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The prion-like spread of protein aggregates is a leading hypothesis for the propagation of neurofibrillary lesions in the brain, including the spread of tau inclusions associated with Alzheimers disease. The mechanisms of cellular uptake of tau seeds and subsequent nucleated polymerization of cytosolic tau are major questions in the field, and the potential for coupling between the entry and nucleation mechanisms has been little explored. We found that in primary astrocytes and neurons, endocytosis of tau seeds leads to their accumulation in lysosomes. This in turn leads to lysosomal swelling, deacidification, and recruitment of ESCRT proteins, but not Galectin-3, to the lysosomal membrane. These observations are consistent with nanoscale damage of the lysosomal membrane. Live cell imaging and STORM superresolution microscopy further show that the nucleation of cytosolic tau occurs primarily at the lysosome membrane under these conditions. These data suggest that tau seeds escape from lysosomes via nanoscale damage rather than wholesale rupture and that nucleation of cytosolic tau commences as soon as tau fibril ends emerge from the lysosomal membrane.

Applying deep learning to high-precision ionospheric parameter prediction is a significant and growing field within the realm of space weather research. This paper proposes an improved model, Mixed Convolutional Neural Network (CNN)—Bidirectional Long Short-Term Memory (BiLSTM), for predicting the Total Electron Content (TEC) in China. This model was trained using the longest available Global Ionospheric Maps (GIM)-TEC from 1998 to 2023 in China, and underwent an interpretability analysis and accuracy evaluation. The results indicate that historical TEC maps play the most critical role, followed by Kp, ap, AE, F10.7, and time factor. The contributions of Dst and Disturbance Index (DI) to improving accuracy are relatively small but still essential. In long-term predictions, the contributions of the geomagnetic index, solar activity index, and time factor are higher. In addition, the model performs well in short-term predictions, accurately capturing the occurrence, evolution, and classification of ionospheric storms. However, as the predicted length increases, the accuracy gradually decreases, and some erroneous predictions may occur. The northeast region exhibits lower accuracy but a higher F1 score, which may be attributed to the frequency of ionospheric storm occurrences in different locations. Overall, the model effectively predicts the trends and evolution processes of ionospheric storms. [ABSTRACT FROM AUTHOR]

Thyrotroph pituitary adenomas have been reported to be a rare cause of 'thyroid storms', causing myriad metabolic and autonomic disturbances. In this case, we describe the second reported case in literature of a 'GH storm' in an infarcted somatotroph adenoma. We describe a residual invasive somatotroph macroadenoma that underwent infarction, producing a dramatic elevation in serum GH levels. While infarction of adenomas may in some cases lead to remission, the patient went on to require re-surgery and re-radiation due to growth of the residual viable tumour. 'GH storms' are rare but interesting events that may occur in somatotroph adenomas. Infarction or apoplexy must be considered when managing residual adenomas. [ABSTRACT FROM AUTHOR]

The fluctuations in the extent of the dry area have profound implications for the delta's ecology, sediment transport, and overall geomorphological development. This study aims to elucidate the effects of various factors, including storms and cold fronts, as well as river discharge, on the dry area of the Wax Lake Delta (WLD), US. Utilizing the Delft3D hydrodynamic model, a series of simulations covering from August to September 2021 was performed to quantify these influences. The model was calibrated and validated using measured water level data, ensuring the reliability of the simulations. Results indicate that the average dry area of the WLD for September 2021 is approximately 25.1 km², which largely depends on meteorological forces and river discharge. Specifically, extreme storms have the potential to submerge the delta, resulting in prolonged periods of inundation. Moreover, the passage of a cold front can lead to a submersion of up to 48% of the delta's area during the pre-frontal phase, followed by an 80% increase in the dry area in the subsequent post-frontal phase, illustrating the transient but significant impact of such events. The study also determines that river discharge has an inverse relationship with the dry area of the delta; an increase in discharge corresponds to a decrease in the dry area, and conversely, a decrease in discharge leads to an expansion of the dry area. The insights gained from this research underscore the importance of integrating meteorological and hydrological data in the management and conservation strategies of deltaic environments. [ABSTRACT FROM AUTHOR]

In the warm seasons of the year, some storms occur that are difficult and complicated to predict. These strong winds that are usually accompanied by dust are known as Haboob in some countries. In the last decade, some of the storms that have occurred over Tehran area, which have caused numerous damages, have included the mechanism of the Haboob event. In this study, a method is introduced for the feasibility of predicting the potential of storms with a down burst structure, that provides defined warning levels for this phenomenon. In the this method, by using a post-processing on the output of a numerical weather prediction model, according to the dynamics and thermodynamic conditions of the weather, a level of warnings is issued for the potential of storm events with down burst mechanism. In the present work, an ensemble forecasting system developed for the WRF model, is used to provide short term predictions of such storms over Tehran area. Five different thermodynamic indices were calculated for the grid points and the process of calculating the potential of a storm event with a down burst structure was carried out by considering the temperature near the earth's surface, the thermodynamic conditions of the atmosphere, the vertical profile of relative humidity, and also checking the presence of dynamic conditions for air ascent. If the thermodynamic conditions and the instabilities of the atmosphere identified by the relevant indicators are conducive and the temperature of the earth's surface and the vertical profile of the relative humidity are appropriate, then the potential of a storm with a down burst structure can be considered probable. The humidity conditions were considered in such a way that the lower levels of the atmosphere have low relative humidity and the higher levels have more relative humidity so that the probability of evaporation of rain before it reaches the earth's surface is high. By combining these conditions for the output of the numerical model, in all of the time steps, three warning levels of the model output for the potential of a storm with a down burst mechanism were presented in the form of yellow, orange and red color zones. Four cases of strong winds and storm, as well as the famous storm that occurred on June the second, 2014, were investigated for the city of Tehran. Various forecasting maps of the output of model run include the mean sea level pressure, the thickness of the layer between the levels of 500 and 1000 hPa, wind speed, the relative vorticity of the level of 500 hPa, geopotential heights of some levels, thermodynamic indices, relative humidity in some pressure levels and the skew-T diagram was prepared at the grid points to analyze the dynamics, thermodynamic and synoptic conditions of the atmosphere. According to the information of the Meteorological Organization of Iran, winds with speeds between 80 to 120 kilometers per hour have been recorded in the meteorological stations of Tehran on these dates. In all these cases, the recorded wind speeds is significantly higher than the direct prediction of numerical weather forecasting models. In fact, it could not be recognized and predicted only by the output of these models. The maps for forecasting the warning level of the feasibility of a storm with a down burst mechanism in all cases investigated in this work during the calculations related to the probability of the occurrence are presented in this study. It seems that the presented method is able to predict the potential of the occurrence of strong winds and storms with down burst structure for the city and province of Tehran. [ABSTRACT FROM AUTHOR]

