Short-term Effects Of Weather Research Articles

Association between weather and hip fracture in adults: a nationwide study in China 198 cities.

Hip fractures represent a significant public health issue due to high incidence in aging society. Evidence of the short-term effects of weather on the risk of hip fracture is limited and inconsistent. We aimed to examine the associations between weather conditions and daily hospital admissions for hip fracture in adults in China. A national time-series analysis between 2014 and 2017 was conducted. Data on daily hospital admissions for hip fracture were obtained from the database of Urban Employee Basic Medical Insurance (UEBMI) and Urban Resident Basic Medical Insurance (URBMI). Weather conditions were acquired from the China Meteorological Data Sharing Service Center. Based on a time-stratified case-crossover design, conditional Poisson regression was used to estimate the impact on relative risk (RR) of weather conditions on hospital admissions for hip fracture. During the study period, a total of 137,504 hospital admissions for hip fractures were identified. All analyzed weather conditions showed consistent significant associations at lag 0 day for each 10 mm increase in precipitation, 10 m/s in wind speed, and 10°C in temperature, with the RR value being 1.079 (95% CI, 1.074-1.083) for precipitation, 1.404 (95% CI, 1.346-1.465) for wind speed, and 1.558 (95% CI, 1.546-1.570) for temperature. Women were more vulnerable to be affected by precipitation and temperature. In conclusion, increased risk for hip fractures in adults is associated with weather conditions. The improved understanding of the relationship between weather conditions and hip fractures hospital admission can be useful for resource allocation and provider preparedness.

Seasonal effects of habitat structure and weather on the habitat selection and home range size of a mammal in agricultural landscapes

Human land use intensified over the last century and simultaneously, extreme weather events have become more frequent. However, little is known about the interplay between habitat structure, direct short-term weather effects and indirect seasonal effects on animal space use and behavior. We used the European hare (Lepus europaeus) as model to investigate how habitat structure and weather conditions affect habitat selection and home range size, predictors for habitat quality and energetic requirements. Using > 100,000 GPS positions of 60 hares in three areas in Denmark and Germany, we analyzed habitat selection and home range size in response to seasonally changing habitat structure, measured as vegetation height and agricultural field size, and weather. We compared daily and monthly home ranges to disentangle between direct short-term weather effects and indirect seasonal effects of climate. Habitat selection and home range size varied seasonally as a response to changing habitat structure, potentially affecting the availability of food and shelter. Overall, habitat structure and seasonality were more important in explaining hare habitat selection and home range size compared to direct weather conditions. Nevertheless, hares adjusted habitat selection and daily home range size in response to temperature, wind speed and humidity, possibly in response to thermal constrains and predation risk. For effective conservation, habitat heterogeneity should be increased, e.g. by reducing agricultural field sizes and the implementation of set-asides that provide both forage and shelter, especially during the colder months of the year.

From days to decades: short- and long-term variation in environmental conditions affect offspring diet composition of a marine top predator

Long-term changes in climate are affecting the abundance, distribution and phenology of species across all trophic levels. Short-term climate variability is also having a profound impact on species and trophic interactions. Crucially, species will experience long- and short-term variation simultaneously, and both are predicted to change, yet studies tend to focus on only one of these temporal scales. Apex predators are sensitive to long-term climate-driven changes in prey populations and short-term effects of weather on prey availability, both of which could result in changes of diet. We investigated temporal trends and effects of long- and short-term environmental variability on chick diet composition in a North Sea population of European shags Phalacrocorax aristotelis between 1985 and 2014. The proportion of their principal prey, lesser sandeel Ammodytes marinus, declined from 0.99 (1985) to 0.51 (2014), and estimated sandeel size declined from 104.5 to 92.0 mm. Concurrently, diet diversification increased from 1.32 (1985) to 11.05 (2014) prey types yr-1, including members of the families Pholidae, Callionymidae and Gadidae. The relative proportion of adult to juvenile sandeel was greater following low sea surface temperatures (SSTs) in the previous year. In contrast, the proportion of Pholidae and prey richness were higher following high SST in the previous year. Within a season, the proportion of sandeel in the diet was lower on days with higher wind speeds. Crucially, our results showed that diet diversification was linked to trends in SST. Thus, predicted changes in climate means and variability may have important implications for diet composition of European shags in the future, with potential consequences for population dynamics.

