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This research examines how red ambient color in restaurants/cafeterias influences food choices. Prior research shows that red directly related to a food product (such as on nutrition labels or plates/cups) leads to avoidance of unhealthy foods. Yet, many successful fast‐food restaurants (e.g., McDonald's and Dairy Queen) use red in their ambiance, suggesting that in the context of food/eating, ambient red may have a different meaning than product‐related red. Indeed, the current research shows that consumers associate ambient red (e.g., wall color) with unhealthy restaurants. The presence of ambient red (vs. blue, gray, or white) leads to greater preference for unhealthy (i.e., high calorie, high fat, and indulgent) food options because consumers draw on ambient factors to make inferences about products sold in a retail establishment and then choose contextually appropriate products. The effect is moderated by the extent to which a consumer associates red with unhealthy restaurants. This research highlights how, in the context of food/eating, the placement of red influences its meaning and ultimately whether consumers approach or avoid unhealthy foods. [ABSTRACT FROM AUTHOR]

The El Niño-Southern Oscillation (ENSO), originating in the central and eastern equatorial Pacific, is a defining mode of interannual climate variability with profound impact on global climate and ecosystems. However, an understanding of how the ENSO might have evolved over geological timescales is still lacking, despite a well-accepted recognition that such an understanding has direct implications for constraining human-induced future ENSO changes. Here, using climate simulations, we show that ENSO has been a leading mode of tropical sea surface temperature (SST) variability in the past 250 My but with substantial variations in amplitude across geological periods. We show this result by performing and analyzing a series of coupled time-slice climate simulations forced by paleogeography, atmospheric CO2 concentrations, and solar radiation for the past 250 My, in 10-My intervals. The variations in ENSO amplitude across geological periods are little related to mean equatorial zonal SST gradient or global mean surface temperature of the respective periods but are primarily determined by interperiod difference in the background thermocline depth, according to a linear stability analysis. In addition, variations in atmospheric noise serve as an independent contributing factor to ENSO variations across intergeological periods. The two factors together explain about 76% of the interperiod variations in ENSO amplitude over the past 250 My. Our findings support the importance of changing ocean vertical thermal structure and atmospheric noise in influencing projected future ENSO change and its uncertainty. [ABSTRACT FROM AUTHOR]

In this paper, the study of the homogeneous resistivity and two‐layer soil influences on the performance of the electrodes of grounding systems subjected to lightning strikes is carried out considering soil ionization. The study is done on the behaviour of the ground electrodes while the resistivity of the soil is altered from small to high value in the case of homogeneous soil, while the study is obtained on two‐layer soils in the case of diverse values of the reflection factor. In the suggested algorithm for two‐layer soils, each layer has its resistivity and dielectric constant, where the dielectric constant and soil resistivity depend on the lightning frequency. The field resulting from lightning strikes, which causes soil ionization, has been studied, and the results have been used to understand the behaviour of ground rods under the influence of lightning strikes. The credibility of the results has been strengthened by comparing it with what others have obtained recently. The article's novelty can be summarized in the investigation of the performance of the electrodes of grounding grids that are installed in high soil resistivity of uniform and two‐layer soils containing the impacts of soil ionization, lightning frequency, soil resistivity, and permittivity variations. [ABSTRACT FROM AUTHOR]

Sentinel-2/MSI and Landsat-8/OLI sensors enable the mapping of ocean color-related bio-optical parameters of surface coastal and inland waters. While many algorithms have been developed to estimate the Chlorophyll-a concentration, Chl-a, and the suspended particulate matter, SPM, from OLI and MSI data, the absorption by colored dissolved organic matter, acdom, a key parameter to monitor the concentration of dissolved organic matter, has received less attention. Herein we present an inverse model (hereafter referred to as AquaCDOM) for estimating acdom at the wavelength 412 nm (acdom (412)), within the surface layer of coastal waters, from measurements of ocean remote sensing reflectance, Rrs (λ), for these two high spatial resolution (around 20 m) sensors. Combined with a water class-based approach, several empirical algorithms were tested on a mixed dataset of synthetic and in situ data collected from global coastal waters. The selection of the final algorithms was performed with an independent validation dataset, using in situ, synthetic, and satellite Rrs (λ) measurements, but also by testing their respective sensitivity to typical noise introduced by atmospheric correction algorithms. It was found that the proposed algorithms could estimate acdom (412) with a median absolute percentage difference of ~30% and a median bias of 0.002 m−1 from the in situ and synthetic datasets. While similar performances have been shown with two other algorithms based on different methodological developments, we have shown that AquaCDOM is much less sensitive to atmospheric correction uncertainties, mainly due to the use of band ratios in its formulation. After the application of the top-of-atmosphere gains and of the same atmospheric correction algorithm, excellent agreement has been found between the OLI- and MSI-derived acdom (412) values for various coastal areas, enabling the application of these algorithms for time series analysis. An example application of our algorithms for the time series analysis of acdom (412) is provided for a coastal transect in the south of Vietnam. [ABSTRACT FROM AUTHOR]

This study investigates the impact of hotel service encounters on guests' behavioral outcomes in 5 and 4-star hotels. It also examines the mediating effect of perceived value and satisfaction on the relationship between service encounters and guests' loyalty. In addition, it investigates the moderating effect of hotel star ratings on the relationship between the study constructs. The study reveals that hotel service encounters significantly impact perceived value but not satisfaction. The hotel staff rather than the atmospherics is an antecedent of loyalty. At the same time, the perceived value of a hotel is an antecedent of satisfaction and loyalty. Meanwhile, it confirms the mediation of perceived value and satisfaction and a hotel's star rating as a moderator. It finds that the hotel star rating moderates the impact of hotel staff on perceived value, satisfaction, and loyalty as it is more robust for 5-star hotels than for 4-star. The theoretical and managerial implications of these findings have also been discussed. [ABSTRACT FROM AUTHOR]

This paper is a study of the visual characteristics of the medieval manuscript diagrams found in Theodosios' Spherics. It provides a new taxonomy of eight types of diagrams found in the manuscript sources, and examines the way in which geometric information is encoded in the manuscript diagrams using a number of visual encodings. It then argues that these diagrams can be used to address ongoing research debates about whether the striking visual characteristics of medieval diagrams in mathematical texts are the result of deliberate choices by the premodern authors, the result of accidents of transmission, or both. Along the way, the paper identifies a further type of transmission error that is prevalent in the medieval transmission of mathematical diagrams. [ABSTRACT FROM AUTHOR]

Physical store atmospherics make up an important dimension of retailing. They shape consumer perception, cognitive and affective reactions, and a variety of behaviors. The literature on exterior atmospherics is scant. However, recent trends suggest that exterior atmospherics can provide value-added services and play a role in providing phygital touchpoints that contribute to consumers' perceptions of safety, seamlessness, and entertainment. This article seeks to examine the strategic potential of exterior atmospherics in shopping experiences and their role in providing competitive advantage in physical retailing in the post-COVID era. This paper is the first to provide a systematic literature review of exterior brick-and-mortar atmospheric variables. The results show that the theoretical frameworks in the extant literature are insufficient in explaining the complex interrelationships that make up a shopping experience. In response to this shortcoming, this paper provides a managerially oriented research agenda through complexity theory and the 'customer journey' framework. [ABSTRACT FROM AUTHOR]

This article considers how affects animate and uphold tourism and settler colonialism. Engaging a 'curious' postdisciplinary research methodology informed by the relational power of listening, I trace the emergence of two interrelated atmospheres in the city of Niagara Falls, Ontario, Canada, both of which exemplify how settler colonialism is built and maintained as a structure of feeling that supports larger processes of worldmaking via tourism. In detailing these two atmospheres and their effects, I illuminate the mechanisms and practices through which tourism-related atmospheric infrastructures overtly and covertly contribute to worldmaking; exemplify how settlers might learn to destabilize, disrupt, or diffuse such atmospherics in and through tourism as a practice of unsettling; and expand on the literature detailing how we might research affective, embodied, and atmospheric moments of tourism. I take inspiration from related critical, interventionist, and narrative work in tourism and build on it to suggest that unsettling tourism—or tourism worldmaking—must be oriented toward mediating agencies of worldmaking like light and sound. [ABSTRACT FROM AUTHOR]

