bluuebunny/crossref_metadata_2025 huggingface dataset:
Current status of design basis earthquake level for nuclear power plant sites in several countries
Authors: Choi Hoseon , Hyun Seung Gyu
Published: March 2021

According to strict criteria step by step for site selection, design, construction and operation, the seismic safety of nuclear power plant (NPP) sites in South Korea are secured by considering design basis earthquake (DBE) level capable of withstanding the maximum ground motions that can occur on the site. Therefore, it is intended to summarize DBE level and its evaluation details for NPP sites in several countries.

Similar but different terms are used for DBE from country to country, i.e. safe shutdown earthquake (SSE), design earthquake (DE), SL2, Ss, and maximum calculated earthquake (MCE). They may differ when applied to actual seismic design process, and only refer to approximate comparisons. This script used DBE as a representative term, and DBE level was based on horizontal values.

The DBE level of NPP sites depends on seismic activity of the area. Japan and Western United States, where earthquakes occur more frequently than South Korea, have high DBE values. The DBE level of NPP sites in South Korea has been confirmed to be similar or higher compared to that of Central and Eastern Unites Sates and Europe, which have similar seismic activity.
Ensemble-based data assimilation of volcanic aerosols using FALL3D+PDAF
Authors: Mingari Leonardo , Prata Andrew , Pardini Federica
Published: March 2021

Modelling atmospheric dispersion and deposition of volcanic ash is becoming increasingly valuable for understanding the potential impacts of explosive volcanic eruptions on infrastructures, air quality and aviation. The generation of high-resolution forecasts depends on the accuracy and reliability of the input data for models. Uncertainties in key parameters such as eruption column height injection, physical properties of particles or meteorological fields, represent a major source of error in forecasting airborne volcanic ash. The availability of nearly real time geostationary satellite observations with high spatial and temporal resolutions provides the opportunity to improve forecasts in an operational context. Data assimilation (DA) is one of the most effective ways to reduce the error associated with the forecasts through the incorporation of available observations into numerical models. Here we present a new implementation of an ensemble-based data assimilation system based on the coupling between the FALL3D dispersal model and the Parallel Data Assimilation Framework (PDAF). The implementation is based on the last version release of FALL3D (versions 8.x) tailored to the extreme-scale computing requirements, which has been redesigned and rewritten from scratch in the framework of the EU Center of Excellence for Exascale in Solid Earth (ChEESE). The proposed methodology can be efficiently implemented in an operational environment by exploiting high-performance computing (HPC) resources. The FALL3D+PDAF system can be run in parallel and supports online-coupled DA, which allows an efficient information transfer through parallel communication. Satellite-retrieved data from recent volcanic eruptions were considered as input observations for the assimilation system.
Analysis of the operational benefits of hybrid hydropower-floating solar photovoltaic systems
Authors: Gadzanku Sika , Dyreson Ana , Lee Nathan
Published: March 2021

Floating solar photovoltaics (FPV) systems have become an attractive RE option due to their potential energy, environmental, and social benefits. FPV systems have been deployed as standalone systems and hybridized with other generation or energy storage technologies. Hybrid FPVs, especially those paired with hydropower plants, are of specific interest because of potential cost and performance benefits such as improved system operation at different time scales, additional energy storage opportunities, improved transmission utilization, reduced solar PV curtailment, and water conservation. Despite the interest in hybrid hydropower-FPV systems, there is limited research quantifying the operational benefits of these hybrid systems. To help address this research gap, this study analyzes the potential grid-level operational benefits of a generic hybrid hydropower-FPV system through a modeling exercise. Using a solar resource time-series and resource data for an example hydropower plant, we quantify the potential curtailment reduction, increased transmission utilization, and changes in seasonal and diurnal electricity generation for the hybrid FPV system compared to stand alone systems. Results suggest that depending on the seasonality of hydropower resources and the ratio of the size of the FPV system to hydropower plant sizes, the hybrid hydropower-FPV system could reduce curtailment and lead to more optimal use of limited water resources.
Influence of Enso in Perú's Cordillera Blanca Glaciers
Authors: Hoyos Zarzosa Lihan Del Rocio , Rojas Macedo Ibeth Celia , Garcia Rojas Christian German , Dávila Roller Luzmila , Tapia Ormeño Pedro
Published: March 2021

In areas located over 2000 m.a.s.l., the warm phase of ENSO (El Niño) is characterized by a decrease in precipitation and an increase in temperature which can reach values above the annual average, while in the cold phase of ENSO (La Niña), precipitation increases and temperature decreases compared to the annual average. In both cases ENSO has an influence on the glacier evolution of the Andes.

The objective of the present investigation is to determine the influence of ENSO in the Cordillera Blanca through satellite images (glacier coverage delimitation) and climatic proxy (ice core) in the Shallap and Artesonraju glaciers respectively for the hydrological years between 2009/2010 to 2018/2019.

