bluuebunny/crossref_metadata_2025 huggingface dataset:
Late Quaternary glacier-based climate reconstruction from the Southern Alps, New Zealand
Authors: Tielidze Levan , Eaves Shaun , Norton Kevin , Mackintosh Andrew , Hidy Alan
Published: March 2022

Geochronological dating of glacial landforms, such as terminal and lateral moraines, are useful for determining the extent and timing of past glaciation and for reconstructing the magnitude and rate of past climate changes. Here we report the first dataset of Late Quaternary glacial maximum extent and its deglaciation from the Ahuriri River valley, Southern Alps, New Zealand (44°23'54''S, 169°39'48''E) based on 66 beryllium-10 (10Be) surface-exposure ages from terminal-lateral moraine systems and glaciated bedrock surfaces situated at different sites of the valley. Our results show that the former Ahuriri Glacier reached its maximum extent 19.8±0.3 ka, which coincides with the global Last Glacial Maximum. By 16.7±0.3 ka, the glacier had retreat ~18 km up-valley and this deglaciation was accompanied by the formation of a shallow proglacial lake. Our surface-exposure chronology from the moraines situated upper right tributary of the Ahuriri River valley also indicates that other subsequent advance of the palaeo glacier culminated at 14.5±0.3 ka ago, while the next re-advance or still stand phases occurred at 13.6±0.3 ka. About 1000 yr later (12.6±0.2 ka), the former glacier built another prominent terminal-lateral moraine ridge in the lower section of the upper right tributary valley. In overall, our result supports the hypothesis that climate was ~5°C colder (ELA depression ~880 m) than present at 19.8±0.3 ka, while it was ~4.4°C colder (ELA depression ~770 m) at 16.7±0.3 ka. Furthermore, local air temperature was lower by 3.6°C (ELA depression ~630 m) during the 14.5-13.6 ka and by 2.0°C (ELA depression ~360 m) at 12.6 ka respectively relative to present. Our results clearly demonstrate the structure of last glacial termination in New Zealand such as strong glacier recession during this time-period in accordance of at least five glacier re advances or still stand phases. This new 10Be surface exposure dataset will help us in better understanding of past glacier-climate interactions in the Southern Alps and in the Southern Hemisphere in general.
Future projections of the Fire Weather Index (FWI) using CORDEX-CORE and CMIP5 and CMIP6 simulations.
Authors: Nogherotto Rita , Raffaele Francesca
Published: March 2022

The Fire Weather Index (FWI) is a meteorologically based index used worldwide to estimate fire danger. In the framework of the CORDEX-CORE project, we investigate how changes in relative humidity, wind, temperature and precipitation can act together in fire danger. Two regional climate models have been used at 0.22° resolution to downscale 3 global climate models from the CMIP5 project. We show results of the high resolution Fire Weather Index (FWI), calculated for 9 CORDEX domains and for two climate scenarios (RCP2.6 and RCP8.5). Mid-future (2041-2060) and Far-future (2081-2100)  fire danger changes are compared with those obtained using two ensembles of CMIP5 and CMIP6 global models. The index is projected to increase in those areas that are already affected by seasonal fires such as Spain and Southern Italy for the Mediterranean Basin, the central band of Brazil, Northern Chile, South Africa and Australia. Global and regional models FWI patterns mostly agree in the seasonal spatial distribution of fires but CORDEX-CORE simulations with their higher resolution are able to catch more in detail fires in areas not detected by global models simulations.
Modelling 500,000,000 years of climate change with a GCM – the role of CO2, paleogeography, insolation, and ice extent during the Phanerozoic
Authors: Lunt Dan , Valdes Paul
Published: March 2022

During the Phanerozoic (the last ~0.5 billion years), the Earth has experienced massive changes in climate, spanning the extensive glaciations of the Permo-Carboniferous (~300 million years ago), to the mid-Cretaceous super-greenhouse (~100 million years ago). Recently, several studies have used geological data to reconstruct global mean temperatures through this period, as a way of characterising the zeroth-order response of the Earth system to its primary forcings.  However, there has been little modelling work that has focussed on these long timescales, due to uncertainties in the associated boundary conditions (e,g., CO2 and paleogeography) and to the computational expense of carrying simulations spanning these long timescales.  Recently, paleogeographic (Scotese and Wright, 2018) and CO2 reconstructions (Foster et al, 2017) have emerged, and model and computational developments mean that we can now run large ensembles of relatively complex model simulations.  In particular, here we present an ensemble of 109 simulations through the Phanerozoic, with a tuned version of HadCM3L that performs comparably with CMIP5 models for the modern, and is also able to produce meridional temperature gradients in warm climates such as the Eocene in good agreement with proxy data.  We show that the model produces global mean temperatures in good agreement with proxy records.  We partition the response to changes in the different boundary conditions (CO2, paleogeography, ice extent, and insolation), and, through energy balance analysis, to surface albedo versus cloud versus water vapour changes.  We also illustrate the ocean and atmospheric circulation changes, with a focus on the role of the changing geography (e.g. the role of a coherent circumglobal ocean in the early Phanerozoic). 
Oceanic load tides in the western United States
Authors: Martens Hilary , Simons Mark , Rivera Luis , van Driel Martin , Boehm Christian
Published: March 2022