A growing proportion of forested landscapes are interspersed with human infrastructure, such as utility lines and roads, increasing the potential for tree-failure consequences due to storms and other causes. Utilities and other institutions have strong incentives to reduce such interactions and allocate substantial resources to risk reduction, but trees and forests in densely populated landscapes also provide significant amenities to society. We present a generalized framework for "Stormwise" forest management, focused on resistance of roadside forests to storms, based on elements of arboricultural and silvicultural practice and tree biomechanics and architecture. We detail results of a multidisciplinary research program focused on management outcomes, opportunities and barriers to implementation, and allocation of investment based on physical and social landscape characteristics. We discuss initial findings, the potential for widespread adoption of resilience-focused management in roadside and infrastructure-adjacent forests, and the importance of such work, considering a changing climate. Study Implications: The research and implementation program we detail here illustrates the potential for "Stormwise" forest management to reduce storm-damage recovery costs, result in fewer and shorter-duration power and transportation interruptions, and allow for low-investment ground-based management in future forest entries. We illustrate a multifaceted, interdisciplinary research program that links the geospatial, social, and biophysical components of understanding forest infrastructure systems. We illustrate how implementation of Stormwise management has the potential to benefit stakeholders such as residents and utilities, offset the substantial economic costs of tree-related power outages, and reduce societal disruptions associated with interactions between trees and infrastructure during storms. [ABSTRACT FROM AUTHOR]

Several offshore platforms operating in the Java Sea have reported experiencing scour at varying depths, raising concerns about the safety and integrity of these structures. Scouring, an erosion phenomenon that occurs around these offshore platform structures due to their presence, is one of the most common issues encountered. The presence of scour can have a significant impact on the safety of these structures. To comprehend the implications of scour on structural safety, sensitivity analysis proves to be an invaluable tool. Sensitivity analysis establishes a relationship between changes in the safety parameters of the structure, obtained through linear analysis, and the depth of scour. By investigating this connection, sensitivity curves can be generated, enabling a conservative prediction of alterations in the strength parameters of the structure due to scour. In this study, a four-legged jacket platform structure underwent linear analysis under storm and seismic conditions using the SACS software. The scour phenomenon was simulated by adjusting the mudline's elevation beneath the structure, modifying the pile coordinates, reducing the length of piles beneath the mudline, and accounting for soil characteristics at each scour depth in the model. The sensitivity analysis revealed that the safety factors of the upper structural components, connections, and piles decrease at varying rates corresponding to each component type as the scour depth of the platform increases. By implementing these sensitivity curves, engineers and operators can make informed decisions regarding the maintenance and retrofitting of offshore platform structures to ensure their ongoing safety and structural integrity in the face of scour-related challenges. This research provides valuable insights into the critical relationship between scour depth and structural safety, enhancing our ability to protect offshore operations in the Java Sea and similar environments.

Summary: An effective scheduling strategy is critical for achieving better performance in real‐time stream processing systems. How to quickly and efficiently process real‐time data stream is always challenging, especially when clusters are collaborating in a Geo‐Distributed computing environment. To address these challenges, we propose an elastic scheduling strategy with Latency Constraints in Geo‐Distributed stream computing environments called Lc‐Stream. This article discusses our work from the following aspects: (1) An optimized data stream redirection method that is proposed based on queuing network algorithm, along with a computing resource model, a latency constrained scheduling model and a communication energy consumption model. (2) An updated node selection method based on the inter‐layer task correlation, to reduce the communication latency between groups at the executor granularity. (3) A network cluster distribution for Geo‐Distributed computing environment to ensure energy saving under low transmission latency. Experimental results show that compared to R‐Storm, Lc‐Stream reduces total latency by over 19% and increases throughput by over 37% in typical cross‐domain multi‐task topologies. Compared to Ts‐Stream, Lc‐Stream also reduces total latency by over 15% and increases throughput by over 21%. At the same time, it helps to balance the load among the systems and avoid overuse of compute nodes. [ABSTRACT FROM AUTHOR]

Temperate forests are particularly exposed to climate change and the associated increase in weather extremes. Droughts, storms, late frosts, floods, heavy snowfalls, or changing climatic conditions such as rising temperatures or more erratic precipitation are having an increasing impact on forests. There is an urgent need to better assess the impacts of climate change and extreme weather events (EWEs) on temperate forests. Remote sensing can be used to map forests at multiple spatial, temporal, and spectral resolutions at low cost. Different approaches to forest change assessment offer promising methods for a broad analysis of the impacts of climate change and EWEs. In this review, we examine the potential of Earth observation for assessing the impacts of climate change and EWEs in temperate forests by reviewing 126 scientific papers published between 1 January 2014 and 31 January 2024. This study provides a comprehensive overview of the sensors utilized, the spatial and temporal resolution of the studies, their spatial distribution, and their thematic focus on the various abiotic drivers and the resulting forest responses. The analysis indicates that multispectral, non-high-resolution timeseries were employed most frequently. A predominant proportion of the studies examine the impact of droughts. In all instances of EWEs, dieback is the most prevailing response, whereas in studies on changing trends, phenology shifts account for the largest share of forest response categories. The detailed analysis of in-depth forest differentiation implies that area-wide studies have so far barely distinguished the effects of different abiotic drivers at the species level. [ABSTRACT FROM AUTHOR]