The climate analysis in both glaciers showed higher annual temperatures and lower precipitation, revealing the influence of the 2015/2016 El Niño on the studied glaciers. There was a prominent reduction in glacier coverage in Shallap, which is supported by the ice core record extracted from Artesonraju, presenting an equivalent accumulated water decrease and an 18O enrichment for this period. These findings point out the influence of the 2015/2016 El Niño that significantly reduced the glacier coverage in both studied areas. On the other hand, the 2011/2012 La Niña event displayed the opposite effect, that is, colder temperatures, less glacier coverage reduction, an increase in the volume of accumulated water and an impoverishment of 18O.

Given the results, it can be affirmed that during an El Niño year the loss of glacier coverage is greater, causing less equivalent water accumulation and an enrichment of 18O; inversely for a La Niña year. These results support previous findings shown in research about glaciers in Peru.
Influence of Dust on Climate during the Mesozoic 
Authors: Lin Qifan , Liu Yonggang
Published: March 2021

Dust in the atmosphere can affect climate by directly absorbing and scattering solar radiation. In present day, most of dust is emitted from the dry regions over North Africa and Arabian Peninsula, it has been shown that they impact on global mean surface temperature, African monsoon, number of tropical cyclones over the Atlantic Ocean, ENSO variability and the strength of Atlantic meridional ocean circulation (AMOC). During the Mesozoic, the continental configuration was very different from the present, the supercontinent Pangea gradually broke up and Atlantic Ocean formed during this time period. On a different continental configuration, the area and location of dry regions may be very different, so the dust emission and atmospheric dust loading is different too. In this work, we use the global Earth system model CESM1.2.2 to examine the influence of dust on climate during the Mesozoic. Specifically, we simulate the dust and climate at two time slices, 250 million years ago (Ma) and 80 Ma. Results show that the atmospheric dust loading in both periods was much higher than that of present day. Such dust induced significant cooling of the surface climate, especially over polar regions.
Modelling the formation and evolution of glaciovolcanic caves and chimneys.
Authors: Unnsteinsson Tryggvi , Flowers Gwenn , Williams-Jones Glyn
Published: March 2021

Localised elevated subglacial or subnivean geothermal activity has the potential to influence the morphology and flow of glaciers. Under conditions where the meltwater produced by these glaciovolcanic interactions is effectively drained away from the geothermal source, glaciovolcanic voids may form. These voids can only exist if the influx of geothermal vapours/gases provides more heat for melting than can be compensated by the inflow of ice. We identify two distinct glaciovolcanic void morphologies: horizontal passageways or chambers beneath the ice/snow, termed caves, and vertical shafts, termed chimneys. Both transient and long-lived caves and chimneys have been observed, with their formation sometimes being precursory or concurrent expressions of volcanic unrest. A better understanding of these features can therefore aid volcano monitoring programs and volcanic hazard assessments. Here we investigate the relationships between glaciological and geothermal conditions and their effects on the formation and evolution of glaciovolcanic caves and chimneys. We adapt existing analytical models, originally developed to describe subglacial hydrology, to derive and balance expressions for the radial melt-opening and creep-closure to find steady-state solutions for cave and chimney geometries. The effects of localised geothermal heat fluxes on fully drained glaciovolcanic voids are further investigated using a numerical full-Stokes ice-flow model. Idealised voids, subject to a prescribed geothermally induced mass balance, are inserted within synthetic glaciers of variable bed slope and thickness. Transient simulations are then used to map out the parameter space that influences the formation and evolution of glaciovolcanic caves and chimneys.
Implementation of higher-order advection schemes in a numerical ice-sheet model for ice-core studies
Authors: Saito Fuyuki , Abe-Ouchi Ayako , Obase Takashi
Published: March 2021

Computation of temperature and age fields by numerical ice-sheet models is an important issue for ice-core related studies.  Generally the evolution of temperature and/or age in an ice-sheet model is formulated using an advection equation.  There are many variation of the formulation, which differ in numerical aspects such as stability, accuracy, numerical diffusivity, conservation and/or computational costs.  Saito et al (2020, GMD) implement Rational Constrained Interpolation Profile (RCIP) scheme on vertical 1-d age computation of ice sheet, and demonstrate its efficiency, in particular, to preserve surface mass balance properties recorded at the deposit in terms of annual layer thickness.  Successively, we have been extending the development using RCIP or similar higher-order advection schemes on 3-d age or temperature computation.  In this study, we demonstrate 1-d temperature computation by various numerical schemes including classical upwind schemes and compare the accuracy of those schemes.
Gravity flow event beds in the middle section of Watermelon Formation in Luanping Basin，eastern China：A new interpretation for its Discovery and genesis.
Authors: Wang Cheng
Published: March 2021

