bluuebunny/crossref_metadata_2025 huggingface dataset:
Bounding global aerosol radiative forcing of climate change
Authors: Bellouin Nicolas ,   Ringberg 2018 review team
Published: March 2020

Aerosol radiative forcing plays an important role in the attribution of past climate changes, estimates of future allowable carbon emissions, and the assessment of potential geoengineering solutions. Substantial progress made over the past 40 years in observing, understanding, and modelling aerosol processes helped quantify aerosol radiative forcing, but uncertainties remain large.

In spring 2018, under the auspices of the World Climate Research Programme's Grand Science Challenge on Clouds, Circulation and Climate Sensitivity, thirty-six experts gathered to take a fresh and comprehensive look at present understanding of aerosol radiative forcing and identify prospects for progress on some of the most pressing open questions. The outcome of that meeting is a review paper, Bellouin et al. (2019), accepted for publication in Reviews of Geophysics. This review provides a new range of aerosol radiative forcing over the industrial era based on multiple, traceable and arguable lines of evidence, including modelling approaches, theoretical considerations, and observations. A substantial achievement is to focus on lines of evidence rather than a survey of past results or expert judgement, and to make the open questions much more specific.

This talk will present the key messages and arguments of the review and identify work that show promise for improving the quantification of aerosol radiative forcing.
Soil Moisture Network Design using Advanced Numerical Weather Prediction modelling and Data Mining technology for Hydrological applications
Authors: Zhuo Lu , Dai Qiang , Han Dawei
Published: March 2020

Soil moisture plays an important role in the partitioning of rainfall into evapotranspiration, infiltration and runoff, hence a vital state variable in the hydrological modelling. However, due to the heterogeneity of soil moisture in space most existing in-situ observation networks rarely provide sufficient coverage to capture the catchment-scale soil moisture variations. Clearly, there is a need to develop a systematic approach for soil moisture network design, so that with the minimal number of sensors the catchment spatial soil moisture information could be captured accurately. In this study, a simple and low-data requirement method is proposed. It is based on the Principal Component Analysis (PCA) and Elbow curve for the determination of the optimal number of soil moisture sensors; and K-means Cluster Analysis (CA) and a selection of statistical criteria for the identification of the sensor placements. Furthermore, the long-term (10-year) soil moisture datasets estimated through the advanced Weather Research and Forecasting (WRF) model are used as the network design inputs. In the case of the Emilia Romagna catchment, the results show the proposed network is very efficient in estimating the catchment-scale soil moisture (i.e., with NSE and r at 0.995 and 0.999, respectively for the areal mean estimation; and 0.973 and 0.990, respectively for the areal standard deviation estimation). To retain 90% variance, a total of 50 sensors in a 22,124 km2 catchment is needed, which in comparison with the original number of WRF grids (828 grids), the designed network requires significantly fewer sensors. However, refinements and investigations are needed to further improve the design scheme which are also discussed in the paper.
Wind-Blown Sand Streamers and Turbulent Flow Structures
Authors: Baas Andreas
Published: March 2020

This contribution presents results of field measurements of wind-blown sand streamers and turbulent flow structures in the boundary layer airflow during gale-force winds on a beach. Sand transport and streamers were measured using Large-Scale Particle Image Velocimetry (LSPIV) combined with laser particle sensors (Wenglors), and airflow turbulence was monitored with a co-located sonic anemometer. The data analysis yields insight into the precise spatio-temporal relationships between sand streamers and near-surface airflow turbulence, at a high resolution of 25 Hz and a centimetre scale, including how high-energy sweeps correlate with the passage of fast-moving saltation clusters, and how Turbulent Kinetic Energy (TKE) may be linked to sediment mass flux.

 
Numerical Modelling of Gravel Transport during Flushing Processes in an Alpine Reservoir
Authors: Harb Gabriele , Schneider Josef
Published: March 2020

Sedimentation processes are in a “dynamic balance” in most natural rivers, but the construction of dams and reservoirs influences these natural conditions. The flow velocities, turbulences and bed shear stresses in reservoirs are reduced compared to free flow conditions, which lead to the deposition of the transported sediment particles. As a further consequence the sediment depositions reduce the storage volume by “filling up” the reservoir. This “reservoir sedimentation” is a problem in several Alpine reservoirs.

In the case of Alpine reservoirs with a small storage volume compared to the annual inflow, such as reservoirs of run-off river power plants, the water depth are usually lower than in reservoirs of storage and pump-storage hydro power plants. A larger part of the suspended sediments is thus transported through the reservoir and deposition of bed load fractions is the main problem. The deposition of coarse sediments at the head of the reservoir may cause problems regarding flood protection by raising the bed level and thus, raising the water level too.

 

This contribution focus on the bed load transport processes during a flushing event in an Alpine reservoir. The reservoir is approximately 1 km long with an initial storage volume of about 250.000 m3. The annual bed load input is rather high, thus the remobilization of the sediment in the reservoir in case of flood events was investigated.

