Warm Season Research Articles

Analysis of pollution status and influencing factors of polybrominated diphenyl ethers in household dust in five cities in northern China

Objective: To investigate the pollution levels and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust in five cities in northern China. Methods: Based on the "Chinese Indoor Environment and Health Surveillance" project carried out by the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention in 2018-2019, during the warm season (April 2018 to September 2018) and the cold season (November 2018 to March 2019), Lanzhou in Northwest China, Shijiazhuang in North China, Panjin in Northeast China, Luoyang in Central China, and Qingdao in East China were selected as the research sites. A total of 87 families were recruited to study residences in real-life scenarios. At the same time, dust samples were collected to detect the concentration of PBDEs. The level of household environmental indicators was measured, and the residential building characteristics and family behavior habits were collected through questionnaires. A total of 142 valid dust samples and 140 valid questionnaires were obtained. The differences in PBDE concentrations across seasons, wind zones, residential building characteristics, and family habits were analyzed. The exploratory factor analysis was performed to investigate the possible sources of PBDEs, and multivariate linear regression was used to explore the factors influencing PBDEs in household dust. Results: The M (Q1, Q3) of total PBDE concentrations in 142 household dust samples in five cities was 144.51 (106.61, 222.65) ng/g in the warm season and 145.10 (98.57, 180.65) ng/g in the cold season, respectively. There were seasonal differences in the concentration of ∑12PBDEs in Luoyang and Shijiazhuang (P<0.01). The concentration of BDE-71 was highest among PBDE homologues, followed by BDE-66 and BDE-47. Three factors were extracted by exploratory factor analysis in the warm season, and the cumulative variance contribution rate was 67.90%. The multivariate linear regression showed that the house completion less than ten years [β (95%CI): 0.186 (0.013, 0.359)], infrequent home cooking [β (95%CI):-0.342 (-0.570, -0.114)], and increased residential PM10 concentration [β (95%CI): 0.001 (0.000, 0.002)] during the warm season, as well as the house far from driveway [β (95%CI): 0.093 (0.013, 0.172)], house area less than 90 m2 [β (95%CI):-0.138 (-0.264, -0.013)], and lower residential xylene concentration [β (95%CI):-0.006 (-0.011, -0.001)] during the cold season might be related to the elevated concentrations of ∑12PBDEs in household dust. Conclusion: The pollution of PBDEs in household dust in five northern cities is at a medium to high level. Years of house completion, frequency of cooking at home, residential PM10 concentration, distance from house to driveway, house area, and residential xylene concentration may influence household PBDE concentrations.

Daily diurnal temperature range associated with emergency ambulance calls: a nine-year time-series study.

Diurnal temperature range (DTR) is associated with the increased risk of morbidity and mortality. However, the relationship between DTR and emergency ambulance calls (EACs), which more accurately and immediately reflect the health impacts of temperature changes, remains underexplored in China. We collected daily data on EACs and meteorological factors from 2009 to 2017 in Guangzhou, China. DTR, representing the temperature range within a day, was calculated by subtracting the minimum temperature from the maximum temperature for each day. Generalized additive models were used to estimate the association between DTR and EACs for all-cause, cardiovascular diseases, and respiratory diseases. Additionally, subgroup and sensitivity analyses were conducted in our study. We found significant associations between daily DTR and EACs. The excess risks (ERs) were 0.47% (95% CI: 0.14, 0.81%) for all-cause EACs, 0.94% (95% CI: 0.46, 1.43%) for cardiovascular-related EACs, and 1.31% (95% CI: 0.76, 1.86%) for respiratory -related EACs at lag01, respectively. Subgroup analyses indicated that these associations were notably stronger among the older, males, and during the warm season. Specifically, there was an increase of 1.16% (95% CI: 0.59, 1.74%) in cardiovascular-related EACs among the older adult, compared to 0.45% (95% CI: -0.21, 1.12%) among those younger than 65 years. Among males, the increase was 1.39% (95% CI: 0.79, 1.99%), compared to 0.13% (95% CI: -0.53, 0.79%) among females. During the warm season, the increase was 1.53% (95% CI: 0.74, 2.34%), compared to 0.75% (95% CI: 0.14, 1.37%) during the cold season. DTR might increase the risk of daily all-cause, cardiovascular-related, and respiratory-related EACs in Guangzhou, China. The associations were particularly strong among older adults, males, and during the warm season. Implementing public health policies is essential to mitigate the adverse health effects of DTR.

