Daily Temperature Range Research Articles

Seasonality and Association With Climate Factors of Epiglottitis in South Korea: A Nationwide Population-Based Study

Background and Objectives The seasonality and climatic relevance of epiglottitis have not yet been fully investigated in a population-based cohort. This study aimed to examine the seasonality of epiglottitis and explore associated climatic factors.Materials and Method In a retrospective cohort study using the Korean National Health Insurance claims database from January 2010 to December 2019, we identified patients with epiglottitis who claimed the following diagnostic codes as a principal or first additional diagnosis: International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes J0510, J0510.001 (acute epiglottitis without obstruction, epiglottitis not otherwise specified), and J0511 (acute epiglottitis with obstruction). We calculated the seasonal ratio as the ratio of the highest to the lowest number of patients per month to compare the degree of seasonality. In addition, the climate data points corresponding to each month were obtained. Thus, we analyzed the correlations between the monthly patient numbers for each disease and various climatic factors.Results There were seasonal variations in the number of patients with epiglottitis, which were highest from winter to spring and lowest in summer. The prevalence of epiglottitis was strongly correlated with the average temperature, ground temperature, relative humidity, precipitation, daily temperature range, and sunlight rate. Additionally, epiglottitis was most prevalent in the <9 age group before 2013, but after 2013, it was most prevalent in the 30–39 age group.Conclusion This large population-based study demonstrated clear seasonality and climatic association in patients with epiglottitis. Further studies exploring the detailed demographic factors affecting epiglottitis are required to address similar diseases more effectively.

Očekivano toplinsko opterećenje Dubrovnika, Osijeka, Rijeke, Zadra i Zagreba prema projekcijama regionalnih klimatskih modela

This paper examines the expected future heat load in five Croatian cities: Dubrovnik, Zadar, Rijeka, Zagreb, and Osijek. The heat load is estimated by temperature-related climate indices and mean, maximum and minimum daily temperatures obtained by climate simulations using two different regional climate models (DHMZ-RegCM4 and SMHI-RCA4) with a horizontal resolution of 12.5 km, forced with two global climate models (EC-EARTH and MPI-ESM-MR/LR) for two different greenhouse gas concentration scenarios (RCP4.5 and RCP8.5). By comparing these variables for the period 2041–2070 with respect to the current climate (defined as that of the period 1991–2020), a significant increase in mean, maximum and minimum temperatures was observed in all analysed combinations of regional and global climate models for all analysed cities. Although there is a difference in results depending on the combination of regional and global models, the largest increase is mainly found in the warm part of the year (April-October), with the strongest warming of Dubrovnik and Rijeka. Due to similar trends in minimum and maximum temperatures, the trend in the daily temperature range is weak. Under warmer climate conditions, the number of days with a maximum air temperature above 25 °C increases in all considered cities (especially in Dubrovnik), as does the number of days with a minimum air temperature exceeding 20 °C (especially in Rijeka and Zadar). Furthermore, a reduction in the number of days with maximum and minimum temperatures below 0 °C is projected for all cities. Nevertheless, some differences are found between coastal and inland cities caused by local factors.

Status of forest remnants invaded by tradescantia (Tradescantia fluminensis Vell.) following introduction of biocontrol beetles and manual clearance after three years

ABSTRACT We compared biocontrol beetles and manual clearing of tradescantia in forest remnants invaded by tradescantia (Tradescantia fluminensis Vell.) on the agriculturally modified Hikurangi floodplain, northern New Zealand, to inform best practice in enhancing native biodiversity. Four forest remnant study sites were used: two on dairy farms and two protected in a reserve. We assessed tradescantia biomass and cover as indicators of biocontrol effectiveness in the short term, and composition and seedling establishment for effectiveness in the longer term. We found the biocontrol treatment (a combination of tradescantia beetles Neolema ogloblini, Neolema abbreviata, and Lema basicostata) was slow in reducing tradescantia biomass and had little effect in promoting regeneration of native forest species after 3 years. Beetle feeding damage was significantly higher at the biocontrol sites; however, tradescantia biomass or cover was not significantly lower. Although tradescantia biomass in the biocontrol treatment was decreasing, several more years would probably be required for beetle populations to increase and reduce biomass sufficiently to facilitate survival of native seedlings. Results between sites were variable, although dairy farm sites had overall higher nutrient status with higher total potassium levels, and lower nitrogen/phosphorus ratios, and generally higher tradescantia biomass. Manual clearing (‘handclear’) of tradescantia increased vascular species richness but was much more labour intensive and required ongoing management of resprouts. Handclear plots also had lower soil water content than control (means = 36% dry weight, 49% dry weight, respectively), a wider range of daily temperatures, and high species losses (as well as gains). Species losses were probably exacerbated by the greater environmental extremes caused by removal of the tradescantia living mulch, and the incomplete recovery of ground cover vegetation and microclimate suitable for seedling regeneration. Biodiversity benefits are likely to accrue slowly following the introduction of biocontrol agents; longer-term, these should prove more cost-effective than handclear.