An open source three-dimensional numerical model with an internal coupled hydrodynamic and morphological part was used to simulate the flushing process. The calibration of the hydrodynamic model was done using ACDP measurements performed at the prototype to calibrate the roughness at the river bed. Additionally an extensive sensitivity analysis was carried out and several sediment transport formulae were tested.
Introduction to the second Geostationary Ocean Color Imager (GOCI-II) and its ground segment
Authors: Han Hee-Jeong , Heo Jae-Moo , Yang Hyun , Choi Woo-Chang , Choi Hey-Min , Park Young-Je
Published: March 2020

As the succeeder of the Geostationay Ocean Color Imager (GOCI), the world first geostationary ocean monitoring satellite, the second GOCI (GOCI-II) will be launched in 2020. GOCI-II has 12 narrow bands of 380~865nm center wavelength for earth observation and an broadband band for star observation. The main goals of this GOCI series are to monitor ocena short-term/long-term phenomena like red-tide blooming, floating algae movements, tidal movements, low sea surface salinity variation, sea surface currents, primary productivity, etc. GOCI-II is able to obtain 10 images for the area around Korean peninsula and an image for the full-disk area in everyday during its 10 years lifetime. To handle this huge GOCI-II data, we have to develop the dedicated GOCI-II Ground Segment (G2GS) system with data acquisition antenna and GOCI-II operating infrastructure. G2GS have good performance like the data distribution output delay within 60 minutes, the 99% system operability with redundancy, etc. G2GS also generates 26 level-2 data products and provides all data with dedicated software program like GOCI-II plug-in of SNAP framework. 
Detecting Synoptic Patterns related to Freezing Rain in Montréal using Deep Learning
Authors: Mittermeier Magdalena , Bresson Émilie , Paquin Dominique , Ludwig Ralf
Published: March 2020

Climate change is altering the Earth’s atmospheric circulation and the dynamic drivers of extreme events. Extreme weather events pose a great potential risk to infrastructure and human security. In Southern Québec, freezing rain is among the rare, yet high-impact events that remain particularly difficult to detect, describe or even predict.

Large climate model ensembles are instrumental for a profound analysis of extreme events, as they can be used to provide a sufficient number of model years. Due to the physical nature and the high spatiotemporal resolution of regional climate models (RCMs), large ensembles can not only be employed to investigate the intensity and frequency of extreme events, but they also allow to analyze the synoptic drivers of freezing rain events and to explore the respective dynamic alterations under climate change conditions. However, several challenges remain for the analysis of large RCM ensembles, mainly the high computational costs and the resulting data volume, which requires novel statistical methods for efficient screening and analysis, such as deep neural networks (DNN). Further, to date, only the Canadian Regional Climate Model version 5 (CRCM5) is simulating freezing rain in-line using a diagnostic method. For the analysis of freezing rain in other RCMs, computational intensive, off-line diagnostic schemes have to be applied to archived data. Another approach for freezing rain analysis focuses on the relation between synoptic drivers at 500 hPa resp. sea level pressure and the occurrence of freezing rain in the study area of Montréal.

Here, we explore the capability of training a deep neural network on the detection of the synoptic patterns associated with the occurrence of freezing rain in Montréal. This climate pattern detection task is a visual image classification problem that is addressed with supervised machine learning. Labels for the training set are derived from CRCM5 in-line simulations of freezing rain. This study aims to provide a trained network, which can be applied to large multi-model ensembles over the North American domain of the Coordinated Regional Climate Downscaling Experiment (CORDEX) in order to efficiently filter the climate datasets for the current and future large-scale drivers of freezing rain.

We present the setup of the deep learning approach including the network architecture, the training set statistics and the optimization and regularization methods. Additionally, we present the classification results of the deep neural network in the form of a single-number evaluation metric as well as confusion matrices. Furthermore, we show analysis of our training set regarding false positives and false negatives.
Relationship between heating/cooling period and changing temperature conditions in the urban areas of Hungary
Authors: Dian Csenge , Talamon Attila , Pongrácz Rita , Bartholy Judit
Published: March 2020

Climate change, extreme weather conditions, and local scale urban heat island (UHI) effect altogether have substantial impacts on people’s health and comfort. The urban population spends most of its time in buildings, therefore, it is important to examine the relationship between weather/climate conditions and indoor environment. The role of buildings is complex in this context. On the one hand UHI effect is mostly created by buildings and artificial surfaces. On the other hand they account for about 40% of energy consumption on European average. Since environmental protection requires increased energy efficiency, the ultimate goal from this perspective is to achieve nearly zero-energy buildings. When estimating energy consumption, daily average temperatures are taken into account. The design parameters (e.g. for heating systems) are determined using temperature-based criteria. However, due to climate change, these critical values are likely to change as well. Therefore, it is important to examine the temperature time series affecting the energy consumption of buildings. For the analysis focusing on the Carpathian region within central/eastern Europe, we used the daily average, minimum and maximum temperature time series of five Hungarian cities (i.e. Budapest, Debrecen, Szeged, Pécs and Szombathely). The main aim of this study is to investigate the effect of changing daily average temperatures and the rising extreme values on building design parameters, especially heating and cooling periods (including the length and average temperatures of such periods).
Towards Eco-circular economy worldwide
Authors: Șișcan Sergiu
Published: March 2020

Nowadays the global ecological crisis continues aggravating. The environmental issues are on agenda, getting increased public attention (e.g. protests caused by waste problems and climate change all around the world). Depleting resources, trash mountains, garbage islands, toxic emissions etc. require change of economy model from linear (resource extraction-production-usage-throwing away) to the circular one (recycled resource-production-usage-recycling). More than that, multiple waste use as well as resources reuse may bring to business and economy billions of dollars.