The solid Earth’s deformation response to surface loading by ocean tides depends on the material properties of Earth’s interior. Comparisons of observed and predicted oceanic load tides can therefore shed new light on the structure of the crust and mantle. Recent advances in satellite geodesy, including altimetry and Global Navigation Satellite Systems (GNSS), have improved the accuracy and spatial resolution of ocean-tide models as well as the ability to measure precisely three-dimensional surface displacements caused by ocean tidal loading. Here, we investigate oceanic load tides in the western United States using measurements of surface displacement made by a dense array of GNSS stations in the Network of the Americas (NOTA). Dominant tidal harmonics from three frequency bands are considered (M2, O1, Mf). We compare the empirical load-tide estimates with predictions of surface displacements made by the LoadDef software package (Martens et al., 2019), with the goal of refining models for Earth’s (an)elastic and density structure through the crust and upper mantle of the western US.
Seismic discontinuities from the Moho to 410 km depth between the Alps and Scandinavia from Sp converted waves
Authors: Kind Rainer , Schmid Stefan , Schneider Felix , Meier Thomas , Yuan Xiaohui
Published: March 2022

We use teleseismic data from all available broadband stations, permanent and mobile, in the entire area. Our processing method applies distance moveout correction, amplitude normalization, sign equalization and summation of traces with piercing points in 1° latitude times 1° longitude cells. The traces are stacked along the picked SV onset times. We obtain very clear signals from the Moho, less strong signals from velocity reductions below the Moho and again clear signals from the 410 km discontinuity. We also see locally velocity reductions just above the 410 km discontinuity. We show a number of profiles through the study area and hope to show maps of all seismic discontinuities. We compare our results with earlier observation.
Dual-frequency radar retrievals of snowfall using Random Forest
Authors: Yu Tiantian , V.Chandrasekar Chandra , Xiao Hui , Yang Ling , Luo Li
Published: March 2022

The microphysical parameters of snowfall directly impact the hydrological and atmospheric models. Dual-frequency radar retrievals of particle size distribution (PSD) parameters are developed and evaluated over complex terrain during the International Collaborative Experiment held during the Pyeongchang 2018 Olympics and Paralympic winter games (ICE-POP 2018). The observations used to develop retrievals were included the NASA Dual-frequency Dualpolarized Doppler Radar (D3R) and a collection of second-generation Particle Size and Velocity (PARSIVEL2) disdrometer. Conventional look-up table method (LUT) and random forest method are applied to the disdrometer data to develop retrievals for volume-weighted mean diameter Dm, the shape factor mu, snowfall rate S, and ice water content IWC. Evaluations are performed between D3R radar and disdrometer observations using these two methods. The results show that the random forest method performs better in retrieving microphysical parameters because the mean errors of the retrievals relative to disdrometer observations are small compared with the LUT method.
High-resolution soil organic carbon mapping at the field scale in Southern Belgium (Wallonia) 
Authors: Zhou Yue , Chartin Caroline , Van Oost Kristof , van Wesemael Bas
Published: March 2022

Accurate soil organic carbon content estimation is critical as a proxy for carbon sequestration, and as one of the indicators for soil health. Here, we collected 497 soil samples during 2015 to 2019, as well as five environmental covariates (organic carbon (OC) input, normalized difference vegetation index (NDVI), elevation, clay and precipitation) at a resolution of 30 m, aggregated these to represent agricultural fields and then compiled a soil organic carbon (SOC) content map for the agricultural region of Wallonia using Gradient Boosting Machine. We calculated OC input from both main crops and cover crops for each individual field. As the cover crops do not occur in the agricultural census, we identified cover crops based on long time-series of NDVI values obtained from the Google Earth Engine platform. The quality of the predictions was assessed by independent validation and we obtained an R2 of 0.77. The Empirical Mode Decomposition indicated that OC input and NDVI were the domain factors at field scale, whereas the remainder of the covariates determined the distribution of SOC at the scale of the entire Walloon region. The SOC map showed an overall northwest to southeast trend i.e. an increase in SOC contents up to the Sambre-Meuse valley followed by a decrease further to the South. The map shows both regional trends in SOC and effects of differences in land use and/or management (including crop rotation and frequency of cover crops) between individual fields. The field-scale map can be used as a benchmark and reference to farmers and agencies in monitoring SOC content changes and optimizing decisions for sustainable land use.
Prediction of Off-Fault Deformation from Strike-slip Fault Structures in clay and sand experiments using Convolutional Neural Networks
Authors: Cooke Michele , Elston Hanna , Chaipornkaew Laainam , Visage Sarah , Souloumniac Pauline , Mukerji Tapan
Published: March 2022