Gravity flow sediment is an important part of hydrocarbon source rock reservoir and an essential reservoir type in international deep water oil and gas exploration. Therefore, the study of gravity flow genesis type, sedimentary characteristics, control factors and sedimentary model in the middle section of Watermelon Formation in Luanping Basin is helpful to improve the understanding of basin evolution and the prediction of deep water reservoir. By using deep water sediment theory and gravity flow research progress, combined with logging, core, outcrop data and sheet analysis, the gravity flow in the middle section of Watermelon Formation in Luanping Basin is interpreted as slide-slump gravity flow, and the middle section of Watermelon Formation is divided into four sliding-slumping periods. The petrological analysis shows that the sediments are mainly granular supported massive conglomerate, coarse sandstone, tuff and volcanic limestone. According to the different causes, it is divided into two types: slide and slump, in which a large number of sliding surfaces are identified at the bottom of the sliding gravity flow, and sliding surfaces, small crumpled structures, faults, collapse deformation structures and drainage structures are identified in the slumping gravity flow. The paleogeomorphology and source supply of Luanping Basin during the period of Watermelon Formation, the obvious transformation of regional geological stress field, the tectonic slope fold belt developed along the source direction, the commonly used geochemical index Sr/Cu and the characteristics C climate index, the short-term eruption of volcano and the induced earthquake jointly reveal: paleogeomorphology, source supply, paleoclimate, tectonic activity, short-term volcanic eruption and induced seismic activity jointly control the formation of gravity flow sediments in the study area. this study provides practical examples and guidance for future evolution in other ancient lacustrine basins and modern basins.
Coupling particle tracking model and satellite data for trajectories prediction
Authors: Li Chaojie , Odermatt Daniel , Bouffard Damien , Wüest Johny , Kohn Tamar
Published: March 2021

Various physical, chemical and biological processes take place three- dimensionally in deep lakes, regulated by complex boundary conditions. Propelled by the rapid development of equipment, technology and computational power, the understanding of deep lakes has steadily advanced. In particular hydrodynamic monitoring and simulation studies have benefitted from combining field observation, numerical simulation and other emerging techniques such as remote sensing. In contrast, water quality parameters are less well investigated by this combination of tools. In this study, we integrate remote sensing techniques with a Lagrangian particle tracking model for lake water quality simulations. Specifically, our goal was to establish a successive individual-based model for health-relevant microorganisms in Lake Geneva. To this end, we combined remote sensing images from the current Sentinel 2 and Sentinel 3 satellites and Delft3D hydrodynamic and particle tracking models. Total suspended matter (TSM), which can both be detected by satellites and simulated by numerical models, is chosen as a parameter of concern. Concentration of TSM in Lake Geneva deduced from remote sensing images is used as observation to compare with particle tracking simulation to support the validation of the numerical model. On the other hand, the model allows to bridge gaps in satellite observations due to cloud coverage. Point source releasing and lake-wide dynamic pattern of TSM are employed as scenario studies to indicate the validation of our particle tracking model, focusing on time spans between 1 to 10 days. Our findings demonstrate that remote sensing images can serve to calibrate and validate the particle tracking water quality model, and in return, the particle tracking model provides the possibilities for data inference and interpolation between satellite images. The flexibility of the Lagrangian particle tracking method poses more possibilities to incorporate flow independent movement, mortality and growth of micro-organisms. It is expected that a more universal and accurate tool for water quality simulation can be created which will facilitate decision making.
Spatial and molecular distributions of dicarboxylic acids, oxocarboxylic acids, and a-dicarbonyls in snow in China
Authors: Zhang Zhimin , Kawamura Kimitaka , Fu Pingqing
Published: March 2021

Snow acts as efficient scavenger of the ambient contaminants, bringing considerable amounts of dissolved organic matter (DOM) from the atmosphere to the freshwater and marine environments. Low molecular weight organic acids are important and ubiquitous chemical constituents in the atmosphere. However, very limited studies so far focused on the distributions of these organic compounds in snow. To investigate the spatial and molecular distributions in snow DOM over North China, twelve fresh snow samples were collected at eight sites including urban, rural and Changdao Island during January-February 2019. The snow samples were analyzed for dicarboxylic acids and related compounds together with dissolved organic carbon (DOC). The DOC concentrations ranged from 0.99 to 14.6 mgC L−1 in melt snow, which exhibited considerable spatial variation that was affected by terrestrial/anthropogenic inputs. Total diacids were very abundant varing from 225 to 1970 μg L−1, whereas oxoacids (28.3–173 μg L−1) and a-dicarbonyls (12.6–69.2 μg L−1) were less abundant. Molecular distributions of diacids were characterized by the predominance of oxalic acid (C2, 95.0–1030 μg L−1). Contrary to the results of other studies, the second largest amount of diacid in the snow samples showed a distinct spatial variation. Higher concentrations of phthalic acids (Ph) in snow samples in Tianjin and Beijing than those in other urban and rural regions suggest significant emissions from vehicular exhausts and incomplete combustion of fossil fuels in megacities. Glyoxylic acid (15.4–116 μg L−1) was the major oxoacids while methylglyoxal (MeGly) was the major a-dicarbonyl. The mass concentration ratio of C9 to total diacids was found to be highest in Changdao Island, indicating a significant input of marine derived unsaturated fatty acids such as oleic acid. These spatial distributions are consistent with photochemical production and the subsequent accumulation under different meteorological conditions. C2 diacid constituted 40–54% of total diacids, corresponding to 1.5–2.6% of snow DOC. The total measured water-soluble organic components represent 5.5–10% of snow DOC, which suggests that there are large amounts of unknown organics that need further investigations.
Comparison of different topographic mass integration schemes in topographic reduction and its impact on geoid modeling: a case study in the Colorado area
Authors: Lin Miao , Li Xiaopeng
Published: March 2021