The very idea of recycle is practiced in the world since long ago. However, it has been done by few resources (collection of waste paper, scrub metal, glass bottles etc.) without shaping an economic system as a whole.

Another problematic issue is that the recycling does not always means to be ecological. The mode of recycling in countries with low eco-standards results in heavy pollution (e.g. e-waste “recycling” by fire at open air in Africa, India leads to emission of toxins; ship recycling in Bangladesh leads to polluted beaches and water). Methods of recycling in developing countries often are primitive and may be dangerous. Sometimes, entrepreneurs from developed countries are responsible for such state of affairs. They send legally or illegally part of wastes for that primitive recycling in developing countries. It is important to have awareness of the fact that everything is interdependent. If one part of the Earth is full of toxins and harmful fumes, its other part is inevitably affected over time. It is necessary to carry out recycling in all countries establishing strict environmental laws worldwide, and to make it based on smart technologies.

Circular economy in its narrowest sense is an economy that simply processes waste.
A serious change in business models, public mentality and government policies is necessary to get to environmentally friendly economy. It aims at lengthening the use cycle of goods (e.g. clothes, mobile phones) and minimizing the personal waste of every citizen. The EU household’s food waste was estimated to be 47 million tons (EU FUSIONS, 2016). “More than 30% of clothes in Europeans’ wardrobes have not been used for at least a year. Once discarded, over half the garments are not recycled but end up in mixed household waste and are sent to incinerators or landfill” (EPRS, 2019). YouGov Omnibus research: a third (34%) of respondents of Singapore have thrown away an item of clothing after wearing it just once. (YouGov, 2017).

Thus, effective circular economy is not just about re-processing and saving resources but, first, emphasizes its focus on greening environment and reducing waste as it is, becoming an eco-circular economy. Secondly, it calls forth measures at not only national or regional level, but also proceeding from “Earth is our common home”, worldwide.
The topological origin of anomalous transport: Persistence of β in the face of varying correlation length.
Authors: Edery Yaniv
Published: March 2020

Traditional concepts for flow in porous media assume that the heterogenous distribution of hydraulic conductivity is the source for the contaminant temporal and spatial heavy tail, a process known as anomalous or non-Fickian transport; this anomalous transport behavior can be captured by the β parameter in the continues time random walk (CTRW) framework. In previous studies we showed that there is a functional form relating the β parameter to the permeability variance1 and fracture alignment in fracture fields2. Moreover, we showed that this variance is strongly influencing the reaction pattern during transport3.  This study shows that as the spatial correlation length, between these heterogenous distribution of hydraulic conductivities, increase, the anomaly of the flow reduces, yet the β value is unchanged suggesting that there is a topological component to the flow field, captured by the β4. This finding is verified by an analysis on the flow field, showing that the changes in the conductivity values have little effect on the flow field morphology, which points to the topological component in the flow.

Y. Edery, A. Guadagnini, H. Scher and B. Berkowitz, Water Resources Research 50 (2), 1490-1505 (2014).

Y. Edery, S. Geiger and B. Berkowitz, Water Resources Research 52 (7), 5634-5643 (2016).

Y. Edery, G. M. Porta, A. Guadagnini, H. Scher and B. Berkowitz, Transport in Porous Media 115 (2), 291-310 (2016).

Y. Edery, arXiv preprint arXiv:1906.07061 (2019).
Towards global fully-distributed regionalization of hydrological model parameters
Authors: Beck Hylke , Pan Ming , Lin Peirong , Seibert Jan , van Dijk Albert , Wood Eric
Published: March 2020

