Daily Evolution Research Articles

Long-term effect of non-invasive brain stimulation on hemispatial neglect, functional outcomes, and mortality after stroke: ELETRON trial extend.

Our primary clinical trial indicated that anodal stimulation of the right posterior parietal region associated with specific and perceptual task training was superior to placebo in reducing stroke-induced hemispatial neglect (HN) immediately after the treatment protocol. However, our primary study did not investigate whether this benefit was maintained in the long term after stroke. Therefore, this study aimed to evaluate the long-term effects of the protocol applied in the ELETRON trial on outcomes associated with HN, functionality, and mortality. This was a pilot, multicenter, prospective, randomized, double-blind trial in patients with HN after stroke who underwent either active tDCS (anodal tDCS or C-tDCS) or sham tDCS in addition to specific and perceptual task training. The outcomes were evaluated on the last day of the session and after 1 year of stimulation (follow-up). Daily evolution rates were calculated as the difference between the values observed between the moments divided by the follow-up time for each individual. The primary outcome was the rate of HN evolution according to the BIT-C scale. The secondary outcome was CBS evolution rate. The exploratory outcomes were the evolution rate of functional disability and autonomy assessed by FIM and BI, quality of life assessed by EQ 5D, stroke severity using the NIHSS, and functional dependence assessed by mRS. Death was examined separately. A linear regression model with a time-adjusted identity link function was used to explain the evolution rates of each outcome of A-tDCS and C-tDCS as a function of sham tDCS. Survival models were adjusted to compare mortality groups. The evolution rate of BIT-C was not different between A-tDCS (B = 3.18; CI: -4.84-11.19; p = 0.438) and C-tDCS (B = -0.95; CI: -8.97-7.07; p = 0.816) with sham. The secondary and exploratory outcomes showed the same pattern. In addition, there were no statistically significant differences in mortality over time between A-tDCS and S-tDCS (B = 0.322; 95 % CI 0.284-6.707; p = 0.689) and between C-tDCS and S-tDCS (B = -0.798; 95 % CI 0.063-3.195; p = 0.425). The benefits of A-tDCS and C-tDCS were maintained for all long-term post-stroke outcomes. RBR-78jvzx - Brazilian Registry of Clinical Trials (Rebec), registered on March 13, 2016.

A dataset of the daily edge of each polynya in the Antarctic

Polynyas play a critical role in the formation of Antarctic Bottom Water and the enhancement of polar primary productivity. Accurate and exhaustive identification of Antarctic polynyas is fundamental to advancing in-depth research. However, due to methodological limitations, previous studies paid more attention to frequent polynyas and infrequent polynyas have not been investigated much despite that they could be vulnerable to climate change. Inspired by a cyclone tracking algorithm, we develop a novel method to overcome challenges identifying all types of polynyas satisfying spatiotemporal criteria and tracing their daily evolution, extracting from an extensive amount of sea ice concentration data. Based on it, we establish a dataset called “Daily Edge of Each Polynya in Antarctica” (DEEP-AA). Validation against remote sensing and ship-based observations confirms DEEP-AA’s reliability. Compared to existing maps, the DEEP-AA identifies a threefold number of polynyas and reveals the seasonal area recovery of infrequent polynyas is earlier than frequent ones.

Dynamics of Daily Glioblastoma Evolution During Chemoradiation Therapy on the 0.35T Magnetic Resonance Imaging-Linear Accelerator