Satellite altimeters are the most common source of wave measurement in phenomenal sea states, with significant wave heights exceeding 14 m. Unfortunately their data is still considered with skepticism, because there is usually no other data to verify the accuracy of the largest values. Here we investigate the self‐consistency of the measurement, and their small scale variability, in order to define an estimate of satellite altimeter precision. Using numerical simulations of ocean surfaces and the processing involved in satellite retracking, we find that wave groups are responsible for a variance in estimated altimeter wave heights that is proportional to the square of the spectral peakedness parameter and the significant wave height. Additional variance induced by speckle noise is proportional to the wave height. The effect of wave groups generally dominates in the most severe storms. This variability requires a relatively large scale smoothing or filtering to yield accurate wave height estimates. For example, the largest ever reported 1 s average significant wave height from altimeters sampled by Jason‐2 in the North Atlantic in 2011, at H‾s=20.1 ${\overline{H}}_{s}=20.1$m, is now interpreted to correspond to a true wave height Hs = 18.5 ± 0.3 m. The difference between 20.1 and 18.5 m is mostly due to wave group contributions to the raw measurement. We argue that wave group effects should not be included in the definition of the significant wave height, just like the maximum wave height differs from the significant wave height. Plain Language Summary: Over most of the past 30 years, satellite altimeters have been the only means to measure wave properties in the most severe ocean storms. How do we know that these data are trustworthy, and how can we define uncertainties? Here we show that as a satellite flies along its orbit, it reports wave height that fluctuate because of the random nature of the wavefield that can be organized in groups at the scale of a few kilometers. We are able to simulate the precision of the measurements, as a function of the wave height and the degree of organization of the wavefield, measured by a "spectral peakedness" parameter. This novel understanding can be used to define the precision of the measurements. For example, as far as we know, the largest reported value for a 1 s averaged satellite measurement of the significant wave height was H‾s=20.1 ${\overline{H}}_{s}=20.1$m in a 2011 North Atlantic Storm, with no precision given. We can now re‐interpret this data as evidence of a true significant wave height Hs = 18.5 ± 0.3 m. The local fluctuations up to 20 m are caused by wave groups and should not be counted in the significant wave height. Key Points: Retracking of altimeter waveforms yields fluctuations in wave height and sea level, correlated at the scale of the effective footprintA good approximation for the effective footprint diameter is the square root of the product of wave height and satellite altitudeEstimating phenomenal wave heights precise to better than 2% requires filtering over wave groups, typically over a distance of 20–50 km [ABSTRACT FROM AUTHOR]

Provinces in the Philippines, such as Ilocos Norte, have areas that struggle to manage water efficiently and mitigate disasters brought on by numerous annual storms despite existing irrigation designs. A more pragmatic approach to irrigation designs is needed to resolve this issue. This study aimed to design and develop a miniature smart water management prototype that combines irrigation and floodwater systems featuring disaster preparedness that the country could implement. The study employed an operational research design to construct a scaled-down smart and autonomous water management system with Internet of Things (IoT) capabilities. The prototype featured contingency measures, irrigation control, and short message services (SMS) through ultrasonic sensors, a soil moisture sensor, and actuators. The results showed that the precision tests of ultrasonic sensors and the soil moisture sensor were precise between readings. All components were functional and in good condition. Acceptability and adaptability tests yielded a weighted mean of 4.07 and 4.13, respectively, translating high levels in each. Ultrasonic and soil moisture sensors have minimal variations in each reading, inferring reliability and consistency. Every constituent component is functional, and the prototype is highly acceptable in design. The prototype is capable of being adapted for modifications and upgrades to accommodate larger scales, suggesting implementation near areas experiencing agricultural challenges. [ABSTRACT FROM AUTHOR]

Heavy precipitation, often associated with weather phenomena such as tropical cyclones, extratropical cyclones (ETCs), atmospheric rivers (ARs), and mesoscale convective systems (MCSs), can cause significant socio‐economic loss. In this study, we apply atmospheric feature trackers to quantify the contributions of these storm types in observational data sets and climate model short‐range hindcasts. We generate a global hourly storm data set at 0.25° spatial resolution covering 2006–2020, based on the tracking results from TempestExtremes and Python FLEXible object TRacKeR. Our analyses show that these four storm types account for 67% of global annual mean precipitation and 82% of top 1% precipitation extremes, with MCSs mainly over the tropics, and ARs and ETCs over the midlatitudes. The percentage of precipitation contributions from these storms also show strong seasonality over many geographical locations. We further apply the tracking results to the Energy Exascale Earth System Model (E3SM) short‐range hindcasts and evaluate how well these storms are simulated. The evaluation show that E3SM, with ∼1° resolution, significantly underestimates storm‐associated precipitation totals and extremes, especially for MCSs in the tropics. Our analysis also suggests that model fails to capture the correct mean diurnal phases and amplitude of MCS precipitation. This phenomenon‐based approach provides a better understanding of precipitation characteristics and can lead to enhanced model evaluation by revealing underlying problems in model physics related to precipitation processes associated with the heavy‐precipitating storms. Plain Language Summary: Earth system models are immensely useful for understanding how the climate system works. However, it is important to recognize that they have limitations including wet or dry precipitation biases caused by complicated factors. On the other hand, different storm types contribute to regional precipitation differently under varying conditions. Attributing precipitation to sourced storm types is a new approach to understanding model precipitation biases. Here we build a new data set to study precipitation from several storm types including tropical cyclones, extratropical cyclones, atmospheric rivers, and mesoscales convection systems. We find that these four storm types explain 67% of global mean precipitation and 82% of extreme precipitation. We also demonstrate the application of this tool for understanding biases in modeled precipitation. The future application of this new tool will shed light on the causes of modeled precipitation biases and underlying model problems. Key Points: A global observational database for tracking four major heavy‐rain storm systems is established for the 2006–2020These four storm systems contribute to over 67% of global annual mean precipitation and over 80% of top 1% precipitation extremesClimate model short‐range hindcasts underestimate the storm‐associated precipitation, especially for heavy precipitation extremes [ABSTRACT FROM AUTHOR]

