Proportion Of Stations Research Articles

Integrating heterogeneous information for modeling non-stationarity of extreme precipitation in the Yangtze River Basin

Extreme precipitation exhibits non-stationary characteristics due to climate change and land use/cover change in recent years. In the literature, probability distributions with varying parameters associated with covariates have been applied to describe the non-stationarity of extreme precipitation. However, there is no consensus on the optimal distributions and the number and type of covariates for constructing non-stationary models. This study comprehensively investigates and determines the optimal distribution models, the type of covariates, and the number of covariates to best characterize the non-stationarity of extreme precipitation, using the Yangtze River Basin as the study area. The time series of four indices representing extreme precipitation of different durations and intensities are fitted by stationary and non-stationary Generalized Additive Models for Location, Scale, and Shape. The models are constructed using seven distributions and four types (time, global climate, local climate, and land cover) of covariates. Each model incorporates one to three covariates simultaneously. The results show that the most preferred distribution is the Generalized Extreme Value distribution for very wet-day precipitation, while the Log-Normal distribution is more suitable for other extreme precipitation indices. For the type of covariates, when using a single covariate, the proportion of stations using a global climate covariate as the best covariate (22.3 %–33.2 % of 193 stations) is close to that using a local climate covariate as the best covariate (22.3 %–27.5 %). The proportion of stations using land cover as the best covariate is much lower (7.3 %–10.9 %), while that using time as the best covariate is the lowest (1.6 %–4.1 %). When using multiple covariates, the models with both global and local climate covariates are mostly selected (8.3 % to 17.6 %) for all extreme precipitation indices. For the number of covariates, one or two covariates are enough to describe the non-stationary behaviors of all extreme precipitation indices. This study emphasizes the necessity to use non-stationary models for extreme precipitation frequency analysis with careful consideration and selection of distributions and covariates.

Temporal and spatial characteristics of high temperatures, heat waves, and population distribution risk in China from 1951 to 2019.

Understanding the relationships between high temperatures (HT) and heat waves (HW) is vital for enhancing human health, especially in areas with dense population. This paper analyzes the temporal and spatial characteristics of different HT and HW intensities, their spatial influence, and the population distribution risk at different HW intensities for 844 meteorological stations between 1951 and 2019. The results indicate that (1) HT and extreme temperature (ET) days are symmetrically distributed along the Huhuanyong Line, from southeast to northwest China. The times, days, and accumulated temperatures of HW, the times, days, and accumulated temperature of strong heat waves (SHW), and the times, days, and accumulated temperature of extreme heat waves (EHW) were distributed similarly; (2) with the increase in high temperatures or heat waves from HT to ET or from HW to SHW, the proportion of stations with an upward trend was always greater in China, while stations with a downward trend were mainly located in the North China Plain and Huai River Basin. For HW, SHW, and EHW, the increasing range of times and days were less than the accumulated temperatures; (3) between 1990 and 2019, there was an expansion of the HW and SHW distribution area with an annual average of more than 10 days, and the EHW distribution area with an annual average of more than 3 days. Moreover, the number of people exposed to HW, SHW, and EHW also increased during this period; and (4) considering the population distribution characteristics and the regional HT and HW characteristics, society needs to form regional adaptation actions for different HT and HW intensities.

Evaluation of Tropical Cyclone Disaster Loss Using Machine Learning Algorithms with an eXplainable Artificial Intelligence Approach

In the context of global warming, tropical cyclones (TCs) have garnered significant attention as one of the most severe natural disasters in China, particularly in terms of assessing the disaster losses. This study aims to evaluate the TC disaster loss (TCDL) using machine learning (ML) algorithms and identify the impact of specific feature factors on the prediction of model with an eXplainable Artificial Intelligence (XAI) approach, SHapley Additive exPlanations (SHAP). The results show that LightGBM outperforms Random Forest (RF), Support Vector Machine (SVM), and Naive Bayes (NB) for estimating the TCDL grades, achieving the highest accuracy value of 0.86. According to the SHAP values, the three most important factors in the LightGBM classifier model are proportion of stations with rainfall exceeding 50 mm (ProRain), maximum wind speed (MaxWind), and maximum daily rainfall (MaxRain). Specifically, in the estimation of high TCDL grade, events characterized with MaxWind exceeding 30 m/s, MaxRain exceeding 200 mm, and ProRain exceeding 30% tend to exhibit a higher susceptibility to TC disaster due to positive SHAP values. This study offers a valuable tool for decision-makers to develop scientific strategies in the risk management of TC disaster.

