Short-term Temperature Variability Research Articles

The association between short-term temperature variability and mortality in Virginia

The objective of this study is to determine the relationship between short-term temperature variability on neighboring days and mortality. The change in maximum temperature in Northern Virginia, Richmond, Roanoke, and Norfolk, Virginia, on neighboring days was calculated from airport observations and associated with total mortality over a multi-county area surrounding each weather station. The association between day-to-day temperature change and mortality, lagged over a 28-day period, was analyzed using distributed lag non-linear models that controlled for air quality, temporal trends, and other factors. Days following large temperature declines were associated with an increased risk of mortality in three of the four locations, and temperature increases were linked to higher mortality risk in two cities. For example, the relative risk of mortality for a 12°C daily temperature decline (1st percentile) was 1.74 [0.92, 3.27] in Roanoke and 1.16 [0.70, 1.92] in Richmond. The net effect of short-term temperature increases was smaller, with the largest relative risk of 1.03 [0.58, 1.83] for a 12°C increase (99th percentile) in maximum temperature in Norfolk. In Richmond and Roanoke, there was an observed lagged effect of increased mortality (maximum relative risks varying from 1.08 to 1.10) that extended from 5 to 25 days associated with large temperature declines of 15°C or more. In contrast, there was a strong and immediate (lag 0–3 day) increase in the risk of mortality (1.10 to 1.15) in northern Virginia and Norfolk when the temperature increase exceeded 10°C (short-term warming). In general, consecutive day warming had a more immediate mortality impact than short-term cooling, when the peak mortality is lagged by one week or more. However, cooling of at least 10°C after a hot (summer) day reduced mortality relative to comparable cooling following a cold (winter) day, which is associated with high mortality. This differential mortality response as a function of temperature suggests that there is some relationship between average temperature, temperature variability, and season. The findings of this study may be useful to public health officials in developing mitigation strategies to reduce the adverse health risks associated with short-term temperature variability.

Ocean weather, biological rates, and unexplained global ecological patterns.

As on land, oceans exhibit high temporal and spatial temperature variation. This "ocean weather" contributes to the physiological and ecological processes that ultimately determine the patterns of species distribution and abundance, yet is often unrecognized, especially in tropical oceans. Here, we tested the paradigm of temperature stability in shallow waters (<12.5 m) across different zones of latitude. We collated hundreds of in situ, high temporal-frequency ocean temperature time series globally to produce an intuitive measure of temperature variability, ranging in scale from quarter-diurnal to annual time spans. To estimate organismal sensitivity of ectotherms (i.e. microbes, algae, and animals whose body temperatures depend upon ocean temperature), we computed the corresponding range of biological rates (such as metabolic rate or photosynthesis) for each time span, assuming an exponential relationship. We found that subtropical regions had the broadest temperature ranges at time spans equal to or shorter than a month, while temperate and tropical systems both exhibited narrow (i.e. stable) short-term temperature range estimates. However, temperature-dependent biological rates in tropical regions displayed greater ranges than in temperate systems. Hence, our results suggest that tropical ectotherms may be relatively more sensitive to short-term thermal variability. We also highlight previously unexplained macroecological patterns that may be underpinned by short-term temperature variability.

Time-series analysis of temperature variability and cardiovascular emergency department visits in Atlanta over a 27-year period.

Short-term temperature variability, defined as the temperature range occurring within a short time span at a given location, appears to be increasing with climate change. Such variation in temperature may influence acute health outcomes, especially cardiovascular diseases (CVD). Most research on temperature variability has focused on the impact of within-day diurnal temperature range, but temperature variability over a period of a few days may also be health-relevant through its impact on thermoregulation and autonomic cardiac functioning. To address this research gap, this study utilized a database of emergency department (ED) visits for a variety of cardiovascular health outcomes over a 27-year period to investigate the influence of three-day temperature variability on CVD. For the period of 1993-2019, we analyzed over 12million CVD ED visits in Atlanta using a Poisson log-linear model with overdispersion. Temperature variability was defined as the standard deviation of the minimum and maximum temperatures during the current day and the previous two days. We controlled for mean temperature, dew point temperature, long-term time trends, federal holidays, and day of week. We stratified the analysis by age group, season, and decade. All cardiovascular outcomes assessed, except for hypertension, were positively associated with increasing temperature variability, with the strongest effects observed for stroke and peripheral vascular disease. In stratified analyses, adverse associations with temperature variability were consistently highest in the moderate-temperature season (October and March-May) and in the 65 + age group for all outcomes. Our results suggest that CVD morbidity is impacted by short-term temperature variability, and that patients aged 65 and older are at increased risk. These effects were more pronounced in the moderate-temperature season and are likely driven by the Spring season in Atlanta. Public health practitioners and patient care providers can use this knowledge to better prepare patients during seasons with high temperature variability or ahead of large shifts in temperature.