Each year, an average of 45 tropical cyclones affect coastal areas and potentially impact forests. The proportion of the most intense cyclones has increased over the past four decades and is predicted to continue to do so. Yet, it remains uncertain how topographical exposure and tree characteristics can mediate the damage caused by increasing wind speed. Here, we compiled empirical data on the damage caused by 11 cyclones occurring over the past 40 years, from 74 forest plots representing tropical regions worldwide, encompassing field data for 22,176 trees and 815 species. We reconstructed the wind structure of those tropical cyclones to estimate the maximum sustained wind speed (MSW) and wind direction at the studied plots. Then, we used a causal inference framework combined with Bayesian generalised linear mixed models to understand and quantify the causal effects of MSW, topographical exposure to wind (EXP), tree size (DBH) and species wood density (ρ) on the proportion of damaged trees at the community level, and on the probability of snapping or uprooting at the tree level. The probability of snapping or uprooting at the tree level and, hence, the proportion of damaged trees at the community level, increased with increasing MSW, and with increasing EXP accentuating the damaging effects of cyclones, in particular at higher wind speeds. Higher ρ decreased the probability of snapping and to a lesser extent of uprooting. Larger trees tended to have lower probabilities of snapping but increased probabilities of uprooting. Importantly, the effect of ρ decreasing the probabilities of snapping was more marked for smaller than larger trees and was further accentuated at higher MSW. Our work emphasises how local topography, tree size and species wood density together mediate cyclone damage to tropical forests, facilitating better predictions of the impacts of such disturbances in an increasingly windier world. [ABSTRACT FROM AUTHOR]

Recent evidence has demonstrated that the transsynaptic nanoscale organization of synaptic proteins plays a crucial role in regulating synaptic strength in excitatory synapses. However, the molecular mechanism underlying this transsynaptic nanostructure in inhibitory synapses still remains unclear and its impact on synapse function in physiological or pathological contexts has not been demonstrated. In this study, we utilized an engineered proteolysis technique to investigate the effects of acute cleavage of neuroligin- 2 (NL2) on synaptic transmission. Our results show that the rapid cleavage of NL2 led to impaired synaptic transmission by reducing both neurotransmitter release probability and quantum size. These changes were attributed to the dispersion of RIM1/2 and GABAA receptors and a weakened spatial alignment between them at the subsynaptic scale, as observed through superresolution imaging and model simulations. Importantly, we found that endogenous NL2 undergoes rapid MMP9- dependent cleavage during epileptic activities, which further exacerbates the decrease in inhibitory transmission. Overall, our study demonstrates the significant impact of nanoscale structural reorganization on inhibitory transmission and unveils ongoing modulation of mature GABAergic synapses through active cleavage of NL2 in response to hyperactivity. [ABSTRACT FROM AUTHOR]

This study investigates event-based rainfall characteristics in Sinai (Egypt) using hourly precipitation data from the Global Satellite Mapping of Precipitation (GSMaP). A hierarchical cluster analysis of a 19-year dataset (2003–2021) identified five regions in Sinai. Distinct storms were identified using a minimum inter-event time of 5 h. The analysis of storm characteristics revealed that rainfall events in Sinai last from 1.7 to 3.6 h, with a mean storm volume of 6.4 mm. Rainfall intensity ranges from 1.7 to 4 mm/h, and the average dry period duration is 34 days. The northern region has the highest frequency of storms (25 events/year). The Weibull distribution was found to fit the best for all rainfall characteristics except for intensity, which was best represented by the generalized extreme value distribution. This study provides valuable insights about rainfall events in Sinai that can be applied to improve flood mitigation strategies and water resources management. [ABSTRACT FROM AUTHOR]

Background: The architecture and composition of glial (GCI) and neuronal (NCI) α-synuclein inclusions observed in multiple system atrophy (MSA) remain to be precisely defined to better understand the disease. Methods: Here, we used stochastic optical reconstruction microscopy (STORM) to characterize the nanoscale organization of glial (GCI) and neuronal (NCI) α-synuclein inclusions in cryopreserved brain sections from MSA patients. Results: STORM revealed a dense cross-linked internal structure of α-synuclein in all GCI and NCI. The internal architecture of hyperphosphorylated α-synuclein (p-αSyn) inclusions was similar in glial and neuronal cells, suggesting a common aggregation mechanism. A similar sequence of p-αSyn stepwise intracellular aggregation was defined in oligodendrocytes and neurons, starting from the perinuclear area and growing inside the cells. Consistent with this hypothesis, we found a higher mitochondrial density in GCI and NCI compared to oligodendrocytes and neurons from unaffected donors (P < 0.01), suggesting an active recruitment of the organelles during the aggregation process. Conclusions: These first STORM images of GCI and NCI suggest stepwise α-synuclein aggregation in MSA. © 2024 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. [ABSTRACT FROM AUTHOR]

A thunderstorm (TS) is a severe weather phenomenon characterized by intense showers, hail, lightning, thunder, tornadoes, turbulence, and gusty winds. It occurs in vertically developed Cumulonimbus (Cb) clouds due to atmospheric instability and has a spatial resolution (meso-scale) of 1 - 100 km. This phenomenon occurs mainly in spring and early summer in our country due to the uplift and condensation of moist and unstable air masses. However, in recent years, these events have become more frequent during mid-summer, early autumn, and even winter months. In this study, the characteristics of TS events in Istanbul, covering the period from 2013 to 2022, including the warm season (May-September) and the cold season (October-April), were examined, and the atmospheric conditions under which they occur were identified. Aviation observations from Sabiha Gökçen International Airport were used to determine the occurrence of TS events, and data from Istanbul Kartal Radiosonde Station were analyzed to obtain upper-level atmospheric parameters. The occurrence of individual TS events or their association with other phenomena was investigated, and the statistics were presented. The daily, monthly, and yearly analyses of TS events during the period were conducted, and the changes in meteorological parameters for both the warm and cold seasons were statistically presented. Meteorological parameters such as temperature, dew point temperature, wind speed, wind direction, and relative humidity were analyzed for both warm and cold season TS events. Additionally, the average changes in each thermodynamic index and atmospheric stability parameter for hot and cold season oraj events were examined using a total of eight indices and parameters.