Glioblastoma changes during chemoradiation therapy are inferred from magnetic resonance imaging (MRI) before and after treatment but are rarely investigated due to logistics of frequent MRI. Using a combination MRI-linear accelerator (MRI-linac), we evaluated changes during daily chemoradiation therapy. Patients with glioblastoma were prospectively imaged daily during chemoradiation therapy on 0.35T MRI-linac and at 3 timepoints with and without contrast on standalone high-field MRI. Tumor or edema (lesion) and resection cavity dynamics throughout treatment were analyzed and compared with standalone T1 postcontrast (T1+C) and T2 volumes. Of 36 patients included in this analysis, 8 had cavity only, 12 had lesion only, and 16 had both cavity and lesion. Of these, 64% had lesion growth and 46% had cavity shrinkage during treatment on MRI-linac scans. The average MRI-linac migration distance was 1.3 cm (range, 0-4.1 cm) for lesion and 0.6 cm (range, 0.1-2.1 cm) for cavity. Standalone versus MRI-linac volumes correlated strongly with R2 values: 0.991 (T2 vs MRI-linac cavity), 0.972 (T1+C vs MRI-linac cavity), and 0.973 (T2 vs MRI-linac lesion). There was a moderate correlation between T1+C and MRI-linac lesion (R2 = 0.609), despite noncontrast MRI-linac inability to separate contrast enhancement from surrounding nonenhancing tumor and edema. From pretreatment to posttreatment in patients with all available scans (n = 35), T1+C and MRI-linac lesions changed together-shrank (n = 6), grew (n = 12), or unchanged (n = 8)-in 26 (74%) patients. Another 9 patients (26%) had growth on MRI-linac, although the T1+C component shrank. In no patient did T1+C lesion grow while MRI-linac lesion shrank. Anatomic changes are seen in patients with glioblastoma imaged daily on MRI-linac throughout the chemoradiation therapy course. As surgical resection cavities shrink, margins may be reduced to save normal brain. Patients with unresected or growing lesions may require margin expansions to cover changes. Limited volume glioblastoma boost trials could consider triggered gadolinium contrast administration for evaluation of adaptive radiation therapy when lesion growth is seen on noncontrast MRI-linac.

Relating microtensiometer-based trunk water potential with sap flow, canopy temperature, and trunk and fruit diameter variations for irrigated ‘Honeycrisp’ apple

Instrumentation plays a key role in modern horticulture. Thus, the microtensiomenter, a new plant-based sensor that continuously monitors trunk water potential (Ψtrunk) can help in irrigation management decisions. To compare the response of the Ψtrunk with other continuous tree water status indicators such as the sap flow rate, the difference between canopy and air temperatures, or the variations of the trunk and fruit diameter, all the sensors were installed in 2022 in a commercial orchard of ‘Honeycrisp’ apple trees with M.9 rootstocks in Washinton State (USA). From the daily evolution of the Ψtrunk, five indicators were considered: predawn, midday, minimum, daily mean, and daily range (the difference between the daily maximum and minimum values). The daily range of Ψtrunk was the most linked to the maximum daily shrinkage (MDS; R2 = 0.42), the canopy-to-air temperature (Tc-Ta; R2 = 0.32), and the sap flow rate (SF; R2 = 0.30). On the other hand, the relative fruit growth rate (FRGR) was more related to the minimum Ψtrunk (R2 = 0.33) and the daily mean Ψtrunk (R2 = 0.32) than to the daily range of Ψtrunk. All indicators derived from Ψtrunk identified changes in tree water status after each irrigation event and had low coefficients of variation and high sensitivity. These results encourage Ψtrunk as a promising candidate for continuous monitoring of tree water status, however, more research is needed to better relate these measures with other widely studied plant-based indicators and identify good combinations of sensors and threshold values.

Adaptive Design of Solar-Powered Energy Systems Based on Daily Clearness State Evolution

The optimal designing of the hybrid energy system (HES) is a challenging task due to the multiple objectives and various uncertainties. Especially for HES, primarily powered by solar energy, the reference solar radiation data directly impact the result of the optimization design. To incorporate the stochastic characteristics of solar radiation into the sizing process, a data-driven stochastic modeling method for solar radiation is proposed. The method involves two layers of stochastic processes that capture the intraday variation and daily evolution of solar radiation. First, the clearness index (CI) is introduced to describe the radiation intensity at different times. Then, the daily clearness state (DCS) is proposed, based on the statistical indicators of the intraday CI. The Markov model is used to describe the stochastic evolutionary characteristics between different DCSs. The probabilistic distribution of the CI under different DCS is obtained based on the diffusion kernel density estimation (DKDE), which is used for the stochastic generation of the CI at various times of the day. Finally, the radiation profile required for the optimal design is obtained by the stochastic generation of the DCS sequences and the intraday clearness index under corresponding states. A case study of an off-grid solar-powered HES is provided to illustrate this methodology.