All hydrological models need to be calibrated to obtain satisfactory streamflow simulations. Here we present a novel parameter regionalization approach that involves the optimization of transfer equations linking model parameters to climate and landscape characteristics. The optimization was performed in a fully spatially distributed fashion at high resolution (0.05°), instead of at lumped catchment scale, using an unprecedented database of daily observed streamflow from 4229 headwater catchments (<5000 km2) worldwide. The optimized equations were subsequently applied globally to produce parameter maps for the entire land surface including ungauged regions. The approach was implemented using a bounded version of the Kling-Gupta Efficiency metric (KGEB) and a gridded version of the HBV hydrological model. Ten-fold cross-validation was used to evaluate the generalizability of the approach and to obtain an ensemble of parameter maps. For the 4229 independent validation catchments, the regionalized parameters yielded a median daily KGEB of 0.30 (equivalent to a conventional KGE of 0.46). The median KGEB improvement (relative to uncalibrated parameters) was 0.21, with improvements obtained for 88 % of the independent validation catchments. These scores compare favourably to those from previous large catchment sample studies. The degree of performance improvement due to the regionalized parameters did not depend on climate or topography. Substantial improvements were obtained even for independent validation catchments located far from the catchments used for optimization, underscoring the value of the derived parameters for poorly gauged regions. The regionalized parameters — available via www.gloh2o.org/hbv — should be useful for numerous hydrological applications requiring accurate streamflow simulations.
The influence of water temperature-phytoplankton feedback in a Regional Earth System Model upon the hydrography and biogeochemistry of the northern Indian Ocean
Authors: Martyanov Stanislav D. , Sein Dmitry V. , Ryabchenko Vladimir A. , Dvornikov Anton Y. , Kumar Pankaj
Published: March 2020

Within the Coordinated Regional Climate Downscaling Experiment (CORDEX) framework, a high-resolution Regional Earth System Model (RESM) was used to understand the effects of various parameterizations of the attenuation of short-wave radiation (SWR) penetrating into the ocean. The RESM comprises of the Max Planck Institute Ocean Model and the Hamburg Ocean Carbon Cycle model (MPIOM/HAMOCC) coupled via the OASIS coupler to the Regional atmosphere Model (REMO), and the Hydrological Discharge model (HD). Two runs of the RESM for the historical period 1950-2017 were performed. In the first run, the model utilized a simple light attenuation parameterization based on the Jerlov water types when the attenuation coefficient varies spatially depending on the water type but does not vary in time. In the second run, the feedback between the ocean and atmosphere through the marine ecosystem was implemented by using the parameterization of light attenuation coefficient as the function of not only water attenuation itself but also phytoplankton concentration, which was implemented in both the physical and biogeochemical model blocks. The obtained model results correspond well to the observed climatic characteristics. In the calculation with phytoplankton-dependent light attenuation parameterization, the average SST was lower than in the case of Jerlov-based parameterization. The greatest difference in SST (more than 1 °C) occurs in the spring and summer periods during the phytoplankton bloom. The SST differences in autumn and winter are less pronounced and do not exceed 0.2 °C and 0.6 °C, respectively. Also, during the period of intensive heating (spring and summer) the SWR in the ocean upper layers calculated by the feedback-based model run is more strongly absorbed in these layers and, as a result, a significant cooling of subsurface layers (25-200 m) occur (up to 1-1.5 ° С). The phytoplankton primary production and its dispersion in the feedback-based model run turned out to be higher, especially during the periods of winter and summer blooms, and the surface concentration of dissolved nitrates was lower than in the reference run (Jerlov-based parameterization) almost the whole year.

The work was supported by the Russian Science Foundation (Project 19-47-02015) and by the grant DST/INT/RUS/RSF/P-33/G of the Department of Science and Technology, Govt. of India.
TFM-ext tool for the groundwater vulnerability assessment within LandSupport project
Authors: Basile Angelo , Terribile Fabio , Bancheri Marialaura ,   LANDSUPPORT H2020 Project n.774234
Published: March 2020

Geo-Spatial Decision Support Systems (S-DSS) can be usefully employed to support the acquisition, management, and processing of both static and dynamic data (e.g., daily climate), data visualization, and computer on-the-fly applications in order to perform simulation modelling all potentially accessible via the Web. S-DSS are becoming more popular by providing operational tools to a large community of end-users and policy-makers for a sustainable landscape management (i.e. for both agriculture and environmental protection) at different spatial and temporal scales.

The scope of this work is to present the implementation of the extended Transfer Function Model (TFM-ext) – described in a companion abstract presented in the same session – as an operative tool for the groundwater vulnerability assessment within the larger S-DSS developed for LandSupport H2020 project (https://www.landsupport.eu).

The tool allows to simulate the mean travel times of a generic solute at different spatio-temporal scales (from the local to the regional scale), considering different land uses.

In particular, operatively, the end-user can evaluate the filtering capacity of the soils, by: i) defining the region of interest; ii) defining the simulation period; iii) choosing between 6 different land use scenarios (bare soil, alpha-alpha, maize, vine, olive and wheat) or consider his/her own management scenario; iv) defining the depth of interest at which evaluate the solute arrival.

The outputs are i) the mean travel times that the input solute (given as a fertilizer concentration related to the land-use scenario) takes to reach the defined depth and ii) the quantity of the input solute that reaches the defined depth after one year from its injection.

The latter information is then associated to the filtering capacity of the soil, which are thus classified according to the percentage of input mass arrived after one year.

The model was implemented as open source Java application, following the standard of the flexibility to changes and to future expansions, of the optimized computational demand and parallelization, required by the project.