Whether and how well people can behave randomly is of interest in many areas of psychological research. The ability to generate randomness is often investigated using random number generation (RNG) tasks, in which participants are asked to generate a sequence of numbers that is as random as possible. However, there is no consensus on how best to quantify the randomness of responses in human-generated sequences. Traditionally, psychologists have used measures of randomness that directly assess specific features of human behavior in RNG tasks, such as the tendency to avoid repetition or to systematically generate numbers that have not been generated in the recent choice history, a behavior known as cycling. Other disciplines have proposed measures of randomness that are based on a more rigorous mathematical foundation and are less restricted to specific features of randomness, such as algorithmic complexity. More recently, variants of these measures have been proposed to assess systematic patterns in short sequences. We report the first large-scale integrative study to compare measures of specific aspects of randomness with entropy-derived measures based on information theory and measures based on algorithmic complexity. We compare the ability of the different measures to discriminate between human-generated sequences and truly random sequences based on atmospheric noise, and provide a systematic analysis of how the usefulness of randomness measures is affected by sequence length. We conclude with recommendations that can guide the selection of appropriate measures of randomness in psychological research. [ABSTRACT FROM AUTHOR]

To investigate the interference effects of lightning on unmanned aerial vehicle (UAV) navigation receivers, an analytical approach for the evaluation of indirect lightning effects is suggested. The blocking mechanism of lightning pulses on the receiver is analyzed using the vector method. A behavioral-level simulation model of the receiver's radio frequency (RF) front-end is constructed, and a lightning pulse injection simulation is performed based on the advanced design system (ADS). The simulation results indicate that lightning pulses induce blocking interference on the RF front-end of the navigation receiver, reducing its sensitivity and dynamic range. This interference is attributed to gain compression and degradation of the noise figure in the low-noise amplifier (LNA). To further validate the simulation results, a pin injection test is carried out to examine the influence of lightning pulses with different peak voltages on receiver sensitivity. The test results indicate a notable reduction in the receiver sensitivity when the lightning pulse peak reaches 250 V. The sensitivity trends across various test panels are consistent, and the damage thresholds are similar. These findings confirm the accuracy of the simulation results. [ABSTRACT FROM AUTHOR]

Lightning generated electromagnetic impulses propagating in the magnetospheric plasma disperse into whistlers – several seconds long radio wave signals with decreasing frequency. Sometimes, multiple reflections form long echo trains containing many whistlers with increasing dispersion. On January 3, 2017, two necessary prerequisites – a pronounced lightning activity and a magnetospheric plasma duct – allowed for observations of a large number of whistler echo trains by the high-latitude station in Kannuslehto, Finland. Our investigation reveals that the duct existed for nearly eight hours. We show that causative lightning sferics arrived to the duct entry from three different winter thunderstorms: a small storm at the Norwegian coast, which produced energetic lightning capable to trigger echo trains in 50% of cases, and two large storms at unexpectedly distant locations in the Mediterranean region. Our results show that intense thunderstorms can repetitively feed electromagnetic energy into a magnetospheric duct and form whistler echo trains after subionospheric propagation over distances as large as 4000 km. When lightning generated whistler waves echo multiple times, they are called whistler echo trains. Here, the authors show lightning strokes from three thunderstorm systems responsible for long-lasting and intense whistler echo trains. [ABSTRACT FROM AUTHOR]

Independent lightning rods are often installed in substation grounding systems for lightning protection. The concentrated discharge channel formed when a lightning current flows to the ground through a grounding electrode will cause electromagnetic interference to the directly buried secondary cable. And the three-dimensional structure of the discharge channel will affect the transient electromagnetic field distribution, thereby affecting the electromagnetic transients on cable shields. In order to explore the influence of soil discharge phenomena on the electromagnetic interference of the directly buried secondary cable, in this paper, we carried out experiments on cables in two different grounding modes, single-ended and double-ended grounding, and captured image of soil discharge channels. The results show that the cable grounding mode will affect the coupling mode that causes the shielding layer current. The relative spatial position of the soil discharge channel and the cable has a significant impact on the magnitude of the shielding layer current under both grounding modes. The water content and salt content of the soil also have different degrees of influence on the coupling current of the shielding layer in different grounding modes. [ABSTRACT FROM AUTHOR]

Chromospheric condensations (CCs) are a prominent feature of flare footpoint heating in the solar flare standard model, yet their timescales and velocities are not well understood. Fisher derived several important analytical relationships, which have rarely been examined with modern spectral observations. The Interface Region Imaging Spectrograph (IRIS) provides a wealth of flare data with a high enough cadence to sufficiently capture CC evolution. We analyzed Doppler shifts in Mg ii 2791 and Fe ii 2814 from a sample of flare footpoint pixels observed by IRIS to compare with Fisher's analytics and recent flare models. We found a detection lifetime of 1 minute occurs in 50% of the sample, with Mg ii showing several pixels with longer values and Fe ii almost categorically shorter, and both growing with the maximum velocity, v max. The shifts' half-life is commonly <40 s and is inversely related to v max, indicating that the first half of the CC evolution has more efficient kinetic energy loss. The lifetime's wide range and growth with v max indicate that the footpoint atmospherics and heating scenarios can vary more widely than first postulated in Fisher. Around 90% of the sample had observable acceleration periods, lasting an average of 38 and 32 s for Mg ii and Fe ii, respectively. These acceleration periods, as well as serving as flare model diagnostics themselves, could potentially be used to calculate other model diagnostics such as the initially accelerated mass. [ABSTRACT FROM AUTHOR]

Context. The pyramid wavefront sensor (PyWFS) provides the required sensitivity for demanding future adaptive optics (AO) instruments. However, the PyWFS is highly nonlinear and requires the use of beam modulation to successfully close an AO loop under varying atmospheric turbulence conditions. This comes at the expense of a loss in sensitivity. Aims. We trained, analyzed, and compared the use of deep neural networks (NNs) as nonlinear estimators for the nonmodulated PyWFS, identifying the most suitable NN architecture for a reliable closed-loop AO. Methods. We developed a novel training strategy for NNs that seeks to accommodate for changes in residual statistics between open and closed loops, plus the addition of noise for robustness purposes. Through simulations, we tested and compared several deep NNs from classical to new convolutional neural networks (CNNs), plus the most recent transformer neural network (TNN; global context visual transformer, GCViT), first for an open loop and then for a closed loop. By identifying and properly retraining the most adequate deep neural net, we tested its simulated performance first in an open loop and then for closing an AO loop at a variety of noise and turbulence conditions. We finally tested the trained NN ability to close a real AO loop for an optical bench. Results. Using open-loop simulated data, we observe that a TNN (GCViT) largely surpasses any CNN in estimation accuracy in a wide range of turbulence conditions. Moreover, the TNN performs better in a simulated closed loop than CNNs, avoiding estimation issues at the pupil borders. When closing the loop at strong turbulence and low noise, the TNN using nonmodulated PyWFS data is able to close the loop, similar to a PyWFS with 12λ/D of modulation. When the noise is increased, only the TNN is able to close the loop, while the standard linear reconstructor fails even when a modulation is introduced. Using the GCViT, we closed a real AO loop in the optical bench and achieved a Strehl ratio between 0.28 and 0.77 for turbulence conditions corresponding to Fried parameters ranging from 6 to 20 cm, respectively. Conclusions. Through a variety of simulated and experimental results, we demonstrate that a TNN is the most suitable architecture for extending the dynamic range without sacrificing sensitivity for a nonmodulated PyWFS. It opens the path for using nonmodulated Pyramid WFSs in an unprecedented range of atmospheric and noise conditions. [ABSTRACT FROM AUTHOR]

The rapid growth of e-commerce and the increasing importance of online shopping experiences necessitate a better understanding of online atmospherics. This research paper presents a comprehensive study on the antecedents of online atmospherics, proposing a conceptual framework to analyze the factors that contribute to a positive online experience. The study divides online atmospherics factors into three main categories: Design Factors, Ambient Factors, and Virtual Agents. Design play a crucial role in shaping users' perceptions and influencing their purchasing decisions. Ambient Factors, create an immersive atmosphere that enhances the overall user experience. Virtual Agents, facilitate user interactions and provide personalized assistance. This research highlights the need for online retailers to holistically consider these factors to optimize their online presence, ultimately leading to improved customer satisfaction, increased user engagement, and higher sales. The proposed conceptual framework serves as a foundation for future empirical studies to further investigate the relationships between these factors and their impact on online atmospherics. [ABSTRACT FROM AUTHOR]