Daily Activity Rhythms of Animals in the Southwest Mountains, China: Influences of Interspecific Relationships and Seasons

Temporal and spatial factors regulate the interactions between apex predators, mesocarnivores, and herbivores. Prey adjust their activity patterns and spatial utilization based on predator activities; in turn, predators also adapt to the activities of their prey. To elucidate the factors influencing the daily activity rhythms of animals, 115 camera traps were established from September 2019 to June 2023 to assess the influences of interspecific relationships and seasons on the daily activity rhythms of animals in the southwest mountains of China. The species captured by the cameras included six Carnivora (such as Panthera pardus and Lynx lynx), six Artiodactyla (such as Moschus spp. and Rusa unicolor), one Primate (Macaca mulatta), and two Galliformes (Crossoptilon crossoptilon, Ithaginis cruentus). The results demonstrated that the 15 species exhibited different activity rhythms and peak activities to reduce intense resource competition. There were differences in the species’ activity rhythms in different seasons, with competition among different species being more intense in the cold season than in the warm season. In predation relationships, the overlap coefficient in the cold season exceeded that of the warm season, possibly due to the abundant resources in summer and food scarcity in winter. In competitive relationships, 15 pairs of species exhibited significantly higher overlap coefficients in the cold season compared to the warm season, possibly due to increased demands for energy during the cold period or seasonal changes in predatory behavior. By analyzing the daily and seasonal activity patterns of dominant species in the study area, temporal niche overlaps were established to compare the competition levels between species. These findings indicate that the activity rhythms of the animals in this area not only result from evolutionary adaptation but are also influenced by season, food resources, and interspecific relationships (predation and competition). Thus, efforts should be made to reduce human interference, protect food resources in the winter, and monitor animals’ interspecific relationships to protect animal diversity and maintain the stability of the ecosystem in this biodiversity hotspot in China.

Drying trend in land and sea in East Asia during the warm season over the past four decades

Abstract The East Asian region is typically characterized by warm and humid conditions from late spring to summer. However, in recent decades, this region has experienced an increase in severe drying conditions, deviating from historical climatological patterns. This study investigated the precipitation-evaporation (P-E) trends across land and sea regions in East Asia (EA) during the extended summer season (April to September) from 1980 to 2022, and the key physical processes driving these trends through moisture budget decomposition and numerical experiments. The results reveal pronounced drying trends in southeastern China and the Yellow Sea and parts of the Korea Strait and Korean Peninsula over the past 43 years. The underlying physical processes driving these drying conditions differ between land and sea in EA. In southeastern China, the drying is driven by dynamic processes, particularly moisture divergence related to wind changes. This is linked to anomalous strengthening of descending motion due to the Indo-Pacific warm pool warming induced by both anthropogenic global warming and natural Pacific Decadal Oscillation-like sea surface temperature (SST) patterns. Conversely, drying in the Yellow Sea and adjacent areas is influenced by thermodynamic moisture advection. The altered humidity distribution due to global warming-induced SST patterns, which are higher over the Northwest Pacific marginal sea and lower in inland China, drives dry air transport from inland China to the Yellow Sea via background southwesterly wind. These findings enhance our understanding of the drying trend and their distinct processes in EA’s land and sea areas during the extended summer.