Topographic reduction is one of the most imperative steps in geoid modeling, where the gravity field inside the masses needs to be modeled. This is quite challenging because no one can measure gravity inside the topography at a desired resolution (only a very limited number of borehole gravity measurements are available in the whole world). Therefore, topographic mass modeling is usually treated either by the residual terrain modeling (RTM) or by the Helmert’s 2nd condensation among other alternative reduction schemes. All of these topographic reductions need intense computation efforts for the integration of topographic mass induced gravity effects. Currently, the most popular tool for topographic mass modeling is the ‘tc’ program available in the GRAVSOFT package. In this program, the mass elements provided by a digital terrain model (DTM) are treated as rectangular prisms which cannot directly take the Earth curvature into account and suffer from geometrical shape change due to meridian convergence. In this study, the tesseroids which are naturally obtained from a DTM are employed and their gravity effects are precisely evaluated by numerical integrations. Four topographic mass integration schemes are proposed and programmed in FORTRAN. Their computational performances in computing the RTM effect, terrain correction, and total topographic effect with and without using parallelizing technique are tested in the Colorado area. Then they are applied to local geoid modeling to see the geoid model differences among these various integration schemes in the RTM case. The numerical findings reveal that: (1) The application of parallelization techniques can greatly reduce the computation time without the loss of any computation accuracy; (2) Among the four integration schemes, the maximum absolute difference of RTM effect, terrain correction, and total topographic effect is about 3 mm, 6 cm, and 7.5 cm for the height anomaly, and 4 mGal, 3 mGal, and 40 mGal for the gravity anomaly; (3) In the RTM case, the geoid model difference can reach a maximum of 1 cm in the target area, and a larger difference should be expected in areas with rougher terrain; (4) The effects on geoid models from mass density anomalies is bigger than the counterparts from DTM errors.
Roles of wave trains and synoptic Rossby waves in creating midlatitude temperature extremes during winter
Authors: Rudeva Irina , Simmonds Ian
Published: March 2021

Rossby waves, found in the westerly flow at the upper troposphere, transfer energy, moisture, and momentum across large distances, being responsible for atmospheric teleconnections. Large-amplitude waves may contribute to rapid changes in wind and temperature, making them import for creating local temperature or precipitation extremes. Wirth et al (2018) separated Rossby waves into a low-frequency type, referred to as Rossby wave trains, and high-frequency, or synoptic, waves. In this work we explore a relative role of these two types in creating seasonal and synoptic temperature extremes in the midlatitudes.

We identify wave propagation regions at 300 hPa using ERA-Interim dataset for JFM 1980 – 2017. Our analysis is based on the daily data. This time scale allows identification of waveguides at a wide range of latitudes, suggesting possibility of Rossby wave propagation between midlatitudes and polar regions, as well as tropics. We show that winter temperature extremes in the midlatitudes are associated with anomalies in both high and low latitudes, while the relative importance of these areas differs across midlatitude regions. Furthermore, we demonstrate, that warm Arctic regions can create cold outbreaks in Siberia and North America.

Analysis of the evolution of midlatitude synoptic extremes reveals the importance of a pre-existing local temperature anomaly, that triggers amplification of large-scale Rossby wave trains and creates a local anomaly in the waveguide. The latter modifies propagation of synoptic scale Rossby waves that further amplify the local temperature anomaly.

References:

Wirth, V., M. Riemer, E. K. M. Chang, and O. Martius, 2018: Rossby Wave Packets on the Midlatitude Waveguide—A Review. Mon. Wea. Rev., 146, 1965–2001. https://doi.org/10.1175/MWR-D-16-0483.1.
Multi-Criteria Decision Analysis of Coastal Inundation at Regional scale
Authors: Shivamurthy Vinay , Aithal Bharath
Published: March 2021

Coastal flooding are natural processes that are both i) essential (providing nutrients to the coastal vegetation, habitats) and ii) hazardous (negatively impact human activities, livelihood, assets, livestock and so on). Climate changes have induced higher frequency of floods, rising sea levels, high amplitude tides and other climatic extremes at regional to global scales. The increasing intensity, duration of floods is proportionately increasing the risks associated with coastal human habitations. The regional risks are defined based on the physical, demographic, socio-economic vulnerability of the habitants. Sea level rise would further enhance the coastal inundations permanently breaching these productive, densely populated regions. This necessitates the need for spatially assessing the relative hazard, vulnerability and risks at regional scales to reduce/mitigate risks.

Indian subcontinent supports the second largest global population, with numerous megacities, towns and villages along the coast and mainland. This study's main objective is to quantify the risk associated with inundations caused by rising sea levels, tidal surge at the regional level. As a case study, Sagar Island located in the verge of Sundarbans, south of West Bengal is considered. Flood risk assessment in the island has been carried out using Multi-Criteria Decision Analysis (MCDA) framework based on 23 spatial parameters.