Geography and developmental plasticity shape post-larval thermal tolerance in the golden star tunicate, Botryllus schlosseri

Local adaptation and phenotypic plasticity play key roles in mediating organisms’ ability to respond to spatiotemporal variation in temperature. These two processes often act together to generate latitudinal or elevational clines in acute temperature tolerance. Phenotypic plasticity is also subject to local adaptation, with the expectation that populations inhabiting more variable environments should exhibit greater phenotypic plasticity of thermal tolerance. Here we examine the potential for local adaptation and developmental plasticity of thermal tolerance in the widespread invasive tunicate Botryllus schlosseri. By comparing five populations across a thermal gradient spanning 4.4° of latitude in the northwest Atlantic, we demonstrate that warmer populations south of the Gulf of Maine exhibit significantly increased (∼0.2 °C) post-larval temperature tolerance relative to the colder populations within it. We also show that B. schlosseri post-larvae possess a high degree of developmental plasticity for this trait, shifting their median temperature of survival (LT50) upwards by as much as 0.18 °C per 1 °C increase in environmental temperature. Lastly, we found that populations vary in their degrees of developmental plasticity, with populations that experience more pronounced short-term temperature variability exhibiting greater developmental plasticity, suggesting the local adaptation of developmental plasticity. By comparing the thermal tolerance of populations across space and through time, we demonstrate how geography and developmental plasticity have shaped thermal tolerance in B. schlosseri. These results help inform our understanding of how species are able to adjust their thermal physiology in new environments, including those encountered during invasion and under increasingly novel climate conditions.

Temperature variability increases the onset risk of ischemic stroke: A 10-year study in Tianjin, China

Epidemiological evidence suggests a correlation between ambient temperature and ischemic stroke. However, evidence on the impact of daily temperature variability on the onset of ischemic stroke is lacking and limited. We aimed to investigate the short-term association between temperature variability and ischemic stroke occurrence in Tianjin. We performed a 10-year analysis of ischemic stroke patients hospitalized in two affiliated hospitals of Tianjin Medical University from 2011 to 2020. Daily meteorological data were collected from the Tianjin Meteorological Bureau. Temperature variability was calculated from the standard deviation (SD) of daily minimum and maximum temperatures over exposure days. A quasi-Poisson generalized linear regression combined with distributed lag non-linear model (DLNM) was used to estimate the effect of temperature variability on daily stroke onset, while controlling for daily mean temperature, relative humidity, long-term trend and seasonality, public holiday, and day of the week. Temperature variability was positively associated with ischemic stroke. A 1°C increase in temperature variability at 0-1 days (TV0-1) was associated with a 4.1% (1.9-6.3%) increase of ischemic stroke onset. In a stratified analysis, men, people aged ≤65 years, and individuals with pre-existing hypertension, hyperlipidemia, hyperhomocysteinemia were more susceptible to temperature variability. Furthermore, the influence pattern of temperature variability on ischemic stroke was different in the cold season (November-April) and the warm season (May-October). Our findings suggested that short-term temperature variability exposure could increase the risk of ischemic stroke, which may provide new insights into the impact of climate change on health.