Short-term effects of weather and air pollution on atopic dermatitis symptoms in children: A panel study in Korea.

IntroductionThe effects of weather and air pollution on the severity and persistence of atopic dermatitis (AD) are important issues that have not been investigated in detail. The objective of our study was to determine the short-term effects of meteorological variables and air pollution on AD symptoms in children.MethodsWe enrolled 177 AD patients with 5 years or younger from the Seoul Metropolitan Area, Korea, and followed for 17 months between August 2013 and December 2014. Symptoms records of 35,158 person-days, including itching, sleep disturbance, erythema, dry skin, oozing, and edema, were obtained. We estimated the effect of meteorological variables including daily mean temperature, relative humidity (RH), diurnal temperature range (DTR), rainfall and air pollutants including particulate matter with an aerodynamic diameter ≤10 μm (PM10), nitrogen dioxide (NO2), and tropospheric ozone (O3) on AD symptoms using a generalized linear mixed model with adjustment for related confounding factors.ResultsA 5°C increase in outdoor temperature and a 5% increase in outdoor RH was associated with 12.8% (95% confidence intervals (CI): 10.5, 15.2) and 3.3% (95% CI: 1.7, 4.7) decrease in AD symptoms, respectively, on the same day. An increase of rainfall by 5 mm increased AD symptoms by 7.3% (95% CI: 3.6, 11.1) for the days with <40 mm rainfall. The risk of AD symptoms increased by 284.9% (95% CI: 67.6, 784.2) according to a 5°C increase in DTR when it was >14°C. An increase in PM10, NO2, and O3 by 10 units increased the risk of AD symptoms on the same day by 3.2% (95% CI: 1.5, 4.9), 5.0% (95% CI: 1.4, 8.8), and 6.1% (95% CI: 3.2, 9.0), respectively.ConclusionExposure to meteorological variables and air pollutants are associated with AD symptoms in young children.

The effects of synoptic weather on influenza infection incidences: a retrospective study utilizing digital disease surveillance.

The environmental drivers and mechanisms of influenza dynamics remain unclear. The recent development of influenza surveillance--particularly the emergence of digital epidemiology--provides an opportunity to further understand this puzzle as an area within applied human biometeorology. This paper investigates the short-term weather effects on human influenza activity at a synoptic scale during cold seasons. Using 10years (2005-2014) of municipal level influenza surveillance data (an adjustment of the Google Flu Trends estimation from the Centers for Disease Control's virologic surveillance data) and daily spatial synoptic classification weather types, we explore and compare the effects of weather exposure on the influenza infection incidences in 79 cities across the USA. We find that during the cold seasons the presence of the polar [i.e., dry polar (DP) and moist polar (MP)] weather types is significantly associated with increasing influenza likelihood in 62 and 68% of the studied cities, respectively, while the presence of tropical [i.e., dry tropical (DT) and moist tropical (MT)] weather types is associated with a significantly decreasing occurrence of influenza in 56 and 43% of the cities, respectively. The MP and the DP weather types exhibit similar close positive correlations with influenza infection incidences, indicating that both cold-dry and cold-moist air provide favorable conditions for the occurrence of influenza in the cold seasons. Additionally, when tropical weather types are present, the humid (MT) and the dry (DT) weather types have similar strong impacts to inhibit the occurrence of influenza. These findings suggest that temperature is a more dominating atmospheric factor than moisture that impacts the occurrences of influenza in cold seasons.

A Global Degree Days Database for Energy-Related Applications

Weather can have a profound effect on energy consumption; especially extremes of hot and cold temperatures. These variations in particular drive residential and commercial energy demand because space heating and cooling is such an important component. Traditional approaches are customized to the specific geography of interest. Energy regulators use a measure of divergence from normal temperatures to estimate peaks in demand when planning future capacity, or to strip out short term weather effects to identify underlying growth trends. Energy traders marry weather forecasts to demand data to identify potential price peaks and troughs. What unites these analyses is that they tend to be either local or short term in nature; or both. However, the customization of methodology to a particular geography renders comparisons of the effects of weather between countries invalid.Targets for improving energy productivity and benchmarking of performance towards meeting such targets between countries requires a consistent global database, both spatially and temporally. To date, no such database has been available to policymakers. KAPSARC has worked with the Euro-Mediterranean Center for Climate Change (CMCC) to create a database covering 147 countries over a period of several decades, based on consistent methodologies such that the impacts of local climate on energy consumption can be analyzed.Differences in the energy productivity of countries are comprised of several factors. These include the industrial structure of the economy, efficiency of equipment and processes, availability of water and differences in weather, among other factors. Differentiating between the factors that are controllable (including economic structure and efficiency) and uncontrollable (including weather and access to water), allows policy to be focused in the areas that it can achieve the most beneficial impact. The CMCC-KAPSARC Weather Normalization Database is one of the tools now available to policymakers to separate the signal from the noise in guiding policies aimed at improving the energy productivity of their economies.

