis of the seismic reflection profiles, the presence of early (syn-UU) salt movement in the profiles parallel to the margin is clear, while the profiles perpendicular to the margin show compressional features mostly active during the Pliocene to Quaternary period.

From the observation of the natural example, and from the comparison with different analogue models, we conclude that offshore Algiers we find the major salt structures and minibasins formed through salt spreading, while the area offshore Boumerdès is characterized by gravity gliding due to the uplifted plateau. Although from this point of view the N-S compressional tectonics favors gravity gliding through the plateau uplift, on the other hand it influences the salt structure development direction, which present a mainly E-W development and a minor and delayed N-S one. A partial influence of the sedimentary body from Algerian rivers on the position of the major salt structures is inferred.
Towards improving the Pareto frontier in environmental models using multi-dataset calibrations coupled with metaheuristic methods
Authors: Finger David C. , Sikorska-Senoner Anna  E.
Published: March 2021

Environmental models, such as hydrological models or water quality models, are incorporate numerical algorithms that describe either empirically or physical-based the large variety of natural processes that govern the flow of water (or other variables) and its components. The purposes of these models range from improving our understanding of the principles of hydrological processes at a catchment scale to making predictions about how anthropogenic activities will influence future water resources. To be applicable, these models require calibration with observed output data, which is most often streamflow for hydrological models. Yet, the complex nature of hydrological processes, on the one hand, and the limited observed data to inform model parameters, on the other hand, evoke the unavoidable equifinality issue in the calibration of these models. This equifinality issue is expressed with the presence of several optimal model parameters that have different values but lead to similar model performance. One way of dealing with this issue is through providing a parameter ensemble with optimal solutions instead of a single parameter set, reported often as parametric model uncertainty.

However, this equifinality issue is far from being solved, as also highlighted by one of 23 Unsolved Problems in Hydrology (UPH). This is particularly the case if more variables than only streamflow are of interest. Our hypothesis is that using more than one dataset for calibrating any environmental model helps reducing the equifinality issue during model calibration and thus improves the identifiability of model parameters. In this review-based study, we present recent examples of hydrological (and water quality) models from literature that have been calibrated within a multiple dataset framework to reduce the equifinality issue. We demonstrate that a multi-dataset calibration yields a better model performance regardless of the complexity of the model. Finally, we show that coupling a multi-dataset model calibration with metaheuristics (such as Monte Carlo or Genetic Algorithm) can help reducing the equifinality of model parameters and improving the Pareto frontier. At the bottom of this study, we outline how such a multi-dataset calibration can lead to better model predictions and how it can help emerging water resources problems due to an emerging climate crisis.

This work contributes to one of the seven major themes of 23 UPH, i.e., Modelling methods. It paths a way forward towards reducing parameter uncertainty in hydrological predictions (UPH question #20) and thus towards improving modelling of hydrologic responses in the extrapolation phase, i.e., under changed catchment conditions (UPH question #19).
Trend in precipitation and drought extremes in southern lowland regions of Europe
Authors: Berényi Alexandra , Pongrácz Rita , Bartholy Judit
Published: March 2021

The effects of climate change on precipitation patterns can be observed on global scale, however, global climate change affects different regions more or less severely. Because of the high variability of precipitation in particular, future changes related to precipitation can be very different, even opposite on continental/regional scale. Even within Europe, the detected trends in precipitation patterns and extremes differ across the continent. According to climate model simulations for the future, Northern Europe is projected to become wetter, while the southern parts of the continent will tend to become drier by the end of the 21st century. The frequency and intensity of extreme precipitation will also increase in the whole continent. The possible shifts in precipitation patterns from wetter to drier conditions with fewer but increased extreme precipitation events can cause severe natural hazards, such as extended drought periods, water scarcity, floods and flash floods, therefore appropriate risk management is essential. For this purpose the analysis of possible hazards associated to specific precipitation-related weather phenomena is necessary and serves as key input.

Since plain regions play an important role in agricultural economy and are more exposed to floods because of their geographic features and the gravitational movement of surface water, our primary goal was to examine temporal and spatial changes in extreme precipitation events and dry spells in three European lowlands, located in the southern part of the continent. We selected the following regions: the Po-Valley located in Italy with humid subtropical climate; the Romanian Plain in Romania, and the Pannonian Plain covering different parts of Hungary, Serbia, Slovakia, Croatia, Romania and Ukraine with humid continental climatic conditions.