Modulating effects of temperature on CO2-inhibited isoprene emissions in Eucalyptus urophylla

Terrestrial vegetation emits substantial amounts of highly reactive isoprene, significantly impacting atmospheric chemistry and climate change. Both atmospheric carbon dioxide (CO2) concentration and temperature can influence plant isoprene emissions; however, whether these factors have a synergistic effect remains unclear, particularly for tropical/subtropical plants. In this study, we conducted in-situ controlled experiments on Eucalyptus urophylla, a representative tropical/subtropical species, to investigate the seasonal variation in the response of isoprene emissions to CO2 concentrations (ISOP-CO2 response) and to identify potential controlling factors. The results showed that high CO2 exerts a nearly linear inhibitory effect on isoprene emissions, as indicated by the slope of the ISOP-CO2 response curve. This inhibitory effect exhibited evident seasonal changes, with stronger suppression during cooler seasons and weaker suppression during warmer seasons. This finding contrasts with the default ISOP-CO2 response in the MEGAN model, which ignored seasonal variation. Further analysis showed a significant correlation between the slope of the ISOP-CO2 response curve and growth temperature from the past 10 days, indicating that these metrics are effective indicators for predicting seasonal changes. Our findings reveal a synergistic mechanism between temperature and CO2 concentration effects on isoprene emissions. By coupling the effects of growth temperature with the ISOP-CO2 response, this mechanism can be integrated into models to provide more accurate predictions of future isoprene emissions, reducing prediction biases, especially during cooler seasons.

The flash droughts across the south-central United States in 2022: Drivers, predictability, and impacts

A rare subseasonal-to-seasonal phenomenon – two consecutive flash drought events interrupted by a period of recovery – occurred across eastern Oklahoma, Arkansas, and southern Missouri, spanning the summer and early fall of 2022. These flash drought events (the first in June–July, the second in August–September) led to severe (D2) and extreme (D3) drought conditions via the United States Drought Monitor across much of the region following the first period of rapid drought intensification, and extreme (D3) and exceptional (D4) drought conditions by the end of the second event. A notable driver of both flash drought events included a persistent upper-level ridge either centered over or shifted west and upstream of the flash drought region, leading to broad-scale subsidence and reduced mid-level moisture which acted to limit precipitation development and increase evaporative demand. In addition, several heatwave events developed during the warm season in 2022 and either (1) acted to drive flash drought development via increased evaporative demand or (2) were enhanced by land surface desiccation and land-atmosphere feedbacks following rapid drought intensification. Furthermore, S2S composite forecasts predicted drought development for both events. However, only 20% of the ensembles predicted rapid drought development associated with flash drought for the first event and 16% of the ensembles predicted rapid drought development during the second event. This result highlights a key challenge in S2S prediction of rapidly developing drought conditions versus that of more conventional and slower drought development. The ensembles that did predict rapid drought intensification were associated with the forecasting of positive 500 hPa geopotential height anomalies over the south-central United States (first event) or an amplified wave pattern centered over the west-central United States (second event). Lastly, the compounding effects of two flash droughts in a single warm season led to substantial impacts on agricultural, environmental, and hydrologic sectors across the region.

Comparison of 2-m surface temperature data between reanalysis and observations over the Arabian Peninsula

The 2-m temperature data is a significant indicator for studying the weather extremes and the exchange of water and energy fluxes between the surface and atmosphere. This study compared three reanalysis datasets, i.e., ERA5, ERA5-Land, and MERRA-2, with observations from in-situ sources from 1990 to 2022 using various statistical error metrics and extreme temperature indices over the Arabian Peninsula (AP) region. We selected these reanalysis datasets due to the continuous improvements and higher spatiotemporal output better capturing the temperature variability. The spatiotemporal climatology shows lower temperatures in winter (<15 °C) and maximum in summer (>35 °C); however, the reanalysis data show more deviations in temperature during the cold season than in the warm season. The reanalysis data underestimated the frequency of the cold (<10 °C) and hot (>30 °C) days across the four regions, except ERA5-Land, which closely followed observed data. The strength of the correlation shows better performance (>0.90) in the cold extremes (cold nights and cold days) frequency than the hot extremes. On an interannual scale, reanalysis products exhibit strong correlations (>0.90) with in-situ data across most regions, particularly in winter and autumn, moderate in spring, and weaker in summer. The reanalysis data shows negative biases in the inland regions and positive biases in the coastal areas with consistent root mean square differences (RMSD) spatiotemporally. The differences in performance are due to the topography and poor representation of the energy fluxes, especially in MERRA-2 as well as missing data in observations. This study recommends ERA5-Land as the first choice for extreme weather simulations in the region, followed by MERRA-2 and ERA5 on the same scale, but proper attention is needed when using reanalysis data for cold and hot extremes.