The role of short‐term temperature variability and light in shaping the phenology and characteristics of seagrass beds

AbstractSeagrass beds inhabit highly heterogeneous temperature regimes that characterize the marine nearshore. Temperature directly influences seagrasses and also provides indirect information on other ecologically relevant environmental variables. Multiple temperature processes operate on seasonal and sub‐seasonal timescales (i.e., hours to months) and include variation from seasonal air–sea heat fluxes, advective heat transport from upwelling and tidal circulation, and daily heating and cooling of shallow waters. Despite this, seagrass–temperature studies typically only examine a single isolated temperature process, often seasonal heating/cooling or marine heatwaves. Furthermore, elucidation of relationships between different short‐term temperature processes and seagrass metrics could provide insights into biologically relevant temperature metrics for seagrasses. Here, we examine the effects of multiple short‐term temperature processes on Zostera marina beds in Atlantic Canada, by describing the seasonal phenology of bed characteristics, plant morphology, and physiology across different temperature regimes and by identifying relationships between different temperature and seagrass metrics. We also include water depth as a proxy for light availability. Four distinct short‐term temperature processes (median temperature, growing degree day [heat accumulation], daily temperature range, and time in the optimal temperature range [5–23°C]) were used to categorize temperature regimes across our study sites as warm and highly variable, or cool and less variable. We found that both temperature regime and light availability were important for leaf area index (LAI) and shoot density, which both decreased with increasing depth yet had the strongest seasonal differences and maximum rates of increase (shoot density) or lowest values and maximum rates of decrease (LAI) in warm and highly variable temperature regimes. These temperature regimes were also associated with seasonal patterns in number of leaves, reduced leaf lengths and number of leaves per shoot, and thinner rhizomes with less carbohydrate storage. Generalized additive models (GAMs) for each seagrass metric using the four temperature processes indicated that while median temperature displayed expected relationships with almost every seagrass metric, inclusion of other temperature processes revealed additional insights not evident from median temperature alone. Our study shows that different sources of short‐term temperature variation influence seagrass properties and that accounting for these will improve our understanding of the temperature–seagrass interaction.

Daily temperature variability in cities and mental health-related hospitalizations

Abstract Despite plausible behavioral and physiological pathways, limited evidence exists on how temperature variability is associated with acute mental health-related episodes. This analysis explored associations between daily temperature range (DTR) and mental health-related hospitalizations in New York State during 1995-2014. A case-crossover design with distributed lag non-linear DTR terms (0-6 days) estimated associations between ZIP Code-level DTR and hospitalizations for mood, anxiety, adjustment, and schizophrenia disorders, adjusting for daily mean temperature, and how associations varied by age, sex, admission type and season. For all outcomes, across most DTR distribution, divergence from the study period daily mean (7.7 °C) yielded a positive association to a threshold (5.2 °C, 25th percentile; 12.2 °C, 90th percentile), beyond which negative associations were observed. For mood disorders, an increase in DTR from 7.7 °C to 12.2 °C was associated with a cumulative 4.8% (95%CI, 4.0%−5.6%) increase in daily hospitalization rates. This increase was highest during transition seasons (6.0%, 4.5%−7.4%) compared with summer (1.8%, 0.6%−3.0%) and winter (-0.6%, -0.7%−1.9%). Evidence for effect-modification by age group and admission type was inconsistent across outcomes, without evidence for effect modification by sex. This study highlights potential impacts of increased temperature variability in a changing climate on mental health-related outcomes.