Precipitation time series were used from the E-OBS v.22 dataset on a 0.1° regular grid. The dataset is based on station measurements from Europe and are available from 1950 onward with daily temporal resolution. For the analysis of main precipitation patterns, dry spells and extreme events, we use 17 climate indices (most of them are defined by the Expert Team on Climate Change Detection and Indices, ECCDI). The analysis focuses on annual and seasonal changes in the three regions. The selected indices are capable to represent the differences and similarities between and within the plains. Our preliminary results show that the occurrence and intensity of extreme precipitation events increased in all regions, while the trends of duration and frequency of dry spells show both intra- and inter regional variability across the plains.
Toward a full 4D seismic tomography: a case study of an active mine
Authors: Piana Agostinetti Nicola , Dahnér-Lindkvist Christina , Dineva Savka
Published: March 2021

Rock elasticity in the subsurface can change in response to natural phenomena (e.g. massive precipitation, magmatic processes) and human activities (e.g. water injection in geothermal wells, ore-body exploitation). However, understanding and monitoring the evolution of physical properties of the crust is a challenging due to the limited possibility of reaching such depths and making direct measurements of the state of the rocks. Indirect measurements, like seismic tomography, can give some insights, but are generally biased by the un-even distribution (in space and time) of the information collected from seismic observations (travel-times and/or waveforms). Here we apply a Bayesian approach to overcome such limitations, so that data uncertainties and data distribution are fully accounted in the reconstruction of the posterior probability distribution of the rock elasticity  We compute a full 4D local earthquake tomography based on trans-dimensional Markov chain Monte Carlo sampling of 4D elastic models, where the resolution in space and time is fully data-driven. To test our workflow, we make use of a “controlled laboratory”: we record seismic data during one month of mining activities across a 800x700x600 m volume of Kiruna mine (LKAB, Sweden). During such period, we obtain about 260 000 P-wave and 240 000 S-wave travel-times coming from about 36000  seismic events. We operate a preliminary selection of the well-located events, using a Monte Carlo search. Arrival-times of about 19 000 best-located events (location errors less than 20m) are used as input to the tomography workflow. Preliminary results indicate that: (1) short-term (few hours) evolutions of the elastic field are mainly driven by seismic activation, i.e. the occurrence of a seismic swarm, close to the mine ore-passes. Such phenomena partially mask the effects of explosions; (2) long-term (2-3 days) evolutions of the elastic field closely match the local measurements of the stress field at a colocated stress cell. 
Riparian zone hydrological rehabilitation along the Gyöngyös stream (Hungary)
Authors: Szőke Előd , Csáki Péter , Kutschi Péter , Kalicz Péter , Gribovszki Zoltán
Published: March 2021

Climate change induced drought periods are likely to cause decline in groundwater level,
which can degrade riparian ecosystems (such as riparian forest). With a reasonable water
supply, water scarcity can be stopped and these valuable ecosystems can be preserved.

The aim of the research was to evaluate the impact of water supply interventions regarding
habitat reconstruction of Doroszló meadows near Kőszeg (west Hungary). Groundwater
monitoring wells have been installed at 4 representative sites of the area. Groundwater wells
were 3–5 m deep and screened at their bottoms (2–4 m). The water level of the wells was
recorded manually, on a weekly basis, with an accuracy of 1 mm. In the neighborhood of the
wells surface close soil moisture values were also measured. Data from April 2019 to
October 2020 were collected. Local meteorological data measured in Kőszeg were also
used for analysis.

Evaluating the data from each well in the pre-intervention period (the analysis of the
relationship of the wells with the control well), we came to the conclusion that the Well-1 and
Well-2 behave similarly. The impacts of the water supply on the groundwater level were
analysed using a “double mass curve” and a “treatment-control space-time deviations”
approach. Result showed that the intervention had a positive effect only on the Well-3 from
the examined wells. The data evaluation denoted that unfortunately the control well was also
affected by water supply interventions.

