julilili42/papers huggingface dataset:
Disaster risk reduction for a resilient world: An online transdisciplinary course to enhance global awareness in training and education&#160;
2024-03-08

In today&amp;#8217;s world, we face many complex societal challenges such as climate change and disaster risk that require input from actors and stakeholders from different fields and disciplines. In higher education, this is made possible, in part, through transdisciplinary course programs. These programs offer courses that equip students and researchers with transdisciplinary competencies and expertise needed to co-create knowledge, develop and practice intercultural and problem-solving skills, and enable change collaboratively.Despite such efforts, many higher education institutes have yet to adapt to the increasingly dynamic world. This is especially evident in geosciences, a field that plays an essential role in addressing key societal issues. While some advances have been made, there is still a significant lack of diversity and discipline integration in geosciences, where many courses are attended and taught by those working within the disciplinary boundaries.&amp;#160;To address this issue, Global Awareness Education, a part of the Transdisciplinary Course Program at the University of T&amp;#252;bingen (Germany), has been offering courses on global issues related to geosciences. These courses engage students of all disciplines (not just geosciences) from both the University of T&amp;#252;bingen and CIVIS (an alliance of 11 leading universities across Europe). Topics covered include: disaster risk reduction, environmental impact assessment, environmental communication, global soil health, climate crisis, indigenous knowledge in climate change as well as art-science collaborative excursions. These courses are interactive and hands-on, and are taught by international teams of educators, researchers and practitioners from the social and natural sciences.Here we focus on our recent (winter semester 2023/24) piloting of one course at the University of T&amp;#252;bingen titled Disaster Risk Reduction for a Resilient World. This course has been adapted from an online, self-led training module that was originally developed for natural hazard students and researchers interested in strengthening their engagement in disaster risk reduction (DRR). We altered the course to make it accessible to students from all disciplines. Specific topics include cascading multi-hazard environments, effective partnerships, stakeholder engagement, theory of change, cultural understanding and positionality, indigenous knowledge, equitable access to information, people-centered DRR, and DRR and sustainable development.Using a survey questionnaire, we assessed students&amp;#8217; perspectives on their skills acquisition, knowledge and their levels of confidence to contribute more effectively to the integrated work needed to improve DRR activities. We also assessed what actions students plan to take as a result of completing the course. In this presentation, we share these results, discuss some challenges we faced in course implementation, and offer potential solutions to these challenges.
Characterizing Nonlinearities in ENSO Dynamics Using Hybrid Machine Learning Models
2024-03-08

Event-to-event differences of the El Ni&amp;#241;o Southern Oscillation (ENSO) result in different patterns of extreme climate conditions globally, which requires ENSO forecasts that accurately predict both the likelihood and the type of an event. One question regarding predictable ENSO dynamics is the extent to which they may be captured by multivariate linear dynamics and, relatedly, whether predictable nonlinearities must be accounted for or may be treated stochastically.In this study, we combine Recurrent Neural Networks with the Linear Inverse Model (LIM) to assess the role of predictable nonlinearities and non-Markovianity in the evolution of tropical Pacific sea surface temperature anomalies. We observe that modeling nonlinearities significantly enhances the forecast accuracy, particularly in the western tropical Pacific within a 9 to 18-month lag time. Our results indicate that the asymmetry of warm and cold events is the main source of the nonlinearity. Moreover, we demonstrate that the predictability of the Hybrid-model can be reliably inferred from the theoretical skill of the LIM whereas a similar assessment is not possible in pure deep learning models.
Stalagmite-based cave flood records as a proxy for reconstruction of extreme rainfall frequency over the Holocene from two different cave sites in South-eastern Brazil
2024-03-08