Monitoring of long‐term vegetation dynamics and responses to droughts of various timescales in Inner Mongolia

AbstractThe characteristics of vegetation and drought for different seasons between 1982 and 2015 in Inner Mongolia were studied based on the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). The response of vegetation to drought over various timescales for different seasons and vegetation types was investigated using the maximum Pearson correlation, allowing a discussion about the possible causes of any changes. The results indicate that the vegetation NDVI in Inner Mongolia showed an increasing trend in different seasons, with spring vegetation NDVI (April–May) having the largest significant increasing rate, followed by the growing season (April–October), autumn (September–October), and summer (June–August). Accordingly, the proportion of stations with decreasing SPEI was, in descending order, summer, growing season, autumn, and spring. Additionally, the magnitude of the SPEI decrease was greater in eastern Inner Mongolia. NDVI and SPEI were positively correlated in most regions of Inner Mongolia, indicating that changes in vegetation in most parts of this region were affected by the spatial and temporal characteristics of drought, the correlation being them being strongest in the growing season, followed by summer, then spring and autumn. Considering the different types of vegetation, forests were less affected by drought, with broadleaf forests more affected than coniferous forests. The meadow steppes and typical steppes were more affected by 12‐month droughts in the growing season and summer, 6‐month droughts in spring, and 3‐month droughts in autumn, with desert steppes mainly affected by 3‐month droughts. The shrubs, sandy vegetation, and cropland were mostly affected by droughts in summer, and show a greater response to 3‐month droughts in autumn. Finally, the water balance was found to be the most important factor affecting the response of vegetation to drought in Inner Mongolia.

Changes to objective structured clinical examinations (OSCE) at Australian medical schools in response to the COVID-19 pandemic

Introduction Objective Structured Clinical Examinations (OSCE) are used to assess clinical skills. We investigated how exit OSCEs changed in Australian medical schools in response to the COVID-19 pandemic. Materials and Methods The lead ACCLAiM assessment academic from 12 eligible Australian medical school members of the Australian Collaboration for Clinical Assessment in Medicine (ACCLAiM) received a 45-item semi-structured online questionnaire. Results All schools (12/12) responded. Exit OSCEs were not used by one school in 2019, and 3/11 schools in 2020. Of eight remaining schools, four reduced station numbers and testing time. The minimum OSCE testing time decreased from 64 min in 2019 to 54 min in 2020. Other modifications included: a completely online ‘e-OSCE’ (n = 1); hybrid delivery (n = 4); stations using: videos of patient encounters (n = 3), telephone calls (n = 2), skill completion without face-to-face patient encounters (n = 3). The proportion of stations involving physical examination reduced from 33% to 17%. Fewer examiners were required, and university faculty staff formed a higher proportion of examiners. Conclusions All schools changed their OSCEs in 2020 in response to COVID-19. Modifications varied from reducing station numbers and changing delivery methods to removing OSCE and complete assessment re-structuring. Several innovative methods of OSCE delivery were implemented to preserve OSCE validity and reliability whilst balancing feasibility.

An multi-BSS multi-user full duplex MAC protocol based on AP cooperation for the next generation WLAN

Aiming at the problems of low efficiency of buffer information collection and sharp drop of system throughput caused by the aggravation of conflicts in the multi basic service set (BSS) high density deployment overlap coverage scenario of next generation wireless local access network (WLAN), an access point cooperation based multi-BSS multi-user full duplex multiple access protocol named as CMMFD is proposed. Firstly, a channel resource allocation algorithm for stations (STA) in overlapping coverage area is designed, in which, the access control (AC) equipment allocates the channel resources for all STA in response to buffer state and interference information (BI) according to the proportion of STA in the overlapped coverage area. Secondly, a BI information collection protocol process based on access point (AP) cooperation sending trigger frame is designed to collect all STA information. After receiving trigger frame, STA will access the channel and report BI information in p-probability according to the channel resources allocated by AC. Finally, a multi-BSS multi-user channel resource allocation algorithm based on full duplex is designed. AC allocates channel resources according to all BI information reported by AP, and schedules STA in the multi-BSS to carry out multi-user full duplex transmission over the sub-channel. Simulation results show that the throughput of the CMMFD protocol improves by 29.6%, compared with Mu-FuPlex protocol and EnFD-OMAX protocol.