Crustal deformation occurs both as localized slip along faults and distributed deformation off faults; however, we have few robust geologic estimates of off-fault deformation over multiple earthquake cycles. Scaled physical experiments simulate crustal strike-slip faulting and allow direct measurement of the ratio of fault slip to regional deformation, quantified as Kinematic Efficiency (KE). We offer an approach for KE prediction using a 2D Convolutional Neural Network (CNN) trained directly on images of fault maps produced by physical experiments of strike-slip loading of wet kaolin. A suite of experiments with different loading rate and basal boundary conditions, contribute over 13,000 fault maps throughout strike-slip fault evolution. Strain maps allow us to directly calculate KE and its uncertainty, utilized in the loss function and performance metric. The trained CNN achieves 91% accuracy in KE prediction of an unseen dataset. We then apply this CNN trained on wet kaolin experiments to strike-slip experiments in dry sand. The different rheology of sand and kaolin may lead to different relationships between fault geometry and off-fault deformation, which can be detected by differences in the predictive power of the CNN trained only on kaolin.  We also apply the trained CNN to crustal maps of off-fault deformation over coseismic, 10ka and 1 Ma time scales. The CNN predicted off-fault deformation overlap available geologic estimates.
A 210Pbex accumulation-decay model for dating moraine soils to trace glacier retreat time
Authors: Jiacun Chen
Published: March 2022

Abstract: This report exploring the potential for using the natural fallout radionuclide 210Pbex to date moraine soils for tracing glacier retreat. Based on the physical processes of 210Pbex deposition, decay and losses due to runoff, a 210Pbex accumulation-decay model was developed, where = 210Pbex inventory (Bq·m-2); = annual inventory of 210Pbex deposition (Bq·m-2); = 210Pb decay coefficient (0.969); = time span (years); b and c = 210Pbex loss coefficients for the runoff pathway. The model was validated with data obtained from the Hailuogou Glacier Valley, Mt. Gongga, in 2016, where nine glacier retreat moraine points were recorded from 1910–1990 along a retreat length of 1750 m in the valley. 210Pbex inventories increased from 3,669.6 ± 218.5 Bq·m-2 at the site where the glacier retreated in 1990 to 10,718.9 ± 167.4 Bq·m-2 in 1910. The coefficients of b = 0.6006 and c = 0.9764 were derived from the 210Pbex inventories at the nine sites with recorded glacier retreat times that were marked with special stone and terrain features. The goodness-of-fit (GOF) for the model predictions of glacier retreat times is 65.5%. The results obtained confirm that the fallout radionuclide 210Pbex has potential for dating moraine soils in other cryosphere regions throughout the world as well as for other types of records forming sedimentary landform sequences such as soils on debris flows and alluvial fans.

Keywords: 210Pbex accumulation-decay model, 137Cs, dating moraine soils, glacier retreat time.  
Investigating microbial constraints on hydrocarbon processing in Guaymas Basin subseafloor sediments with sill intrusions 
Authors: Teske Andreas, P. , Mara Paraskevi , Vázquez Mirna , Baker Brett , Morono Yuki , Edgcomb Virginia ,   Expedition 385 Scientists
Published: March 2022

Guaymas Basin is a young marginal rift basin in the Gulf of California characterized by active seafloor spreading and rapid deposition of organic-rich sediments derived from highly productive overlying waters and terrigenous sediments from nearby continental margins. Catalyzed by the steep geothermal gradient, sedimentary organic material of photosynthetic origin turns into a diverse spectrum of hydrocarbons that accumulate especially in deep, hot sediments, and might supply substrates for hydrocarbon-degrading microorganisms. The “from magma to microbe” perspective on these processes motivated International Ocean Discovery Program Expedition 385“Guaymas Basin Tectonics and Biosphere.”

Hydrocarbon concentrations were determined in sediment samples selected from eight drilling sites on the flanking regions and in the northern axial graben of Guaymas Basin. Total petroleum hydrocarbon (C9-C44) concentrations increased from ca. 50-250 mg/kg towards >2000 mg/kg at in-situ temperatures above 80°C. A similar increase from ca. 10 mg/kg towards >100 mg/kg was observed for total saturated hydrocarbons. These gradients are shaped by abiotic hydrocarbon generation above 80°C at depth, and possibly by microbial hydrocarbon degradation at cooler temperatures in the upper sediment column. In a two-pronged approach, we are currently investigating the activity of bacterial/fungal consortia, isolated from Guaymas Basin surficial sediments, in the oxidation of selected alkanes and polyaromatics that occur at Guaymas Basin. In parallel, we explore the diversity, depth range and in-situ temperature range of bacteria, archaea and fungi in the Guaymas Basin subsurface sediments using PCR and metagenomic sequencing, to constrain microbial hydrocarbon cycling in the deep subsurface. Updates on these ongoing investigations will be presented.
Assessment of Transfer Learning Techniques to Improve Streamflow Predictions in Data-Sparse Regions
Authors: Khoshkalam Yegane , Rahmani Farshid , Rousseau Alain N. , Abbasnezhadi Kian , Shen Chaopeng , Foulon Etienne
Published: March 2022