NASA's Ice, Cloud, and land Elevation Satellite (ICESat-2), designed for surface altimetry, plays a pivotal role in providing precise ice sheet elevation measurements. While its primary focus is altimetry, ICESat-2 also offers valuable atmospheric data. Current conventional processing methods for producing atmospheric data products encounter challenges, particularly in conditions with low signal or high background noise. The thresholding technique traditionally used for atmospheric feature detection in lidar data uses a threshold value to accept signals while rejecting noise, which may result in signal loss or false detection in the presence of excessive noise. Traditional approaches for improving feature detection, such as averaging, lead to a trade-off between detection resolution and accuracy. In addition, the discrimination of cloud from aerosol in the identified features is difficult given ICESat-2's single wavelength and lack of depolarization measurement capability. To address these challenges, we demonstrate atmospheric feature detection and cloud–aerosol discrimination using deep learning-based semantic segmentation by a convolutional neural network (CNN). The key findings from our research are the effectiveness of a deep learning model for feature detection and cloud–aerosol classification in ICESat-2 atmospheric data and the model's surprising capability to detect complex atmospheric features at a finer resolution than is currently possible with traditional processing techniques. We identify several examples where the traditional feature detection and cloud–aerosol discrimination algorithms struggle, like in scenarios with several layers of vertically stacked clouds, or in the presence of clouds embedded within aerosol, and demonstrate the ability of the CNN model to detect such features, resolving the boundaries between adjacent layers and detecting clouds hidden within aerosol layers at a fine resolution. [ABSTRACT FROM AUTHOR]

The research aims to unearth the influence of major factors of Indoor(Green Spaces and Green Ambient Atmospherics) and Outdoor Green Atmospherics on employee well-being in Indian 5-star hotels. Responses were obtained from 328 employees in the Indian tourism sector using a non-probabilistic purposive sampling method. A partial least-square structural equation modeling (PLS-SEM) was applied for the analysis. The findings revealed that green indoor and outdoor atmospherics have a significant positive contribution toward the well-being and enhanced work environment among the workforce with work stress being a significantly negative mediator. The findings contribute to the existing studies as it empirically verify the hypothesized relationships. [ABSTRACT FROM AUTHOR]

In recent years, synthetic aperture radar (SAR) interferometry (InSAR) has emerged as a valuable tool for measuring water level change (WLC) to study hydrodynamic processes in coastal wetlands. However, the highly dynamic wet atmosphere conditions common in these areas have a significant impact on InSAR observations, producing errors in the derived values. Standard methods for estimating atmospheric noise in InSAR time series lack the spatial or temporal resolution needed to adequately correct for wet tropospheric delays. In this study, we utilize the Independent Component Analysis (ICA) signal decomposition technique to identify the likely WLC signal and eliminate atmospheric noise in a time series derived from rapid repeat measurements made with the L‐band uninhabited aerial vehicle synthetic aperture radar airborne instrument. The method compares in‐situ water level measurements with the independent components (IC) to identify the ICA components corresponding to WLC. The signal‐to‐noise ratio between the WLC after the ICA‐based filtering and in situ water level gauges used for validation reaches 16 dB compared to an average of 2.6 dB before filtering. The excluded IC are used to generate maps showing a time series of likely atmospheric features. The identified features in the maps generally correspond to atmospheric features identifiable in Next Generation Weather Radar (NEXRAD) S‐band ground weather radar reflectivity maps collected during the SAR acquisitions. The method is sufficiently general to be applied to any InSAR‐derived surface displacement time series. Key Points: Independent Component Analysis (ICA) is used to remove the wet troposphere noise in an InSAR‐derived time series of water level change in wetlandsIn‐situ data are used to identify components showing water level change and the other components used to generate tropospheric delay mapsThe filtered water level change values have improved accuracy based on measurements from water gauges located throughout the wetlands [ABSTRACT FROM AUTHOR]

Lidar (Light Detection and Ranging), utilizes laser based remote sensing data to measure distances and properties of objects by analysing reflected light, serving diverse applications. Lidar signals in the middle atmosphere face challenges like noise and atmospheric uncertainties. Lidar signal denoising and temperature retrievals are crucial for accurate measurements, improving data reliability in atmospheric research. Lidar signal denoising is the process of reducing unwanted noise or interference from Lidar data, enhancing accuracy and reliability. To address the issues Shuffle Attention with Encoder and Decoder based Deep Convolutional Neural Network (SAED-DCNN) is proposed. The Lidar signal undergoes preprocessing, including normalization, followed by convolution and pooling encoding in the autoencoding layer of SAED-DCNN. Leveraging Deep Convolutional Neural Network (DCNN) and encoder-decoder Framework, with shuffle attention, enhances spatial interactions for reducing Lidar signal noise. the introduction of enhanced spider wasp optimization addresses computational complexity, optimizing SAED-DCNN parameters, presenting an innovative Lidar signal enhancement approach. The suggested framework exhibits outstanding performance, achieving signal-to-noise ratio and root mean squared error of 28.135 dB and 68.113, respectively. These metrics underscores the mode's efficacy in overcoming denoising challenges, establishing it as a robust denoising solution. [ABSTRACT FROM AUTHOR]

In this work, we propose a differential complementary split-ring resonator (CSRR) sensor as the resonating element for permittivity analysis of liquid samples. In comparison to conventional non-differential sensors, differential sensors are found to be immune to environmental changes. The proposed sensor operates at 2.35 GHz of the ISM band and is built on a low-cost FR4 substrate. The sensor is thoroughly optimized and validated using Ansys High Frequency Structure Simulator software. Multiple liquid samples covering a wide dielectric range of 1–111 are used to determine the sensing performance of the sensor. The sensitivity of the sensor is found to be high and on par with recent works related to differential CSRR sensors. Based on the frequency of the transmission notch observed, a fit equation is developed to determine the dielectric constant of unknown samples. The proposed differential sensor promises to be a good alternative to traditional CSRR sensors for requirements involving noise and atmospheric fluctuations. [ABSTRACT FROM AUTHOR]

• A novel optimization algorithm integrating random and grid search mechanisms as function calls. • A cost-effective low inference time deep learning model for detecting 2D ionospheric plasma structures from all-sky airglow images. • The issue of uncertainty quantification has been addressed using the approach of bootstrapping. The ionosphere, part of the Earth's atmosphere, where different plasma irregularities/structures are generated through various electrodynamical processes. Airglow imaging is one of the tools to observe various morphological features of these irregularities. We aim to help all-sky airglow imaging-based ionospheric research by proposing novel deep learning at the edge framework for the detection of different types of mid-latitude ionospheric plasma structures (medium scale traveling ionospheric disturbances with single and multiple bands, and plasma bubbles). The primary challenge was to find an optimal deep neural network by considering the trade-off between accuracy and inference time. In order to address this, a novel hyperparameter optimization technique has been used that integrates the approaches of random and grid search mechanisms as a compact function. The random function generates the subspace for hyperparameters to check the convergence of the model while the grid search creates possible combinations to tune these hyperparameters. Our novel optimization method for deep learning inference at the edge led us to a low-cost, high-accuracy convolutional neural network (CNN) model, which outperformed the complex state-of-the-art deep learning models such as Inception-v3, DenseNet169, VGG16, and VGG19. For airglow image-based plasma structure detection, the proposed model recorded an accuracy of 99.9% with an inference time of 5.8 s. This was an improvement of about 4% in accuracy while 85% reduction in inference time over the best-performing baseline. There was about 93% reduction in the number of model parameters with respect to the best-performing baseline. Uncertainty quantification has also been performed in the present work through bootstrapping to validate the robustness of the proposed model. The findings of our study show the promise of deep learning at the edge for all-sky airglow imaging systems by demonstrating an alternate low-cost, high-accuracy deep neural network. [ABSTRACT FROM AUTHOR]