Results indicate, within a century (1922 – 2020), the island has lost most of its natural vegetation (mangroves - Sundarbans) (47% to 3%), with increasing cultivated (agriculture, horticulture) spaces (77.4 %) and built-up environs (8.2%). Sea level rise varies from 4.4 mm/year (South) to 5.25 mm/year (North) and in the last century has breached over 2824 hectares of mainland. The study's findings reveal 19.8% of horticulture and 33.3% of agriculture assets are highly exposed to natural hazards. 1.34% population are at relatively very high-risk levels, 17.81% at high-risk levels. The study's findings reveal the variable importance of socio-economic, demographic, topographic and proximity to public service, in defining the flood vulnerability and risk towards the habitants. The approach and findings of paves the way for planning authorities to prioritise risk mitigation strategies that are region-specific to reduce the impact of inundation due to natural hazards

Keywords: Sea level rise, Flood risk, MCDA, Vulnerability, flood hazard
1-Step ahead 5-Day Forecast of Normalized Burn Ratio using a Combination of Sentinel-2 and Machine Learning
Authors: Achieng Kevin , Enderlin Ellyn
Published: March 2021

Wildfires have become one of the world’s most destructive extreme events. In the US west-coast, for example, wildfire has caused severe loss of property, lives, and vegetation. Timely burn severity estimation is useful for planning and management of after-fire rehabilitation.  This study investigates plausibility of forecasting the normalized burn ratio (NBR), using machine learning models  – recurrent neural network (RNN), long-short term memory (LSTM), and Gated Recurrent Unit (GRU) – and Sentinel-2 imagery, for Campfire, California, U.S. The Campfire is the deadliest and most destructive wildfire in history of California’s wildfires. Sentinel-2 is used in this study because it captures remotely sensed images at high spatial and temporal resolutions of 10 m and 5 days, respectively. The resulting NBR time-series has a 5-hour interval. One-interval look-back in the ML algorithm results in a one-step 5-day prediction. To estimate NBR at the current time step, the machine learning method uses output from previous time-step and input of the current time-step as input variables to the model.  Results of this study show that combining machine learning and Sentinel-2 images produces plausible NBR 1-step ahead 5-day forecasts. 
Evaluation of soil moisture stress parameterizations in MEGAN model against MOFLUX field data and satellite observations of formaldehyde from OMI 
Authors: Opacka Beata , Stavrakou Trissevgeni , Müller Jean-François , Bauwens Maite , Miralles Diego , Koppa Akash , Pagán Biranna , Guenther Alex B.
Published: March 2021

Biogenic volatile organic compounds (BVOCs) are emitted globally at about 1,100 Tg per year, with almost half of the share entailed by isoprene. Isoprene is highly reactive in the atmosphere, and its degradation impacts the atmospheric composition through the generation of ozone (in presence of NOx typical of polluted areas) and secondary organic aerosols, which both pose a risk to human health. Extreme weather conditions like heatwaves and droughts can substantially affect the emissions of isoprene in ways that are largely unknown. This limited knowledge is owed to the scarcity of isoprene flux measurements under drought stress conditions. The Missouri Ozarks AmeriFlux (MOFLUX) site is located in a high isoprene-emitting oak-hickory forested region with recurring drought occurrences. Until today, it is the only site with isoprene flux measurements that capture drought behaviour.

In this study, we use the state-of-the-art MEGAN biogenic emission model (Guenther et al., 2006; 2012) coupled with the canopy model MOHYCAN (Müller et al., 2008) to estimate isoprene emissions and evaluate two different parameterizations of the soil moisture stress factor (γSM): (a) the one used in MEGANv2.1, which consists of a simple dependence on soil water content and the permanent wilting point with inputs either from ERA-Interim or the GLEAMv3 reanalysis (Martens et al., 2017), and (b) the parameterization available in MEGANv3 (Jiang et al., 2018), which considers the physiological effects of drought stress on plant photosynthesis as defined in the Community Land Model (CLM4.5), which embeds the MEGAN model.  The effect of γSM on isoprene estimates is assessed against measurements of isoprene fluxes at the MOFLUX field site collected during the mild summer drought in 2011 (Potosnak et al., 2014) and the severe drought in 2012 (Seco et al., 2015). Based on the comparisons at the MOFLUX site, we perform an optimization of the empirical parameters of the MEGANv2.1 soil moisture stress parameterization. In addition, the parameterization is further evaluated using spaceborne formaldehyde (HCHO) columns observed by the OMI sounder. To this end, we perform multiyear simulations (2005-2016) of atmospheric composition with the IMAGES global chemistry-transport model (Müller et al., 2019) using isoprene emission datasets obtained for several variants of the parameterization. We evaluate the resulting HCHO column distributions and their interannual variability against OMI HCHO columns over drought-prone regions.