Modifying factors and temporal trends of adverse health effects of short-term exposure to PM2.5 in Canada (2001–2018)

Considerable evidence has been accumulated on serious acute health outcomes associated with short-term exposure to ambient fine particulate matter (PM2.5). Modifying factors of those associations, however, have been less explored and need further analyses. In this national study, we investigated whether short-term effects of PM2.5 are modified according to region, cause of mortality/hospitalization, season, age, and sex. PM2.5-related adverse health effects were estimated by an ecological time-series study, covering about 80 % of the Canadian population for 18 years (2001–2018). We estimated city-specific associations using daily averages of PM2.5 and temperature, and daily counts of hospitalizations and mortality (non-accidental all-cause, circulatory, and respiratory). National and regional associations were then estimated with a 2-stage model. We considered potential modifying factors of PM2.5-related adverse health effects, and examined linear trends in the annual associations. Nationally, PM2.5 exposure was associated with both hospitalizations and mortality, and there was evidence of differences by the modifying factors. Of the various causes, circulatory mortality and respiratory hospitalization were more attributable to PM2.5 exposure. We found regional differences for both all-cause hospitalization and all-cause mortality, and seasonal differences for respiratory hospitalization (warm season) and circulatory hospitalization (cold season). Circulatory mortality risk was significant for seniors and females. All-cause hospitalizations appeared to gradually decrease over time, but annual all-cause mortality remained constant at 0.6 % of the population. Adverse health effects of PM2.5 exposures may depend on not only PM2.5 concentration, but also other factors (region, cause, season, age, sex). National estimates for the baseline (age ≥ 1 year, both sexes) risk cannot be interpreted without consideration of the differences by modifying factors. Study findings can be used by seniors, women, and those who have pre-existing health conditions to make informed decisions regarding their health risks from daily exposure to ambient PM2.5.

Vulnerability to heat-related mortality and the effect of prevention measures: a time-stratified case-crossover study in Switzerland.

Swiss climate scenarios predict increases in the frequency and intensity of extreme heat episodes in the future. For the effective prevention of heat-related mortality, several aspects of the population's vulnerability to heat must be understood on a local level. A nationwide analysis of individual death records was conducted, enabling a more comprehensive understanding than typical heat studies based on aggregated data. A total of 320,306 individual death records from the Swiss National Cohort with precise address information during the warm season (May to September) from 2003-2016 were linked to indoor and outdoor high-resolution daily temperature estimates. A time-stratified case-crossover study combined with distributed lag non-linear models was then performed to assess the temperature-mortality associations for various causes of death and to estimate the potential effect modification of individual characteristics. Additionally, it was explored whether the effect of extreme heat changed over time in regions with and without cantonal heat-health action plans (HHAPs). Using the temperature with the lowest cause-specific mortality risk (minimum mortality temperature) as the reference temperature, extreme heat (defined as ambient daily maximum temperature reaching 33 °C) was associated with a strong increase in all-cause mortality (odds ratio (OR): 1.21, 95% CI: 1.17-1.25) and disease-specific mortality from Alzheimer's disease and dementia (OR: 1.67, 95% CI: 1.48-1.88), COPD (OR: 1.37, 95% CI: 1.12-1.67), diabetes (OR: 1.34, 95% CI: 1.06-1.70), and myocardial infarction (OR: 1.26, 95% CI: 1.10-1.44). Indoor temperatures above 24 °C were found to be critical for mortality. The population most vulnerable to heat included older adults (≥75 years), unmarried individuals, people with a low education level, older women with low neighbourhood socioeconomic position, and men under 75 years old with low socioeconomic position. Overall, the risk of heat-related all-cause mortality in 2009-2016 was lower than that in 2003-2008. The decrease was significantly stronger in the region where cantonal HHAPs were implemented. This study provides important information for planning targeted and effective measures to reduce heat-related health risks in Switzerland. It demonstrates that HHAPs contribute to reducing heat-related mortality, although they may not reach the high-risk population of individuals with low socioeconomic position. Future prevention efforts should also target the less privileged population, including people younger than 75 years.