The variability of the shortwave radiative fluxes at the surface and top of atmosphere (TOA) is examined in a pre‐industrial modeling setup using the Pacific Decadal Oscillation (PDO) as a possible pacemaker of atmospheric decadal‐scale variability. Within models from the Coupled Model Intercomparison Project—Phase 6, downwelling shortwave radiation at the surface, the net shortwave fluxes at the surface and TOA, as well as cloud radiative effects show remarkably similar patterns associated with the PDO. Through ensemble simulations designed with a pure PDO pattern in the North Pacific only, we show that the PDO relates to about 20%–40% of the unforced year‐to‐year variability of these shortwave fluxes over the Northern Hemispheric continents. The sea surface temperature imprint on shortwave‐flux variability over land is larger for spatially aggregated time series as compared to smaller areas, due to the blurring effect of small‐scale atmospheric noise. The surface and TOA radiative flux anomalies associated with the PDO index range of [−1.64; 1.64] are estimated to reach up to ±6 Wm−2 for North America, ∓3 Wm−2 for India and ±2 Wm−2 for Europe. We hypothesize that the redistribution of clouds in response to a North Pacific PDO anomaly can impact the South Pacific and North Atlantic SSTs. Plain Language Summary: We investigate how solar radiation at Earth's surface and the top of the atmosphere, which are mainly controlled by cloudiness, can vary over decades as a response to a horseshoe pattern typical for the North Pacific sea surface temperatures (SSTs)—the Pacific Decadal Oscillation (PDO). We use idealized climate model simulations to show that about a third of the year‐to‐year changes in solar radiation over the Northern Hemispheric continents are related to this phenomenon. These changes are more noticeable when looking at large areas rather than small ones, as high frequency smaller scale atmospheric variations can obscure the bigger picture. By keeping the PDO fixed to a constant negative value, implying below average cold sea surface temperatures off the western coast of North America and warmer than average temperatures toward Japan, we show that North America and Europe exhibit a reduction in cloudiness, while clouds increase in India. The same with an opposite sign is true for a positive PDO anomaly. These changes in cloud patterns might further affect SSTs in the South Pacific and North Atlantic oceans. Key Points: The Pacific Decadal Oscillation (PDO) is a prominent pacemaker for variability, accounting for about 1/3 of the shortwave flux year‐to‐year variability over NH continentsA negative PDO anomaly leads to a reduction in atmospheric shortwave reflectivity (clouds) in North America and Europe and an increase in IndiaThe redistribution of clouds in response to a North Pacific PDO anomaly might influence SSTs in the South Pacific and North Atlantic [ABSTRACT FROM AUTHOR]

Space plasma turbulence plays a relevant role in several plasma environments, such as solar wind and the Earth's magnetosphere–ionosphere system, and is essential for describing their complex coupling. This interaction gives rise to various phenomena, including ionospheric irregularities and the amplification of magnetospheric and ionospheric currents. The structure and dynamics of these currents have relevant implications, for example, in studying ionospheric heating and the nature of electric and magnetic field fluctuations in the auroral and polar environments. In this study, we investigate the nature of small-scale fluctuations characterizing the ionospheric magnetic field in response to different geomagnetic conditions. We use high-resolution (50 Hz) magnetic data from the ESA's Swarm mission, collected during a series of high-latitude crossings, to probe the scaling features of magnetic field fluctuations in auroral and polar cap regions at spatial scales still poorly explored. Our findings reveal that magnetic field fluctuations in field-aligned currents (FACs) and polar cap regions across both hemispheres are characterized by different scaling properties, suggesting a distinct driver of turbulence. Furthermore, we find that geomagnetic activity significantly influences the nature of energy dissipation in FAC regions, leading to more localized filamentary structures toward smaller scales. [ABSTRACT FROM AUTHOR]

A solar eclipse (SE) can cause disturbances in all subsystems of the Earth–atmosphere–ionosphere–magnetosphere system, including the geomagnetic field. Using the data obtained at 15 stations of the INTERMAGNET network, the temporal variations of all components of the geomagnetic field are analyzed. It is found that the SE has been accompanied by a disturbance of the X-, Y-, and Z-components. The largest disturbances have been detected for the X-component (south–north). There has been a steady tendency to increase the disturbance of the X-component with an increase in the area of the solar disk obscuration. The disturbance magnitude of the X-component level under the influence of the SE is calculated. It is believed that the main mechanism for generating the magnetic effect is the disturbance of the ionospheric current system at the heights of the dynamo region. The results of observations and calculations are in good agreement with each other. In addition to a stable aperiodic effect lasting approximately 100...180 min, an increase in the range of fluctuations in the geomagnetic field level has been observed during the SE. This may indicate the generation of quasi-periodic disturbances of the geomagnetic field in the range of atmospheric gravity waves. [ABSTRACT FROM AUTHOR]

Despite the acknowledged connection between physical environment and human behavior, the literature often underestimates the crucial role of hotel spatial layout and its relation to other factors in shaping customer loyalty. The layout of theme hotels is often simply considered a general environmental consideration, ignoring its far-reaching impact. This research proposes that guests staying at theme hotels will perceive value when utilizing the layout and appreciate all aspects of hotel facilities. This, in turn, influences their value perception and loyalty to the hotel. To analyze the data, confirmatory factor analysis and path analysis were employed on a sample of 298 individuals who stayed in theme hotels. The findings from these analyses reveal that both the hotel layout and the external environment positively influence guests' evaluations of the internal environment (R2 = 0.640). Furthermore, the evaluation of the internal environment and layout significantly impacts guests' perceived values (R2 = 0.517), subsequently shaping their loyalty to the hotel (R2 = 0.370). Perceived value emerges as a vital mediating factor between the layout and customer loyalty. This study presents compelling evidence that spatial layout significantly influences customer loyalty in theme hotels through perceived value, transcending internal and external environmental boundaries. [ABSTRACT FROM AUTHOR]

We present the observations of field‐aligned currents and the equatorial electrojet during the 23 March 2023 magnetic storm, focusing on the effect of the drastic decrease of the solar wind dynamic pressure occurred during the main phase. Our observations show that the negative pressure pulse had significant impact to the magnetosphere‐ionosphere system. It weakened large‐scale field‐aligned currents and paused the progression of the storm main phase for ∼3 hr. Due to the sudden decrease of the plasma convection after the negative pressure pulse, the low‐latitude ionosphere was over‐shielded and experienced a brief period of westward penetration electric field, which reversed the direction of the equatorial electrojet. The counter electrojet was observed both in space and on the ground. A transient, localized enhancement of downward field‐aligned current was observed near dawn, consistent with the mechanism for transmitting MHD disturbances from magnetosphere to the ionosphere after the negative pressure pulse. Plain Language Summary: The solar wind is a continuous stream of charged particles blowing from the Sun. The Earth's magnetic field forms a protective shield around our planet, called the magnetosphere, which deflects most of the solar wind particles away from the Earth. Disturbances in the solar wind can interact with the magnetosphere and impact the Earth's upper atmosphere (ionosphere). The interaction creates electric fields forcing charged particles to move in the magnetosphere, which creates electric currents flowing along the magnetic field lines connecting to the high‐latitude ionosphere and drives the movement of charged particles there. The low‐latitude ionosphere is generally shielded from these electric fields. Sudden changes in the solar wind can break such balance, leading to the electric field penetration to low latitudes. We examined how the magnetosphere and ionosphere interacted during the 23 March 2023 geomagnetic storm, focusing on what happened when the solar wind dynamic pressure suddenly decreased. We found the pressure drop caused a sudden decrease of the high‐latitude electric field, resulting in a brief period of overshielding and the electric field in the equatorial ionosphere reversed its direction. This changed the direction of the equatorial electrojet, a major electric current in the ionosphere at the magnetic equator. Key Points: Direct evidence of prompt penetration of electric field in the equatorial ionosphere caused by negative solar wind pressure pulseTransient counter electrojet caused by westward penetration electric field after the arrival of negative pressure pulseSignificant decrease of global large‐scale field‐aligned currents (FACs) and transient enhancement of localized FAC in response to negative pressure pulse [ABSTRACT FROM AUTHOR]