Tree species composition is known to influence forest productivity, but its effect on forest resilience to disturbances such as storms remains largely unexplored. Furthermore, climate is likely to influence forest resilience directly but also to influence the effect of tree species composition on resilience. In Europe, storm‐induced tree mortality is currently increasing across all climatic biomes. Understanding the drivers of forest resilience to storms and its consistency across climates appears to be crucial for predicting the consequences of climate change for European forests.In this study, we used a simulation approach with an integral projection model calibrated with National Forest Inventory (NFI) data at the European scale. We restricted our simulations to tree species assemblages observed in the NFI data, covering a species diversity gradient nested within a climate gradient. We quantified functional diversity and the mean position of each species assemblage at equilibrium on two functional axis: (i) conservative versus fast growing and (ii) low versus high recruitment. We disturbed each species assemblage from equilibrium using species‐specific storm disturbance mortality probabilities and quantified the assemblages' resistance (inverse of immediate basal area loss), recovery (slope of post‐disturbance increase in basal area) and resilience (inverse of the cumulative deviation of basal area from the undisturbed state).We found that on average, species‐rich assemblages had higher recovery and resilience to storm disturbance, while functional diversity improved resistance and recovery. When analysing how this effect varied with climate, we found that diversity significantly increased resistance and resilience in the climatic margins only. Finally, we found that storm resilience was also driven by species mean position along both functional axes. In particular, the conservative‐productive axis had an effect two to three times greater than diversity: forests dominated by conservative species were more resistant and resilient, but had lower recovery than species assemblages dominated by fast‐growing species.Taken together, these results show that climate and tree species composition interact to control the ability of forests to resist and recover from a storm disturbance through both direct and indirect effects. As such, our findings should help to better anticipate climate change consequences for forest ecosystems. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Storms (thunderstorms or windstorms) are common meteorological phenomena in Europe. They produce rain, lightning, strong winds or hail and are capable of causing serious failures in rail transport. We identified 14,786 incidents associated with storms, which took place on the Czech rail network between 2002 and 2021. This represented 5% of all reported rail incidents in Czechia over the monitored period. Using the exact binomial test and a grid covering each combination of month and hour, we found that these incidents were concentrated between May and August in the early morning and afternoon hours. Most of the rail problems were concentrated on only a small number of days, indicating the significant impact of severe storms. The incidents (82%) were associated with rail device failures and/or power outages, such as malfunctions of switches, signals or communication and safety devices. In addition, tree falls on rail infrastructure were also common. The total train delay time exceeded 3917 h, and in some cases rail traffic was even completely disrupted. Based on the findings, which provide unique insight into the impacts of storms on railways, mitigation measures are discussed. This is particularly important given climate change, which may lead to an increased likelihood of severe weather and associated damage in the future. [ABSTRACT FROM AUTHOR]

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Simple Summary: Imepitoin is a medication that can be used to treat anxiety in dogs. Previous studies have shown that imepitoin when given at a dose of 30 mg/kg PO BID (milligram per kilogram of body weight by mouth twice a day), can reduce noise-related anxiety in dogs. However, this dosage may be higher than needed for some dogs. We aimed to determine how safe and effective this medication is for the treatment of storm-related fear and anxiety in dogs when started at a lower dose (10 mg/kg PO BID) and, if needed, when increased to a higher dose of 20 or 30 mg/kg PO BID. We determined the three dosages were safe and reduced clinical signs of storm related fear and anxiety in this study design. More side effects were seen in the 20 mg/kg PO BID group than in the 10 mg/kg PO BID group, which supports the use of this medication at an individually titrated dose starting at 10 mg/kg PO BID. Imepitoin is a low-affinity partial agonist for benzodiazepine binding sites of gamma-aminobutyric acid receptors with anxiolytic effects. It has been shown to reduce anxiety during noise-related events in dogs when given at 30 mg/kg PO BID, although this dose was associated with ataxia and increased appetite in some cases. The objective of this study was to assess its safety and efficacy for storm anxiety when started at 10 mg/kg PO BID and titrated to effect up to 30 mg/kg PO BID during storm season. Significant decreases in anxiety scores were seen in weekly surveys and storm logs (SLs) at 10, 20 and 30 mg/kg PO BID. Serious adverse events (AEs) were not reported in any subject. Ataxia was the most commonly reported non-serious AE (14/33), followed by increased hunger (13/33). The frequency of AEs was higher in the 20 mg/kg PO BID group than in the 10 mg/kg group PO BID. No clinically significant changes were seen in lab work pre- and post-study. In conclusion, Imepitoin given during storm season at doses ranging from 10 to 30 mg/kg PO BID reduced clinical signs of fear and anxiety during storms for the dogs in this study. These findings support the use of an individually titrated dose. [ABSTRACT FROM AUTHOR]