Teleconnection Between Early Winter Monsoon System and Harmful Algal Blooms in Shallow Lake Taihu

AbstractThere is a long history of observation and monitoring at local scales with a focus on meteorological modulation of lakes, however, the features at the local scale are heavily influenced by large‐scale atmospheric circulation. Harmful algal blooms (HABs) in large shallow eutrophic lakes are susceptible to local meteorological conditions, but their response to climate system variability is rarely considered. This study reveals that HABs in Lake Taihu, the third largest freshwater lake in subtropical China, are promoted by the weakened East Asian monsoon system in precursory early winter, but show no response in late winter with the low temperature unfavorable for algal metabolism. The weak early winter monsoon system is characterized as the northward‐shifted polar front jet and eastward‐tilted East Asian Trough. The accompanied anomalous descending motion decelerates surface winds over the middle to lower reaches of the Yangtze River including Taihu basin by strengthening atmospheric stratification and decreasing turbulent activity in the lower troposphere. The weakened surface winds reduce sediment resuspension and improve underwater light availability in Lake Taihu, providing favorable light condition for phytoplankton growth. It is indicated that the early‐winter surface winds rather than simultaneous nutrient supply, play a dominant role on the interannual variability of algal biomass in Lake Taihu. The positive algal biomass anomaly in early winter tends to persist and promote HABs in the following warmer seasons. Our finding validates the interannual teleconnection between climate system and HAB variation in Lake Taihu, and provides insights on predicting HABs in subtropical East Asian shallow lakes.

Extended spectrum cephalosporin (ESC) resistant Escherichia coli: Trends and seasonality in the Netherlands from 2014 to 2022

BackgroundAntimicrobial resistance (AMR) in livestock and the environment likely contribute to the prevalence of AMR in humans with potential detrimental effects on human health. As such, annual mandatory monitoring of AMR in livestock occurs within the European Union (EU), according to harmonised methods. Extended-spectrum cephalosporins-resistant (ESC-resistant) Escherichia coli (E. coli), including extended-spectrum β-lactamases (ESBL), AmpC β-lactamases (AmpC) and carbapenemase producing E. coli, are considered of particular importance and are therefore included in the monitoring program. MethodsUsing results from the annual monitoring of ESC-resistant E. coli from 2014–2022, trends in prevalence per animal sector were determined over the complete time period, as well as potential seasonal effects. ResultsDuring these nine years, significant changes were observed in the prevalence of ESC-resistant E. coli, in broilers, dairy cattle and veal calves, while no changes in prevalence were seen in slaughter pigs. Furthermore, the prevalence of ESC-resistant E. coli is positively correlated with warmer seasons (summer and autumn) for both dairy cattle and veal calves, while no associations were found for broilers and slaughter pigs. While temperature itself may play a role in the prevalence of ESC-resistant E. coli, other factors affecting the selective landscape, such as antibiotic usage, will also play a role. ConclusionA combined analysis of antimicrobial usage and prevalence of ESC-resistant E. coli through the year, both in livestock and human samples, would be an interesting follow-up of this study.