Extreme rainfall events are expected to become more frequent and intense worldwide due to climate change, as indicated by the Sixth Assessment Report from the Intergovernmental Panel on Climate Change. This includes the most populated region in South America, southern and southeastern Brazil, where several studies document a consistent pattern of intense rainfall increases. The increasing intensity and frequency of these events have a direct impact on society, triggering natural disasters such as flash floods and landslides, accounting for 74% of natural disaster-related deaths and an impact of 6.2 billion dollars between 2010 and 2019. The scarcity of available data and limitations to the instrumental period hamper assessments regarding the frequency and intensity of extreme rainfall events beyond this period. This limitation precludes the assessment of how larger-scale forcings, atmospheric circulation, and environmental changes can affect the frequency and magnitude of those events. Previous studies show that extreme rainfall events in the study area are caused by Extratropical Cyclones and Frontal Systems, as well as the South Atlantic Convergence Zone. Our 5-year cave flood monitoring indicates that extreme rainfall events are responsible for triggering the cave floods, therefore stalagmites subjected to those cave floodings can be used as a proxy for extreme rainfall events. In this context, we use a large set of Holocene stalagmites collected from two different caves (Lage Branca and Malfazido cave). Reconstructions are based on detrital layers within stalagmites identified using thin-section petrography. Records from Malfazido cave exhibit a higher sensitivity to high-frequency cave flood events (subdecadal to decadal frequency), as demonstrated by reconstructions. In contrast, Lage Branca records are sensitive to high-magnitude events (multidecadal, centennial, or multi-centennial frequency) due to their high topographic position (20-50 m above the underground river) and slow growth rate. We present new cave flood records for Malfazido and Lage Branca caves, covering the last 7000 years and 10000 years, respectively. Periods of increased occurrence of flood layers in the stalagmites are observed for both caves around 4.1 kyr during the transition from the Middle to Late Holocene. For higher-frequency events, a remarkable increase in cave flood frequency is observed during the Little Ice Age. To assess the mean climate state in which the changes in frequency are observed, a high-resolution multiproxy record based on stalagmites (&amp;#948;13C, &amp;#948;18O, trace elements) is used to reconstruct paleohydrology and environmental conditions. New paleoflood cave records from both caves are used to assess how the frequency of extreme rainfall events can vary over time, providing insights into how different forcings and climate changes, such as atmospheric circulation changes and variations in SSTs, can affect the frequency of those events.
Frontoparietal network integrity supports cognitive function despite atrophy and hypoperfusion in pre-symptomatic frontotemporal dementia: multimodal analysis of brain function, structure and perfusion
2024-03-08

ABSTRACT INTRODUCTION Genetic mutation carriers of frontotemporal dementia can remain cognitively well despite neurodegeneration. A better understanding of brain structural, perfusion and functional patterns in pre-symptomatic stage could inform accurate staging and potential mechanisms. METHODS We included 207 pre-symptomatic genetic mutation carriers and 188 relatives without mutations. The grey matter volume, cerebral perfusion, and resting-state functional network maps were co-analyzed using linked independent component analysis (LICA). Multiple regression analysis was used to investigate the relationship of LICA components to genetic status and cognition. RESULTS Pre-symptomatic mutation carriers showed an age-related decrease in the left frontoparietal network integrity while non-carriers did not. Executive functions of mutation carriers became dependent on the left frontoparietal network integrity in older age. DISCUSSION The frontoparietal network integrity of pre-symptomatic mutation carriers showed a distinctive relationship to age and cognition compared to non-carriers, suggesting a contribution of the network integrity to brain resilience, despite atrophy and hypoperfusion.
Comparison of advanced multicriteria decision and FAO models for land suitability assessment&#160;
2024-03-08

Land suitability assessment is an important process in modern agricultural management, involving the evaluation of various factors such as soil properties, climate, relief, hydrology, crop varieties and socio-economic considerations. Various methods have been used to assess land suitability, such as the parametric method developed by Sys et al. (1991) and the FAO (1976) approach to land evaluation. Determining the relative weighting of the factors that influence land suitability is a particularly challenging step in the evaluation process. An alternative to these procedures is the use of multi-criteria decision making (MCDM) techniques, which enable land managers and policy makers to make informed decisions about land use and development. Spatial MCDM techniques include complex spatial data and methods such as the Technique of Preference Ordering by Similarity to the Ideal Solution (TOPSIS), which are widely used in the agricultural sector. TOPSIS determines the optimal alternative according to the principle of minimizing the proximity to the ideal solution and maximizing the distance to the negative ideal solution. The aim of this study was to assess the suitability of land for wheat cultivation in western Iran, a country facing the challenge of becoming self-sufficient in wheat. Seventy soil profiles were selected and described on the basis of a geomorphologic map and the content of various soil properties and wheat yield were determined. MCDM (TOPSIS) and FAO models were applied and evaluated according to wheat yield. The Shannon entropy method (SHE) was used to extract the criteria weights. Land suitability assessment was mapped using a Random Forest machine learning model and auxiliary variables. According to the results of the Shannon entropy method, slope, cation exchange capacity (CEC) and calcium carbonate equivalent (CCE) are the most important criteria for wheat cultivation. Furthermore, the results are also confirmed by the spatial autocorrelation between the key criteria and wheat yield. These results also show that the soil suitability values calculated with the TOPSIS model have a higher correlation with wheat yield than the values calculated with the FAO model (0.73 and 0.67, respectively). The spatial distribution of the suitability values for wheat cultivation showed that 30 to 33% of the areas were very suitable, 13-16% moderately suitable and 51% and 57% unsuitable. For the areas with high and medium suitability, the TOPSIS and FAO results were largely in agreement, in contrast to the areas with low suitability. This study provided a comprehensive approach to land suitability for wheat cultivation using advanced MCDM techniques and machine learning, which can be beneficial for sustainable land management and food security in Iran and similar regions.
A systematic comparison of predictive models on the retina
2024-03-09