The hemispheric differences in the impact of the geomagnetic storms of June 2015 and December 2015 are investigated. A meridional chain of ground observatories along 95°E ± 10°E (conjugate point-GNSS receiver/Ionosonde), satellite in-situ measurements (SWARM/COSMIC/C-NOFS), and Total Electron Content maps are utilized. Symmetric negative (positive) effects were noted during the main phase of the June (December) storm but hemispheric asymmetry was manifested during the recovery phase. The quiet time hemispheric asymmetry was reversed during both storms with positive TEC effects on the winter side. Differential VTEC and NmF2 responses exhibited seasonal variation. On 23 June 2015, the VTEC enhancements in the southern low latitude were large and consistent in contrast to the weak response in NmF2. In contrast, during the December storm, the NmF2 depletion in southern low latitude was more severe than the corresponding depletion in VTEC. The topside density/TEC enhancement in the southern low latitude recorded by SWARM was much higher than 300 % during the morning of 23 June. The SWARM Ne/TEC profile as well as the ground GPS TEC map showed a third latitudinal maximum around −45° dip angle of field lines in southern low latitudes on 23 June, in addition to the conventional EIA crests. Similarly, an early morning maximum was recorded at + 45° dip (northern hemisphere) on 21 December. The hmF2 measured by the southern hemisphere ionosonde and COSMIC satellite showed an anomalously higher altitude of the F2-layer on 23 June while C/NOFS recorded equator-ward meridional flow velocity. The reversal of the hemispheric asymmetry and the additional storm time transient maximum on the winter side is attributed to the equator-ward winds surge in the winter hemisphere due to storm time heating of the polar region. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Natural Hazards & Environment (JNHE) / Doğal Afetler ve Çevre Dergisi (DACD) is the property of Artvin Coruh University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Enhancements in electron density in the D‐region ionosphere attributed to the precipitation of high‐energy electrons, have previously been inferred from increases in cosmic radio noise absorption (CNA) using ground‐based riometers. However, there have been few studies of CNA observations at multi‐point stations distributed in longitudes. Thus, the spatio‐temporal development of the global distribution of CNA is not well understood. In this study, we investigated the longitudinal extent of CNA using simultaneous riometer observations at six stations at subauroral latitudes in Canada, Alaska, Russia, and Iceland. These stations are located encircling the earth at ∼60° north magnetic latitudes. We have conducted simultaneous observations of CNA at these stations since October 2017. Here we focus on seven substorms during a geomagnetic storm 25–28 August 2018 and study the spatio‐temporal development of the global distribution of CNA during these substorms. For all seven substorms, some stations observed CNA enhancements after the substorm onsets. In five cases, the CNA enhancements started around midnight and expanded eastward. The other two cases show westward and anti‐sunward development of CNA. The eastward expansion of CNA indicates the eastward drift of high‐energy electrons, which is the source of the CNA, due to gradient and curvature drift in the geomagnetic field. The westward expansion of CNA may correspond to westward expansion of the substorm injection region due to dawn‐to‐dusk electric fields. These results indicate that spatio‐temporal development of CNA at subauroral latitudes corresponds to high energy electron drift in the inner magnetosphere. Plain Language Summary: The inner magnetosphere contains plasma particles with a wide range of energies. High‐energy electrons (>30 keV) in the inner magnetosphere are accelerated and lost while rotating longitudinally around the earth. They cause satellite failures and astronaut exposure. It is important to study high‐energy electrons and understand the dynamics of electrons in the inner magnetosphere for safe space utilization and space weather forecasting. The electron density in the ionosphere, which is enhanced by the precipitation of these high‐energy electrons, has been inferred using sensitive ground‐based radio receivers called riometers as an increase in cosmic radio noise absorption (CNA). However, there have been few studies of cosmic radio noise absorption (CNA) observations at multi‐point stations distributed in longitude to show how this takes place on a global scale. In this study, we investigated the longitudinal extent of CNA using simultaneous riometer observations at six stations at subauroral latitudes in Canada, Alaska, Russia, and Iceland, focusing on the 25–28 August 2018, geomagnetic storm. Our results show that CNA enhancements started around midnight and expanded both eastward and westward around the Earth. Electrons are known to systematically drift in the inner magnetosphere and we discuss the propagation of CNA by considering that. Key Points: This is the first report of longitudinal development of cosmic radio noise absorption (CNA) for storm‐time substorms using six ground riometers at subauroral latitudesCNA enhancements expanded eastward (5 cases), westward (1 cases), and anti‐sunward (1 case)Spatio‐temporal development of CNA at subauroral latitudes corresponds to high energy electron drift in the inner magnetosphere [ABSTRACT FROM AUTHOR]

Applying deep learning to high-precision ionospheric parameter prediction is a significant and growing field within the realm of space weather research. This paper proposes an improved model, Mixed Convolutional Neural Network (CNN)—Bidirectional Long Short-Term Memory (BiLSTM), for predicting the Total Electron Content (TEC) in China. This model was trained using the longest available Global Ionospheric Maps (GIM)-TEC from 1998 to 2023 in China, and underwent an interpretability analysis and accuracy evaluation. The results indicate that historical TEC maps play the most critical role, followed by Kp, ap, AE, F10.7, and time factor. The contributions of Dst and Disturbance Index (DI) to improving accuracy are relatively small but still essential. In long-term predictions, the contributions of the geomagnetic index, solar activity index, and time factor are higher. In addition, the model performs well in short-term predictions, accurately capturing the occurrence, evolution, and classification of ionospheric storms. However, as the predicted length increases, the accuracy gradually decreases, and some erroneous predictions may occur. The northeast region exhibits lower accuracy but a higher F1 score, which may be attributed to the frequency of ionospheric storm occurrences in different locations. Overall, the model effectively predicts the trends and evolution processes of ionospheric storms.

This article discusses the impact of extreme weather events on the movement and behavior of wild animals, specifically airborne animals like birds. The study focuses on the behavior of a GPS-equipped streaked shearwater caught in a large typhoon over mainland Japan. The bird exhibited swirling flight at high altitudes, with speeds and altitudes much higher than its regular flights. The study highlights the need to understand how volant animals survive and navigate under extreme weather conditions and how the increasing frequency of severe storms affects wildlife. [Extracted from the article]

Centromeric chromatin is thought to play a critical role in ensuring the faithful segregation of chromosomes during mitosis. However, our understanding of this role is presently limited by our poor understanding of the structure and composition of this unique chromatin. The nucleosomal variant, CENP-A, localizes to narrow regions within the centromere, where it plays a major role in centromeric function, effectively serving as a platform on which the kinetochore is assembled. Previous work found that, within a given cell, the number of microtubules within kinetochores is essentially unchanged between CENP-A-localized regions of different physical sizes. However, it is unknown if the amount of CENP-A is also unchanged between these regions of different sizes, which would reflect a strict structural correspondence between these two key characteristics of the centromere/kinetochore assembly. Here, we used super-resolution optical microscopy to image and quantify the amount of CENP-A and DNA within human centromere chromatin. We found that the amount of CENP-A within CENP-A domains of different physical sizes is indeed the same. Further, our measurements suggest that the ratio of CENP-A- to H3-containing nucleosomes within these domains is between 8:1 and 11:1. Thus, our results not only identify an unexpectedly strict relationship between CENP-A and microtubules stoichiometries but also that the CENP-A centromeric domain is almost exclusively composed of CENP-A nucleosomes. [ABSTRACT FROM AUTHOR]