Sequential Imputation of Missing Spatio-Temporal Precipitation Data Using Random Forests

Meteorological records, including precipitation, commonly have missing values. Accurate imputation of missing precipitation values is challenging, however, because precipitation exhibits a high degree of spatial and temporal variability. Data-driven spatial interpolation of meteorological records is an increasingly popular approach in which missing values at a target station are imputed using synchronous data from reference stations. The success of spatial interpolation depends on whether precipitation records at the target station are strongly correlated with precipitation records at reference stations. However, the need for reference stations to have complete datasets implies that stations with incomplete records, even though strongly correlated with the target station, are excluded. To address this limitation, we develop a new sequential imputation algorithm for imputing missing values in spatio-temporal daily precipitation records. We demonstrate the benefits of sequential imputation by incorporating it within a spatial interpolation based on a Random Forest technique. Results show that for reliable imputation, having a few strongly correlated references is more effective than having a larger number of weakly correlated references. Further, we observe that as the proportion of stations with incomplete records increases, there is a higher percentage of stations that benefit from sequential imputation. Overall, we present a new approach for imputing missing precipitation data which may also apply to other meteorological variables.

Paradigm shift in aerosol chemical composition over regions downwind of China

A rapid decrease in PM2.5 concentrations in China has been observed in response to the enactment of strong emission control policies. From 2012 to 2017, total emissions of SO2 and NOx from China decreased by approximately 63% and 24%, respectively. Simultaneously, decreases in the PM2.5 concentration in Japan have been observed since 2014, and the proportion of stations that satisfy the PM2.5 environmental standard (daily, 35 µg/m3; annual average, 15 µg/m3) increased from 37.8% in fiscal year (FY) 2014 (April 2014 to March 2015) to 89.9% in FY 2017. However, the quantitative relationship between the PM2.5 improvement in China and the PM2.5 concentration in downwind regions is not well understood. Here, we (1) quantitatively evaluate the impacts of Chinese environmental improvements on downwind areas using source/receptor analysis with a chemical transport model, and (2) show that these rapid emissions reductions improved PM2.5 concentrations both in China and its downwind regions, but the difference between SO2 and NOx reduction rates led to greater production of nitrates (e.g., NH4NO3) due to a chemical imbalance in the ammonia–nitric acid–sulfuric acid–water system. Observations from a clean remote island in western Japan and numerical modeling confirmed this paradigm shift.

Spatial segregation between Iberian lynx and other carnivores

Rabbits represent the bulk of its diet as for many other Iberian predators. This study addresses how the presence of the Iberian lynx affects the spatial distribution of the mesocarnivore community at landscape scale in the Sierra de Andújar. We studied mesocarnivore presence by sampling at 230 camera trapping stations, located in areas with and without lynx. We used a x2–test to compare the proportion of stations in which each species of carnivore were recorded in the zones with and without lynx. The proportion of camera trapping stations in which red fox (Vulpes vulpes), Egyptian mongoose (Herpestes ichneumon), beech marten (Martes foina), wildcat (Felis sylvestris) and common genet (Genetta genetta) were detected was significantly lower in the area where lynx were present than in the area where it was absent. No significant differences between the two types of areas were found for badgers (Meles meles). Our results highlight the role of the lynx as apex predators and the benefits that the recovery of Iberian lynx populations would entail in terms of trophic interactions and restored disrupted ecosystems processes.Key words: Intraguild competition, Carnivores, Phototrapping, Apex preda

Spatial and temporal variability of mean daily wind speeds in the Czech Republic, 1961-2015