Reliable streamflow predictions are critical for managing water resources for flood warning, agricultural irrigation apportionment, hydroelectric production, to name a few. However, there are geographical heterogeneities in available observed streamflow data, river basin geophysical attributes, and meteorological data to support such predictions. Moreover, in data-sparse regions, both process-based and data-driven models have difficulties in being sufficiently calibrated or trained; increasing the difficulty to achieve satisfactory predictions. That being mentioned, it is possible to transfer knowledge from regions with dense and available measured data to data-sparse regions. In earlier work, we have shown that transfer learning based on a long short-term memory (LSTM) network, pre-trained over the conterminous United States, could improve daily streamflow prediction in Quebec (Canada) when compared to a semi-distributed hydrological model (HYDROTEL). The dataset used for pre-training (source dataset) was the Catchment Attributes and Meteorology for Large-sample Studies (CAMELS), while the data for the basins located at the target locations (local dataset) were extracted from the Hydrometeorological Sandbox-École de Technologie Supérieure (HYSETS). Both datasets provide access to various types of information with different spatial resolutions. While HYSETS is generally spanning from 1950 to 2018, the temporal interval for most of the basins reported in CAMELS goes back to 1980. The types of data included in both CAMELS and HYSETS include daily meteorological data (precipitation, temperature, etc.), streamflow observations, and basins physiographic attributes (i.e., considered time-invariant or static). In this work, the techniques applied to further improve streamflow simulations included the use of: (i) streamflow observations and simulated flows from HYDROTEL as input to the LSTM model, (ii) different forcing (meteorological data) and static attribute data from the source and the local datasets, and (iii) additional basins from HYSETS with similar climatological features for model training. The ultimate goal was to improve the accuracy of the predicted hydrographs with an emphasis on enhancing the prediction of peak flows by transfer learning while using the Kling-Gupta efficiency (KGE) and Nash-Sutcliffe efficiency (NSE) metrics. This investigation has revealed the benefits of using transfer learning techniques based on deep learning models to improve streamflow predictions when compared to the application of a distributed hydrological models in data-sparse regions.
Assessing the potential for mass movements of the Danube Bend (Hungary) endangering transport infrastructure: an integration of field observations and UAV and other imagery
Authors: Székely Balázs , Rozman Gábor , Bitiukova Ekaterina , Vörös Fanni , Kovács Béla
Published: March 2022

The Danube Bend is one of the environmental hotspots of Northern Hungary.
Numerous geodynamic, geomorphological, fluvial and anthropogenic processes contribute to the formation of spectacular and dynamic landscapes, which result in mass movements of varying magnitude, threatening the transport infrastructure crossing the area. The combination of continuous uplift and the incision of the Danube, the largest river in Central Europe, has created steep slopes in critical or sub-critical state for mass movements. Recent landslides, which have brought road and rail traffic to a standstill for considerable periods, have shown that research into the (in)equilibrium of slopes is an important issue.

For this study, a variety of remote sensing observations have been integrated, including satellite and UAV imagery, LiDAR data and derived data, as well as field observations Workflows such as laser scanning and Structure from Motion to create digital surface and digital terrain models with an accuracy of tenths of a metre horizontally and a few centimetres vertically.
Vegetation is also an important issue, as it can partly stabilise slopes and can provide protection, so detailed mapping has also been carried out. Geomorphological observations, satellite and recent UAV imagery were used to map the potential for mass movements, and a rough estimate of the amount of loose material available for mass movements was made. The results provide important spatial and temporal input for road safety and the maintenance and safe upkeep of roads and railways.

MÁV Hungarian State Railways is thanked for providing facilities and data.

FV is supported by EFOP-3.6.3-VEKOP-16-2017-00001: Talent Management in Autonomous Vehicle Control Technologies – (financed by the Hungarian Government & the European Social Fund).

BK is supported by the NRDI Fund of Hungary, Thematic Excellence Programme no. TKP2020-NKA-06 (National Challenges Subprogramme) funding scheme.
Assessment of Flood-Damaged Cropland Trends Under Future Climate Scenarios Using Convolutional Neural Network
Authors: Lazin Rehenuma , Shen Xinyi , Anagnostou Emmanouil
Published: March 2022

Every year flood causes severe damages in the cropland area leading to global food insecurity. As climate change continues, floods are predicted to be more frequent in the future. To cope with the future climate impacts, mitigate damages, and ensure food security, it is now imperative to study the future flood damage trends in the cropland area. In this study, we use a convolutional neural network (CNN) to estimate the damages (in acre) in the corn and soybean lands across the mid-western USA with projections from climate models. Here, we extend the application of the CNN model developed by Lazin et. al, (2021) that shows ~25% mean relative error for county-level flood-damaged crop loss estimation. The meteorological variables are derived from the reference gridMet datasets as predictors to train the model from 2008-2020. We then use downscaled climate projections from Multivariate Adaptive Constructed Analogs (MACA) dataset in the trained CNN model to assess future flood damage patterns in the cropland in the early (2011-2040), mid (2041-2070), and late (2071-2100) century, relative to the baseline historical period (1981-2010). Results derived from this study will help understand the crop loss trends due to floods under climate change scenarios and plan necessary arrangements to mitigate damages in the future.