Verification of the Deterministic and Probabilistic Radar Nowcasting of Precipitation in Warm and Cold Seasons in the European Part of Russia

Verification of the Deterministic and Probabilistic Radar Nowcasting of Precipitation in Warm and Cold Seasons in the European Part of Russia

Greenhouse gas emissions from rotating biological contactors combined with hybrid constructed wetlands treating polluted river

The rotating biological contactors combined with hybrid constructed wetlands (R-HCWs) has promising treatment performance, however, concerns persisted regarding greenhouse gases (GHGs) emissions. In this study, GHGs in the R-HCWs was evaluated, and results revealed that R-HCWs facilitated nitrogen conversion and provided alternating oxygen environments, thereby promoting the reduction of N2O and CH4 emissions. Therefore, the comprehensive global warming potential (8.7±2.7 g CO2-eq·m-3·d-1) for handling unit volume of river water was low, thus, greater ecological benefits were achieved. The relative abundance of functional microorganisms such as Bacillus, Acinetobacter, Nitrospira and norank_f__norank_o__SBR1031, increased due to warm season, which promoted the nitrogen cycle and N2O emission reduction. Anammox and denitrifying bacteria showed significantly correlated with N2O and CH4 emissions (p < 0.01). This study provides valuable insights for the potential adoption of biological and ecological integrated treatment approach optimized for improving water and mitigating GHGs emissions.

Spatial Variation of Changes in Extreme Discharge Seasonality Across the Northeastern United States

ABSTRACTThe Northeast United States exhibits significant spatial heterogeneity in flood seasonality, with spring snowmelt‐driven floods historically dominating northern areas, while other regions show more varied flood seasonality. While it is well documented that since 1996 there has been a marked increase in extreme precipitation across this region, the response of flood seasonality to these changes in extreme precipitation and the spatial distribution of these effects remain uncertain. Here we show that, historically, snowmelt‐dominated northern regions were relatively insensitive to changes in extreme precipitation. However, with climate warming, the dominance of snowmelt floods is decreasing and thus the extreme flood regimes in northern regions are increasingly susceptible to changes in extreme precipitation. While extreme precipitation increased everywhere in the Northeastern United States in 1996, it has since returned to near pre‐1996 levels in the coastal north while remaining elevated in the inland north. Thus, the inland north region has and continues to experience the greatest changes in extreme flooding seasonality, including a substantial rise in floods outside the historical spring flood season, particularly in smaller watersheds. Further analysis reveals that while early winter floods are increasingly common, the magnitude of cold season floods (Nov‐May) have remained unchanged over time. In contrast, warm season floods (June‐Oct), historically less significant, are now increasing in both frequency and magnitude in the inland north. Our results highlight that treating the entire Northeast as a uniform hydroclimatic region conceals significant regional variations in extreme discharge trends and, more generally, climate warming will likely increase the sensitivity of historically snowmelt dominated watersheds to extreme precipitation. Understanding this spatial variability in increased extreme precipitation and increased sensitivity to extreme precipitation is crucial for enhancing disaster preparedness and refining water management strategies in affected regions.

Agronomic evaluation of 15 warm season grasses grown in temporarily waterlogged soils in Northeastern Argentina

Soils with temporarily waterlogged conditions are common in Northeastern Argentina. Fifteen accessions and hybrids of cultivated and native warm season grasses (Acroceras macrum, Urochloa species, Hemarthria altissima and Paspalum species) were planted in Basail, Chaco, in a completely randomized block design in November 2019. Initial, autumn and spring forage yield were measured in February 2020, July 2021 and December 2021, respectively. Plant height and plant diameter were evaluated in February 2020. Cold tolerance was estimated after the first frost in July 2021. Initial forage yield was between 29 and 181 g/plant. Urochloa mutica exhibited the greatest initial forage yield. Autumn and spring forage yield varied from 306 to 2,183 g/m2 and from 153 to 710 g/m2, respectively. U. mutica showed the highest autumn forage yield, however, it was the most damaged by cold weather. H. altissima hybrids were the most productive during spring and were cold tolerant. There were differences in plant height (7.5–49 cm) and plant diameter (68–268 cm) among the grasses. Grasses with prostrate, intermediate and upright growth habits were identified. Results indicate all grasses tested were adapted to humid Northeastern Argentina and varied in their morphological and agronomic traits.