Influence of large-scale circulation and local feedbacks on extreme summer heat in Argentina in 2022/23

The summer of 2022/23 in Argentina set a record with ten heatwaves. Here, we compare the synoptic and thermodynamic conditions of the four heatwaves with the largest spatial extent using ERA5 reanalysis data. All heatwaves were associated with mid-level anticyclonic anomalies but with different characteristics: three were quasi-stationary high-pressure systems, while one was transient. We also find that enhanced surface fluxes strongly influenced the daily temperature evolution. Furthermore, we perform an attribution exercise using the analogue technique to measure the contributions of atmospheric circulation, soil moisture, and climate change. For quasi-stationary events, the main contribution came from the circulation (up to 2 °C relative to random flow in the present climate). Conversely, the transient heatwave showed a stronger association with extreme soil moisture deficits, with an estimated increase of ~+1 °C relative to wetter conditions. Climate change has also increased the intensity of heatwaves by +0.5 to +1.2 °C relative to previous decades.

A Bayesian inference approach to extract circuit model parameters and analyze photovoltaic degradation from power production data

Power production data can be a valuable resource to analyze photovoltaic (PV) performance without the need for field surveys. Recent work has demonstrated the exciting possibility of leveraging this data to extract circuit model parameters and current-voltage properties of a PV system, but further development is needed to bolster these initial findings. Here, instead of using a classical optimization approach, we switch to the Bayesian framework to solve this complex multi-solution problem. This allows us to construct probability distributions over the model parameters, get a comprehensive picture of the solution space, and quantify prediction uncertainty. As a result, we can define confidence intervals for the system’s electrical properties and consistently track their daily evolution. Our results are validated with laboratory measurements for five silicon and thin-film modules, and our scalable approach works with on-site as well as online weather data, which opens new prospects for remote PV monitoring, modeling, and degradation analysis for real-life applications.

Thermodynamic characteristics of extreme heat waves over the middle and lower reaches of the Yangtze River Basin

In August 2022, an exceptionally long-lasting heat wave (HW) affected the middle and lower reaches of the Yangtze River basin. This study uses the JRA55 daily reanalysis datasets to elucidate the thermodynamic characteristics of the daily evolution of historical extreme HWs in this region via the heat budget equation. HWs are generally characterized by the occurrence of anticyclonic circulation anomaly throughout the troposphere and positive air temperature anomaly with the maximum amplitude in the boundary layer. The anticyclonic anomaly can induce compression heating in the entire troposphere and warm zonal advection in the boundary layer. Meanwhile, due to the reduced cloud cover, more shortwave radiation reaches the ground surface, and the sensible heat flux becomes an important source of diabatic heating before the onset of HWs. The accumulated excessive heat in the HWs is primarily damped through the emission of longwave radiation and meridional thermal advection. For the HW in August 2022, its extreme persistence is mainly caused by prolonged adiabatic heating, enhanced diabatic heating during the developing stage and weakened diabatic cooling during the decay stage. The upper-level portion of the anticyclonic circulation anomalies is linked to the strengthened South Asia High. After applying the state-of-the-art dynamic metric, i.e., local finite wave activity, we reveal that the formation of the anomalous South Asia High in August 2022 is associated with the Stokes drift flux rather than the dispersion of Rossby wave energy. This characteristic sets it apart from other extreme HWs.

Individual mobility deep insight using mobile phones data

The data sets provided by Information and Communication Technologies have been extensively used to study the human mobility in the framework of complex systems. The possibility of detecting the behavior of individuals performing the urban mobility may offer the possibility of understanding how to realize a transition to a sustainable mobility in future smart cities. The Statistical Physics approach considers the statistical distributions of human mobility to discover universal features. Under this point of view the power laws distributions has been extensively studied to propose model of human mobility. In this paper we show that using a GPS data set containing the displacements of mobile devices in an area around the city Rimini (Italy), it is possible to reconstruct a sample of mobility paths and to study the statistical properties of urban mobility. Applying a fuzzy c-means clustering algorithm, we succeed to detect different mobility types that highlight the multilayer structure of the road network. The disaggregation into homogeneous mobility classes explains the power law distributions for the path lengths and the travel times as an overlapping of exponential distributions, that are consistent with a maximum entropy Principle. Under this point of view it is not possible to infer other dynamical properties on the individual mobility, except for the average values of the different classes. We also study the role of the mobility types, when one restricts the analysis to the an origin-destination framework, by analyzing the daily evolution of the mobility flows.