We statistically evaluate the global distribution and energy spectrum of electron precipitation at low‐Earth‐orbit, using unprecedented pitch‐angle and energy resolved data from the Electron Losses and Fields INvestigation CubeSats. Our statistical results indicate that during active conditions, the ∼63 keV electron precipitation ratio peaks at L > 6 at midnight, whereas the spatial distribution of precipitating energy flux peaks between the dawn and noon sectors. ∼1 MeV electron precipitation ratio peaks near midnight at L > ∼6 but is enhanced near dusk during active times. The energy spectrum of the precipitation ratio shows reversal points indicating energy dispersion as a function of L shell in both the slot region and at L > ∼6, consistent with hiss‐driven precipitation and current sheet scattering, respectively. Our findings provide accurate quantification of electron precipitation at various energies in a broad region of the Earth's magnetosphere, which is critical for magnetosphere‐ionosphere coupling. Plain Language Summary: Precipitation into the Earth's upper atmosphere is an important loss process of radiation belt electrons and can change the ionospheric conductance and atmospheric chemistry. Electrons can be moved into the loss cone through either wave‐particle interactions or due to special magnetic field geometries, such as current sheet scattering (CSS). To determine the relative contribution of wave‐particle interactions and CSS, it is crucial to investigate the global distribution and energy spectra of the electron precipitation rate. Previous measurements of energetic electron precipitation at low‐Earth‐orbit either had low resolution in pitch angle and energy or were contaminated by ions and penetrating particles. In this study, we used data from the twin Electron Losses and Fields INvestigation CubeSats, which do not suffer from similar deficiencies, to statistically analyze the dependence of energetic electron precipitation rates on geomagnetic activity, with high resolution in both pitch angle and energy. These findings cast new light on the physical mechanisms that determine the precipitation rate from the magnetosphere into the atmosphere and may have implications for future studies of the ionospheric conductivity and atmospheric chemistry. Key Points: A global survey of electron precipitation is performed using the pitch angle and energy resolved data from Electron Losses and Fields INvestigation CubeSatsAt ∼1 MeV, electron precipitation is strongest at L > ∼6 near midnight and is enhanced near dusk during active timesThe energy spectrum of the precipitation ratio shows reversal points indicating energy dispersion in L shells in the slot region and L > ∼6 [ABSTRACT FROM AUTHOR]

Measurements of Very Low Frequency (VLF) signals from navy transmitters carry direct information about the D‐region ionosphere and have been widely utilized for detecting the electron density at D‐region altitudes, but not frequently for the atmospheric waves therein. Atmospheric waves have been extensively studied using the total ionospheric electron content, but if and how they are correlated with the D‐region ionosphere and VLF measurements still remains poorly investigated. In this study, we have conducted a comprehensive analysis using 7‐year measurements (2016–2022) of VLF signals from the JJI, NWC, and VTX transmitters as being recorded in Suizhou, China. These three transmitter‐receiver paths are representative and the corresponding observations constitute a valuable data set to investigate the periodicities of VLF data. Different from previous studies, we have utilized the ensemble empirical mode decomposition and Lomb‐Scargle methods to determine the periodicities of these data. By contrasting these paths, prominent periodicities ranging from 2 to 730 days have been found, with clear diurnal variation and suggestive latitudinal/longitudinal dependence. Moreover, we have found that the mesospheric temperature is closely related with the annual oscillation of VLF measurements, while this oscillation has a low correlation with solar Lyman‐α fluxes or geomagnetic activity. The oscillations with relatively shorter periods are likely atmospheric waves such as gravity waves, planetary waves, or harmonics of these waves. Our results suggest that, in addition to the electron density, the subionospheric VLF technique can be potentially utilized to remotely sense atmospheric waves that propagate up to or through the D‐region ionosphere. Plain Language Summary: Radio waves in the very low frequency range (VLF, 3–30 kHz) can propagate long distances within the Earth's atmosphere between the surface and the D‐region ionosphere, a region at altitudes of 60–100 km that is influenced by both solar fluxes that propagate through the upper atmosphere to the D‐region ionosphere and atmospheric waves from the lower atmosphere. Measurements of VLF waves from navy transmitters have been widely utilized to detect the electron density of D‐region ionosphere, but not the atmospheric waves therein. Toward this goal, we have investigated the VLF measurements recorded by our detector in Suizhou, China. These signals originate from the JJI transmitter in Japan, the NWC transmitter in Australia, and the VTX transmitter in India. The results show that these VLF signals have clear periodic oscillations ranging from 2 to 730 days, exhibiting notable variation between daytime and nighttime conditions, and suggestive dependence on the latitudes/longitudes the VLF propagation path crosses. Moreover, we have analyzed the main reason for the annual oscillation of VLF measurements and found that the annual oscillation is mainly driven by the mesospheric temperature. Our work demonstrates the potential usage of the VLF technique in remotely sensing the atmospheric waves of D‐region ionosphere. Key Points: We have quantified the periodicities of 7‐year VLF measurements using the empirical mode decomposition and Lomb‐Scargle methodsPeriods ranging from 2 to 730 days have been found with clear diurnal dependence and latitudinal/longitudinal dependenceThe annual oscillation is closely correlated with mesospheric temperature, while low correlation with Lyman‐α fluxes or geomagnetic activity [ABSTRACT FROM AUTHOR]

Global navigation satellite system (GNSS) provides users with all-weather, continuous, high-precision positioning, navigation, and timing (PNT) services. In the operation and use of GNSS, the influence of the space environment is a factor that must be considered. For example, during geomagnetic storms, a series of changes in the Earth's magnetosphere, ionosphere, and upper atmosphere affect GNSS's positioning performance. To investigate the positioning performance of global satellite navigation systems during geomagnetic storms, this study selected three geomagnetic storm events that occurred from September to December 2023. Utilizing the global positioning system (GPS)/Beidou navigation satellite system (BDS) dual-system, kinematic precise point positioning (PPP) experiments were conducted, and the raw observational data from 100 stations worldwide was analyzed. The experimental results show that the positioning accuracy of some stations in high-latitude areas decreases significantly when using the conventional Geometry Free (GF) cycle-slip detection threshold during geomagnetic storms, which means that the GF is no longer applicable to high-precision positioning services. Meanwhile, there is no significant change in the satellite signal strengths received at the stations during the period of the decrease in positioning accuracy. Analyzing the cycle-slip rates for stations where abnormal accuracy occurred, it was observed that stations experiencing a significant decline in positioning accuracy exhibited serious cycle-slip misjudgments. To improve the kinematic PPP accuracy during magnetic storms, this paper proposes an adaptive threshold for cycle-slip detection and designs five experimental strategies. After using the GF adaptive threshold, the station positioning accuracy improved significantly. It achieved the accuracy level of the quiet period, while the cycle-slip incidence reached the average level. During magnetic storms, the ionosphere changes rapidly, and the use of the traditional GF constant threshold will cause serious cycle-slip misjudgments, which makes the dynamic accuracy in high latitude areas and some mid-latitude areas uncommon, while the use of the GF adaptive threshold can alleviate this phenomenon and improve the positioning accuracy in the high-latitude regions and some of the affected mid-latitude areas during the magnetic storms. [ABSTRACT FROM AUTHOR]