 

Reference:

[1] Lazin, R., Shen, X., & Anagnostou, E. (2021). Estimation of flood-damaged cropland area using a convolutional neural network. Environmental Research Letters, 16(5), 054011.
Accelerating the Lagrangian particle tracking in hydrologic modeling at continental-scale
Authors: Yang Chen , Ponder Carl , Wang Bei , Tran Hoang , Zhang Jun , Swilley Jackson , Condon Laura , Maxwell Reed
Published: March 2022

Unprecedented climate change and anthropogenic activities have induced increasing ecohydrological issues. Large-scale hydrologic modeling of water quantity is developing rapidly to seek solutions for those issues. Water-parcel transport (e.g., water age, water quality) is as important as water quantity to understand the changing water cycle. However, current scientific progress in water-parcel transport at large-scale is far behind that in water quantity. The known cause is the lack of powerful tools to handle observations and/or modeling of water-parcel transport at large-scale with high spatiotemporal resolutions. Lagrangian particle tracking based on integrated hydrologic modeling stands out among other methods because it accurately captures the water-parcel movements. Nonetheless, Lagrangian approach is computationally expensive, hindering its broad application in hydrologic modeling, particularly at large-scale. EcoSLIM, a grid-based particle tracking code, calculates water ages (e.g., evapotranspiration, outflow, and groundwater) and identifies source water composition (e.g., rainfall, snowmelt, and initial subsurface water), working seamlessly with the integrated hydrologic model ParFlow-CLM. EcoSLIM is written in Fortran and is originally parallelized by OpenMP (Open Multi-Processing) using shared CPU memory. As a result, we accelerate EcoSLIM by implementing it on distributed, multi-GPU platform using CUDA (Compute Unified Device Architecture) Fortran.

We decompose the modeling domain into subdomains. Each GPU is responsible for one subdomain. Particles moving out of a subdomain continue moving temporarily in halo grid-cells around the subdomain and then are transferred to the neighbor subdomains. Different transfer schemes are built to balance the simulation accuracy and the computing speed. Particle transfer leverages the CUDA-aware MPI (Message Passing Interface) to improve the parallel efficiency. Load imbalance among GPUs induced by irregular domain boundaries and heterogeneity of flow paths is observed. A load-balancing scheme, borrowed from Particle-In-Cell and modified based on the characteristics of EcoSLIM, is established. The simulation starts on a number of GPUs fewer than the total scheduled GPUs. The manager MPI process activates an idle GPU for a subdomain once the particle number on its current GPU(s) is over a specified threshold. Finally, all scheduled GPUs are enabled. Tests of the new code from catchment-scale (the Little Washita watershed), to regional-scale (the North China Plain), and then to continental-scale (the Continental US) using millions to billions of particles show significant speedup and great parallel performance. The parallelized EcoSLIM is a promising tool for the hydrologic community to accelerate our understanding of the terrestrial water cycle beyond the water balance in the changing world.
Numerical Modelling and Validation for Three-dimensional Boulder Transport during Tsunami
Authors: Xu Xiujun , Tang Hui
Published: March 2022

Coastal boulders are usually the results of extreme wave events, and many imply tsunami events, which can cause significant damage and dramatic coastline changes. However, the interpretation of boulder accumulations still remains challenging. Recent boulder transport studies primarily focus on steady flow conditions with discontinuous simulations. Time-varying characteristics of tsunami waves and topography have been ignored in previous researches. To explore the boulder transport mechanisms under different boundary conditions and topographies, we establish a new sediment transport model that includes three different transport modes (sliding, suspension, and rolling) and tracks the boulder movement processes in actual topography and flow conditions. Using the field observation distribution of boulders during Chile 2010 Tsunami at Bucalemu, we validate the stability and accuracy of the boulder transport model and invert the potential hydrodynamic properties of the tsunami. The results show that our model can effectively simulate and predict the tsunami boulder transport hazard and hydrodynamic characteristics. The initiation and transport of boulders in interaction with various geophysical flows, including tsunamis, is essential for understanding geophysical flows dynamics, assessing natural hazards, and also for interpreting sedimentary evidence.
Determination of Rill Erodibility and Critical Shear Stress of Saturated Purple Soil Slopes
Authors: Li Dandan , Chen Xiaoyan , Han Zhen , Gu Xiaojie , Li Yanhai
Published: March 2022