Near-IR Spectral Observations of the Didymos System: Daily Evolution Before and After the DART Impact Indicates that Dimorphos Originated from Didymos

Ejecta from Dimorphos following the DART mission impact significantly increased the brightness of the Didymos–Dimorphos system, allowing us to examine subsurface material. We report daily near-IR spectroscopic observations of the Didymos system using NASA’s IRTF that follow the evolution of the spectral signature of the ejecta cloud over 1 week, from 1 day before the impact. Overall, the spectral features remained fixed (S-type classification) while the ejecta dissipated, confirming that both Didymos and Dimorphos are constructed from the same silicate material. This novel result strongly supports binary asteroid formation models that include the breaking up of a single body due to rotational breakup of kilometer-wide bodies. At impact time +14 and +38 hr, the spectral slope decreased, but the following nights presented an increasing spectral slope that almost returned to the preimpact slope. However, the parameters of the 1 μm band remained fixed, and no “fresh”/Q-type-like spectrum was measured. We interpret this as follows. (1) The ejecta cloud is the main contributor (60%–70%) to the overall light during the ∼40 hr after impact. (2) Coarser debris (≥100 μm) dominated the ejecta cloud, decreasing the spectral slope (after radiation pressure removed the fine grains ≤10 hr after impact). (3) After approximately 1 week, the ejecta cloud dispersed enough to make the fine grains on Didymos’s surface the dominant part of the light, increasing the spectral slope to the preimpact level. (4) A negligible amount of nonweathered material was ejected from Dimorphos’s subsurface, suggesting that Dimorphos was accumulated from weathered material ejected from Didymos’s surface.

Analysis of Daytime and Night-Time Aerosol Optical Depth from Solar and Lunar Photometry in Valladolid (Spain)

Aerosol optical depth (AOD) at night-time has become a hot topic in recent years due to the development of new instruments recording accurate ground-based lunar irradiance measurements, and the development of calibration methods and extraterrestrial irradiance models adapted to lunar photometry. This study uses all daytime and night-time AOD data available at Valladolid (Spain) from October 2016 to March 2022 in order to analyze its behavior and the added contribution of night data. The annual, monthly and daily AOD evolution is studied comparing daytime and night-time values and checking the correlation between them. For this purpose, the daily averages are computed, showing an annual pattern, with low AOD values throughout the year (mean value of AOD at 440 nm: 0.122), where winter months have the lower and summer the higher values, as observed in previous studies. All these AOD values are modulated by frequent desert dust events over the Iberian Peninsula, with a strong influence on daily and monthly mean values in February and March, where the strongest desert outbreaks occurred. The added new data confirm these results and the good correlation between daytime and night-time data. Also, a complete daily evolution is shown, observing that AOD and Ångström exponent (AE) mean values vary by only ±0.02 in 24 h, with a maximum value at 06:00 UTC and minimum at 18:00 UTC for both parameters.

Interannual variability of ground surface thermal regimes in Livingston and Deception islands, Antarctica (2007–2021)

AbstractThe absence of vegetation in most ice‐free areas of Antarctica makes the soil surface very sensitive to atmosphere dynamics, especially in the western sector of the Antarctic Peninsula, an area within the limits of the permafrost zone. To evaluate the possible effects of regional warming on frozen soils, we conducted an analysis of ground surface temperatures (GSTs) from 2007 to 2021 from different monitoring sites in Livingston and Deception islands (South Shetlands archipelago, Antarctica). The analysis of the interannual evolution of the GST and their daily regimes and the freezing and thawing indexes reveals that climate change is showing impacts on seasonal and perennially frozen soils. Freezing Degree Days (FDD) have decreased while Thawing Degree Day (TDD) have increased during the study period, resulting in a balance that is already positive at the sites at lower elevations. Daily freeze–thaw cycles have been rare and absent since 2014. Meanwhile, the most common thermal regimes are purely frozen – F1 (daily temperatures < = −0.5°C), isothermal – IS (ranging between −0.5°C to +0.5°C), and purely thawed – T1 (> = +0.5°C). A decrease in F1 days has been observed, while the IS and T1 days increased by about 60 days between 2007 and 2021. The annual number of days with snow cover increased between 2009 and 2014 and decreased since then. The GST and the daily thermal regimes evolution point to general heating, which may be indicative of the degradation of the frozen soils in the study area.