Ocean–atmosphere interactions largely control the variabilities of the climate system on Earth. However, how much atmospheric internal signals contribute to climate variabilities remains uncertain over many parts of the globe. Here, we develop an interactive ensemble coupled model (called Hydra‐SINTEX) to investigate the influences of atmospheric internal variations (AIVs) on the mean‐states and variability of the climate system. The results show that, while climatological mean‐states are little affected, the AIVs can largely influence climate variabilities over the globe. We pay particular attention to two regions, that is, the tropical eastern Indian Ocean, which is the key area of the Indian Ocean Dipole (IOD), and the subtropical North Pacific. We found that sea surface temperature (SST) variabilities in these two regions are much reduced without the AIVs but with distinct mechanisms. Without the AIVs, the intensity of the IOD is largely reduced in association with weakened air–sea coupling in the tropics. This indicates the importance of atmospheric noise forcing on the development of the IOD. In contrast, the reduction of SST variability in the subtropical North Pacific is caused by the absence of the AIVs that are generated by both mid‐latitude atmospheric processes and weakened remote influence of the tropical SST in accordance with the reduced SST signals there. Plain Language Summary: Ocean–atmosphere interactions are pivotal in shaping Earth's climate system. However, how much atmospheric internal variations (AIVs) contribute to climate variabilities remains uncertain in many places over the globe. Here, we have devised an interactive ensemble coupled model (called Hydra‐SINTEX), allowing us to explore the impacts of the AIVs on the mean‐states and variabilities of the climate system. The results reveal that, while climatological mean‐states remain little affected, the AIVs significantly influence global climate variabilities. We focus on two specific regions: the tropical eastern Indian Ocean, a critical area for the Indian Ocean Dipole (IOD), and the subtropical North Pacific. We have observed that SST variabilities in these regions are notably reduced in the absence of the AIVs through distinct mechanisms. In the case of the IOD, the absence of the AIVs leads to a considerable decrease in its intensity. This underscores the significance of atmospheric noise forcing in influencing the development of the IOD. Conversely, the reduction of SST variability in the subtropical North Pacific can be attributed to the absence of the AIVs generated by mid‐latitude atmospheric processes and the diminished influence of tropical SST signals. Key Points: A developed interactive ensemble model is to investigate the impacts of atmospheric internal variations (AIVs) on climate variabilitiesThe results suggest that the AIVs largely impact sea surface temperature (SST) variability but with distinct regional featuresWithout the AIVs, variabilities of the SST in the tropics and extra‐tropics are much reduced [ABSTRACT FROM AUTHOR]

An accurate modeling of the ionosphere electron density is pivotal to guarantee the effective operation of communication and navigation systems, particularly during Space Weather events. Despite the crucial contribution of empirical models like the International Reference Ionosphere (IRI), their limitations in predicting ionospheric variability, especially under geomagnetically disturbed conditions, are acknowledged. The solution proposed in this work involves integrating real‐time, spatially distributed ionospheric measurements into climatological models through data assimilation. To enhance our predictive capabilities, we present an upgrade of the IRI UP data‐assimilation method, incorporating real‐time vertical total electron content (vTEC) maps from the IONORING algorithm for nowcasting ionospheric conditions over Italy. This approach involves updating the IRI F2‐layer peak electron density description through ionospheric indices, to finally produce real‐time maps over Italy of the ordinary critical frequency of the F2‐layer, foF2, which is crucial for radio‐propagation applications. The IRI UP–IONORING method performance has been evaluated against different climatological and nowcasting models, and under different Space Weather conditions, by showing promising outcomes which encourages its inclusion in the portfolio of ionospheric real‐time products available over Italy. The validation analysis highlighted also what are the current limitations of the IRI UP–IONORING method, particularly during nighttime for severely disturbed conditions, suggesting avenues for future enhancements. Plain Language Summary: Ensuring the smooth operation of communication and navigation systems based on both High‐Frequency and GNSS radio signals relies on accurately modeling the density of electrons in the ionosphere. Existing empirical models, like the International Reference Ionosphere (IRI), have limitations in predicting small‐scale spatial and temporal changes in the ionosphere, especially during severe Space Weather events. This work proposes a solution by incorporating real‐time ionospheric measurements into a background model through a process called data assimilation. Specifically, the IRI UP method has been upgraded by assimilating real‐time vertical total electron content maps from the IONORING algorithm for nowcasting ionospheric conditions over Italy. The performance of this upgraded method has been tested against different models and for different Space Weather conditions, showing promising results. These findings open avenues for future improvements contributing to enhancing our ability to predict and adapt to dynamic changes in the Earth's ionosphere, of which various communication and navigation technologies would benefit. Key Points: IRI UP method upgrade through the assimilation of real‐time vTEC maps from IONORING for nowcasting ionospheric conditions over ItalyIRI UP outputs real‐time foF2 maps over Italy through the ingestion of ionospheric effective indices maps in the background IRI modelIt has been successfully tested against several climatological and nowcasting models, and under different Space Weather conditions [ABSTRACT FROM AUTHOR]

Large‐scale ionospheric gradients associated with the solar terminator can deflect high frequency (HF) radio waves to off‐great circle paths during the morning and evening, negatively impacting technologies reliant on HF radio wave propagation. For example, geolocation algorithms used by scientific and military over‐the‐horizon radars (OTHRs) generally assume on‐great circle propagation, and thus lateral deviations from the great‐circle path can lead to positioning errors. In this study, radio wave propagation is simulated via 3D numerical ray traces though an empirical, high‐latitude model ionosphere initialized for a variety of times of the day and year to explore and quantify high‐latitude off‐great circle propagation associated with the solar terminator. Analysis of these simulations show large scale east‐west ionospheric gradients due to the solar terminator can cause lateral deviations in north‐directed propagation paths exceeding 20° at sunrise and sunset depending on radio wave frequency, though the largest portion of received signal power tends to experience maximum deflections of 5°. An exploration of the dependence of propagation direction on deflection shows that propagation paths parallel to the solar terminator tend to experience the largest deflections. Since the solar terminator at high latitudes is at an angle with respect to north in the winter and summer, propagation paths oriented west or east of north can experience larger deflections than north oriented paths at sunrise and sunset during these times of year. Impacts of these diurnal deflections on the operation of OTHR and scientific radar are discussed, as well as possible strategies for mitigating them. Plain Language Summary: High frequency (HF) radio waves are able to travel long distances by bouncing between the ionosphere (an upper layer of the Earth's atmosphere) and the ground. HF radio waves transmitted north can have their paths deflected east or west by changes in the ionosphere that happen at sunrise and sunset. In this paper, simulations of radio waves are used to explore how large these deflections can be and how they change over the course of the day and year. It is found that north pointing radio signals at certain frequencies can be deflected by more than 20° at sunrise and sunset. These simulations are also used to explore how radio waves transmitted in different directions are deflected at sunrise and sunset. It is found that radio waves transmitted along the dividing line between day and night tend to experience the largest deflections. The Earth is tilted with respect to its rotation, meaning this dividing line is not always aligned with North. The deviation from north is largest in the winter and summer. This means that radio waves transmitted west or east of north at these times of year can experience larger deflections than northward transmissions. Key Points: The lateral deflection of high frequency radio waves caused by the solar terminator is investigated with ray tracing simulationsNorth‐south propagation paths can experience significant (>20°) deflections in the morning and eveningEast‐west paths can also see significant deflections at high latitudes, at times when the solar terminator is also oriented east‐west [ABSTRACT FROM AUTHOR]

Mass changes in the hydrosphere represent an important contributor to polar motion (PM) variations, especially at seasonal time scales (i.e., annual and semiannual). Although well studied, hydrological angular momentum (HAM) remains a major source of uncertainty in estimating PM excitation. In this work, we use a large number of climate models from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to determine HAM series both from individual models and their combination, formed with a multimodel mean, a weighted mean, and a three-cornered hat (TCH) method. The CMIP6-based HAM series are analysed in several spectral bands and evaluated with a reference hydrological signal in geodetically observed PM excitation (GAO). HAM determined from CMIP6 were also compared to HAM calculated from Gravity Recovery and Climate Experiment (GRACE) measurements. We find that while climate models do not allow for reliable estimation of nonseasonal changes in HAM, they can help interpret seasonal variability. For annual prograde and semiannual retrograde oscillations, several combined CMIP6- based series exhibit higher amplitude and phase consistency with GAO than the corresponding series computed from GRACE data. Whether one uses a simple average of the models, a weighted average, or a combination of models from the TCH method has little impact on the resulting HAM series and their level of agreement with GAO. Our study advances the understanding of hydrological signal in Earth's rotation at seasonal time scales. [ABSTRACT FROM AUTHOR]