Three local scale cases are available at the moment (Telesina Valley-IT, Marchfeld-AT and Zala County-HU). Future developments will aim to apply TFM-ext towards larger European spatial extent areas (e.g. regional scales). Furthermore, future develoments  will aim to support selected implementations of Water Framework and Nitrates directives, especially with respect to the systematic required mapping revision of Nitrate Vulnerable Zone and the adoption of best practice.

 
The asynergies of disaster risk reduction measures in Afghanistan
Authors: de Ruiter Marleen , de Bruijn Jens , Daniell James , Englhardt Johanna , Ward Philip , de Moel Hans
Published: March 2020

Many countries face the risk of multiple hazards. The UNDRR’s Global Platform for Disaster Risk Reduction have called upon the science community for an increased understanding of the complexities of multi-hazard risk (UNDRR 2019). Nonetheless, in the currently prevailing risk assessment paradigm, risk is often represented as static and fragmented in terms of hazard types. While positively influencing the risk of one hazard, DRR measures can have adverse effects on the risk of another hazard type thereby increasing the vulnerability of the built environment, exacerbating impacts and potentially causing compound or cascading disasters. For example, wood-frame buildings tend to perform well under ground shaking but are likely to sustain higher damages due to an inundation than concrete buildings. We refer to these negative impacts between hazards as the asynergy of a DRR measure. Due to the predominantly single-hazard approach, the potential asynergies of DRR measures remain poorly understood.

In a case study of Afghanistan, we calculate the asynergies of building level DRR measures for floods and earthquakes. To this extent, we develop two increased-resilience scenarios where a decrease in flood and earthquake vulnerability are mimicked. These scenarios are used to assess the asynergies and to illustrate to what degree a risk reduction of one risk may actually be offset by an increase of the other risk. This can then be used to show which type of measure is worthwhile in which area.

An improved capability of understanding risk more holistically would strongly benefit first responders, aid organizations, urban planners and decision makers in designing sustainable DRR measures. We discuss several key potential asynergies of building level DRR measures for floods and earthquakes tailored to decrease the risk of one hazard on the risk of the other hazard. Finally, we outline a roadmap highlighting key future research and policy directions, and possible ways to strengthen coherent policies for DRR.
Introducing new global electromagnetic modeling solver
Authors: Kruglyakov Mikhail , Kuvshinov Alexey
Published: March 2020

 In this contribution, we present novel global 3-D electromagnetic forward solver based on a numerical solution of integral equation (IE) with contracting kernel. Compared to widely used x3dg code which is also based on IE approach, new solver exploits alternative (more efficient and accurate) numerical algorithms to calculate Green’s tensors, as well as an alternative (Galerkin) method to construct the system of linear equations (SLE). The latter provides guaranteed convergence of the iterative solution of SLE. The solver outperforms x3dg in terms of accuracy, and, in contrast to (sequential) x3dg, it allows for efficient parallel computations, meaning that the code has practically linear scalability up to the hundreds of processors.
Simulating melting of fault gouge at the local scale
Authors: Mollon Guilhem , Aubry Jerôme , Schubnel Alexandre
Published: March 2020

Melting of fault gouge during fast co-seismic slip has been widely documented in laboratory studies. Because the real-time observation and local probing of this phenomenon is experimentally out of reach at the present time, the implication of melting on fault weakening are not yet fully understood,. Physics-based numerical modelling of a synthetic sliding interface could thus be a way to bring a better understanding of this physico-mechanical process.

In this study, we present a numerical work paving the way towards such an understanding. It is implemented in MELODY, a numerical tool combining Discrete Element Method (DEM) and a Multibody Meshfree Approach (i.e. highly deformable DEM). In this model, a small patch of seismic fault filled with granular gouge (composed of perfectly rigid and incrompressible grains with realistic angular shapes) is simulated. By shearing this simulated fault, we produce highly deformable gouge particles within a melted layer.

Numerical results show that melting processes have strong consequences on the fault rheology, by reducing shear stress and favouring the localization of the deformation on the sliding interface. Results are compared with experimental observations on saw-cut faults deformed in triaxial conditions in the laboratory. Future developments including thermal diffusion within the gouge and in the surrounding medium are described.
Mechanical Properties of Native Tree Species for Soil Bioengineering in Northeastern Mexico
Authors: Zavala Rebeca , Cantú Israel , Sánchez Laura , González Humberto , Estrada Eduardo , Kubota Tetsuya
Published: March 2020