Temperature variability and common diseases of the elderly in China: a national cross-sectional study

BackgroundIn the context of climate change, it has been well observed that short-term temperature variability (TV) could increase the overall and cause-specific mortality and morbidity. However, the association between long-term TV and a broader spectrum of diseases is not yet well understood, especially in the elderly.MethodsOur study used data from the fourth Urban and Rural Elderly Population (UREP) study. Long-term TV was calculated from the standard deviation (SD) of daily minimum and maximum temperatures within the study periods (2010–2014, 2011–2014, 2012–2014, 2013–2014, and 2014). Ten self-reported diseases and conditions were collected by questionnaire, including cataract, hypertension, diabetes, cardio-cerebrovascular diseases, stomach diseases, arthritis, chronic lung disease, asthma, cancer, and reproductive diseases. The province-stratified logistic regression model was used to quantify the association between long-term TV and the prevalence of each disease.ResultsA total of 184,047 participants were included in our study. In general, there were significant associations between TV and the prevalence of most diseases at the national level. Cardio-cerebrovascular disease (OR: 1.16, 95% CI: 1.13, 1.20) generated the highest estimates, followed by stomach diseases (OR: 1.15, 95% CI: 1.10, 1.19), asthma (OR: 1.14, 95% CI: 1.06, 1.22), chronic lung diseases (OR: 1.08, 95% CI: 1.03, 1.13), arthritis (OR: 1.08, 95% CI: 1.05, 1.11), and cataract (OR: 1.06, 95% CI: 1.02, 1.10). Moreover, the associations varied by geographical regions and across subgroups stratified by sex, household income, physical activity, and education.ConclusionsOur study showed that long-term exposure to TV was associated with the prevalence of main diseases in the elderly. More attention should be paid to the elderly and targeted strategies should be implemented, such as an early warning system.

Global, regional, and national burden of mortality associated with short-term temperature variability from 2000–19: a three-stage modelling study

SummaryBackgroundIncreased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19.MethodsIn this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades.FindingsAn increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2–4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7–5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3–10·4), followed by Europe (4·4%, 2·2–5·6) and Africa (3·3, 1·9–4·6).InterpretationGlobally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability.FundingAustralian Research Council, Australian National Health & Medical Research Council.

Socioeconomic inequality in vulnerability to all-cause and cause-specific hospitalisation associated with temperature variability: a time-series study in 1814 Brazilian cities

BACKGROUND AND AIM: Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil. METHODS: We collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0·25° × 0·25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita and GDP per capita over the study peroid. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability (TV) and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. RESULTS:We included a total of 147 959 243 hospitalisations (59·0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV0–1) increased by 0·52% (95% CI 0·50−0·55). For lower-middle-income cities, this risk was 0·63% (95% CI 0·58–0·69), for upper-middle-income cities it was 0·50% (0·47–0·53), and for high-income cities it was 0·39% (0·33–0·46). The socioeconomic inequality in vulnerability to TV0–1 was especially evident for people aged 0–19 years (effect estimate 1·21% for lower-middle income vs 0·52% for high income) and people aged 60 years or older (0·60% vs 0·43%), and for hospitalisation due to infectious diseases (1·62% vs 0·56% ), respiratory diseases (1·32% vs 0·55% ), and endocrine diseases (1·21% vs 0·32% ). CONCLUSIONS:People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability, which could exacerbate existing health and socioeconomic inequalities in Brazil. KEYWORDS: Temperature extremes and variability, Socio-economic factors (non-chemical stressors), Environmental justice, Environmental disparities

Short-term temperature variability in a tropical Andean city Manizales, Colombia

The climatic variability in the Tropical Andes area is high, both spatially and temporally, and its analysis must be carried out both in the short and long term depending on the available information. This type of spatial-temporal analysis provides tools for planning and environmental management in urban areas, given its high complexity. This investigation focuses on a diagnosis of the diurnal cycle and the analysis of the monthly temperature structure in 13 stations located in the city of Manizales, Caldas (Colombia). This applied research aims to understand the behavior of the temperature in a tropical Andes city in Colombia, where the spatial-temporal complexity of this variable improve the urban and hydrological planning strategies. Results correspond to what has been previously defined by other authors for the Andean zone: city temperature shows very stable patrons, yet important variations in temperature range across the city are appreciated during the day.