This research has been supported by the Ministry of Agriculture in Hungary.
Freshwater export from the south-east Greenland shelf into the Irminger Sea and relation to wind events
Authors: Duyck Elodie , De Jong Femke
Published: March 2021

Greenland Ice Sheet melt and freshening of the Arctic Ocean lead to increased discharge of freshwater into the East Greenland Current. If this additional freshwater reaches the convective regions of the Subpolar North Atlantic it could weaken deep mixing and affect the strength of the Atlantic Meridional Overturning Circulation. In particular, freshwater exported away from the South-East Greenland shelf could affect deep convection in the Irminger Sea, which has recently been shown to have a key role in the Atlantic overturning circulation. Though export of fresh shelf surface water is well observed west of Greenland, there is still little insight into surface water export from the East Greenland shelf to the Irminger Sea.

The East Greenland Current Drifter Investigation of Freshwater Transport drifter deployment conducted in August 2019 at 65°N on the eastern side of Greenland, resulted in five out of 30 drifters being exported away from the east Greenland shelf, four of which were exported at Cape Farewell. The specific wind regime at Cape Farewell is a potential driving factor for enhanced freshwater export in the area. While persistent south-eastward barrier winds push surface waters to the coast over most of the eastern shelf, Cape Farewell experiences strong eastward wind events such as tip-jets that could cause off-shelf export. Using wind data from the ERA-5 atmospheric reanalysis, we compute Ekman transport along the east Greenland shelf. We find greater probability for off-shelf Ekman transport at Cape Farewell than along the rest of the shelf, confirming that the area is the most likely to contribute to wind-driven freshwater export to the Irminger Sea. Wind and surface velocity data from a high-resolution model (2 km) are used to further investigate and quantify freshwater export at Cape Farewell and how it relates to local wind events.
Fracture detection using multi seismic attributes ant-tracking in the Rag-e-Sefid oilfield, SW Iran
Authors: Tajmir Riahi Zahra , Sarkarinejad Khalil , Faghih Ali , Soleimany Bahman , Payrovian Gholam Reza
Published: March 2021

Abstract

The detailed characterization of faults and fractures can give valuable information about the fluid flow through petroleum reservoir and directly affect the hydrocarbon exploration and production programs. In this study, large- and small-scale fractures in the Asmari horizon of the Rag-e-Sefid oilfield were characterized using seismic attribute and well data analyses. Different spatial filters including finite median hybrid (SO-FMH), dip-steered median, dip-steered diffusion, and fault enhancement filters were used on 3D seismic data to reduce noise, enhance the seismic data quality, and create a 3D seismic steering cube. In the next step, seismic attributes such as coherency, similarity, variance, spectral decomposition, dip, and curvature were applied to identify structural features. In order to check the validity of these structural features, results from seismic attributes calibrated by the interpreted fractures from image logs in the Rag-e-Safid oilfield. Then, the ant-tracking algorithm applied on the selected seismic attributes to highlight faults and fractures. These attributes combined using neural network method to create multi-seismic attributes, view different fault- or fold-sensitive seismic attributes in a single image, and facilitate the large-scale fractures extraction process. Finally, automatic fault and fracture extraction technique used to reduce human intervention, improve accuracy and efﬁciency for the large-scale fracture interpretation and extraction from edge volumes in the Asmari horizon of the Rag-e-Sefid oilfield. In addition to, small- scale fractures were characterized by the obtained information from the image logs interpretation for sixteen wells. All the detected fractures from seismic and well data have been divided into eight fracture sets based on their orientation and using the statistical analysis. The obtained results show that fractures characteristics and their origin are different in the northwestern and southeastern parts of the Rag-e-Sefid oilfield. The NW Rag-e-Sefid and Nourooz Hendijan Izeh Faults reactivation during Zagros orogeny led to create the dextral shear zone and P, R, R′, T, Y- fracture sets in the northwestern part of the Rag-e-Safid oilfield. Also, activity of the SE-Rag-e-Sefid thrust fault during Zagros orogeny caused to form fault-related fractures sets in the southeastern part of the Rag-e-Sefid field. In addition to, axial, cross axial, oblique fracture sets in the Asmari horizon of the Rag-e-Sefid oilfield were created by folding phase during Zagros orogeny. The obtained results were used to fracture modeling in the Asmari horizon of the Rag-e-Sefid oilfield.