In recent years, the effect of soil bioengineering has played a very important role on slope stability. However, our area of study is constantly under the influence of small-scale earthquakes and extreme events of heavy rainfall which cause potentially unstable conditions on the slopes. The mechanical properties of the root systems tensile strength (Ts) and modulus of elasticity (Eroot) of four native species were analyzed for a potential use as soil bioengineering elements. We investigated if tensile strength (N/mm2) and modulus of elasticity of roots (N/mm2) was different between studied species: Cercis canadensis, Celtis laevigata, Quercus rysophylla and Ligustrum lucidum. The species considered were selected based on their native characteristics and widespread existence on the slopes. Regarding tree forest species, the tests were conducted with the Universal Testing Machine Shimadzu type SLFL-100KN. The relationships among root diameter, tensile strength (Ts), and modulus of elasticity (Eroot) was negative and could be fitted with a power regression equation, showing highly significant   values p<0.01.Celtis laevigata showed the maximum value of tensile strength (Ts) 28.11 N/mm2 while the minimum value of tensile strength was observed in Ligustrum lucidum 5.27 N/mm2. For the variable modulus of elasticity (Eroot) Celtis laevigata  showed the maximum value of 90.01N/mm2 while the minimum value of modulus of elasticity was observed in Ligustrum lucidum 29.16 N/mm2.Results of mechanical proprieties are showed the following ascending order: Ligustrum lucidum < Quercus rysophylla < Cercis canadensis < Celtis laevigata. Likewise, Celtis laevigata showed the highest tensile strength and modulus of elasticity of all investigated species.

 

Key words: root, tensile strength, modulus or elasticity.

 

 
Solar flare effect on the ionospheric current in the polar region: a new phenomena
Authors: Yamauchi Masatoshi , Johnsen Magnar , Enell Carl-Fredrik
Published: March 2020

Solar flares are known to enhance the ionospheric electron density in the D- and E-region, enhancing twin vortex pattern in the dayside (e.g., Curto et al., 1994).  The geomagnetic deviation due to this current system is called as "crochet" or "SFE (solar flare effect)".  For X-flares, the crochet is easily detected as an enhancement in ASY-D index (Sing et al., 2012).  Since the effect is expected stronger at low solar zenith angles where solar radiation is high, high-latitude behavior (> 70° geographic latitudes: GGlat) has not been well studied and simply assumed as minor (such as weak return current).

However, the X flares on 6 September 2017 (X2.2 at 9 UT and X9.3 at 12 UT), caused large non-substorm geomagnetic disturbances at high latitudes, lasting much longer than the burst of electron density enhancement in the the D- and E-region (Yamauchi et al., 2018).  Both the polarity and duration turned out to be different from mid-latitude crochet which is characterized by short-lived (< 30 min) dH<0: dH is positive for over 5 hours with much higher amplitude than the crochet although the event took place near equator.  In addition, this dH showed oscillations on the order of 30 minute.  Since the X-ray intensity during 12-17 UT was higher than X-flare criterion until 17 UT, this long-lasting dH>0 with peak at 74-75 GGLat must also be caused by the X-flare.  The EISCAT radar data showed strong enhancement of convection lasting hours after the flare onset and relevant bursty (< 10 min) enhancement of the electron density.  This is consistent with long-lasting positive dH.  On the other hand, density oscillation period is about 15 min and different from the oscillation period of dH.   

Using Norwegian geomagnetic chain and EISCAT data, we examined X flares (> X2.0) for past two solar cycles, and found that (1) dH>0 at > 70 GGLAT with dH<0 (and positive ASY-D change is quite common) at lower latitude, (2) duration of crochet (dH<0) is shorter at higher latitude as the start timing and amplitude of dH>0 becomes earlier and larger at higher latitude, (3) at some latitude, crochet (dH<0) disappears and dH>0 dominates the entire period much longer than the crochet, and (4) electron density enhancement is spike-like no matter the duration of X-flare.  We interpret this long-lasting dH>0 is caused by independent mechanism from crochet.

Reference
Curto et al. (1994): doi:10.1029/93JA02270
Singh et al. (2012): doi:10.1016/j.jastp.2011.12.010
Yamauchi et al. (2018): doi:10.1029/2018SW00193
A novel bioflocculant for chromium (Ⅵ) and arsenic (Ⅲ) removal: Extracellular polymeric substance (EPS) of Pseudomonas fluorescens
Authors: He Ning
Published: March 2020

Bioflocculants produced by microorganisms have advantages in removing heavy metals because of their environmental friendliness and biodegradability. In this study, the bioflocculant from a soil bacteria was investigated for its application in chromium (Ⅵ) and arsenic (Ⅲ) removal. The bioflocculant-producing strain was indentified as Pseudomonas fluorescens. It showed maximum flocculating activity of 2579.94 U/mL and yield of 4.84 g/L under optimal condition. With a fed‑batch fermentation strategy, bioflocculant production was further enhanced by 32.6%. The bioflocculant was as extracellular polymer substance composed of 76.67% polysaccharides and 15.8% protein with a molecular weight of 117 kDa. It showed excellent capacities in heavy metal removal, 80.13 and 45.93 mg/g for chromium(Ⅵ) and arsenic (Ⅲ), respectively. The bioflocculant outperformed conventional adsorption materials and could represent a promising biotechnology for the remediation of environmental problems.
Validation and improvement of Taiwan Emission inventory for air quality modeling
Authors: Chuang Ming-Tung , Chou Charles C.-K , Lin Chuan-Yao
Published: March 2020