UV filter occurrence in beach water of the Mediterranean coast - A field survey over 2 years in Palavas-les-Flots, France.

A 2-year sampling campaign was realized on French Mediterranean beach (Palavas-les-Flots Hérault) in order to measure the concentration of UV filters released from the sunscreen used by bathers. Multiple factors suspected of playing determining roles in the UV filter pattern in water were explored, such as the seasonal and daily time evolutions, or the vertical and horizontal distributions, and they were regarded through the UV filter characteristics. The beach was monitored during periods of high and low tourist attendance, typically before, during and after the summer peak. The beachgoers attendance was counted. Bathing water was sampled distinctly from the bulk column and from the top surface layer, testing different sampling tools. Sediments and mussels were also sampled and analysed as potential UV filter sinks. Three organic UV filters (octocrylene OCR, avobenzone BMDBM and octyl methoxycinnamate OMC) and one mineral (titanium dioxide TiO2 ) were studied here as representatives of the current cosmetic market. Summer peak attendance on the beach was confirmed associated with peak levels of UV filter concentration in the bathing water, even more pronounced during a heat wave period. This relation was also observed at day scale with an afternoon peak, suggesting a rapid evolution of the UV filter pattern in water. Contrasted fates were measured between the four studied UV filters, that could be mainly explained by their respective characteristics, i.e. particulate or dissolved, hydrophilic or lipophilic, lifetime. Generally, this resulted in a concentration ranking TiO2 > OCR > OMC > BMDBM, ranging from 0.5 to 500 μg/L. The most lipophilic and recalcitrant OCR was found most vertically differentiated and over concentrated in the top surface layer of water. Finally, a large horizontal heterogeneity was also observed in the UV filter concentration pattern, raising the need for sample replicates that cover a significant area. This work fulfils some knowledge gaps on the issue of UV filter release in coastal environments, not only by providing original field data and methodological recommendations but also importantly in the comparison made of organic and mineral UV filters, which are often considered separately and rarely evaluated at the same time.

Discrimination in Times of Crises and the Role of the Media

Can the extent of ethnic discrimination change quickly, and what circumstances and mechanisms make such changes possible? I address these questions by using scraped data to study the daily evolution of customer discrimination against Arab doctors in Israel from January 2020 to June 2021. Results show that: (1) the outbreak of the coronavirus crisis in March 2020 led to a dramatic decline in discrimination; (2) the eruption of a wave of ethnic riots in May 2021 had the opposite effect; (3) media coverage of the contribution of Arab doctors to the fight against the pandemic helped bring about the first change. (JEL D91, I12, J15, J44, L82)

Impact of different sources of precursors on an ozone pollution outbreak over Europe analysed with IASI+GOME2 multispectral satellite observations and model simulations

Abstract. We examine the impact of different sources of ozone precursors on the daily evolution of successive ozone pollution outbreaks across Europe in July 2017 by using a multispectral satellite approach called IASI+GOME2 and a tropospheric chemistry reanalysis named TCR-2. IASI+GOME2, combining IASI (Infrared Atmospheric Sounding Interferometer) and GOME-2 (Global Ozone Monitoring Experiment-2) measurements respectively in the infrared and the ultraviolet, allows the observation of the daily horizontal distribution of ozone in the lowermost troposphere (defined here as the atmospheric layer between the surface and 3 km above sea level). IASI+GOME2 observations show a fair capacity to depict near-surface ozone evolution as compared to surface measurements from 188 European stations for the period 15–27 July 2017. At the beginning of this event (on 16 July), an ozone outbreak is initially formed over the Iberian Peninsula likely linked with high temperature-induced enhancements of biogenic volatile organic compound concentrations and collocated anthropogenic emissions. In the following days, the ozone plume splits into two branches, one being transported eastward across the western Mediterranean and Italy and the other one over western and Central Europe. The southern branch encounters ozone precursors emitted over the Balkan Peninsula by wildfires along the coast of the Adriatic Sea and biogenic sources in the inland region of the peninsula. Ozone concentrations of the northern plume are enhanced by photochemical production associated with anthropogenic sources of ozone precursors over Central Europe and by mixing with an ozone plume arriving from the North Sea that was originally produced over North America. Finally, both ozone branches are transported eastwards and mix gradually as they reach the northern coast of the Black Sea. There, emissions from agricultural fires after harvesting clearly favour photochemical production of ozone within the pollution plume, which is advected eastwards in the following days. Based on satellite analysis, this paper shows the interplay of various ozone precursor sources to sustain a 2-week-long ozone pollution event over different parts of Europe.