Abstract Understanding the nonlinear encoding mechanisms of retinal ganglion cells (RGCs) in response to various visual stimuli presents a central challenge in neuroscience, driving the development of increasingly complex predictive models. Here, we systematically evaluate linear-nonlinear (LN) models – applying various regularization techniques – and convolutional neural networks (CNNs) of increasing depth, to predict RGC responses to white noise and natural movies. Our analysis includes publicly available datasets from marmoset and salamander retinas. We demonstrate that LN models, when equipped with appropriate inductive biases, can achieve robust predictive performance on neural responses to both white noise and natural movie stimuli. The optimal inductive biases vary substantially across datasets and stimulus types, indicating that the LN model’s performance is susceptible to these choices. This warrants care when using LN models as baselines: their performance is not fixed, and inappropriate design choices can lead to “unfair” comparisons. However, even in the optimal inductive bias scenario, CNNs consistently outperform LN models across conditions, confirming the advantage derived from their nonlinear representation capacity. Investigating cross-stimulus generalization, we observe that models trained on white noise generalize better to natural movies than vice versa. Notably, LN models exhibit a smaller performance gap between in-domain and cross-domain predictions compared to CNNs, suggesting that the nonlinear processing captured by CNNs is more stimulus-specific. Overall, this study provides valuable benchmarks and methodological insights for neuroscientists designing predictive models of retinal encoding.
Geology and geomorphology of the Jan 1st 2024 Mw 7.6 Noto Peninsula Earthquake: observations and context.
2024-03-09

On January 1st 2024, a Mw 7.6 earthquake shook the Noto Peninsula on the Sea of Japan coast of Central Japan causing over 202 casualties and &gt;100 missing (at the time of submission). The quake follows a period of intensifying seismic activity starting in 2020. The Mw 6.3 Oku-Noto earthquake of May 5 2023 was the previous largest event of the sequence. The Jan. 1 2024 Noto Peninsula earthquake significantly impacted the Peninsula. A large number of landslides and rockfalls dissected the road network. Liquefaction damaged infrastructure up to 150 km away from the epicenter. Meter-scale coseismic uplift modified the northern shoreline with displacement of the coastline by up to 200 m seaward discernible on SAR and aerial image data. At the time of abstract submission (Jan. 10 2024) we only have limited preliminary observations. It appears that the Noto Earthquake ruptured the same or adjacent fault to the May 5 2023 Mw 6.5 earthquake and was in the vicinity of the March 25 2007 Mw 6.9 Noto earthquake. Coseismic displacement measured geodetically shows uplift of up to +3&amp;#8211;4 m (SAR) in the northwest of the peninsula (Wajima-shi), and +1.06 m (GPS) in the main town of Wajima-shi. The uplift magnitude decreases gradually to the SE. The uplift is near zero (SAR) or -0.3 m (GPS) on Noto Island (Nanao-shi) 30 km to the south of the town of Wajima. Surface deformation goes back to near zero (GPS) a further 20 km to the south.The coseismic deformation pattern broadly reflects the deformation recorded in the Noto landscape. Long-term moderate rock uplift in the north gives way to a complex history of long-term slow uplift around Noto Island that likely includes sustained episodes of subsidence, highlighted by its sinuous &amp;#8220;drowned&amp;#8221; coastline. Along the western shore (Shika-machi), marine terraces presumed to be 120 ka (last Interglacial) show a gradient in elevation also decreasing to the south. In the north, the newly emerged platform does not have a higher marine terrace counterpart. This may reflect the relationship between high wave power and moderate rock uplift resulting in the long-term retreat of the coastline and erosion of any terrace. The Noto Peninsula also holds widespread evidence of drainage reorganization that would reflect varying boundary conditions, in particular rock uplift, in deeper time beyond 100&amp;#8217;s ka. The similarities between recent landscape morphology and coseismic displacement suggest that the Jan. 1 2024 rupture fits a recent pattern of crustal strain in Noto Peninsula (at least up to 100 ka). Earlier deformation pattern (&gt;100&amp;#8217;s ka) likely happened along different faults and/or at different rates as reflected by the transient drainage network.By conference time, we will present field observations collected after the rescue and emergency work is completed.
Objective tuning of an EMIC using present-day observations and Last Glacial Maximum climate reconstructions
2024-03-09