Swarms of repeating stick-slip icequakes triggered by snow loading at Mount Rainier volcano

We have detected over 150,000 small (M 3000 m) on the glacier-covered edifice and occur primarily in weeklong to monthlong swarms composed of simultaneous distinct families of events. Each family contains up to thousands of earthquakes repeating at regular intervals as often as every few minutes. Mixed polarity first motions, a linear relationship between recurrence interval and event size, and strong correlation between swarm activity and snowfall suggest the source is stick-slip basal sliding of glaciers. The sudden added weight of snow during winter storms triggers a temporary change from smooth aseismic sliding to seismic stick-slip sliding in locations where basal conditions are favorable to frictional instability. Coda wave interferometry shows that source locations migrate over time at glacial speeds, starting out fast and slowing down over time, indicating a sudden increase in sliding velocity triggers the transition to stick-slip sliding. We propose a hypothesis that this increase is caused by the redistribution of basal fluids rather than direct loading because of a 1–2 day lag between snow loading and earthquake activity. This behavior is specific to winter months because it requires the inefficient drainage of a distributed subglacial drainage system. Identification of the source of these frequent signals offers a view of basal glacier processes, discriminates against alarming volcanic noises, documents short-term effects of weather on the cryosphere, and has implications for repeating earthquakes, in general.

Weather related mortality in high-, middle- and low-income countries - differences and similarities

Background. The increased number of publication of time series studies of the short term effects of weather on daily mortality facilitates a more detailed comparison of temperature- (and rainfall) mortality functions across populations. There is a lack of evidence regarding weather effects in tropical and sub-tropical climates. Aims. To review published studies on weather effects on daily mortality in low, middle and high income countries, and describe important differences in response functions between populations. Methods. Review published studies that quantify the impact of temperature and rainfall on daily mortality outcomes in populations in high, middle and low income countries. Results: Published studies from low income countries or in tropical climates include several from the CLIMIMO collaboration that used demographic surveillance data from the inDEPTH network. Both high and low temperatures increase the risk of acute mortality in most populations in low and middle-income countries, with cold effects dominating in some populations. The heat and cold effect estimates (slopes) and thresholds are quite heterogeneous. Differences in effects in adults, children and the elderly reflect the underlying disease profiles, particularly where mortality from infectious diseases is high. Rainfall effects are particularly important in rural populations where malaria mortality is high. Conclusions: Population specific weather-health relationships are determined by climate and non-climate factors. Urban and rural populations in low and middle income settings have different health profiles and socio-economic determinants of health status which make them more susceptible to weather effects, particularly in children. Epidemiological analyses can provide limited information on the causal mechanisms by which environmental temperature and rainfall affect acute mortality. Lack of long-term and daily time series data on health outcomes in low income settings remains a limitation to research on short-term health effects.

Short-term effects of weather on the incidence of hand, foot and mouth disease in Guangzhou city

有研究表明,手足口病在潮湿季节有病例增加的趋势[1].广州市近年来手足口病流行,并有夏秋季高发的特点[2].本研究使用分布滞后非线性模型(DLNM)探索气象对手足口病发病的影响[3]. 关键词：气象因素;手足口病;短期效应