City-scale model for COVID-19 epidemiology with mobility and social activities represented by a set of hidden Markov models

Background and objectiveSARS-CoV-2 emerged by the end of 2019 and became a global pandemic due to its rapid spread. Various outbreaks of the disease in different parts of the world have been studied, and epidemiological analyses of these outbreaks have been useful for developing models with the aim of tracking and predicting the spread of epidemics. In this paper, an agent-based model that predicts the local daily evolution of the number of people hospitalized in intensive care due to COVID-19 is presented. MethodsAn agent-based model has been developed, taking into consideration the most relevant characteristics of the geography and climate of a mid-size city, its population and pathology statistics, and its social customs and mobility, including the state of public transportation. In addition to these inputs, the different phases of isolation and social distancing are also taken into account. By means of a set of hidden Markov models, the system captures and reproduces virus transmission associated with the stochastic nature of people's mobility and activities in the city. The spread of the virus in the host is also simulated by following the stages of the disease and by considering the existence of comorbidities and the proportion of asymptomatic carriers. ResultsAs a case study, the model was applied to Paraná city (Entre Ríos, Argentina) in the second half of 2020. The model adequately predicts the daily evolution of people hospitalized in intensive care due to COVID-19. This adequacy is reflected by the fact that the prediction of the model (including its dispersion), as with the data reported in the field, never exceeded 90% of the capacity of beds installed in the city. In addition, other epidemiological variables of interest, with discrimination by age range, were also adequately reproduced, such as the number of deaths, reported cases, and asymptomatic individuals. ConclusionsThe model can be used to predict the most likely evolution of the number of cases and hospital bed occupancy in the short term. By adjusting the model to match the data on hospitalizations in intensive care units and deaths due to COVID-19, it is possible to analyze the impact of isolation and social distancing measures on the disease spread dynamics. In addition, it allows for simulating combinations of characteristics that would lead to a potential collapse in the health system due to lack of infrastructure as well as predicting the impact of social events or increases in people's mobility.

Daily and Subdaily Wind and Divergence Variations Observed by a Shipborne Doppler Radar off the Southwestern Coast of Sumatra

Abstract This study investigated the daily cycle of the wind and divergence fields observed off the southwestern coast of Sumatra during a field campaign of the Years of the Maritime Continent pilot study. An algorithm was developed to retrieve kinematic variables from the single-Doppler data collected aboard the Research Vessel Mirai from 24 November to 13 December 2015. The observed daily cycles of the wind and divergence fields consisted of diurnal, semidiurnal, and short-term variations. Diurnal wind variation was characterized by deep and three-dimensional circulation. There was an approximate phase locking of the semidiurnal variation to the diurnal variation, both in the wind and divergence fields. The short-term wind variation occurred at a time scale of ∼1–3 h, and this pattern was associated with density currents or mesoscale gravity waves. Up to 73% of the daily vertical motion variance can be attributed to the diurnal and semidiurnal vertical motion variations with comparable strengths. Concurrently, precipitation propagated offshore in phase with density currents and mesoscale gravity waves. Our results suggest that diurnal and semidiurnal wind variations dominate the daily evolution of precipitation, whereas density currents and mesoscale gravity waves control offshore propagation. Additionally, it appears that the daily precipitation cycle is modulated by multiple-time-scale wind variabilities of less than a day, which is also responsible for the development of strong nocturnal convection off the southwestern coast of Sumatra. Significance Statement To improve our understanding of the daily wind and divergence cycle off the southwestern coast of Sumatra, we examined wind data collected by a shipborne Doppler radar. The observed daily cycles of the wind and divergence fields consisted of diurnal and semidiurnal variations, as well as a 1–3-h variation associated with a density current or mesoscale gravity wave. Our results suggest that diurnal and semidiurnal wind variations dominate the daily evolution of precipitation, whereas density currents and mesoscale gravity waves control offshore propagation. Thus, we highlight the role of multiple-time-scale wind variabilities of less than a day in modulating the daily precipitation cycle off the southwestern coast of Sumatra.