This contribution analyses the spatio-temporal variability of mean daily wind speeds (MDWSs) over the territory of the Czech Republic in the 1961-2015 period, using series from the 119 meteorological stations of the Czech Hydrometeorological Institute. These series were quality-controlled and homogenised by application of the standard normal homogeneity test, after Alexandersson, and the Maronna and Yohai test. The spatial variability of MDWSs is analysed in terms of annual and seasonal data, which exhibit a clear relationship to orographic character, with the highest values in highland and mountain areas. Spatial relationships between stations are interpreted by means of correlation graphs, which express the dependence of MDWSs on the altitude of the stations and the distance between them. Analysis of monthly, seasonal and annual linear trends for 4 altitudinal intervals and the entire Czech Republic shows a decreasing tendency, almost statistically significant. Taking the 119 stations individually, a certain proportion of stations also displays positive trends. Comparison of MDWS variability with circulation indices shows a closer relationship to the Central European Zonal Index than to the North Atlantic Oscillation Index. The results obtained are discussed with respect to problems associated with wind speed measurements, particularly the change from standard to automatic wind speed measurements, and a broadly occurring decline in measured wind speed series in recent decades (wind stilling).

Meteorological hazard assessment based on trends and abrupt changes in rainfall characteristics on the Korean peninsula

This study presents a statistical approach for assessing meteorological hazards based on trends and abrupt changes in precipitation characteristics. Daily rainfall data from 64 stations in South Korea (SK) and 27 stations in North Korea (NK) were used to identify temporal patterns in the rainfall characteristics of both regions using seven rainfall indices, such as the total annual rainfall and annual number of wet days. This study suggests the use of three steps in identifying meteorological hazards based on two statistical analyses. In step 1, we conducted a trend analysis of a 10-year moving average of the rainfall index using the Mann-Kendall (MK) trend test. Most stations (65.6 %) in SK exhibit clear increasing trends in five indices, whereas far fewer have data indicating any trends in five of the indices in NK (25.9 %). In step 2, abrupt changes in all rainfall indices were identified using a Bayesian Change Point (BCP) approach. The results contradict those from the MK trend analysis. The proportion of stations in NK where trends were identified is much higher than that in SK. In step 3, the results from the two previous steps were integrated to identify the meteorological hazards based on the identified trend and change point. The BCP approach can be used to identify meteorological hazards that MK cannot, as the former approach focuses on the change point during the entire period. As a result, meteorological stability at the sites of weather stations can be identified, and then the meteorological hazards across the entire Korean peninsula can be spatially interpolated. Although SK and NK are located on the same peninsula, distinct differences in the trends were observed.

Exploring the abundance–occupancy relationships for the Georges Bank finfish and shellfish community from 1963 to 2006

Abundance-occupancy (A-O) patterns were explored temporally and spatially for the Georges Bank finfish and shellfish community to evaluate long-term trends in the assemblage structure and to identify anthropogenic and environmental drivers impacting the ecosystem. Analyses were conducted for 32 species representing the assemblage from 1963 to 2006 using data from the National Marine Fisheries Service's annual autumn bottom trawl survey. For individual species, occupancy was considered the proportion of stations with at least one individual present, and abundance was estimated as the mean annual number of fish captured per station. Intraspecific relationships were estimated to provide information on utilization of space by a species. Multispecies interspecific relationships over all species for each year were fitted to estimate assemblage structural changes over the time series. Results indicated that the slopes and strengths of interspecific A-O relationships significantly declined over the duration of the time series, and this decline was significantly related to groundfish landings. However, the rate of decline was not constant, and a breakpoint analysis of interspecific slopes indicated that 1973 was a period of "state" change. More importantly a jackknife-after-bootstrap analysis indicated that the early 1970s followed by the 1990s were periods of higher than average probability of significant break points. While it is difficult to determine causation, the results suggest that long-term impacts such as habitat fragmentation may be influencing the species assemblage structure in the Georges Bank ecosystem. Further, we used slopes from the intraspecific A-O relationships to derive a measure of a species' potential risk of hyperstability, where catch rates remain high as the population declines. Combining this measure of the risk of hyperstability with resilience to exploitation provided a means to rank species risk of decline due to both demographics and the interaction of the behaviors of the species and fishing fleets.