Climate models rely on parametrizations of unresolved Earth system processes. These often include uncertain parameters that are estimated in a procedure called tuning, where the model output is optimized with respect to selected climate observations. Most models are tuned against present-day observations. However, if the parametrizations robustly represent the underlying physics, a tuned set of model parameters should be valid independent of the simulated climate, including climate states very different from present-day such as the Last Glacial Maximum (LGM).Here, we present the procedure for and the results of an iterative Bayesian tuning of PlaSim-LSG, an Earth system model of intermediate complexity (EMIC). Its low computational cost allows for long simulation periods and large ensembles. For a preliminary tuning restricted to observational information from recent decades, we find a less realistic LGM state of the Atlantic Meridional Overturning Circulation (AMOC) and sea ice distribution than in the default model version. This could imply that tuning based only on present-day observations might be insufficient to target significantly colder climates such as the LGM. However, prior sensitivity studies have shown that PlaSim-LSG is capable of simulating a wide range of AMOC states under varying ocean diffusivity parameters and handling of freshwater runoff. Therefore, we redefine tuning targets, combining present-day observations with LGM climate reconstructions. We investigate how the weighting of the different climate state metrics in the tuning target impacts the resulting present-day and LGM climates. The goal of this exploratory approach is to test parameter sensitivity and identify state-dependent parameters. This could be used in the future to inform model development decisions by focusing on improving parametrizations with highly state-dependent parameters.
Duplex Structures in the EastGRIP Ice Core - the Loss of Stratigraphic Integrity
2024-03-09

The EastGRIP ice core is drilled through the Northeast Greenland Ice Stream, which has a surface velocity of 55 m/yr&amp;#160;towards NNE at the drill site. Deriving a better understanding of internal deformation and the rheology within an ice stream is crucial for ice flow models and projections of future solid ice discharge. We use the line scanner to make the stratigraphy visible and document disturbances in the layering in the depth region from 1375 to 2120 m covering a large part of the Glacial Period. Disturbances are visible in cuts perpendicular to the ice flow direction, and not in cuts parallel to flow. Between these two extremes, we have a gradual change in type and amount of disturbances. As with all other ice cores, the ice in the EastGRIP ice core is thinned vertically. Due to the advanced thinning of layers, it is clear that the visible structures are not the remnants of surface features, such as sastrugi. &amp;#160;However, the disturbances, or deformation structures, are the result of strain caused by the stress field at the EastGRIP site, which is described by a compressional component perpendicular to and an extensional component parallel to the ice flow direction. In most samples cut perpendicular to ice flow, i.e. with the compressional setting visible, we find structures, very similar to geological duplex structures. We identify duplex structures extending the width of the core by the sudden change of layer tilt within one bag at a time. Duplex structures are confined by layer parallel shear zones, with tilted layers in between them. The small-scale shear zones only become evident due to the deformation they cause and can extend well beyond these visible structures. We furthermore suggest, that shear zones are present parallel to layering, but do not show up, as a lateral displacement of layers, does not disrupt the vertical profiles. We discuss one example, from a depth of 1651 m (26 ky b2k), in detail. We further investigate approx. 30 m of chemical CFA data, mainly NH4+ and Ca++, from the same depth. We find peaks that double, in both the visual stratigraphy as well as the CFA data. These may be a result of the duplex structures that stack the stratigraphy and have the potential to disturb the climate record. Our results display the importance of understanding internal deformation when interpreting the climate record.
Thresholds of Meteorological Factors Conductive to Severe Summer Ozone Pollution in China and Relation of Occurrence Frequency with Large Scale Circulations
2024-03-09

Daily thresholds of meteorological factors relative to severe summer ozone pollution are determined in the North China Plain (NCP), the Fenhe River and Weihe River Plain (FWP), the Sichuan Basin (SCB), the Changjiang River Plain (CJR) and Pearl River Delta (PRD) by combing ozone concentrations at air quality monitoring stations and meteorological elements at weather stations. These regions share same daily thresholds, namely maximum temperature above 30 &amp;#176;C, relative humidity below 80%, rainfall below 10 mm and radiation in the scope of 17~27 MJ/m2 together with wind speed in the range of 0.5~3.0 m/s. The adverse meteorological frequency combining daily thresholds of wind speed and radiation shows individual trend and periodic characteristics in each region after conducting 10-year moving average, namely rising with 3~6 percentage points/decade in NCP (in June), FWP (in June, July and August) and CJR (in July) while decreasing with 2~3 percentage points in SCB in July and August. However, there are no apparent trends in PRD. Additionally, these frequencies are periodic with 8.3 years to 25 years. The frequencies are positively related to Western Pacific Subtropical High (WPSH) in NCP, FWP, CJR and PRD, while negatively relevant in SCB. The correlate coefficients between Southern Oscillation and the frequencies vary in regions and months. With cyclo-stationary empirical orthogonal function analysis, we also substantiate impacts of global warming, Pacific Decadal Oscillation, El-Nino and La-Nina on WPSH in two typical months. These would give us more insights on meteorological effects on ozone pollution and be helpful for its projection.