Daily thermal variability does not modify long-term gene expression relative to stable thermal environments: A case study of a tropical fish

Global warming is leading to an increase in the frequency and intensity of extreme weather events, magnifying the breadth of temperatures faced by ectotherms across days and seasons. Despite the importance and ecological relevance of diurnal thermal variability, the vast majority of knowledge on gene expression patterns and physiology stems from animals acclimated to constant temperatures or in the early stages of exposure to a new temperature regime. If heterothermal environments modulate responses differently from constant thermal environments, our existing capacity to forecast impacts of climate warming may be compromised. To address this knowledge gap, we acclimated barramundi (Lates calcarifer) to 23 °C, 29 °C (optimal), 35 °C and to thermal cycling conditions (23–35 °C daily with a mean of 29 °C) and sampled liver and white muscle tissue before acclimation and after 2 and 17 weeks of acclimation. NanoString nCounter technologies were used to measure expression of 20 genes related to metabolism, growth and maintenance of cellular homeostasis. Acclimation to cool and warm conditions caused predictable changes in whole-animal performance (metabolism and growth) and the underlying gene expression patterns. Acclimation to a cycling temperature regime did not change the molecular regulation of metabolism or growth compared with barramundi acclimated to constant 29 °C, nor did it cause any discernible effects on whole-animal performance. However, the heat shock response was higher in the former group, suggesting that barramundi under a daily temperature cycle have an increased need for cellular chaperoning to minimise detrimental effects of temperature on proteins. We conclude that the genetic regulation of metabolism and growth may be more dependent on the mean daily temperature than on the daily temperature range.

Analysis of factors influencing energy-saving advantages of outside and inside insulation of exterior walls in intermittent air-conditioned buildings

An effective approach to reducing building energy is determining the proper insulation location of the exterior walls. Two conflicting conclusions were found in previous research that focused on the optimal insulation location of exterior walls in buildings with intermittently operated convective air systems (CASs). Why conflicting conclusions are produced and which factors influence them have not yet been answered. Thus, this paper analyzes the generation of the transmission load through the exterior walls with outside and inside insulation, and accordingly evaluates the parameters that might affect the energy-saving advantage of two insulation locations. An analytic model is utilized to calculate the heat transfer through the exterior walls. Results show that the heat stored in exterior walls’ inner layer during CAS off-periods is the key to determining the relative energy-saving of two insulation locations. Furthermore, the relative energy-saving increases with thermal capacity of exterior envelopes and air change rate but decreases with the increase in thermal capacity of interior envelopes and setpoint temperature. Based on these, a predictive model is devised to determine the proper insulation location of exterior wall. A critical daily sol-air temperature range beyond which the relative energy-saving advantage transitions is found using the model.

Glaciological and meteorological investigations of an Alpine debris-covered glacier: the case study of Amola Glacier (Italy)

Debris-covered glaciers are common in many regions of the world, and accurately modelling their melt is of increasing importance for water resources planning, and biological and ecological research. In this study, we investigate meteorological and glaciological conditions and estimate the melt of Amola Glacier (a small debris-covered glacier in the Adamello-Presanella Massif, Italian Alps) using an empirical approach, based on shortwave radiation, surface temperature, debris thickness and thermal resistance. Meteorological conditions are determined from a supraglacial automatic weather station, while the model is calibrated using i) field data acquired during the ablation season 2020, including a network of ablation stakes and thermistors, ii) modelled solar radiation and iii) thermal imagery from Landsat 8 TIRS.The analysis of glacier meteorological conditions shows a high prevalence of cloud-covered (50.60% of daytime observations) and humid conditions, with a high daily air temperature range (22.24 °C). Analysis of thermistor data suggests that a linear thermal gradient of the debris layer can be assumed when the model is run at daily resolution. Modelled debris thickness, surface temperatures and melt capture patterns observed on the field, including the decrease in debris thickness and increasing melt with elevation and their variability across the glacier surface. The root mean square error between measured and observed melt is 0.16 m, corresponding to 22% of the average observed melt, in line with the performance of empirical models for debris-free and debris-covered ice. The model could thus be used to provide a first estimate of debris-covered ice melt for glaciers in the Adamello region. Improvements to the model would require measuring all energy fluxes on the glacier from a weather station and investigating their spatial distribution on the glacier surface.