The hydrological conditions near the soil surface influence the soil erosion process, as determined by the soil erodibility and critical shear stress. The soil erodibility and critical shear stress of saturated purple soil slopes were computed and compared with those of unsaturated purple soil slopes. The detachment capacities computed through the numerical method (NM), modified numerical method (MNM) and analytical method (AM), from rill erosion experiments on saturated purple soil slopes at different flow rates (2, 4, and 8 L min−1) and slope gradients (5, 10, 15, and 20°), were used to comparatively compute the soil erodibility and critical shear stress. The computed soil erodibilities and critical shear stresses were also compared with those of unsaturated purple soil slopes. At the different slope gradients ranging from 5° to 20°, there were no significant differences in the soil erodibilities of the saturated purple soil and also in those of the unsaturated purple soil. The critical shear stresses slightly varied with the slope gradients. The saturated purple soil was relatively significantly more susceptible to erosion. The NM overestimated the soil erodibility of both saturated and unsaturated soils by 31% and underestimated the critical shear stress. The MNM yielded the same soil erodibility and critical shear stress values as the AM. The results of this study supply parameters for modeling rill erosion of saturated purple soil slope.
Introducing s-Ink.org – a community portal for sharing quality science graphics
Authors: Shephard Grace E. , Crameri Fabio , Straume Eivind O.
Published: March 2022

Everyone, be it scientists, students, teachers, media outlets, or the public, regularly turn to a “google” image search when exploring a scientific concept. Yet, the recovered images are often suboptimal in terms of [1] scientific quality and accuracy, and/or [2] the aesthetics and artistic value. One such common example from the solid Earth sciences, is the (false) impression that the Earth’s mantle is molten, red, and that mantle plume upwellings exclusively coincide with mid-oceanic ridges. Another common issue might be that the labels or content are not sufficient for the users purpose (e.g. axes not indicated, features not labelled). Furthermore, scientists often spend a lot of time and energy in making images (whether for manuscripts, presentations or outreach) and are willing to share their image for anyone to re-use or modify. However, a central, convenient means to share them is lacking and, crucially, them to be readily found by others. To help address this, we have created the online s-Ink collection (s-Ink.org; Crameri et al., in submission). It is a free, community-driven exchange platform for high quality, science-related graphical products. We document several key graphical quality measures to ensure that submissions maximise accessibility (e.g. via scales or colour choices), broaden applicability (e.g. through modifiable vector-based options), and facilitate creativity (e.g. via graphic design principles). Products can include conceptual illustrations, templates, data visualizations, animations, icons, and more. Contributions will be shared with the entire community under a clearly stated license, so that individual efforts will be acknowledged. The content can be downloadable either directly from the s-Ink website or via a link to an external site or repository (for example, in the case of large or pre-existing content). With this abstract we will showcase the website, discuss data and science visualization, encourage feedback and invite contributions all EGU22 attendees.
Simulations of North American ice sheet at the LGM with FAMOUS-BISICLES and its sensitivity to global temperatures
Authors: Sherriff-Tadano Sam , Gandy Niall , Ivanovic Ruza , Gregoire Lauren , Lang Charlotte , Gregory Jonathan , Smith Robin
Published: March 2022

Understanding the response of ice sheets to global temperature changes is a critical issue for the climate community. To accurately simulate future ice sheet evolution, we need to know the strength of feedbacks between the climate and ice sheets. Testing the ability of coupled climate-ice sheet models to simulate past ice sheet extent can provide a way to evaluate the models and ground truth projections. One example is the Last Glacial Maximum (LGM), when huge ice sheets covered the Northern Hemisphere, especially over the North America. Here, we performed simulations of the North American ice sheet and climate of the LGM with a recently updated ice sheet-atmosphere coupled model Famous-Ice (Smith et al. 2021, Gregory et al. 2020). The model consists of a low-resolution atmospheric general circulation model Famous (Smith et al. 2008) and an ice sheet model BISICLES (Cornford et al. 2013). It calculates the surface mass balance over ice sheets based on an energy budget scheme and incorporates an updated albedo scheme, which accounts for albedo changes associated with modifications in surface air temperature, grain size and density of the snow. The atmospheric model reproduces the surface mass balance of the modern Greenland ice sheet reasonably well (Smith et al. 2021). Simulations of projections of future sea-level rise (Gregory et al. 2020) and the LGM (Gandy et al. in prep) have also been performed with Famous-Ice using a different ice sheet model GLIMMER.

We present simulations of the LGM with interactive ice sheets in North America and Greenland using FAMOUS-BISICLES. Uncertain input parameters controlling the surface temperatures and ice albedo are varied in our simulations. The global temperature is specified by applying fixed sea surface temperature in the atmospheric model producing a global cooling that ranges from -3K to -6.5K in the simulations. The bare ice minimum albedo is varied from 0.2 to 0.7, which corresponds to the range in PMIP3 models. Our results show a better representation of North American ice sheet when forced with a colder LGM (-6.5K) and high bare ice albedo. We will further discuss potential roles of model biases and compare our results with simulations performed with FAMOUS-GLIMMER (Gandy et al. in prep).
Azimuthal and latitudinal changes of the near-Earth magnetotail current sheet structure during multiple dipolarizations of a substorm
Authors: Nakamura Rumi , Slavin James , Schmid Daniel , Sun Weijie ,   The April 10, 2020 BepiColombo Earthflyby Substorm Study Team
Published: March 2022