Vasseur, P.L.; Collins, S.A., and Selman, W., 2023. Effects of tropical cyclones and other severe weather events on Reddish Egret (Egretta rufescens) populations in Louisiana, U.S.A. Journal of Coastal Research, 39(6), 1124–1136. Charlotte (North Carolina), ISSN 0749-0208. Tropical cyclones (i.e. tropical depressions, tropical storms, and hurricanes) and other extreme weather events directly impacting Louisiana from 2016–21 were examined to determine their effects on adult Reddish Egrets equipped with satellite transmitters in SE (n = 11) and SW (n = 14) Louisiana. Fourteen tropical cyclones (six hurricanes, five tropical storms, one tropical depression, and two extratropical cyclones) impacted Louisiana during the study, and telemetry data were reviewed immediately on and around (±1 day) the arrival of each storm to monitor any movements and individual survival. As many as nine of 25 (36%) transmittered Reddish Egrets presumably died from the direct impacts of five tropical cyclones; seven of nine mortalities were associated with three major hurricanes. Mortality was presumed based on stationary GPS fixes for multiple days or the termination of data transmission following a storm. All mortalities were presumed, as no carcasses were recovered. Previous telemetry studies reported Reddish Egrets often survived intense tropical cyclones and direct impacts were not appreciable at the population level. Yet, more than one-third of the transmittered birds in the sample population potentially died from storm-related impacts, and the population may have declined drastically, assuming some unmarked individuals also likely died. Because the Reddish Egret is restricted to coastal habitats, the species appears to be particularly vulnerable to tropical cyclone effects. If predictions of increased frequency and intensity of tropical cyclones by the end of this century are accurate, these storms pose a significant threat to Reddish Egret populations. With accelerated loss and degradation to suitable coastal habitats, protection and restoration of key foraging and nesting sites for sensitive species similar to the Reddish Egret are needed in Louisiana and other disturbance-prone areas along the Gulf Coast. [ABSTRACT FROM AUTHOR]

Na-K-2Cl cotransporter 1 (NKCC1) regulates chloride influx in neurons and thereby GABAA receptor activity in normal and pathological conditions. Here, we characterized in hippocampal neurons the membrane expression, distribution and dynamics of exogenous NKCC1a and NKCC1b isoforms and compared them to those of the chloride extruder K-Cl cotransporter 2 (KCC2). We found that NKCC1a and NKCC1b behave quite similarly. NKCC1a/1b but not KCC2 are present along the axon initial segment where they are confined. Moreover, NKCC1a/1b are detected in the somato-dendritic compartment at a lower level than KCC2, where they form fewer, smaller and less compact clusters at perisynaptic and extrasynaptic sites. Interestingly, ~60% of dendritic clusters of NKCC1a/1b are colocalized with KCC2. They are larger and brighter than those devoid of KCC2, suggesting a particular NKCC1a/1b-KCC2 relationship. In agreement with the reduced dendritic clustering of NKCC1a/1b compared with that of KCC2, NKCC1a/1b are more mobile on the dendrite than KCC2, suggesting weaker cytoskeletal interaction. NKCC1a/b are confined to endocytic zones, where they spend more time than KCC2. However, they spend less time in these compartments than at the synapses, suggesting that they can rapidly leave endocytic zones to increase the membrane pool, which can happen in pathological conditions. Thus, NKCC1a/b have different membrane dynamics and clustering from KCC2, which helps to explain their low level in the neuronal membrane, while allowing a rapid increase in the membrane pool under pathological conditions. [ABSTRACT FROM AUTHOR]

The ratio of O to N2 number densities (O/N2) at different altitudes is an important parameter in describing thermospheric neutral composition changes and their effects on the ionosphere during geomagnetic storms. However, storm‐induced vertical variations in O/N2 and its dependence on the O and N2 perturbations are still not fully understood. Here, the Thermosphere/Ionosphere Electrodynamics General Circulation Model simulations were used to investigate the responses of thermospheric composition at different pressure levels to the super geomagnetic storm occurred on November 20 and 21 in 2003. Our analysis shows that the behaviors of O/N2 perturbations on different pressure levels are similar above ∼180 km altitude. In the middle and low thermosphere of below ∼300 km, the storm‐time O/N2 decrease is mainly caused by a large reduction of O number density. However, N2 enhancement plays a vital role in O/N2 decreases in the upper thermosphere. The O/N2 enhancement is mainly attributed to the N2 decreases at all pressure levels. The changes of O and N2 number densities at a constant pressure level can be explained by the perturbations of their mass mixing ratio (mmr) and total mass density (ρ). The regions of the O/N2 decrease are characterized by the O mmr decrease and N2 mmr enhancement, whereas the regions of the O/N2 increase are characterized by the O mmr increase and N2 mmr decrease. The ρ value that shows the decrease globally at most pressure levels during the storm either enhance or reduce the O and N2 perturbations. Plain Language Summary: The column O/column N2 density ratio (∑O/N2) was usually used to describe thermospheric neutral composition responses to geomagnetic storms and the storm effects on ionospheric plasma density. However, thermospheric circulation changed considerably during the storm, resulting in discrepancies in composition at different altitudes. Additionally, the daytime electron density changes during geomagnetic storms are more related to those of local O/N2 at a given altitude, not the ∑O/N2. Therefore, it is important to fully understand the storm‐induced vertical variations in O, N2 and O/N2 perturbations. In this paper, the vertical variations in O/N2 and its dependence on the O and N2 perturbations during the 20–21 November 2003 storm are investigated by the numerical simulations. Our results shows that the behaviors of O and N2 perturbations depend much on the altitude, but those of O/N2 on different pressure levels are similar, especially above ∼180 km. This study helps us better understand the physical process of storm‐time ∑O/N2 variations based on the observations. Key Points: In middle and low thermosphere of below ∼300 km, storm‐time decreases of the ratio of O/N2 volume density are mainly caused by O reductionIn the upper thermosphere, N2 enhancement plays a vital role in the decreases of the ratio of O/N2 volume density during the stormAt all pressure levels, storm‐time increases of the ratio of O/N2 volume density depend more on the N2 decreases [ABSTRACT FROM AUTHOR]

The extent and severity of disaster displacement in small island developing states (SIDS) often go unreported or underreported in global assessments due to the total number of affected people falling below established thresholds. Additionally, post-disaster assessments prepared by various international relief agencies often present conflicting evidence, and largely do not offer substantial insights into national and subnational spatial and temporal patterns of displacement, particularly with respect to the disproportionate risk that certain localities, communities and populations face over time. This article is a case study of hurricane induced displacement in a Caribbean SIDS – The Bahamas. It triangulates data from a publicly-available global disaster database, weather and post-disaster reports from national government departments and agencies, and newspaper articles. Its qualitative-dominant synthesis represents the best available evidence of hurricane risk across the archipelago between 2004 and 2019, organized according to hazard (winds, storm surge, flooding), exposure (people, livelihoods, assets etc. adversely affected), and vulnerability (the propensity or predisposition for adverse impacts). It finds that 11 hurricanes across three periods caused displacement in one or more of the 17 major islands. In identifying the emerging spatial and temporal patterns, it proposes two alternative core-periphery models for The Bahamas. These models not only provide a more accurate account of the islands’ exposure and sensitivity to hurricanes, but also highlight the geographical factors that should be considered as the basis for future plans, actions, strategies or policies that seek to build equitable resilience to these and other climate-amplified hydrometeorological events in SIDS.