Simulation of Soil Temperature under Plateau Zokor's (Eospalax baileyi) Disturbance in the Qinghai Lake Watershed, Northeast Qinghai-Tibet Plateau.

The soil temperature is a key factor affecting the fragile terrestrial ecosystems on the Qinghai-Tibet Plateau, and has been remarkably altered by the soil mammal's disturbance. This study first analyzed the soil temperature variation in grassland, mound, and bald patch under the disturbance of plateau zokor (Eospalax baileyi) from October 2018 to July 2020 in the Qinghai Lake watershed. Then, the SHAW (simultaneous heat and water) model was used to simulate the soil temperature change of three land surface types, and the sensitivity of soil temperature to environmental parameters before and after the disturbance was explored. The results showed the following: (1) The daily range of soil temperature was mound > bald patch > grassland, which became smaller as the depth increased, due to the co-influence of vegetation coverage and soil bulk density. There was an obvious hysteresis of soil heat transfer for grassland, as compared with mound and bald patch, especially at 5 and 15 cm depths. (2) The SHAW model was applicable for the simulation of soil temperature under the plateau zokor's disturbance, especially during the growing season, and had better simulation accuracy for deep soil. (3) Air-entry potential and pore-size distribution index obviously affected soil temperature change, because of the change in root system and soil pores under the plateau zokor's disturbance. With the evolution of disturbance process, the response of soil temperature to the leaf area index weakened gradually, owing to the different duration of disturbance and restoration. In general, the plateau zokor's disturbance alters the soil properties and vegetation characteristics, and further, distinctly affects heat transfer and soil temperature.

Optimizing Soil Moisture Conservation and Temperature Regulation in Rainfed Jujube Orchards of China’s Loess Hilly Areas Using Straw and Branch Mulching

The implementation of the “Returning Farmland to Forest” project in the loess hilly region of China has led to the establishment of large-scale economic forests, which have become the dominant industry driving local economic development. However, the region faces challenges such as drought, water shortages, and an uneven distribution of precipitation, which have a severe impact on the growth of economic forests, including jujube trees. Water stress significantly reduces yield and efficiency, posing a threat to the sustainable and healthy development of jujube ecological and economic forests. Therefore, this study aimed to address these issues by implementing straw mulching (SM) and jujube branch mulching (BM) measures in the mountainous jujube economic forests. Through long-term monitoring and statistical analysis, the study investigated the effects of different mulching treatments on soil moisture and soil temperature. The research findings reveal that both SM and BM significantly increased soil moisture in the 0–280 cm soil layer during the jujube growing season (p < 0.05). In both normal precipitation (2014) and drought (2015) years, SM increased average soil moisture content by 5.10% and 4.60%, respectively, compared to the uncovered treatment (CK). SM also had a positive impact on the soil moisture content in each layer of the soil profile. However, BM only increased soil moisture content in the 40–100 cm and 220–280 cm soil layers. Additionally, SM and BM reduced the variation of soil moisture, with SM showing a more significant effect in regulating soil moisture and achieving more stable moisture levels. During the jujube growing seasons in 2014 and 2015, SM and BM decreased soil temperature in the 0–10 cm soil layer. The temperature difference compared to CK decreased with increasing soil depth. SM had an overcooling effect, while BM reduced the temperature before the fruit expansion period and maintained warmth afterward. Both SM and BM also reduced the daily range and variation range of soil temperature, with SM having a more pronounced effect. The temperature of the 0–20 cm soil layer exhibited the strongest correlation with air temperature, and SM showed the weakest response. In conclusion, adopting straw mulching and jujube branch mulching in rain-fed jujube orchards in the loess hilly region not only saves materials and reduces costs but also contributes to water retention and temperature regulation. Straw mulching, in particular, plays a more significant role in moisture retention and temperature regulation and is advantageous for soil management in rain-fed jujube orchards. These research findings provide a scientific basis for optimizing water and heat management in orchards with limited water resources.