Archeozoological materials of the settlement of the golden horde time Podymalovo–1

The article presents the results of an archaeozoological study of osteological materials collected during 2022 excavations at the Podymalovo-1 settlement. The settlement dates back to the Golden Horde period and lays in Ufimsky District, the Republic of Bashkortostan. The analysis of the animal species range, the anatomical spectrum of their bones, age and size of slaughtered animals, traces of pathological changes in their bones suggests a reconstruction of the main economic activities of the settlement's inhabitants. It is found that domestic ungulates at Podymalovo-1 were used by farms in multiple ways. The population kept cattle, small ruminants and horses. Cattle breeding was associated with dairy and meat production, while horses were mainly used for farm work. Livestock was kept until mature. It can be explained through their lifetime use to obtain milk, wool, or help. The monument shows traces of leather production and bone carving. Animal bones were used as raw materials for bone items and tools. Beef and horse meat dominated in the settlement residents' diet. Probably, as they consumed horse meat mostly, and never had pork as their meat, they acquired associ- ated ethnic and cultural traditions and religious prohibitions. Determining the season when domestic ungulates were slaughtered showed that people lived there all year round, while livestock was slaughtered more often in warm seasons than in cold ones. The settlement’s life was the most intense in summer and autumn presumably because Podymalovo-1 residents actively interacted with passing trade caravans.

Seasonal dynamics of Haemaphysalis tick species as SFTSV vectors in South Korea.

To date, the majority of tick surveillance studies have primarily focused on warmer seasons, which are considered optimal periods for ticks to actively seek hosts and transmit pathogens through blood-feeding activities. Consequently, tick species active during winter have often been overlooked, leading to an underestimation of their significance in transmitting severe fever with thrombocytopenia syndrome virus (SFTSV). In this study, we aimed to examine year-round tick prevalence with SFTSV and illuminate the role of the winter-dominant species, Haemaphysalis flava, in South Korea. Through rigorous identification facilitated by a primer set designed specifically for this purpose, we emphasize that H. flava, a competent vector species, harbors SFTSV in the winter season, thereby acting as an overwintering reservoir for the virus. This phenomenon may contribute to a higher infection rate among ticks in the following year.

Diurnal temperature range and cardiopulmonary health in Taiwan: Evaluating impacts, thresholds, and vulnerable groups

The health impacts of the diurnal temperature range (DTR), which may be affected by climate change, have received little attention. The objectives of this study were (1) to evaluate the association of DTR and cardiopulmonary outcomes, (2) to select the proper thresholds for a DTR warning system, and (3) to identify vulnerable groups. The weather and health records in Taiwan from 2000 to 2019, with a maximum DTR of 12.8 °C, were analyzed using generalized additive models. The health outcomes included cardiovascular (CVD) and respiratory disease (RD) categories and several sub-categories, such as ischemic heart disease, stroke, pneumonia, asthma, and chronic obstructive pulmonary disease. The results showed that the associations of DTR and cardiopulmonary outcomes were as significant as, and sometimes even stronger than, those of the daily maximum temperature and daily minimum apparent temperature in the warm and cold seasons, respectively. The significant association began at DTR of 6 °C, lower than previously reported. The identified DTR warning thresholds were 8.5 and 11 °C for the warm and cold seasons, respectively. DTR is statistically significantly associated with a 5–36% and a 9–20% increase in cardiopulmonary emergency and hospitalized cases in the warm season with a 1 °C increase above 8.5 °C, respectively. In the cold season, DTR is significantly associated with 7–41%, 4–30%, and 36–100% increases in cardiopulmonary emergency, hospitalized, and mortality with a 1 °C increase above 11 °C, respectively. People with hypertension, hyperglycemia, and hyperlipidemia had even higher risks. Vulnerable age and sex groups were identified if they had a lower DTR–health threshold than the general population, which can be integrated into a warning system. In conclusion, DTR may be increased on a local or city scale under climate change; a DTR warning system and vulnerable group identification may be warranted in most countries for health risk reduction.