Using data from fleet of spacecraft in the near-Earth night-side magnetosphere, we study the three-dimensional evolution of the magnetotail current sheet following the expansion phase onset of a moderate substorm (AL ~-450 nT) after 09:10 UT, April 10, 2020.  Magnetotail disturbances are observed by GOES 17 and Cluster in the midnight region.  During this substorm the BepiColombo spacecraft traversed the premidnight region duskward at 9-11 RE downtail during its Earth Flyby.  The four Cluster satellites, which were separated mainly in north-south direction, crossed the inner magnetosphere successively from north to south. They enable us to monitor the vertical (latitudinal) structure and the sequential changes of the magnetotail current sheet until the end of the recovery phase of the substorm, around 11 UT.  Multiple dipolarizations and multiple transient field-aligned currents (FAC) were observed by Cluster.  The first dipolarization around the onset, which was detected by GOES 17 in the geosychronous region, was accompanied by a plasma sheet expansion observed by the two leading Cluster 3 and 4 satellites. BepiColombo in the premidnight region observed continuous thinning of the current sheet, a typical signature of the growth phase, accompanied by a couple of transient magnetic signatures indicating flux rope and/or TCR formation around the onset.  Cluster 1 detected the most intense FAC associated with the dipolarization event starting around 10 UT, when the two BepiColombo MPO and MIO spacecraft observed dipolarization and energetic particle injection. These observations indicate the duskward and tailward expansion in the course of multiple dipolarizations.  Using the unique dataset from the multi-point observations, we examine the structure of the large-scale current sheet and analyze the embedded transient intense field-aligned current disturbances. By also comparing with an empirical magnetic field model, we obtain the changes of the near-Earth magnetotail structure during the multiple dipolarization event.
Temporal characteristics of debris flow surges
Authors: Zhang Jun , Li Yong , Guo Xiaojun , Yang Taiqiang , Liu Daochuan , Yu Bin
Published: March 2022

Abstract: Debris flow is one of the most destructive geomorphological events in mountainous watersheds, which usually appears in form of successive surge waves as observed all over the world. In particular, debris flows in the Jiangjia Gully (JJG) in southwest China have displayed a great variety of surge phenomena; each debris flow event contains tens or hundreds of separate surges originating from different sources. Therefore, the surge sequence of an event must encode the information of debris flow developing. The UAV (unmanned aerial vehicle) photos provide an overview of debris-flow sources, showing the different potential of debris flow; and surge sequences present various patterns responding to the rainfall events. Then the variety of rainfalls and material sources determine the diversity of surge sequence. Using time series analysis to the surge discharge sequences, we calculate the Hurst exponent, the autocorrelation function, and the power spectrum exponent, and find that all the sequences commonly share the property of long-term memory and these parameters are correlated in exponential form, with values depending on rainfall patterns. Moreover, all events show a gross trend of discharge decay, despite the local rainfall process, which implies the intrinsic nature of the surge sequence as a systematic behavior of watershed. It is expected that these findings are heuristic for establishing mechanisms of debris flow initiation and evolution in a watershed.
Distribution and Sedimentation of Microplastics in Taihu Lake
Authors: zhang qiji , qian xin
Published: March 2022

Microplastics have been reported in environmental media for decades, but gaps in our knowledge about them still remain. We investigated the third biggest freshwater lake in China – Taihu Lake – and the 30 major rivers around it. Microplastics were detected in lake water and sediment, and in river water, at abundances varying from 1.7 to 8.5 items/L, 460 to 1380 items/kg and 1.8 to 18.2 items/L, respectively. Inflow rivers were more polluted with microplastics than outflow rivers. The most common shape was fragment. Microplastic sizes of < 100 μm dominated in inflow rivers, 100–200 μm dominated in lake water and outflow rivers. The average size of microplastics in outflow rivers (200.4 μm) was larger than that in inflow rivers (166.2 μm). Microplastics of < 100 μm only accounted for 28% in the lake surface water but were as high as 70% in the sediment, indicating that smaller microplastics may more easily settle in the lake. The main components of the microplastics were identified as being polyvinyl chloride and polyethylene. There were about 1.2× 106 items/s microplastics entered Taihu Lake. Four main rivers located at northwestern lake accounted for 79% of the total inflow microplastic fluxes.
Energy efficiency through household water use efficiency: a survey on public perception of household water and water-related energy use in Ireland
Authors: Bello-Dambatta Aisha , Bellini Roberta , Williams Prysor
Published: March 2022

We recently launched a citizen science project on household water-energy efficiency as part of the cross-border, interdisciplinary Dŵr Uisce research project on improving the energy performance and long-term sustainability of the water sectors in Ireland and Wales. Citizen science is emerging as a critically important means of democratising science by engaging the public to contribute to the creation of solutions to some of the most important topical global challenges like climate change.

The main aim of the citizen science project is to engage with and collaborate with the public to improve understanding of water-related energy use in Irish homes to help assess the most effective means of improving the efficiency and sustainability of household water-related energy use through water use efficiency.