Socioeconomic inequality in vulnerability to all-cause and cause-specific hospitalisation associated with temperature variability: a time-series study in 1814 Brazilian cities

Exposure to temperature variability has been associated with increased risk of mortality and morbidity. We aimed to evaluate whether the association between short-term temperature variability and hospitalisation was affected by local socioeconomic level in Brazil. In this time-series study, we collected city-level socioeconomic data, and daily hospitalisation and weather data from 1814 Brazilian cities between Jan 1, 2000, and Dec 31, 2015. All-cause and cause-specific hospitalisation data was from the Hospital Information System of the Unified Health System in Brazil. City-specific daily minimum and maximum temperatures came from a 0·25° × 0·25° Brazilian meteorological dataset. We represented city-specific socioeconomic level using literacy rate, urbanisation rate, average monthly household income per capita (using the 2000 and 2010 Brazilian census), and GDP per capita (using statistics from the Brazilian Institute of Geography and Statistics for 2000-15), and cities were categorised according to the 2015 World Bank standard. We used quasi-Poisson regression to do time-series analyses and obtain city-specific associations between temperature variability and hospitalisation. We pooled city-specific estimates according to different socioeconomic quartiles or levels using random-effect meta-analyses. Meta-regressions adjusting for demographic and climatic characteristics were used to evaluate the modification effect of city-level socioeconomic indicators on the association between temperature variability and hospitalisation. We included a total of 147 959 243 hospitalisations (59·0% female) during the study period. Overall, we estimated that the hospitalisation risk due to every 1°C increase in the temperature variability in the current and previous day (TV0-1) increased by 0·52% (95% CI 0·50-0·55). For lower-middle-income cities, this risk was 0·63% (95% CI 0·58-0·69), for upper-middle-income cities it was 0·50% (0·47-0·53), and for high-income cities it was 0·39% (0·33-0·46). The socioeconomic inequality in vulnerability to TV0-1 was especially evident for people aged 0-19 years (effect estimate 1·21% [1·11-1·31] for lower-middle income vs 0·52% [0·41-0·63] for high income) and people aged 60 years or older (0·60% [0·50-0·70] vs 0·43% [0·31-0·56]), and for hospitalisation due to infectious diseases (1·62% [1·46-1·78] vs 0·56% [0·30-0·82]), respiratory diseases (1·32% [1·20-1·44] vs 0·55% [0·37-0·74]), and endocrine diseases (1·21% [0·99-1·43] vs 0·32% [0·02-0·62]). People living in less developed cities in Brazil were more vulnerable to hospitalisation related to temperature variability. This disparity could exacerbate existing health and socioeconomic inequalities in Brazil, and it suggests that more attention should be paid to less developed areas to mitigate the adverse health effects of short-term temperature fluctuations. None.

Impact of temperature variability on childhood allergic rhinitis in a subtropical city of China

BackgroundMany studies have shown an association of childhood respiratory diseases with short-term temperature variability such as diurnal temperature range (DTR) and temperature change between two neighboring days (TCN). However, the impact of temperature variability on allergic rhinitis (AR) has not been investigated so far. This study sought to evaluate the short-term effect of temperature variability (i.e., TCN and DTR) on AR, as well as to identify vulnerable subpopulations.MethodWe collected daily data on emergency room visits and outpatients for AR and weather variables in Hefei, China during 2014–2016. A distributed lag non-linear model that controlled for long-term trend and seasonality, mean temperature, relative humidity, day of week was used to fit the associations of AR with DTR and TCN. Stratified analyses by age, sex and occupation were also performed.ResultsDuring the study period, there were a total of 53,538 cases and the average values of DTR and TCN were 8.4 °C (range: 1.0 °C to 21.2 °C) and 0 °C (range: − 12.2 °C to 5.9 °C), respectively. While we did not observe an adverse effect of DTR on AR, TCN was significantly associated with increased risk of AR. Specifically, a large temperature drop between two adjacent days (3.8 °C, 5th percentile of TCN) has a delayed and short-lasting effect on AR, with the estimated relative risk of 1.02 (95% confidence interval: 1.01 to 1.04) at lag 12. Moreover, boys and children older than 15 years seemed to be more vulnerable to the effect of TCN.ConclusionsThis study provided evidence of an adverse effect of large temperature drops between two adjacent days on childhood AR. Attention paid to boys and older children may help prevent AR attacks.