This work is conducted in the frame of the ALBERI project, funded by the Belgian Science Policy Office through the STEREO III programme.
Effects of grid scale and resulting initial bed disturbance differences on the evolution of braided rivers
Authors: Wang Changjin , Hu Peng
Published: March 2021

Physics-based models have been increasingly developed in recent years and applied to simulate the braiding process and evolution of channel units in braided rivers. Braided rivers are the river network system characterized by the staggered distribution of bars and channels. In the numerical calculation, the grid scale affects the behavior process and morphological description of braided rivers. In this paper, a 2D numerical model is used to simulate the evolution of the braided rivers where the transport of load bed sediment plays a dominant role. In the natural scale braided rivers evolution modeling, the difference of the braided rivers' morphological characteristics under different grid scales is discussed, and the influence of different distribution of topographic disturbance caused by grid scale difference on the morphological characteristics of braided rivers is discussed. The study shows that the grid scale does not affect the description of braided rivers evolution process, and braided rivers evolve in the same way regardless of grid scale (within a reasonable range). However, the statistical characteristics of braided rivers are greatly affected by the grid scale. The braiding index increases as the grid scale decreases, but when the grid scale decreases to a certain extent (20m in this paper), the braiding index no longer increases. The number and average height of bars in braided rivers increase with the decrease of grid scale, and the average area of bar near riverbed also increases with the decrease of grid scale, but the average area of bar near water surface does not change with the change of grid scale. In general, the higher the grid resolution is, the more similar the bar morphology in the numerical model is to that in natural rivers. In addition, the different distribution of topographic disturbance caused by the grid scale difference has an influence on the braiding intensity and the bar morphology of the braided rivers, but the influence degree is much smaller than that caused by the grid scale difference.
It is time to interact: chronology and ecology in studying plant Si
Authors: Katz Ofir
Published: March 2021

Plant Si plays considerable roles in plant, animal. Ecosystem and global ecologies, including biogeochemical cycles. Understanding the ecological roles of plant Si and their evolutionary history is fundamental for increasing our understanding of this phenomenon, its origins, and its significance for past, present and future ecosystems. For these reasons, plant Si research is becoming increasingly interdisciplinary and superdisciplinary. Nevertheless, understanding the evolution of this phenomenon and its interactions with biogeochemical cycles – and furthermore understanding the implications for current and prospected environmental change – is hindered by inappropriate consideration of chronology and community ecology.

studies of the evolution of plant Si uptake, its ecology and its effects on ecosystem functioning suggest multiple types of Si-C interactions. These include – for example – Si-C tradeoffs within plants, a role of Si uptake and cycling in the C cycle (mostly C sequestration through NPP, weathering and occlusion), and Si mediating plant responses to CO2 changes. While these suggest that plant Si may have evolved partially in response to changing CO2 concentrations throughout the Cainozoic, implied by the contemporaneous spread of Si-rich grasslands when CO2 levels drop. However, recent paleontological and molecular suggest no temporal match. Likewise, the possibility of Si-rich grasses and abrasion-adapted grazers is also challenged by evidence for Si having an antiherbivory role on the one hand, and lack of chronological matches on the other hand. These discrepancies may stem, in part, from two considerations that may often be overlooked, about chronology, ecology and how they connect.

First, species and their traits, as well as whole ecosystems, should be seen in the context of their entire evolutionary history, and may therefore reflect not only adaptations to extant selective forces but be anachronisms. Moreover, evolutionary history and evolutionary transitions are complex, resulting in true and apparent asynchronisms. Second, evolution and ecology are multi-scalar, in which various phenomena and processes act at various scales. In ecology, there can be great differences between how a single species responds (e.g., in monoculture) and how different responses of different species interact to shape communities, and further how changes in communities interact with other ecosystem components to shape ecosystems.

Consequently, our understanding of how plant Si may have evolved in response to CO2 and herbivory, and how it may affect ecosystem functions such as biogeochemical cycling under current environmental changes, requires further thinking.
Weakening Satellite Era and Future Tropical Atlantic Sea Surface Temperature Variability
Authors: Prigent Arthur , Imbol Koungue Rodrigue Anicet , Lübbecke Joke , Brandt Peter , Harlaß Jan , Latif Mojib
Published: March 2021

Since 2000, a substantial weakening in the equatorial and southeastern tropical Atlantic sea surface temperature (SST) variability is observed. Observations and reanalysis products reveal, for example, that relative to 1982–1999, the March‐April‐May SST variability in the Angola‐Benguela area (ABA) has decreased by more than 30%. Both equatorial remote forcing and local forcing are known to play an important role in driving SST variability in the ABA. Here we show that compared to 1982–1999, since 2000, equatorial remote forcing had less influence on ABA SSTs, whereas local forcing has become more important. In particular, the robust correlation between the equatorial zonal wind stress and the ABA SSTs has substantially weakened, suggesting less influence of Kelvin waves on ABA SSTs. Moreover, the strong correlation linking the South Atlantic Anticyclone and the ABA SSTs has reduced. Multidecadal surface warming of the ABA could also have played a role in weakening the interannual SST variability.