The North Pacific sea surface temperature (SST) has a profound climatic influence. The El Niño‐Southern Oscillation (ENSO) significantly impacts the North Pacific SST; however, the influence of the distinct phases of ENSO on SST predictability remains unclear. To overcome the model limitations, this study assessed SST predictability under diverse ENSO phases using reanalysis. The predictability limit of the North Pacific SST under La Niña (8.4 months) is longer than that under Neutral (5.9 months) and El Niño (5.5 months) conditions, which unveils asymmetry. This asymmetry mirrors contemporary multimodal prediction skills. Error growth dynamics reveal La Niña's robust signal strength with a slow error growth rate, in contrast to El Niño's weaker signal and faster error growth. There exhibits intermediate signal strength and elevated error growth in Neutral condition. Physically, predictability signal strength aligns with SST variability, whereas the error growth rate correlates with atmospheric‐ocean heating anomalies. La Niña, which induces positive heating anomalies, minimizes the impact of atmospheric noise, resulting in lower error growth. The result is beneficial for improving North Pacific SST predictions. Plain Language Summary: The North Pacific sea surface temperature (SST) significantly impacts global climate, particularly in East Asia and the United States. Accurate prediction of North Pacific SST, which is crucial for seasonal and interannual forecasting, remains a focal point in atmospheric and oceanic research. This study investigates how the El Niño‐Southern Oscillation (ENSO) influences SST predictability in the North Pacific during different phases (El Niño, La Niña, Neutral). Using reanalysis data, this research introduces the concept of predictability limit (PL), revealing an asymmetry in the PL response: La Niña extends the PL to 8.4 months, El Niño shortens it to 5.5 months, and Neutral falls in 5.9 months. This asymmetry aligns with the existing prediction skills. Examining the error growth dynamics, La Niña exhibits a robust SST signal with slower error growth, whereas El Niño displays a weaker signal with faster error growth. Neutral, meanwhile, shows a high signal strength but large error growth. This study sheds light on these differences in SST predictability and provides valuable insights for refining North Pacific SST predictions through model advancements. Key Points: El Niño‐Southern Oscillation phases asymmetrically impact North Pacific sea surface temperature (SST) predictability: El Niño (5.5 months), La Niña (8.4 months), Neutral (5.9 months)Error growth dynamics vary: La Niña displays strong signals with slow growth, El Niño exhibits weak signals and rapid growthA positive heating anomaly from La Niña reduces atmospheric noise impact, resulting in a smaller error growth rate of the North Pacific SST [ABSTRACT FROM AUTHOR]

A fully automated processing system for measuring long-term ground deformation time series and deformation rates frame-by-frame using the Differential Interferometric Synthetic Aperture Radar (DInSAR) processing technique was developed and tested. Among the several factors that affect DInSAR's precision, such as temporal decorrelation and atmospheric noise, it was observed that seasonal spatial-temporal variability in radar penetration depth is the greatest contributor to the loss of precision of the long-term deformation rate measurement. This spatial-temporal signal is described for a specific region in the northern US; however, it is widely observed in multiple regions. In these regions, a gradual penetration depth increase is observed in fall and winter, and an abrupt penetration depth decrease is observed in spring. The latter effect is likely caused by rapid melting of ice and snow that, at the same time, significantly reduces interferometric coherence. Within a specific geographic region, radar penetration depth spatially varies proportionally to the elevation due to an elevation-dependent temperature gradient, producing artifacts that correlate well with the topography. This signal does not extend to high-elevation regions (above ~2500 m) that do not experience seasonal thawing, which allows for distinguishing it from the topography-dependent atmospheric signals. Without accounting for the spatial-temporal variability in radar penetration depth, deformation time series in these areas can contain either an annual periodic signal with an amplitude of over 0.1 m or, if the abrupt penetration depth decrease produced by melting is not resolved due to lower coherence, an erroneous interannual trend. Spatial-temporal variability in radar penetration depth needs to be better understood and corrected to improve the precision of long-term deformation rate products, particularly in regions susceptible to seasonal freezing and thawing. [ABSTRACT FROM AUTHOR]

Infrared multispectral imaging technology can achieve the long-distance, wide-ranging and fast detection of target gas, and has been widely used in the fields of dangerous-gas detection and environmental monitoring. However, due to the difficulty in acquiring background radiation as well as atmospheric disturbance and noise interference in the detection process, the quantitative detection of gas concentration has become a difficult problem to solve. Therefore, this paper proposes an inversion method for gas column concentration based on infrared multispectral imaging technology. Firstly, infrared background radiation images of the non-target gas absorption spectrum band were collected and converted into background radiation images of the target gas absorption spectrum band according to the dual-channel mapping relationship. Then, combined with the gas radiation images of the target gas absorption spectrum band, the column concentration distribution of the gas was obtained by using the measured calibration relationship between absorbance and column concentration. Experiments of gas detection in different environments were carried out, and the column concentration distribution of the target gas was inverted using this method; the results showed that the average relative error of the inversion of the gas column concentration was 4.84%, which enables the quantitative detection of gas column concentration in a complex environment. [ABSTRACT FROM AUTHOR]

Slow and long-term variations of sea surface temperature anomalies have been interpreted as a red-noise response of the ocean surface mixed layer to fast and random atmospheric perturbations. How fast the atmospheric noise is damped depends on the mixed layer depth. In this work we apply this theory to determine the relevant spatial and temporal scales of surface layer thermal inertia in lakes. We fit a first order auto-regressive model to the satellite-derived Lake Surface Water Temperature (LSWT) anomalies in Lake Garda, Italy. The fit provides a time scale, from which we determine the mixed layer depth. The obtained result shows a clear spatial pattern resembling the morphological features of the lake, with larger values (7.18± 0.3 m) in the deeper northwestern basin, and smaller values (3.18 ± 0.24 m) in the southern shallower basin. Such variations are confirmed by in-situ measurements in three monitoring points in the lake and connect to the first Empirical Orthogonal Function of satellite-derived LSWT and chlorophyll-a concentration. Evidence from our case study open a new perspective for interpreting lake-atmosphere interactions and confirm that remotely sensed variables, typically associated with properties of the surface layers, also carry information on the relevant spatial and temporal scales of mixed-layer processes. [ABSTRACT FROM AUTHOR]

This essay attends to the formal atmospherics of early modern drama—the ways in which the felt, affective conditions of playing could help to make one play seem like or unlike others. Specifically, it traces the development and function of a distinctive formal pattern used in the multisensory representation of battle. Commotion (literally, "continuous or recurring motion") is punctuated in these plays by moments of stillness, which are signaled through the language of breath and breathing: characters, players, and playgoers "pause" and "take breath" together. Turning to the early histories and to Shakespeare's collaboratively written Henry VI plays in particular, this essay argues that this structuring pattern of commotion and stillness, noise and quiet, shapes the plays of the first tetralogy in ways that help to organize attention and underscore the experience of dramatic time. [A.D] [ABSTRACT FROM AUTHOR]

Abstract—A theoretical formalism has been developed to calculate the electromagnetic fields generated in the atmosphere–ionosphere system by a finite-length underground horizontal current source. A numerical model with a realistic profile of the ionosphere in a vertical geomagnetic field has been constructed based on this theory. It is shown that the apparent impedance of the electromagnetic field produced by an underground source on the Earth surface is an order of magnitude higher than the Earth impedance; this can be used to discriminate perturbations from seismogenic sources. The presented results of numerical modeling allow us to relate perturbations created by a large-scale underground source in the magnetic field of the Earth surface and in the electric field in the ionosphere. Based on these model estimates, it is concluded that many of the ULF electric field perturbations detected in satellite data prior to earthquakes cannot be attributed to direct emission from seismogenic sources. [ABSTRACT FROM AUTHOR]

Earthquake source parameters can be estimated using seismological observations, but the identification of the fault responsible is often complicated by location uncertainties and the inherent ambiguity between nodal planes. Satellite Interferometric Synthetic Aperture Radar (InSAR) can be used to observe ground deformation and model fault geometry but is limited by climate conditions (water vapour) and ground coverage (dense vegetation). In the tropics, the atmosphere is dynamic and most regions are densely vegetated, making detecting coseismic deformation challenging. Here, we perform a systematic inspection of coseismic interferograms from Sentinel-1 SAR images, to assess their suitability for detecting coseismic deformation in Costa Rica. Using data from the seismological network, we target seven earthquakes between 2016 and 2020 with depths |$\le \, 20$| km and magnitudes M w 5.3–6.2. For each event, we use the seismic parameters to compute line-of-sight displacements for ascending and descending geometries and for both nodal planes and generate 12- and 24-d coseismic interferograms where available. We obtain interferograms with coseismic displacement signals for three of the seven earthquakes. We invert the geodetic data to retrieve the earthquake source parameters but the lack of offshore geodetic coverage causes trade-offs between parameters and large uncertainties. The Jacó and Golfito earthquakes likely occurred on the subduction interface and the geodetic locations were 6–9 km closer to the coast than previous seismic estimates. The Burica earthquake occurred on a shallow steeply dipping thrust fault in the outer forearc. For the other earthquakes, no coseismic deformation was detected due to atmospheric noise or poor coherence. These results demonstrate the suitability of 12-d Sentinel-1 interferograms for monitoring shallow earthquakes of magnitude > M w 5.7 in Central America. This approach can be used to begin a surface deformation catalogue for the region, which will ultimately help improve the understanding of active deformation processes and improve hazard maps. [ABSTRACT FROM AUTHOR]