The performance of air quality modeling (AQM) depends largely on the uncertainty of emission inventory. Since the emission data is an important input for AQM, this study tried to validate the controversial emission inventory. The Taiwan EPA (TEPA) has released the latest TEDS10.0 (Taiwan Emission Database System, version 10.0) based on 2016. This emission has attracted high arguments among governments and academics. This study applied the SMOKE v4.6 (Sparse Matrix Operator Kerner Emissions) to process the TEDS. The study used the CEMS (Continuous Emission Monitoring System) data and replaced temporalized large point source which accounts for 70% of all point source emissions, updated the biogenic emission calculation, improved the temporal profile of NH3, several area sources, and all mobile sources. Then we utilized the CMAQ (Community Modeling and Analysis System) model to simulate a PM2.5 event. However, the performance of the abovementioned improvement for emission processing is still not satisfactory. Therefore, this study tried to adjust the emission inventory according to the comparison of simulations and observations. The performance of air quality modeling has been improved after adjustment.  Meanwhile, this study provided suggestions of several aspects to be improved to the TEPA.
The Northeast China Persistent Drought in Spring-Summer of 2017: Joint Roles of Teleconnection and Land-atmosphere Coupling
Authors: zeng dingwen , yuan xing
Published: March 2020

Northeast China (NEC) suffered its worst persistent drought event in recent decades from March to July of 2017 with devastating impacts on the environment and agriculture. Previous drought mechanism studies focused on the atmospheric remote response to Arctic sea ice and ENSO, while less attention was paid to synergistic effects of large-scale teleconnections and local land-atmosphere coupling. Here we show that a strong positive phase of Arctic Oscillation in March triggered the NEC drought, and a quasi-stationary Rossby wave train maintained the drought with an anticyclone located over the area south to Lake Baikal (ASLB) in April-July. By using a land-atmosphere coupling index based on the persistence of positive feedback between boundary layer and land surface, we find that the NEC and ASLB experienced a wet coupling in March while a persistently strengthened dry coupling in April-July. Over ASLB, the dry coupling and sinking motion increased surface sensible heat, decreased cloud cover, and weakened longwave absorption, resulting in a diabatic heating anomaly in the lower atmosphere and a diabatic cooling anomaly in the upper atmosphere. This anomalous vertical heating profile generated a negative anomaly of potential vorticity, indicating that the land-atmosphere coupling had a phase-lock effect on the Rossby wave train originating from upstream areas, and therefore maintained the NEC drought over downstream regions. Numerical simulations with and without surface sensible heating are being conducted to verify the influence of teleconnected land-atmosphere coupling, i.e., dry land conditions over ASLB in May can cause positive height anomaly over ASLB and NEC during June-July through heating the low level atmosphere. Our study suggests that upstream quasi-stationary wave pattern strengthened by land-atmosphere coupling should be considered in diagnosing persistent droughts especially over northern mid-latitudes.
Modelling sub-daily phytoplankton dynamics and analysing primary production controls in the lower Thames catchment, UK
Authors: Pathak Devanshi , Hutchins Michael , Edwards François
Published: March 2020

River phytoplankton provide food for primary consumers, and are a major source of oxygen in many rivers. However, high phytoplankton concentrations can hamper river water quality and ecosystem functioning, making it crucial to predict and prevent harmful phytoplankton growth in rivers. In this study, we modify an existing mechanistic water quality model to simulate sub-daily changes in water quality, and present its application in the River Thames catchment. So far, the modelling studies in the River Thames have focused on daily to weekly time-steps, and have shown limited predictive ability in modelling phytoplankton concentrations. With the availability of high-frequency water quality data, modelling tools can be improved to better understand process interactions for phytoplankton growth in dynamic rivers. The modified model in this study uses high-frequency water quality data along a 62 km stretch in the lower Thames to simulate river flows, water temperature, nutrients, and phytoplankton concentrations at sub-daily time-steps for 2013-14. Model performance is judged by percentage error in mean and Nash-Sutcliffe Efficiency (NSE) statistics. The model satisfactorily simulates the observed diurnal variability and transport of phytoplankton concentrations within the river stretch, with NSE values greater than 0.7 at all calibration sites. Phytoplankton blooms develop within an optimum range of flows (16-81 m3/s) and temperature (11-18° C), and are largely influenced by phytoplankton growth and death rate parameters. We find that phytoplankton growth in the lower Thames is mainly limited by physical controls such as residence time, light, and water temperature, and show some nutrient limitation arising from phosphorus depletion in summer. The model is tested under different future scenarios to evaluate the impact of changes in climate and management conditions on primary production and its controls. Our findings provide support for the argument that the sub-daily modelling of phytoplankton is a step forward in better prediction and management of phytoplankton dynamics in river systems.
Nutrient constraints on the Amazon carbon sink: from field measurements to model projections
Authors: Fleischer Katrin , Quesada Carlos Alberto , Lapola David , Fuchslueger Lucia , Lugli Laynara , Reichert Tatiana , Rammig Anja
Published: March 2020