To investigate future changes in tropical Atlantic SST variability, an ensemble of nested high-resolution coupled model simulations under the global warming scenario RCP8.5 is analyzed. SST variability in both the ABA and equatorial cold tongue is found to decrease along with reduced western equatorial Atlantic zonal wind variability.  
Changes of Köppen–Trewartha climate types in the Tibetan Plateau during the mid-Holocene, present day, and the future based on high-resolution datasets
Authors: Huang Lingxin , Huang Wei , Feng Song , Yang Kun , Chen Fahu
Published: March 2021

Based on the Köppen–Trewartha climate classification schemes, we examined the shifts in terrestrial climate regimes in the Tibetan Plateau (TP) by analyzing the WorldClim high-resolution (~25 km) downscaled climate dataset for the mid-Holocene (MH, 6,000 cal yr BP), the present day (PD, 1970-2000), and in the future (2041-2060, represented by 2050). The climate types of the PD are compared to those of the MH and the future. Our aim was to place ongoing anthropogenic climatic and environmental changes in the TP within the context of changes due to natural forcing in the three selected warm period, and to determine the differences in the spatial expression of ecosystem among these selected periods. The results indicate that the climate of the TP will continue to warm in the future. The intensity of the South Asian monsoon may increase in the future which will affect precipitation in the southern TP. There will be a significant decrease in the areas covered by polar climate, while the spatial coverage of the other climate types will increase. A tropical climate which did not exist in the MH and PD will develop in some areas and the shrinking polar climate indicates that the cryosphere of the TP will change significantly, which in turn may cause the climate system to pass a tipping point and cause irreversible consequences. The large changes in the climate regimes of the TP suggest that there will be a widespread redistribution of the surface vegetation and significant changes in plant species distributions by 2050. Compared to changes in precipitation, increasing temperature is the dominant factor that driving the change of climate types in the TP. The warming alone may cause the climate types to change in more than 20% areas by 2050.
Evaluating Satellite Capability in Supporting Traditional Air Quality Monitoring for the Finnish Ministry of the Environment
Authors: Virta Henrik , Sundström Anu-Maija , Ialongo Iolanda , Tamminen Johanna
Published: March 2021

We present the results of two projects completed for the Finnish Ministry of the Environment that assessed the capability of satellites in supporting traditional in situ air quality (AQ) measurements. These projects analysed the correlation of co-located NO2 measurements from the TROPOspheric Monitoring Instrument (TROPOMI, measuring in molec./cm2) and traditional air quality stations (measuring in µg/m3) in Finland and Europe in 2018 and 2019, and used the results to estimate annual mean ground-level NO2 concentrations in Finland’s 14 different AQ monitoring regions.

We find that the correlation is dependent on the location of the AQ station, with city stations having a higher correlation than rural background stations. This is expected, as the variability of NO2 levels in Finnish rural areas is usually within TROPOMI’s random measurement error. We also find that the estimated annual mean regional ground level NO2 concentrations compare well to the in situ measurements, as the associated uncertainties provide reliable upper estimates for ground level concentrations. These estimates were used to establish that annual NO2 concentrations were below the EU limit in two AQ monitoring regions with no active ground stations.

We also analyse TROPOMI’s and the Ozone Monitoring Instrument’s (OMI) ability to study the spatial distribution of NO2 over Finland using gridded maps. Oversampled TROPOMI measurements are able to distinguish relatively small sources such as roads, airports and refineries, and the difference in concentrations between weekdays and weekends. TROPOMI is also able to detect emissions from different sources of NO2 such as cities, mining sites and industrial areas. Long time series measurements from OMI show decreasing NO2 levels over Finland between 2005 and 2018.

The studies were conducted on behalf of the Finnish Ministry of the Environment, and showcase how satellite measurements can be used to supplement traditional air quality measurements in areas with poor ground station coverage. Launched in 2017, TROPOMI is currently the highest-resolution air quality sensing satellite, and its societal uses are only beginning to be realised. Future Sentinel missions, especially the geosynchronous Sentinel-4, will further extend satellite air quality monitoring capabilities and enable continuous daytime observations in cloud-free conditions.
Groundwater flow pattern and age distribution under transient conditions
Authors: Jin Menggui , Li Yan , Wang Jiale , Liang Xing
Published: March 2021