&lt;p&gt;Temperature Variability and Hospital Admissions for Chronic Obstructive Pulmonary Disease: Analysis of Attributable Disease Burden and Vulnerable Subpopulation&lt;/p&gt;

PurposeChronic obstructive pulmonary disease (COPD) is a major cause of chronic diseases causing considerable social and economic burden globally. Despite substantial evidence on temperature-COPD association, few studies have investigated the acute effect of temperature variability (TV), a potential trigger of exacerbation of COPD disease, and it remains unknown what fraction of the disease burden of COPD is attributable to TV.Patients and MethodsBased on 71,070 COPD hospitalizations during 2013–2015 in Guangzhou, China, we conducted a time-series analysis using quasi-Poisson regression to assess the association between TV and hospital admission for COPD after adjusting for daily mean temperature. Short-term TV was captured by the standard deviation of hourly or daily temperatures across various exposure days. We also provided the fraction (total number) of COPD attributable to TV. Stratified analyses by admission route, sex, age, occupation, marital status and season were performed to identify vulnerable subpopulations.ResultsWe found a linear relationship between TV and COPD hospitalization, with a 1°C increase in hourly TV and daily TV associated with 4.3% (95%CI: 2.2–6.4) and 4.0% (2.3–5.8) increases in COPD, respectively. The greater relative risks of TV identified males, people aged 0–64 years, blue collar, and divorced/widowed people as vulnerable population. There were 12.0% (8500 cases) of COPD hospitalization attributable to hourly TV during the study period. Daily TV produced similar estimates of relative effects (relative risk) but grater estimates of absolute effects (attributable fraction) than hourly TV.ConclusionWe concluded that TV was an independent risk factor of COPD morbidity, especially among the susceptible subgroups. These findings would be helpful to guide the development of targeted public intervention.

Association between temperature variability and daily hospital admissions for cause-specific cardiovascular disease in urban China: A national time-series study.

BackgroundEpidemiological studies have provided compelling evidence of associations between ambient temperature and cardiovascular disease. However, evidence of effects of daily temperature variability on cardiovascular disease is scarce and mixed. We aimed to examine short-term associations between temperature variability and hospital admissions for cause-specific cardiovascular disease in urban China.Methods and findingsWe conducted a national time-series analysis in 184 cities in China between 2014 and 2017. Data on daily hospital admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke were obtained from the database of Urban Employee Basic Medical Insurance (UEBMI) including 0.28 billion enrollees. Temperature data were acquired from the China Meteorological Data Sharing Service Center. Temperature variability was calculated from the standard deviation (SD) of daily minimum and maximum temperatures over exposure days. City-specific associations between temperature variability and cardiovascular disease were examined with overdispersed Poisson models controlling for calendar time, day of the week, public holiday, and daily mean temperature and relative humidity. Random-effects meta-analyses were performed to obtain national and regional average associations. We also plotted exposure-response relationship curve using a natural cubic spline of temperature variability. There were 8.0 million hospital admissions for cardiovascular disease during the study period. At the national-average level, a 1-°C increase in temperature variability at 0–1 days (TV0–1) was associated with a 0.44% (0.32%–0.55%), 0.31% (0.20%–0.43%), 0.48% (0.01%–0.96%), 0.34% (0.01%–0.67%), and 0.82% (0.59%–1.05%) increase in hospital admissions for cardiovascular disease, ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke, respectively. The estimates decreased but remained significant when controlling for ambient fine particulate matter (PM2.5), NO2, and SO2 pollution. The main limitation of the present study was the unavailability of data on individual exposure to temperature variability.ConclusionsOur findings suggested that short-term temperature variability exposure could increase the risk of cardiovascular disease, which may provide new insights into the health effects of climate change.

Halistatt Cycle Subarctic Fennoscandian Temperature and Its Possible Link with Solar Activity

Reconstruction of summer temperature at subarctic Fennoscandia (68°–70° N, 20°–30° E), based on tree-ring data, was compared with three solar activity reconstructions, obtained by means of 14C and 10Be. It was shown that temperature proxy reconstructs well both long-term and short-term temperature variability. Weak, but significant positive correlation between reconstructed temperature (Helama et al., 2010) averaged over 40 years, and solar proxies was found during BC 5495–AD 1895. It was shown that Hallstatt cyclicity (1800–2300 years) is the main common feature in temperature and solar proxies. Possible mechanisms of the solar–temperature link over subarctic Fennoscandia are discussed.