Maintenance of the last step of the cold chain: on-farm refrigerator storage and performance

Failure of the cold chain and thermal damage to refrigerated vaccines can result in losses for cattle owners and safety issues for cattle. The primary objectives of this study were to quantify characteristics of refrigerator operating temperatures on re­gional dairy and veterinary operations, including the percent­age of time that refrigerators spent outside the recommended temperature interval (RTI) of 36°F to 46°F (2°C to 8°C) for vac­cine storage, the mean daily temperature range (MDTR), and identify variables associated with those characteristics.

Higher daily temperature range at depth is linked with higher thermotolerance in antipatharians from the canary islands

Sensitivity to ocean warming is generally expected to be lower in populations from more heterogeneous thermal environments, owing to greater phenotypic plasticity and/or genotype selection. While resilience of benthic populations from thermally fluctuating environments has been investigated at a variety of spatial scales, this has received limited attention across depths and has remained unresolved for Antipatharian corals, key habitat-forming species across a wide bathymetric range in all of the world oceans. In this study, we aimed at addressing the thermal sensitivity of Antipatharian corals across depths characterized by different levels of temperature fluctuations. We used an acute ramping experimental approach to compare the thermal sensitivity of colonies of (1) the branched Antipatharian Antipathella wollastoni (Gray, 1857) from two distinct depths (25 and 40 m) in Gran Canaria (Canary Islands, Spain); and of (2) unbranched mesophotic (80 m) Stichopathes species, from Lanzarote (Canary Islands, Spain; S. gracilis (Gray, 1857)), and Stichopathes sp. clade C from Mo’orea, French Polynesia. Results showed that the daily temperature range in Gran Canaria was larger at mesophotic depths (3.9 °C vs. 2.8 °C at 40 and 25 m, respectively) and this coincided with lower thermal sensitivity in mesophotic colonies of A. wollastoni. Second, S. gracilis from Lanzarote showed a lower thermal sensitivity than the previously studied Stichopathes sp. clade C from Mo’orea (French Polynesia) inhabiting a less variable habitat. These results are in line with the climate variability hypothesis, which states that populations under more variable thermal conditions have a lower sensitivity to warming than those from more stable environments, as they have adapted/acclimated to these higher levels of temperature fluctuations.

Bartlett–Lewis Model Calibrated with Satellite-Derived Precipitation Data to Estimate Daily Peak 15 Min Rainfall Intensity

Temporal variability of rainfall is extreme in the rangelands of northern Australia and occurs at annual, decadal, and even longer timescales. To maintain long-term productivity of the rangelands of northern Australia under highly variable rainfall conditions, suitable land management practices are assessed using rangeland biophysical models, e.g., GRASP (GRASs Production). The daily maxima of the 15 min rainfall intensity (I15) are used to predict runoff and moisture retention in the model. The performance of rangeland biophysical models heavily relies on the I15 estimates. As the number of pluviograph stations is very limited in northern Australian rangelands, an empirical I15 model (Fraser) was developed using readily available daily climate variables, i.e., daily rainfall total, daily diurnal temperature range, and daily minimum temperature. The aim of this study is to estimate I15 from daily rainfall totals using a well-established disaggregation scheme coupled with the Bartlett–Lewis rectangular pulse (BLRP) model. In the absence of pluviograph data, the BLRP models (RBL-E and RBL-G) were calibrated with the precipitation statistics estimated using the Integrated Multi-satellitE Retrievals for GPM (global precipitation measurement) (IMERG; 30 min, 0.1° resolution) precipitation product. The Fraser, RBL-E, and RBL-G models were assessed using 1 min pluviograph data at a single test site in Darwin. The results indicated that all three models tended to underestimate the observed I15, while a serious underestimation was observed for RBL-E and RBL-G. The underestimation by the Fraser, RBL-E, and RBL-G models consisted of 23%, 38%, and 50% on average, respectively. Furthermore, the Fraser model represented 29% of the variation in observed I15, whereas RBL-E and RBL-G represented only 7% and 11% of the variation, respectively. A comparison of RBL-E and RBL-G suggested that the difference in the spatial scales of IMERG and pluviograph data needs to be addressed to improve the performance of RBL-E and RBL-G. Overall, the findings of this study demonstrate that the BLRP model calibrated with IMERG statistics has the potential for estimating I15 for the GRASP biophysical model once the scale difference between IMERG and point rainfall data is addressed.