The distribution of groundwater ages under transient conditions are investigated by a numerical model coupled groundwater flow and age, and the nested pattern of groundwater flow are determined by the probability density function of residence time. The variation of local groundwater flow system to the fluctuation of upper boundary head evolves rapidly. During the process from the initial steady to the unsteady state, the groundwater age field evolves with simulation time and gradually reaches a new dynamic equilibrium after about 50 years. The age abrupt interface between the local and intermediate flow systems gradually shifts upward, and the scale of the local flow system gradually decreases. The groundwater ages of the regional and intermediate flow systems are mainly controlled by the long-term dynamic component of the upper boundary head, while the local flow systems are mainly influenced by the transient periodic fluctuation. The location of the stagnation points are mainly controlled by the upper boundary head. The larger head difference between recharge and discharge area is, the greater penetrated depth of the stagnation point is. The location of the stagnation point indicates the penetrated depth of the local flow system. The larger head fluctuates, the deeper stagnation point is, leading to a greater penetration depth of the local flow system. Molecular dispersion causes the scatters of residence time probability density function to aggregate near the inflection point, and the aggregation area mainly locates at the junction of basin-scale flow systems. The transition of groundwater flow field will intensify the mixing of old and new water, leading to the blurring or even disappearance of the residence time abrupt interface. The dispersion of groundwater mixing is poor in steady state, and the convective-dispersive effect gradually increases with time in unsteady state. Traditional hydraulics methods based on flow nets and stagnation points can effectively identify the groundwater flow system, but the differences in groundwater chemical characteristics and ages at long-term scales cannot be clearly described by these methods, as well as the evolution of groundwater flow system at long time scale. The groundwater residence time distribution expressed by the probability density function, which comprehensively involves the spatial and temporal information of groundwater interaction, can help accurately distinguish different groundwater flow systems at long time scales. The methods proposed in this study will act as a meaningful guidance for the delineation of groundwater flow system in the real world.
The more is not the merrier – an informed selection of climate model ensembles can enhance the quantification of hydrological change
Authors: Kiesel Jens , Stanzel Philipp , Kling Harald , Fohrer Nicola , Jähnig Sonja C. , Pechlivanidis Ilias
Published: March 2021

Production of a large ensemble of climate simulations suitable for impact assessments is an attempt to enhance our knowledge about the associated uncertainties in future projections. However, the actual quantification of the change in the climate and its impact relies on the ensemble of models selected, particularly given the wide availability of climatic simulations from various initiatives, i.e. CMIP5, CORDEX.

Here, we hypothesize that historical streamflow observations contain valuable information to investigate practices for the selection of climate model ensembles. We apply eight selection methods (based on democracy, diversity of GCM, diversity of RCM, maximum information minimum redundancy, best performing hindcasted climate depiction, best performing hydrological model, simple climate model averaging and reliable ensemble average) to subset an ensemble available from 16 combinations of Euro-CORDEX GCM-RCM by comparing observed to simulated streamflow shift of the Danube from a reference period (1960–1989) to an evaluation period (1990–2014). Simulations are carried out with the well-performing Upper Danube COSERO hydrological model, spanning a calibration and evaluation period of more than 100 years. Comparison against no selection shows that an informed selection of ensemble members improves the quantification of climate change impacts where methods that maintain the diversity and information content of the full ensemble are favourable. In addition, the method followed allows the assessment which individual climate models perform best, where only three of 16 models were able to correctly reproduce the direction of streamflow change in each season.

Prior to carrying out climate impact assessments, we propose splitting the long-term historical data and using it to test climate model performance, sub-selection methods, and their agreement in reproducing the indicator of interest, which further provide the expectable benchmark of near- and far-future impact assessments. This test can further be applied in multi-basin experiments to obtain a better understanding of uncertainty propagation and uncertainty reduction in hydrological impact studies.
General Relativistic effects acting on GNSS orbits with a focus on Galileo satellites launched into incorrect orbital planes
Authors: Sośnica Krzysztof , Bury Grzegorz , Zajdel Radosław , Kaźmierski Kamil , Ventura-Traveset Javier , Prieto Cerdeira Roberto , Mendes Luis
Published: March 2021

Three orbital effects emerging from general relativity are typically considered for Earth-orbiting satellites: the Schwarzschild effect, Lense-Thirring effect or frame-dragging, and the de Sitter or geodetic precession effect. For circular orbits and short satellite orbital arcs, the dominating Schwarzschild effect is difficult to determine, because it causes a constant radial acceleration which can be absorbed by a small modification in the gravitational constant GM term or a constant offset in the estimated semi-major axis of a satellite orbit. To separate the effects caused by the Schwarzschild effect from other orbital effects, especially those emerging from orbit modeling issues of non-gravitational accelerations, eccentric satellite orbits should be employed.

The first pair of satellites belonging to the Galileo satellite system was accidentally launched into non-circular orbits with height variations between from 17,180 km for the perigee to 26,020 km for the apogee. The eccentric orbits introduced new opportunities for the verification of the effects emerging from general relativity when employing the Galileo constellation. Galileo satellites are equipped with two techniques for precise orbit determination: microwave GNSS antennas and SLR retroreflectors which allow for deriving their orbits of superior quality.

In this study, we discuss effects in GNSS orbits emerging from general relativity. We concentrate on those effects that exceed the value of 1 mm over 1 day, thus are of fundamental importance for precise orbit determination in satellite geodesy and precise high-quality products of the International GNSS Service. We show that the semi-major axis of Galileo satellites in eccentric orbits varies between -29 mm in perigee to -9 mm in apogee due to the Schwarzschild term. For GNSS geostationary satellites with the inclination angle close to zero, the omission of the de Sitter effect may cause an error of the determination of the right ascension of ascending node exceeding the value of 1 meter after 1 day. Finally, we discuss the suitability of using GPS, GLONASS, and Galileo satellite orbits to determine the values of the Post-Newtonian Parameters γ and β and all limitations related to the observability of these parameters at GNSS heights and systematic errors emerging from non-gravitation orbit perturbations.