The International Reference Ionosphere (IRI) model is widely used in the ionospheric community and considered the gold standard for empirical ionospheric models. The development of this model was initiated in the late 1960s using the FORTRAN language; for its programming approach, the model outputs were calculated separately for each given geographic location and time stamp. The Consultative Committee on International Radio (CCIR) and International Union of Radio Science (URSI) coefficients provide the skeleton of the IRI model, as they define the global distribution of the maximum useable ionospheric frequency foF2 and the propagation factor M(3,000)F2. At the U.S. Naval Research Laboratory, a novel Python tool was developed that enables global runs of the IRI model with significantly lower computational overhead. This was made possible through the Python rebuild of the core IRI component (which calculates ionospheric critical frequency using the CCIR or URSI coefficients), taking advantage of NumPy matrix multiplication instead of using cyclic addition. This paper explains in detail this new approach and introduces all components of the PyIRI package. [ABSTRACT FROM AUTHOR]

High latitude ionospheric density structures such as polar cap patches and arcs are capable of deflecting high frequency (HF) radio waves to off‐great circle paths, and are likely detrimental to technologies dependent on HF radio propagation. In this study, nearly 2.5 years of 4.6–14.4 MHz data from a multi‐frequency HF radio link between Qaanaaq, Greenland and Alert, Canada are used to investigate high‐latitude off‐great circle propagation in the polar cap. After an example of HF radio propagation affected by polar cap patches is shown in detail, a statistical analysis of the occurrence and impacts of off‐great circle deflections in the polar cap is presented. Off‐great circle propagation is shown to be increasingly common with increasing frequency up to 11.1 MHz, such that averaged over 1 year, received 11.1 MHz signals experienced deflections >30° from the great circle direction 65.6% of the time. The occurrence of these deflections across the year is shown to be at a maximum in the winter, while occurrence across the day varies with season. Trends across both time of day and time of year for 11.1 and 14.4 MHz deflections are consistent with polar cap patch occurrence trends. Off‐great circle deflections are shown to be associated with increased time‐of‐flights, a larger range of positive and negative Doppler shifts, increased Doppler spreads, and lower signal‐to‐noise ratios. These results are discussed in the context of ionospheric phenomena in the polar cap, and implications for over‐the‐horizon radars operating at high latitudes. Plain Language Summary: High frequency (HF) radio waves can travel long distances by bouncing between the ground and the ionosphere; an upper layer of the Earth's atmosphere, allowing them to be used for communications and surveillance in remote locations. However, strong space weather can change the paths these radio waves take, causing problems for HF radio technologies. In this paper, radio transmissions sent between Qaanaaq, Greenland and Alert, Canada are studied in order to better understand how often HF radio waves are deflected by space weather at high latitudes, and what effect these deflections have on the signals themselves. After a brief example of what space weather deflections look like, transmissions sent over a whole year are studied to determine how deflections depend on radio frequency, time of day, and time of year. Then, the effects these deflections have on other signal properties is studied. It is found that deflections are very common at high latitudes, especially in the winter. Deflections tend to increase the travel time of signals, change their frequency, and reduce their signal strength. These results are shown to be connected to polar cap patches and arcs; which are common space weather phenomena near the poles. Key Points: Off‐great circle propagation occurring in the polar cap is studied using years of data from an HF radio link in the polar capLarge (greater than 30°) deflections from the great circle are shown to be very common, especially in the winterThese deflections are shown to affect HF radio signals in ways that are consistent with interactions with polar cap patches and arcs [ABSTRACT FROM AUTHOR]

Purpose: This study aims to identify the irritating aspects in the mall environment that impact shoppers with disability and explore the opportunities to design inclusive mall environments. Design/methodology/approach: A mixed-methods design was used in which data collected using a survey (n = 1,434 shoppers with and without disability) were analyzed by structural equation modeling (SEM) and repeated-measures two-way ANOVA. In addition, qualitative data were obtained from critical incident technique (CIT) stories (n = 521) from shoppers with and without disability. Findings: Mall environmental irritants evoke feelings of irritation that mediate the impacts of "inconvenient ambient conditions," "the annoying socialscape" and "overwhelming design and atmospherics" on decreased mall-visit frequency. Compared with shoppers without disability, shoppers with disability suffer more from these irritating aspects of the mall environment, as evidenced by significantly greater high-activation unpleasant emotions. The "poor access and accessibility" category of irritants mainly affects the mall experiences of shoppers with disability. Practical implications: Based on the findings, this study offers spatial-, temporal-, social-, material- and virtual-oriented recommendations for the design of inclusive retail spaces. The authors suggest that people with disability have a unique "lived experience" perspective on retail environments and that solutions should be co-created based on ongoing consultations with shoppers and employees with disability. Originality/value: To the best of the authors' knowledge, this study offers the first systematic, comprehensive comparison of the impact of environmental irritants on shoppers with and without disability and extends the literature on irritating aspects of retail environments from individual stores to malls. [ABSTRACT FROM AUTHOR]

Imaging has been an important strategy for exploring space weather. The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) is a joint Chinese Academy of Sciences (CAS) and European Space Agency (ESA) mission, aiming at studying the interaction between Earth's magnetosphere and solar wind near the subsolar point via soft X-ray imaging. As the boundary of Earth's magnetosphere, magnetopause is a significant detection target to mirror solar wind's change for the SMILE mission. In preparation for inverting three-dimensional magnetopause, we proposed an OESA-UNet model to detect the magnetopause position. The model obtains magnetopause with a U-shaped structure, in an end-to-end manner. Inspired by attention mechanisms, these blocks are integrated into ours. OESA-UNet captures low and high-level feature maps by adjusting the receptive field for precise localization. Adaptively pre-processing the image provides a prior for the network. Availability metrics are designed to determine whether it can serve three-dimensional inversion. Lastly, we provided ablation and comparison experiments by qualitative and quantitative analysis. Our recall, precision, and f1 score are 93.8%, 92.1%, and 92.9%, respectively, with an average angle deviation of 0.005 under the availability metrics. Results indicate that OESA-UNet outperforms other methods. It can better serve the purpose of magnetopause tracing from an X-ray image. [ABSTRACT FROM AUTHOR]

Non-parametric morphology statistics have been used for decades to classify galaxies into morphological types and identify mergers in an automated way. In this work, we assess how reliably we can identify galaxy post-mergers with non-parametric morphology statistics. Low-redshift (z ≲ 0.2), recent (t post-merger ≲ 200 Myr), and isolated (r > 100 kpc) post-merger galaxies are drawn from the IllustrisTNG100-1 cosmological simulation. Synthetic r -band images of the mergers are generated with SKIRT9 and degraded to various image qualities, adding observational effects such as sky noise and atmospheric blurring. We find that even in perfect quality imaging, the individual non-parametric morphology statistics fail to recover more than 55 per cent of the post-mergers, and that this number decreases precipitously with worsening image qualities. The realistic distributions of galaxy properties in IllustrisTNG allow us to show that merger samples assembled using individual morphology statistics are biased towards low-mass, high gas fraction, and high mass ratio. However, combining all of the morphology statistics together using either a linear discriminant analysis or random forest algorithm increases the completeness and purity of the identified merger samples and mitigates bias with various galaxy properties. For example, we show that in imaging similar to that of the 10-yr depth of the Legacy Survey of Space and Time, a random forest can identify 89 per cent of mergers with a false positive rate of 17 per cent. Finally, we conduct a detailed study of the effect of viewing angle on merger observability and find that there may be an upper limit to merger recovery due to the orientation of merger features with respect to the observer. [ABSTRACT FROM AUTHOR]