Short Term Effects of Weather on Hand, Foot and Mouth Disease

BackgroundHand, foot, and mouth disease (HFMD) outbreaks leading to clinical and fatal complications have increased since late 1990s; especially in the Asia Pacific Region. Outbreaks of HFMD peaks in the warmer season of the year, but the underlying factors for this annual pattern and the reasons to the recent upsurge trend have not yet been established. This study analyzed the effect of short-term changes in weather on the incidence of HFMD in Singapore.MethodsThe relative risks between weekly HFMD cases and temperature and rainfall were estimated for the period 2001–2008 using time series Poisson regression models allowing for over-dispersion. Smoothing was used to allow non-linear relationship between weather and weekly HFMD cases, and to adjust for seasonality and long-term time trend. Additionally, autocorrelation was controlled and weather was allowed to have a lagged effect on HFMD incidence up to 2 weeks.ResultsWeekly temperature and rainfall showed statistically significant association with HFMD incidence at time lag of 1–2 weeks. Every 1°C increases in maximum temperature above 32°C elevated the risk of HFMD incidence by 36% (95% CI = 1.341–1.389). Simultaneously, one mm increase of weekly cumulative rainfall below 75 mm increased the risk of HFMD by 0.3% (CI = 1.002–1.003). While above 75 mm the effect was opposite and each mm increases of rainfall decreased the incidence by 0.5% (CI = 0.995–0.996). We also found that a difference between minimum and maximum temperature greater than 7°C elevated the risk of HFMD by 41% (CI = 1.388–1.439).ConclusionOur findings suggest a strong association between HFMD and weather. However, the exact reason for the association is yet to be studied. Information on maximum temperature above 32°C and moderate rainfall precede HFMD incidence could help to control and curb the up-surging trend of HFMD.

Short-term Effects of Weather on Hand, Foot, and Mouth Disease

Background: Hand, foot, and mouth disease (HFMD) outbreaks leading to clinical and fatal complications have increased since late 1990s; especially in the Asia Pacific Region. Outbreaks of HFMD peak ...

College Students’ Perceptions About the Plausibility of Human-Induced Climate Change

Overcoming students’ misconceptions may be a challenge when teaching about phenomena such as climate change. Students tend to cite short-term weather effects as evidence to support or refute long-term climate transformations, which displays a fundamental misunderstanding about weather and climate distinctions. Confusion about weather and climate may also reflect student misunderstanding about deep time, a concept that spans several scientific content areas. This study examines the relationships between students’ understanding of deep time and their understandings of the distinctions between weather and climate, as well as how these understandings influence students’ perceptions about the plausibility of human-induced global climate change. Undergraduate students enrolled in an introductory science class on global climate change completed measures of their (a) understanding of distinctions between weather and climate, (b) knowledge of deep time, and (c) plausibility perceptions of human-induced climate change, both at the beginning and end of the course. The study includes comparison groups of similar students enrolled in introductory physical geography classes. Results revealed that greater knowledge of deep time and increased plausibility perceptions of human-induced climate change provide significant explanation of variance in students’ understanding of weather and climate distinctions. Furthermore, students achieve significantly increased understanding of weather and climate, even with brief instruction.

Environmental Exposures and Invasive Meningococcal Disease: An Evaluation of Effects on Varying Time Scales

Invasive meningococcal disease (IMD) is an important cause of meningitis and bacteremia worldwide. Seasonal variation in IMD incidence has long been recognized, but mechanisms responsible for this phenomenon remain poorly understood. The authors sought to evaluate the effect of environmental factors on IMD risk in Philadelphia, Pennsylvania, a major urban center. Associations between monthly weather patterns and IMD incidence were evaluated using multivariable Poisson regression models controlling for seasonal oscillation. Short-term weather effects were identified using a case-crossover approach. Both study designs control for seasonal factors that might otherwise confound the relation between environment and IMD. Incidence displayed significant wintertime seasonality (for oscillation, P < 0.001), and Poisson regression identified elevated monthly risk with increasing relative humidity (per 1% increase, incidence rate ratio = 1.04, 95% confidence interval: 1.004, 1.08). Case-crossover methods identified an inverse relation between ultraviolet B radiation index 1–4 days prior to onset and disease risk (odds ratio = 0.54, 95% confidence interval: 0.34, 0.85). Extended periods of high humidity and acute changes in ambient ultraviolet B radiation predict IMD occurrence in Philadelphia. The latter effect may be due to decreased pathogen survival or virulence and may explain the wintertime seasonality of IMD in temperate regions of North America.