The project consists of two key parts: a cross-sectional survey that assessed the current public perception of household water and water-related energy use, followed by a longitudinal study where participants record water use at home to assess the actual current household micro-component water use and associated water-related energy use. The findings of the project will be used to quantify the potential of climate action through household water-energy use efficiency in reducing emissions and costs, and to develop up-to-date best practice guidelines for climate action from household water use efficiency.

We will be presenting the results of the cross-sectional survey on current perception of household water and water-related energy use. The survey, open to all households in the Republic of Ireland, ran for 7 weeks in September and October 2021 and a prize draw was used to incentivise participation. We received a total of 265 responses of which 23 responses were partially completed responses (8.7%); however, data available for non-completed responses does not indicate any difference compared to completed responses, and it may well be possible some non-completed responders went on to restart the survey after it timed out. The survey consisted of 60 questions grouped by general questions on household water use (e.g., water provision, and water and energy metering) and household water use types (bathroom, kitchen, cleaning and laundry, and outdoor water use). Itwas designed to be disaggregated by the Irish Central Statistics Office (CSO) household demographic and socio-economic census as a segmentation framework: location, household type, household age, housing status, employment status, household income and household size (disaggregated by age). The responses are found to be generally representative compared with the most recent 2016 census data in terms of location, employment status, housing status, household income, household type, and household age.
Microbial cell distribution in the Guaymas Basin subseafloor biosphere, a young marginal rift basin with rich organics and steep temperature gradient
Authors: Morono Yuki , Teske Andreas , Galerne Christophe , Bojanova Diana , Edgcomb Virginia , Meyer Nicolette , Schubert Florian , Toffin Laurent ,   IODP Expedition 385 Scientists
Published: March 2022

Guaymas Basin is a young marginal rift basin in the Gulf of California characterized by active seafloor spreading and rapid sediment deposition, including organic-rich sediments derived from highly productive overlying waters and terrigenous sediments from nearby continental margins. The combination of active seafloor spreading and rapid sedimentation within a narrow basin results in a dynamic environment where linked physical, chemical, and biological processes regulate the cycling of sedimentary carbon and other elements. This continuum of interrelating processes from magma to microbe motivated International Ocean Discovery Program Expedition 385 and is reflected in its title, “Guaymas Basin Tectonics and Biosphere.”

During IODP Expedition 385, organic-rich sediments with sill intrusions on the flanking regions and in the northern axial graben of Guaymas Basin (in eight sites) were drilled and core samples were recovered. Those cored samples were examined for their microbial cell abundance in a highly sensitive manner by density-gradient cell separation at the super clean room of Kochi Core Center, Japan, followed by direct counting on fluorescence microscopy. Cell abundance in surficial seafloor sediment (~109 cells/cm3) was roughly 1000 times higher than the bottom seawater (~106 cells/cm3) and gradually decreased with increasing depth and temperature. In contrast to the cell abundance profile observed at Nankai Trough (IODP Exp. 370), the gradual decrease of cell abundance was observed up to around 75ºC, and we detected microbial cells even at hot horizons above 100ºC.

We will present the overview of the microbial cell distribution in the Guaymas Basin and discuss its relation to the current and past environmental conditions, e.g., temperature and sill-intrusion, etc.
Control Simulation Experiments with the Lorenz-96 Model
Authors: Sun Qiwen , Miyoshi Takemasa , Richard Serge
Published: March 2022

The successful development of numerical weather prediction (NWP) helps better preparedness for extreme weather events. Weather modifications have also been explored, for example, when enhancing rainfalls by cloud seeding. However, it is generally believed that the tremendous energy involved in extreme events prevents any attempt of human interventions to avoid or to control their occurrences.

In this study, we investigate the controllability of a chaotic dynamical system by adding small perturbations to generate amplified effects and to prevent extreme events. The high sensitivity to initial conditions would ultimately lead to modifications of extreme events with infinitesimal perturbations. Based on this idea, we extend the well-known observing systems simulation experiment (OSSE) and design the control simulation experiment (CSE) with the Lorenz-96 model, a widely-used toy system in data assimilation studies. We also study the sensitivity of the control to the amplitude of the perturbation, the forecast length, the localized perturbation and the partial observations. The CSE would be applicable to other chaotic dynamical systems including realistic numerical weather prediction models.
Analysis of correlations between geomagnetic storms and emergency shutdowns in the part of Almaty power grid for 2016-2021
Authors: Nurgaliyeva Kuralay
Published: March 2022

In this research the analysis of shutdowns in long power line SS147AL169A in Almaty power grid for 2016-2021 was done. For the analyzed period, there were 16 emergency shutdowns. 6 of them occurred due to evident external causes. Other 10 cases analyzed for the possibility of a connection with the geomagnetic environment. Initial analysis showed a possible connection between the automatic operation of relay protection and the presence of geomagnetically induced currents. This is due to the geomagnetic situation, which was before the moment the relay was triggered. At the moment, more detailed calculations are being carried out.

This research has been/was/is funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant No. AP00000000).