Interspecific variation in seedling responses to seed limitation and habitat conditions for 14 Neotropical woody species

1 We assessed the relative importance of dispersal and niche processes in structuring plant populations at the seedling stage for 14 woody plant species (12 trees and 2 lianas) in an old-growth tropical forest of French Guiana. 2 We combined long-term data from a network of 160 stations, each comprising a seed trap and two to three neighbouring seedling plots, with fine-scale quantification of environmental variables. 3 For each species, we quantified seed limitation as the proportion of seed traps that were not reached by seeds, and establishment limitation as the proportion of stations where seeds arrived but where seedlings did not occur. All species showed strong seed limitation, whereas only one species showed significant establishment limitation. 4 We determined the proportion of variance in local seedling density explained by either seed density or environmental factors, and we assessed the effect of environment on seedling survival. 5 Although seeds showed considerable spatial clumping in all species, seed density explained a significant fraction of the variance in seedling density for only five species. Habitat preferences explained a significant fraction of the variance in seedling density for six species. Of the remaining species, four showed no significant relationship with either seed arrival or habitat conditions. 6 Environmental effects on local seedling abundance were weakly related to those on seedling survival. When seedling density was significantly correlated with a given environmental factor, survival was usually not correlated with that factor. Habitat association patterns might change over time, as environmental filtering operates. 7 Synthesis. Our results show that both seed arrival and habitat preferences contribute to explaining the abundance of tropical woody species at the seedling stage, but their relative importance showed important interspecific differences. Although our study was limited to a subset of woody species, they accounted for 27% of the individuals composing the seedling layer. Thus, our findings are likely to have important consequences in the structuring of the seedling community.

Service Differentiation Using the Capture Effect in 802.11 Wireless LANs

We investigate the effects of using dual transmission power to achieve quality-of-service (QoS) differentiation in IEEE 802.11 wireless LANs. Specifically, we assume all stations employ the standard IEEE 802.11 distributed coordination function (DCF), with the exception that some stations transmit at a higher power than others. Consequently, in the event of a collision involving frames from both power levels, a high-power frame is more likely to be received correctly as a result of the so-called capture effect (i.e. received at a power sufficiently higher than that of the interference, allowing it to be decoded correctly). This effectively leads to QoS differentiation between two classes, corresponding to the high-power and low-power stations. We develop a Markov model for the IEEE 802.11 DCF in a network with dual transmission power over a Rayleigh-fading channel, and use it to evaluate the resulting performance, in terms of the key metrics of throughput and delay. We explore how the performance of the service classes depends on the proportion of stations in each class and the transmission power ratio, focusing in particular on the bounds achieved in the limit case of 'ideal differentiation', characterised by a perfect capture probability of high-power frames. We find that significant performance differentiation between high-power and low-power stations is achieved even with transmission power ratios that are not very high, leading us to conclude that employing multiple transmission power levels is a viable and efficient approach for service quality differentiation in wireless LANs.

Forecasting streamflows in Australia using the tropical Indo-Pacific thermocline as predictor

Summary Subsurface ocean temperatures in the tropical Indo-Pacific region are used in a regression prediction scheme for the direct prediction of runoff in 48 representative catchments in northern and eastern Australia. The thermocline, represented by the second unrotated principal component of the 20 °C isotherm depth, is coupled with the Nino3 index to form the predictive model. The relevance of the subsurface oceanic information is evaluated by comparing results with two alternatives, both based on the use of sea surface temperatures. Using lags of 6 and 12 months, the three approaches are applied to forecast the runoff for January, April, July and October, each representing the four seasons. The skills of the three prediction schemes are measured and compared using the linear error in probability space (LEPS) score. Consensus hindcasts, which are linear combinations of the three prediction schemes, were also made for all lags and seasons. In terms of skill, the superiority of the thermocline-based model over the other two models is evident in both individual and consensus forecasting experiments. Except for October forecasts at six months lead-time, the thermocline model consistently garnered the largest proportion of stations where it is most skillful. The number of stations with the best forecasts from the thermocline model usually increased when the lead-time was doubled from 6 to 12 months affirming the suitability of the thermocline for long-term projections. In consensus forecasting, the thermocline-based model usually scored the largest weight among the three models. In many instances, this weight was greater than the combined weight of the two SST-based models. Results of the combined forecasting experiment also demonstrated the higher skill of consensus forecasts compared to the skill of forecasts using individual models.