The Amazon rainforest faces immense pressures from human-induced deforestation and climate change and its future existence is largely indeterminate. Accurately projecting the forest’s response to future conditions, and thus preparing for the best possible outcome, requires a sound process-based understanding of its ecological and biogeochemical functioning. The intact forest acts as a sink of atmospheric carbon dioxide (CO2), however, this invaluable function is slowing down for unclear reasons, according to long-term plot measurements of tree growth. Earth system models, on the other hand, assume a continuous sink of carbon into the 21st century, predominantly driven by CO2 fertilization, concurrently buffering against adverse effects by climate change. Advancing empirical and experimental evidence points to strong nutrient constraints on the Amazon carbon sink, foremostly by phosphorus and other cations, so that the projected strength of the future carbon sink is certainly unrealistic. It is highly uncertain, however, to which degree nutrients are and will diminish elevated CO2-induced productivity, and to which extent plant-based mechanisms may upregulate phosphorus supply or optimize phosphorus use to facilitate the increasing demand by elevated CO2. Site-scale ecosystem model ensemble analysis underscores the diverging hypotheses on phosphorus feedbacks we are currently facing. In addition, heterogeneous soil phosphorus availability across the Amazon basin, in combination with a hyperdiverse plant community, challenges current efforts to project phosphorus constraints on the future of the Amazon carbon sink. We here give an outlook of current progress and future research needs of model-experiment integration to tackle this pressing question.
Water in the circular economy: using recycled water for sub-irrigation purposes
Authors: Bartholomeus Ruud P. , van Huijgevoort Marjolein H.J. , van Loon Arnaut
Published: March 2020

Agricultural crop yields depend largely on soil moisture conditions in the root zone. Climate change leads to more prolonged drought periods that alternate with more intensive rainfall events. With unaltered water management practices, reduced crop yield due to drought stress will increase. Therefore, both farmers and water management authorities search for opportunities to manage risks of decreasing crop yields. Available groundwater sources for irrigation purposes are increasingly under pressure due to the regional coexistence of land use functions that are critical to groundwater levels or compete for available water. At the same time, treated wastewater from industries and domestic wastewater treatment plants are quickly discharged via surface waters towards sea. Exploitation of these freshwater sources may be an effective strategy to balance regional water supply and agricultural water demand. We present results of a pilot study in a drought sensitive region in the Netherlands, concerning agricultural water supply through reuse of industrial treated wastewater. The Bavaria Beer Brewery discharges treated wastewater to the surface water. Nevertheless, neighboring farmers invest in sprinkler irrigation to maintain their crop production during drought periods. Doing so, increasing pressure is put on the regional groundwater availability. Within a pilot study, a sub-irrigation system has been installed, by using subsurface drains, interconnected through a collector drain, and connected to an inlet control pit for the treated wastewater to enter the drainage system. Sub-irrigation is a subsurface irrigation method that can be more efficient than classical, aboveground irrigation methods using sprinkler installations. Additionally, sub-irrigated water that is not used for plant transpiration recharges the groundwater. We combine both process-based modeling of the soil-plant-atmosphere system and field experiments to i) investigate the amount of water that needs to be and that can be sub-irrigated, and ii) quantify the effect on soil moisture availability and herewith reduced needs for aboveground irrigation from groundwater.
The Single-column Urban Boundary Layer Intercomparison Modelling Experiment (SUBLIME): results of revised recipe
Authors: Steeneveld Gert-Jan , Tsiringakis Aristofanis ,   SUBLIME
Published: March 2020

Models for weather and climate have been actively populated with urban canopy models in the last decade. Urban canopy models are available with different levels of complexity. In an earlier study several urban canopy models have been evaluated in offline mode (Grimmond et al. 2011). However, in reality these schemes operate within a numerical weather prediction model, and are coupled with the atmospheric boundary layer. Within the SUBLIME model intercomparison study, single-column models equipped with urban canopy models are evaluated against observations for a clear sky case over London. As such we aim to unravel whether model sensitivity for urban morphological parameters is similar in coupled and uncoupled model. Moreover, the SUBLIME project provides a benchmark for future model evaluation and further development. The SUBLIME experiment consists of a forecast task over a 54 hour period (23-25 July 2012), during which clear sky conditions persisted over London. It consists of two main stages, firstly an offline urban canopy model run, to determine how the surface scheme performs. This is followed by a run in which the urban canopy model is coupled to a single-column model to simulate the coupling to the urban boundary layer. Model forcing data were provided by flux tower, LIDAR and radiosonde observations. Additional external forcings for geostrophic wind speed and advection of heat, moisture and momentum which could not be directly observed were simulated using, 3-D WRF (Weather Research and Forecasting model) model runs. This presentation will discuss the modelling results using the new revised external forcings. We evaluate model outcomes against surface radiation and energy balance observations for both stages. For the second stage, modelled vertical profiles of wind, temperature and humidity as well as boundary-layer height are compared against observations and between models. Finally, differences in model results are identified and the physical processes responsible for these are explored using process diagrams.