Quantity and spectroscopic properties of soil dissolved organic matter (DOM) as a function of soil sample treatments: Air-drying and pre-incubation

The dissolved organic matter (DOM) in soils is essentially defined by the way in which it is obtained. Therefore, we need to understand as to how pre-treatment of a soil will affect the characteristics of DOM, since this fraction may be strongly influenced by a soil’s water content. The effect of two different pre-treatments on DOM from the A-horizons of a large variety of ecosystems and regions were compared. In both cases the soils were allowed to air-dry. In one case the air-dried soil was directly extracted (AD), while in the other case it was pre-incubated for 1 week at 50% of its water holding capacity (INCU). AD is simpler, but INCU brings the soil, and especially its microbial population, back to a standardised state, which is more representative of the usual state in the field. Both methods are used whenever an adjustment of the soil water content is essential to compare different regions or to eliminate short term weather effects. A significant regression indicated that the dissolved organic carbon (DOC) extracted from INCU samples was only 20% of AD DOC. Both the absorptivity (UV absorption divided by DOC) of 86% of the samples, and a fluorescence emission spectrum based Humification Index in all cases increased as a result of pre-incubation. This would indicate that labile compounds released during drying were metabolised during the incubation. However, the magnitude of this increase varied, and no correlation with soil organic and microbial carbon, pH, or texture could be detected. The results show that DOM extracted from AD and INCU soils is not comparable and that the differences are mainly due to the impact of air-drying on the microbial activity.

Short-term effects of weather on bird migration: A field study using multivariate statistics

Fluctuations in nocturnal bird migration were studied during 84 nights in the period 30 April to 4 June, 1959, to 1961, using radar from Cape Cod, Massachusetts, U.S.A. Two groups of species could be distinguished. Songbirds (of many different species) passed northeast in large numbers over the mainland of New England; waterbirds (ducks, geese and gulls) passed east-northeast in smaller numbers over the Gulf of Maine. The waterbirds began to migrate 2 to 3 hr before sunset, the songbirds some 3 4 hr after sunset. Both movements continued in substantial numbers throughout the night, but shifts in the mean orientation led to smaller counts around midnight. Tests for bias in measuring the density of migration were negative. The main source of random errors was spatial variation in the density of birds before take-off. Measurements of the density of migration each evening were compared with measurements of nineteen weather variables in the area of take-off. Reasonably good fits to a multiple linear regression model were obtained if a nonlinear transformation (e.g. the 10th root) of the migration density was used as dependent variable. Migration density was significantly correlated with high and rising temperature, low and falling pressure, low but rising humidity, and the onshore (southeast) component of the wind velocity. Migration of songbirds was slightly suppressed by rain, but no other weather variable was significant. Migration was correlated both with the weather at the time of takeoff, and with the changes in weather during the previous 24 hr; at least in the case of the waterbirds, the changes were more important. At least for the songbirds, migration tended to be sparsest in the few days before full moon, but not during periods of cloudy weather. The density of migration was positively correlated with that on the previous night, largely due to auto-correlation in the weather variables. Migration of waterbirds tended to be sparser than expected on the second and third nights after a large departure, but denser than expected after 4 or more nights of delay. No such tendencies were found in the songbirds; after a night of migration songbirds tended to fly again on the next night. The relation between migration and weather was non-linear at both ends of the scale. Migration was usually suppressed in cold rains and reversed in cold northwest airstreams. It occurred strongly in the west-central part of a high pressure cell but tended to decline after the arrival of humid tropical air. Only minor differences were found between the behaviour of waterbirds and songbirds. Few precise conclusions can be drawn about the behaviour of individual birds. Multivariate statistics on uncontrolled variables permit inferences only of association, not of cause-and-effect. Errors are possible if important variables are omitted, or wrongly scaled. Migration was significantly correlated with high temperatures, high clouds and lack of rain at the birds' destination on the following day, but not with cloud cover and only weakly with wind direction. A computer experiment showed that the observed behaviour was very close to the optimum for predicting these variables at the destination. The behaviour is probably adapted to avoid rain, fog and cold air on arrival at the destination. These results differ considerably from those reported previously, but do not necessarily conflict with them. The main difference is the more elaborate statistical model used in this paper. Experimental studies of Zugunruhe are reviewed briefly. Most or all experimental studies have demonstrated only long-term effects of weather variables on Zugunruhe; confining birds in experimental situations may upset a system of checks and balances between external variables required for the expression of short-term effects of weather on migration.