Sensitivity of the Southern Hemisphere Wintertime Teleconnection to the Location of ENSO Heating

Abstract The Southern Hemisphere extratropical atmospheric circulation response to anomalous convection in the tropical western and eastern Pacific Ocean is distinctly different. The response to westward-located heating has a meridional dipole in the South Pacific with large zonal scale and appears unable to be interpreted simply as a stationary Rossby wave train that disperses poleward and eastward from a tropical source like the meridionally arched response to eastward-located heating. This study investigates the cause of this asymmetry by examining the daily evolution of the response to suddenly switching on steady diabatic heating over a western and central/eastern equatorial Pacific location using large-ensemble integrations from the Community Atmosphere Model version 5. We focus on the austral winter months when the subtropical jet supports the development of an effective Rossby wave source in the subtropical westerlies and acts as a waveguide. We show that the subtropical jet strongly influences the height response to the western tropical Pacific heating, promoting prominent zonal circumglobal propagation. Development of a transient eddy feedback in the extratropical storm track after approximately 10 days appears to play a primary role in establishing the time-mean response, which we test through comparison with similar experiments conducted using a simplified linear model. Conversely, the height anomalies for eastern tropical Pacific heating, farther away from the subtropical jet core, have larger meridional propagation, dispersing in a typical Hoskins–Karoly manner into the Southern Hemisphere extratropics, while the transient eddy feedback plays a secondary role for the establishment of the steady response.

Subseasonal Predictability of the July 2021 Extreme Rainfall Event Over Henan China in S2S Operational Models

AbstractA record‐breaking flooding event occurred in Zhengzhou, Henan Province of China during 17–23 July 2021, causing hundreds of deaths and vast economic losses. Here, we evaluated the predictability of this extreme rainfall event and the impacts of tropical cyclones (TCs) using subseasonal‐to‐seasonal (S2S) operational models. On the monthly timescale, most models initialized in late June reasonably predicted the wet‐in‐north and dry‐in‐south patterns of anomalous rainfall over China in July, accompanied by the well‐predicted westward extension of the western North Pacific subtropical high (WNPSH) and eastward stretching of the South Asian High. On the weekly timescale, only four models captured the location, probability, and sudden intensification of the rainfall extremes in advance of 1 week, largely due to their reasonable prediction of WNPSH variability in mid‐latitudes. However, the S2S models still underestimated the super extremeness of this event. The prediction discrepancies came from the poor predictability of Typhoon IN‐FA and its impact on the daily evolution of the extreme rainfall event, even within a few days forecast lead. Compared with the observation, the prediction bias of tropical disturbance changed the environmental monsoon airflow to induce the earlier warning of rainfall extremes prior to the formation of IN‐FA. After the formation of IN‐FA, the prediction bias of the typhoon's moving speed distorted the typhoon location, which incorrectly predicted the moisture convergence center and underestimated their remote impacts on this heavy rainfall event.

Business Email Compromise Phishing Detection Based on Machine Learning: A Systematic Literature Review

The risk of cyberattacks against businesses has risen considerably, with Business Email Compromise (BEC) schemes taking the lead as one of the most common phishing attack methods. The daily evolution of this assault mechanism’s attack methods has shown a very high level of proficiency against organisations. Since the majority of BEC emails lack a payloader, they have become challenging for organisations to identify or detect using typical spam filtering and static feature extraction techniques. Hence, an efficient and effective BEC phishing detection approach is required to provide an effective solution to various organisations to protect against such attacks. This paper provides a systematic review and examination of the state of the art of BEC phishing detection techniques to provide a detailed understanding of the topic to allow researchers to identify the main principles of BEC phishing detection, the common Machine Learning (ML) algorithms used, the features used to detect BEC phishing, and the common datasets used. Based on the selected search strategy, 38 articles (of 950 articles) were chosen for closer examination. Out of these articles, the contributions of the selected articles were discussed and summarised to highlight their contributions as well as their limitations. In addition, the features of BEC phishing used for detection were provided, as well as the ML algorithms and datasets that were used in BEC phishing detection models were discussed. In the end, open issues and future research directions of BEC phishing detection based on ML were discussed.