Higher temperature variability in deforested mountain regions impacts the competitive advantage of nocturnal species.

Deforestation is a major contributor to biodiversity loss, yet the impact of forest loss on daily microclimate variability and its implications for species with different daily activity patterns remain poorly understood. Using a recently developed microclimate model, we investigated the effects of deforestation on the daily temperature range (DTR) in low-elevation tropical regions and high-elevation temperate regions. Our results show that deforestation substantially increases DTR in these areas, suggesting a potential impact on species interactions. To test this hypothesis, we studied the competitive interactions between nocturnal burying beetles and all-day-active blowfly maggots in forested and deforested habitats in Taiwan. We show that deforestation leads to increased DTR at higher elevations, which enhances the competitiveness of blowfly maggots during the day and leads to a higher failure rate of carcass burial by the beetles at night. Thus, deforestation-induced temperature variability not only modulates exploitative competition between species with different daily activity patterns, but also likely exacerbates the negative impacts of climate change on nocturnal organisms. In order to limit potential adverse effects on species interactions and their ecological functions, our study highlights the need to protect forests, especially in areas where deforestation can greatly alter temperature variability.

Male blue wildebeest increase activity during the rut, but not at the expense of rest

Rest is a state of adaptive inactivity that increases the efficiency of activity by regulating its timing and reducing energy use when activity is not beneficial. Thus, animals can go without rest when specific demands, such as mating, favour being awake. Sexually active male blue wildebeest (bulls) are typically territorial, and it has been reported that when a bull is protecting a harem during the mating season (rut), he neither eats nor rests. We examined the daily activity and inactivity patterns of dominant bulls by means of actigraphy for 3 months, which included the rut. We also measured faecal androgen metabolite (fAM) levels and subcutaneous temperature, both of which have variances known to delineate the rut. During the rut, wildebeest bulls experienced higher levels of activity, fAM, and a greater daily range of subcutaneous temperature. Despite previous reports, the male blue wildebeest rested daily during the rut, and while the amount of rest was low, it was not substantially lower than prior to the rut. The amount of time spent inactive increased substantially after the rut. The timing of daily activity and inactivity patterns did not vary substantially across the recording period. Across the recording period, the average daily ambient temperatures decreased (seasonality), and the subcutaneous temperature followed this pattern, although it was not as marked. It appears that in the post-rut period a substantive increase in time spent at rest occurs, potentially allowing the wildebeest bulls time to recover following a period of intense activity.

The increase in intensity and frequency of surface air temperature extremes throughout the western South Atlantic coast

The climate is changing. At this stage, it is important to specify an ‘extreme’ climate and identify patterns that indicate its potential harm worldwide, including the coastal zones. Herein, we considered extremes based on the “Peaks Over Threshold” method from the “Extreme Value Theory”. We looked after geographical patterns of surface air temperature (SAT) extremes (e.g., Tmax, Tmin, daily temperature range (DTR), and inter-daily temperature range) over the last 40 years throughout the Brazilian coast. Overall, we found a trend increase in intensity and frequency, but the duration was barely affected. The latitudinal pattern of extremes and the temperatures considered extremes followed the settled perception that areas in higher latitudes will be more affected by the extent of warming. Additionally, the seasonal pattern of DTR demonstrated to be a good approach to make inferences about air mass changes, but joint analyses on extremes with other atmospheric variables are desirable. Given the potential effects of extreme climates on society and natural systems over the world, our study highlights the urge for action to mitigate the effects of the increase in SAT in coastal zones.