Assessing Drought Impacts on Gross Primary Productivity of Rubber Plantations Using Flux Observations and Remote Sensing in China and Thailand

Rubber (Hevea brasiliensis Muell.) plantations are vital agricultural ecosystems in tropical regions. These plantations provide key industrial raw materials and sequester large amounts of carbon dioxide, playing a vital role in the global carbon cycle. Climate change has intensified droughts in Southeast Asia, negatively affecting rubber plantation growth. Limited in situ observations and short monitoring periods hinder accurate assessment of drought impacts on the gross primary productivity (GPP) of rubber plantations. This study used GPP data from flux observations at four rubber plantation sites in China and Thailand, along with solar-induced chlorophyll fluorescence (SIF), enhanced vegetation index (EVI), normalized difference vegetation index (NDVI), near-infrared reflectance of vegetation (NIRv), and photosynthetically active radiation (PAR) indices, to develop a robust GPP estimation model. The model reconstructed eight-day interval GPP data from 2001 to 2020 for the four sites. Finally, the study analyzed the seasonal drought impacts on GPP in these four regions. The results indicate that the GPP prediction model developed using SIF, EVI, NDVI, NIRv, and PAR has high accuracy and robustness. The model’s predictions have a relative root mean square error (rRMSE) of 0.22 compared to flux-observed GPP, with smaller errors in annual GPP predictions than the MOD17A3HGF model, thereby better reflecting the interannual variability in the GPP of rubber plantations. Drought significantly affects rubber plantation GPP, with impacts varying by region and season. In China and northern Thailand (NR site), short-term (3 months) and long-term (12 months) droughts during cool and warm dry seasons cause GPP declines of 4% to 29%. Other influencing factors may alleviate or offset GPP reductions caused by drought. During the rainy season across all four regions and the cool dry season with adequate rainfall in southern Thailand (SR site), mild droughts have negligible effects on GPP and may even slightly increase GPP values due to enhanced PAR. Overall, the study shows that drought significantly impacts rubber the GPP of rubber plantations, with effects varying by region and season. When assessing drought’s impact on rubber plantation GPP or carbon sequestration, it is essential to consider differences in drought thresholds within the climatic context.

Supervised Learning-Based Prediction of Lightning Probability in the Warm Season

The accurate prediction of lightning is crucial for forecasters to respond effectively to its related hazards. The rapid development and confined spatial extent of convective storms, in which lightning frequently occurs, pose considerable challenges for accurately predicting their locations using numerical weather prediction (NWP) models. Lightning occurrence is often prognosed using thermodynamic parameters, convective available potential energy (CAPE), the severe weather threat index (SWEAT), the lifted index (LI), etc. A high-resolution NWP model provides a prediction of these thermodynamic parameters at high spatiotemporal resolution with high accuracy for a few hours. However, a complicated algorithm is required to handle all the useful high-resolution variables from the NWP model. The recently emerging machine learning technique can solve this issue by properly handling these “big data” without any model distributional assumption. In this study, we developed a random forest algorithm for nowcasting and very short-range forecasting (useful for ~6 h), named LightningRF. LightningRF was trained by using lightning occurrence as a response variable and characteristic parameters from the NWP as predictors. It was also applied to analysis and forecast fields, showing a high probability of lightning within the observed lightning regions. This highlights the potential of helping forecasters improve their lightning forecasting skills using real-time probabilistic forecasts from a trained model.