Seasonal temperature variability and emergency hospital admissions for respiratory diseases: a population-based cohort study

BackgroundClimate change increases global mean temperature and changes short-term (eg, diurnal) and long-term (eg, intraseasonal) temperature variability. Numerous studies have shown that mean temperature and short-term temperature variability are both...

The mortality burden of hourly temperature variability in five capital cities, Australia: Time-series and meta-regression analysis

BackgroundUnstable weather, such as intra- and inter-day temperature variability, can impair the health and shorten the survival time of population around the world. Climate change will cause Earth's surface temperature rise, but has unclear effects on temperature variability, making it urgent to understand the characteristics of the burden of temperature variability on mortality, regionally and nationally. ObjectivesThis paper aims to quantify the mortality risk of exposure to short-term temperature variability, estimate the resulting death toll and explore how the strength of temperature variability effects will vary as a function of city-level characteristics. MethodsTen-year (2000–2009) time-series data on temperature and mortality were collected for five largest Australia's cities (Sydney, Melbourne, Brisbane, Perth and Adelaide), collectively registering 708,751 deaths in different climates. Short-term temperature variability was captured and represented as the hourly temperature standard deviation within two days. Three-stage analyses were used to assess the burden of temperature variability on mortality. First, we modelled temperature variability-mortality relation and estimated the relative risk of death for each city, using a time-series quasi-Poisson regression model. Second, we used meta-analysis to pool the city-specific estimates, and meta-regression to explore if some city-level factors will modify the population vulnerability to temperature variability. Finally, we calculated the city-specific deaths attributable to temperature variability, and applied such estimates to the whole of Australia as a reflection of the nation-wide death burden associated with temperature variability. ResultsWe found evidence of significant associations between temperature variability and mortality in all cities assessed. Deaths associated with each 1°C rise in temperature variability elevated by 0.28% (95% confidence interval (CI): 0.05%, 0.52%) in Melbourne to 1.00% (95%CI: 0.52%, 1.48%) in Brisbane, with a pooled estimate of 0.51% (95%CI: 0.33%, 0.69%) for Australia. Subtropical and temperate regions showed no apparent difference in temperature variability impacts. Meta-regression analyses indicated that the mortality risk could be influenced by city-specific factors: latitude, mean temperature, population density and the prevalence of several chronic diseases. Taking account of contributions from the entire time-series, temperature variability was estimated to account for 0.99% to 3.24% of deaths across cities, with a nation-wide attributable fraction of 1.67% (9.59 deaths per 100, 000 population per year). ConclusionsHourly temperature variability may be an important risk factor of weather-related deaths and led to a sizeable mortality burden. This study underscores the need for developing specific and effective interventions in Australia to lessen the health consequences of temperature variability.

Impact of short-term temperature variability on emergency hospital admissions for schizophrenia stratified by season of birth.

Diurnal temperature range (DTR) and temperature change between neighboring days (TCN) are important meteorological indicators closely associated with global climate change. However, up to date, there have been no studies addressing the impacts of both DTR and TCN on emergency hospital admissions for schizophrenia. We conducted a time-series analysis to assess the relationship between temperature variability and daily schizophrenia onset in Hefei, an inland city in southeast China. Daily meteorological data and emergency hospital admissions for schizophrenia from 2005 to 2014 in Hefei were collected. After stratifying by season of birth, Poisson generalized linear regression combined with distributed lag nonlinear model (DLNM) was used to examine the relationship between temperature variability and schizophrenia, adjusting for long-term trend and seasonality, mean temperature, and relative humidity. Our analysis revealed that extreme temperature variability may increase the risk for schizophrenia onset among patients born in spring, while no such association was found in patients born in summer and autumn. In patients born in spring, the relative risks of extremely high DTR comparing the 95th and 99th percentiles with the reference (50th, 10°C) at 3-day lag were 1.078 (95% confidence interval (CI) 1.025-1.135) and 1.159 (95% CI 1.050-1.279), respectively. For TCN effects, only comparing 99th percentile with reference (50th, 0.7°C) was significantly associated with emergency hospital admissions for schizophrenia (relative risk (RR) 1.111, 95% CI 1.002-1.231). This study suggested that exposure to extreme temperature variability in short-term may trigger later days of schizophrenia onset for patients born in spring, which may have important implications for developing intervention strategies to prevent large temperature variability exposure.