Reduction of critical positive temperature gradients in jointed plain concrete pavements

ABSTRACT Temperature gradients in concrete pavements significantly affect fatigue damage accumulation, with high gradients having the potential to reduce performance under vehicle loads. While temperature profiles are non-linear throughout the depth, an equivalent linear temperature gradient (ELTG) accounts for the effect of temperature in pavement design. Critical ELTG values are difficult to predict because ELTG is affected by design parameters as well as climate conditions and varies diurnally and seasonally. To identify critical parameters which affect ELTG, a database of hourly temperature profiles was generated for a series of jointed plain concrete pavements (JPCP) throughout Pennsylvania. A stepwise regression model was developed with an R2 of 0.81 to determine maximum daily ELTG as a function of the design parameters and climate. This equation can assist engineers in making decisions on when superloads can be transported without significant damage or performing falling weight deflectometer testing will be most informative. Slab thickness, concrete albedo, and daily temperature range (DTR) were the most significant parameters that affected ELTG. A higher albedo showed an equivalent effect in reducing maximum ELTG as increasing the thickness of the slab. This finding can be used to reduce maximum gradients, which will increase the predicted service life of JPCPs.

Evaluation of Empirical Daily Solar Radiation Models for the Northeast Coast of the Iberian Peninsula

The ability to accurately predict daily solar radiation reaching the earth’s surface is essential in applications such as solar power generation. Given their ease of use, many empirical models have been proposed based on different dependent variables such as cloud cover, daily temperature range, etc. In this study we evaluate 23 of these models for the prediction of daily solar radiation in the northern coastal zone of the Iberian Peninsula. Daily measurements during the period 2000–2018 from 16 meteorological stations spread over this area are used to adjust the parameters of each model, whose predictive capacity is then evaluated using measurements made between 2019 and 2022. Using different statistical metrics to assess their predictive performance, it was found that models based on hours of sunshine and level of cloudiness are significantly more accurate than those based on maximum and minimum daily temperature and day of the year. Specifically, the sunshine-based model by SBM3 obtained the highest Global Performance Indicator at 5.05. The results offer insight on the ability of each type of empirical model to accurately predict daily solar radiation in the Mediterranean region.

Hospital admission tendencies caused by day-to-day temperature changes during summer: a case study for the city of Novi Sad (Serbia).

Increased temperature risk in cities threatens the health and well-being of urban population and is fueled by climate change and intensive urbanization. Consequently, further steps must be taken for assessing temperature conditions in cities and their association with public health, in order to improve public health prevention at local or regional level. This study contributes to solving the problems by analyzing the connection between extreme temperatures and the tendencies of all-cause hospital admissions. The analyses used (a) 1-h air temperature data, and (b) daily data of all-cause hospital admissions. The datasets include the summer period (June, July, August) for the years 2016 and 2017. We tested the effects of two temperature indices, day-to-day change in maximum temperature - Tmax,c and daily temperature range - Tr, with all-cause hospital admission subgroups, such as all-cause cases - Ha, hospital admissions in the population below 65 - Ha<65, and hospital admissions in the population aged 65 and over - Ha≥65. The results show the highest values of Ha when Tmax,c is between 6 and 10 °C. Therefore, more intensive hospital admissions can be expected when Tmax increases from day-to-day (positive values of Tmax,c), and it is more visible for Ha and Ha<65 (1 °C = 1% increase in hospital admissions). Also, Tr values between 10 °C and 14 °C cause an increase in the number of hospital admissions, and it is more noticeable for Ha≥65.

Exploring the Impact of Winter Storm Uri on Power Outage, Air Quality, and Water Systems in Texas, USA

Texas was hit by a record-setting cold snap from the 14–17 February 2021 after three decades that resulted in power outages, disruption of the public water systems, and other cascading effects. This study investigates the unprecedented impact of winter storm Uri on power outages, air quality, and water systems in Texas, USA. Analysis of the Parameter Regression of Independent Slopes Model (PRISM) gridded climate data showed that the average daily freezing temperature range was 0–−19 °C on 14 February 2021, with severe levels (−17–−19 °C) occurring in the Texas High Plains. Our results showed that the extreme freezing temperature persisted from 14–17 February 2021, significantly affecting power operation and reliability, and creating power outages across Texas. Uri impacted the public water systems and air quality on time scales ranging from a few minutes to several days, resulting in 322 boiling notices. The air quality index level exceeded the standard limit by 51.7%, 61.7%, 50.8%, and 60% in Dallas–Fort Worth, Houston–Galveston, Austin, and Lubbock regions. The level of the pollutants exceeded the EPA NAAQS standard allowable limits during winter storm Uri. In general, this study gives information on the government’s future preparedness, policies, communication, and response to storm impacts on vulnerable regions and communities.