Temperate forests are particularly exposed to climate change and the associated increase in weather extremes. Droughts, storms, late frosts, floods, heavy snowfalls, or changing climatic conditions such as rising temperatures or more erratic precipitation are having an increasing impact on forests. There is an urgent need to better assess the impacts of climate change and extreme weather events (EWEs) on temperate forests. Remote sensing can be used to map forests at multiple spatial, temporal, and spectral resolutions at low cost. Different approaches to forest change assessment offer promising methods for a broad analysis of the impacts of climate change and EWEs. In this review, we examine the potential of Earth observation for assessing the impacts of climate change and EWEs in temperate forests by reviewing 126 scientific papers published between 1 January 2014 and 31 January 2024. This study provides a comprehensive overview of the sensors utilized, the spatial and temporal resolution of the studies, their spatial distribution, and their thematic focus on the various abiotic drivers and the resulting forest responses. The analysis indicates that multispectral, non-high-resolution timeseries were employed most frequently. A predominant proportion of the studies examine the impact of droughts. In all instances of EWEs, dieback is the most prevailing response, whereas in studies on changing trends, phenology shifts account for the largest share of forest response categories. The detailed analysis of in-depth forest differentiation implies that area-wide studies have so far barely distinguished the effects of different abiotic drivers at the species level.

When a storm begins at low tide, the tide will increase with time. However, when a storm begins at high tide, the tide will decrease during the storm. Therefore, to achieve more accurate estimations of sliding distance, both the tide-level change and the tide level itself should be considered. In this study, a new approach to taking the change in tide level into account when calculating the sliding distance of gravity-type breakwaters during storms is proposed. Conducting the numerical analysis, we found that, when typhoons begin at low tide, the sliding distance of the breakwater increases when considering the change in tide level, and conversely, when they begin at high tide, the change in tide level results in the sliding distance being shortened. Therefore, considering the change in tide level with time can result in a more accurate and realistic estimation of the sliding distance of the breakwater being attained. This is expected to contribute greatly to the development of deformation-based performance design methods for breakwaters. [ABSTRACT FROM AUTHOR]

Effective and time-efficient aircraft assistance and guidance in severe weather environments remains a challenge for air traffic control. Air navigation service providers around the globe could greatly benefit from specific and adapted meteorological information for the controller position, helping to reduce the increased workload induced by adverse weather. The present work proposes a radar-based nowcasting algorithm providing compact meteorological information on convective weather near airports for introduction into the algorithms intended to assist in air-traffic management. The use of vertically integrated liquid density enables extremely rapid identification and short-term prediction of convective regions that should not be traversed by aircraft, which is an essential requirement for use in tactical controller support systems. The proposed tracking and nowcasting method facilitates the anticipation of the meteorological situation around an airport. Nowcasts of centroid locations of various approaching thunderstorms were compared with corresponding radar data, and centroid distances between nowcasted and observed storms were computed. The results were analyzed with Method for the Object-Based Evaluation from the Model Evaluation tools software (MET-10.0.1, Developmental Testbed Center, Boulder, CO, US) and later integrated into an assistance arrival manager software, showing the potential of this approach for automatic air traffic assistance in adverse weather scenarios. [ABSTRACT FROM AUTHOR]

A rare large-scale hail process in Yantai and Weihai City in the autumn of 2021 was analyzed based on the surface meteorology, high-altitude observation and S-band radar detection data. The results showed that this process was influenced by shallow trough, and strong upper-level jet stream in the middle and upper levels guided the intrusion of mid-level cold air into the warm and humid environment at the lower level. The shear lines and trunk lines in the lower level also provided certain triggering conditions for uplift, brewing conditions suitable for the occurrence and development of strong convection. The vertical wind shear was unusually large, and vertical wind shear was up to 10 ml s at 0 - 1 km, 20 ml s at 0 - 3 km, and 32 ml s at 0 - 6 km, which was conducive to the growth of the storm. In this process, isolated multi-cell thunderstorm was generated at the beginning, and then it developed and strengthened continuously, moving to the southeast. In the later stage, a convection cell was born at the boundary between Yantai and Weihai, and developed into supercell storm. The storm lasted for a long time, and continued to develop and strengthen as it moved eastward, affecting most areas of Weihai from northwest to southeast. In the development stage of the storm, the radar reflectivity factor had obvious characteristics of hook echo and three-body scatter spike, and there was echo overhang and other hail echo features in the middle layer. Weak mesocyclone appeared at a low elevation, and there was the potential for the occurrence of tornado. [ABSTRACT FROM AUTHOR]

Copyright of China Rural Water & Hydropower is the property of China Rural Water & Hydropower Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Abstract The ratio of O to N2 number densities (O/N2) at different altitudes is an important parameter in describing thermospheric neutral composition changes and their effects on the ionosphere during geomagnetic storms. However, storm‐induced vertical variations in O/N2 and its dependence on the O and N2 perturbations are still not fully understood. Here, the Thermosphere/Ionosphere Electrodynamics General Circulation Model simulations were used to investigate the responses of thermospheric composition at different pressure levels to the super geomagnetic storm occurred on November 20 and 21 in 2003. Our analysis shows that the behaviors of O/N2 perturbations on different pressure levels are similar above ∼180 km altitude. In the middle and low thermosphere of below ∼300 km, the storm‐time O/N2 decrease is mainly caused by a large reduction of O number density. However, N2 enhancement plays a vital role in O/N2 decreases in the upper thermosphere. The O/N2 enhancement is mainly attributed to the N2 decreases at all pressure levels. The changes of O and N2 number densities at a constant pressure level can be explained by the perturbations of their mass mixing ratio (mmr) and total mass density (ρ). The regions of the O/N2 decrease are characterized by the O mmr decrease and N2 mmr enhancement, whereas the regions of the O/N2 increase are characterized by the O mmr increase and N2 mmr decrease. The ρ value that shows the decrease globally at most pressure levels during the storm either enhance or reduce the O and N2 perturbations.