Functional diversity of catch mitigates negative effects of temperature variability on fisheries yields.

Temperature variation within a year can impact biological processes driving population abundances. The implications for the ecosystem services these populations provide, including food production from marine fisheries, are poorly understood. Whether and how temperature variability impacts fishery yields may depend on the number of harvested species and differences in their responses to varying temperatures. Drawing from previous theoretical and empirical studies, we predict that greater temperature variability within years will reduce yields, but harvesting a larger number of species, especially a more functionally diverse set, will decrease this impact. Using a global marine fisheries dataset, we find that within-year temperature variability reduces yields, but current levels of functional diversity (FD) of targeted species, measured using traits related to species' responses to temperature, largely offset this effect. Globally, high FD of catch could avoid annual losses in yield of 6.8% relative to projections if FD were degraded to the lowest level observed in the data. By contrast, species richness in the catch and in the ecosystem did not provide a similar mitigating effect. This work provides novel empirical evidence that short-term temperature variability can negatively impact the provisioning of ecosystem services, but that FD can buffer these negative impacts.

Long-term variability of temperature and precipitation in the Czech Lands: an attribution analysis

Among the key problems associated with the study of climate variability and its evolution are identification of the factors responsible for observed changes and quantification of their effects. Here, correlation and regression analysis are employed to detect the imprints of selected natural forcings (solar and volcanic activity) and anthropogenic influences (amounts of greenhouse gases—GHGs—and atmospheric aerosols), as well as prominent climatic oscillations (Southern Oscillation—SO, North Atlantic Oscillation—NAO, Atlantic Multidecadal Oscillation—AMO) in the Czech annual and monthly temperature and precipitation series for the 1866–2010 period. We show that the long-term evolution of Czech temperature change is dominated by the influence of an increasing concentration of anthropogenic GHGs (explaining most of the observed warming), combined with substantially lower, and generally statistically insignificant, contributions from the sulphate aerosols (mild cooling) and variations in solar activity (mild warming), but with no distinct imprint from major volcanic eruptions. A significant portion of the observed short-term temperature variability can be linked to the influence of NAO. The contributions from SO and AMO are substantially weaker in magnitude. Aside from NAO, no major influence from the explanatory variables was found in the precipitation series. Nonlinear forms of regression were used to test for nonlinear interactions between the predictors and temperature/precipitation; the nonlinearities disclosed were, however, very weak, or not detectable at all. In addition to the outcomes of the attribution analysis for the Czech series, results for European and global land temperatures are also shown and discussed.

Seasonality of foliar respiration in two dominant plant species from the Arctic tundra: response to long-term warming and short-term temperature variability

Direct measurements of foliar carbon exchange through the growing season in Arctic species are limited, despite the need for accurate estimates of photosynthesis and respiration to characterise carbon cycling in the tundra. We examined seasonal variation in foliar photosynthesis and respiration (measured at 20°C) in two field-grown tundra species, Betula nana L. and Eriophorum vaginatum L., under ambient and long-term warming (LTW) conditions (+5°C), and the relationship of these fluxes to intraseasonal temperature variability. Species and seasonal timing drove most of the variation in photosynthetic parameters (e.g. gross photosynthesis (Agross)), respiration in the dark (Rdark) and light (Rlight), and foliar nitrogen concentration. LTW did not consistently influence fluxes through the season but reduced respiration in both species. Alongside the flatter respiratory response to measurement temperature in LTW leaves, this provided evidence of thermal acclimation. The inhibition of respiration by light increased by ~40%, with Rlight : Rdark values of ~0.8 at leaf out decreasing to ~0.4 after 8 weeks. Though LTW had no effect on inhibition, the cross-taxa seasonal decline in Rlight : Rdark greatly reduced respiratory carbon loss. Values of Rlight : Agross decreased from ~0.3 in both species to ~0.15 (B. nana) and ~0.05 (E. vaginatum), driven by decreases in respiratory rates, as photosynthetic rates remained stable. The influence of short-term temperature variability did not exhibit predictive trends for leaf gas exchange at a common temperature. These results underscore the influence of temperature on foliar carbon cycling, and the importance of respiration in controlling seasonal carbon exchange.