Long-term Temporal Variability Research Articles

Variable structures in the stellar wind of the HMXB Vela X-1

Strong stellar winds are an important feature in wind-accreting high-mass X-ray binary (HMXB) systems. Exploring their structure provides valuable insights into stellar evolution and their influence on surrounding environments. However, the long-term evolution and temporal variability of these wind structures are not fully understood. This work probes the archetypal wind-accreting HMXB Vela X-1 using the Monitor of All-sky X-ray Image (MAXI) instrument to study the orbit-to-orbit absorption variability in the $2–10$ keV energy band across more than 14 years of observations. Additionally, the relationship between hardness ratio trends in different binary orbits and the spin state of the neutron star is investigated. We calculated X-ray hardness ratios to track absorption variability, comparing flux changes across various energy bands, as the effect of absorption on the flux is energy-dependent. We assessed variability by comparing the hardness ratio trends in our sample of binary orbits to the long-term averaged hardness ratio evolution derived from all available MAXI data. Consistent with prior research, the long-term averaged hardness ratio evolution shows a stable pattern. However, the examination of individual binary orbits reveals a different hardness ratio evolution between consecutive orbits with no evident periodicity within the observed time span. We find that fewer than half of the inspected binary orbits align with the long-term averaged hardness evolution. Moreover, neutron star spin-up episodes exhibit more harder-than-average hardness trends compared to spin-down episodes, although their distributions overlap considerably. The long-term averaged hardness ratio dispersion and evolution are consistent with absorption column densities reported in literature from short observations, indicating that a heterogeneous wind structure -- from accretion wakes to individual wind clumps -- likely drives these variations. The variability observed from orbit to orbit suggests that pointed X-ray observations provide limited insights into the overall behaviour of the wind structure. Furthermore, the link between the spin state of the neutron star and the variability in orbit-to-orbit hardness trends highlights the impact of accretion processes on absorption. This connection suggests varying accretion states influenced by fluctuations in stellar wind density.

Tree-ring maximum latewood density reveals unprecedented warming and long-term summer temperature in the upper Indus Basin, northern Pakistan

Understanding long-term temperature variability in the Upper Indus Basin (UIB), northern Pakistan, and its driving mechanisms is challenging due to the scarcity of long observational records and available literature. In this study, we reconstructed a 651-year (1370–2020 CE) warm-season (March–September) temperature record using the tree-ring maximum latewood density (MXD) of blue pine (Pinus wallichiana). The reconstruction explains 57 % of the variance in actual temperature during the common calibration period (1972–2020 CE). Our analysis identified ten high-temperature periods (temperature > 20.9 °C) and nineteen low-temperature periods (temperature < 19.8 °C), with the coldest years being 1392, 1707, 1817, and 1837, and the warmest years being 2013, 2016, 2017, and 2018. Spatial correlation analysis reveals a significant positive correlation with field temperature, predominantly in neighboring regions, and a significant negative correlation with relative humidity and precipitation. Multi-taper spectral analysis shows inter-annual (1.9, 2.5, 2.7, 5.5 years) and interdecadal (11, 18, 23, 25, 40, 71 years) cycles, suggesting a potential linkage with the Atlantic Multidecadal Oscillation (AMO). The negative linkage between our reconstruction and the region's standardized Palmer Drought Severity Index (scPDSI) indicates that continued temperature increase could result in severe drought in northern Pakistan in the near future. During the 20th century, the UIB experienced two distinct warming phases: 1948–1970 CE and 1994–2020 CE. The warming rate during 1994–2020 CE was 0.5 °C higher, indicating unprecedented recent warming. The reconstructed temperature record also demonstrates a large-scale spatiotemporal signal and a strong connection with most recorded volcanic eruptions. These findings enhance our understanding of long-term temperature variability in the region, highlighting the significance of MXD in reconstructing past temperature patterns.

Variation and Forecasting of Land Surface Temperature in Malaysia

Long-term variations in temperature and weather patterns provide evidence that the planet is experiencing global warming. The detrimental consequences of global warming on the ecosystem have affected people, plants, and animals. The rising Land Surface Temperature (LST) in a region has become a crucial indicator for determining specific climate change policies. Malaysia is divided into Peninsular Malaysia and Sabah Sarawak, located on Borneo Island, comprising four super-regions and 36 sub-regions. The distance between sub-regions, measured in latitudes and longitudes, is 150 pixels (equivalent to 95 kilometres), covering the entire country. This study uses data from NASA’s Terra satellites’ Moderate Resolution Imaging Spectroradiometers (MODIS) covering 2000–2022. Eight, four, and three knots were deployed on the cubic spline equation to analyse cyclical data, variation, and the LST forecast from 2022 to 2030. The global mean rise in LST variation per decade is 0.445°C, with a significance level of 5%, from a confidence interval of [0.377, 0.507]°C. The average predicted fluctuation in LST indicates a significant rise of 0.383°C per decade. Malaysia has not shown a significant decrease in LST acceleration at the 0.05 significance level, and a p-value of 0.06 suggests that LST variation is still increasing. Compared to the Sabah Sarawak group, which experiences LST deceleration, most Peninsular Malaysia group experiences LST acceleration.

Rainfall And Drought Characteristics For Crop Planning In Cuttack District Of Odishastate, India

The increasing frequency of agricultural droughts and variability in rainfall patterns over the past three decades prompted this study, which analyzed 34 years of block-wise daily rainfall data (1988-2021) from Cuttack district, Odisha. The aim was to determine the long-term average and temporal variability of rainfall on weekly, monthly, seasonal, and annual scales, with a focus on identifying strategies to mitigate production risks in the region. The average annual rainfall in Cuttack was 1597.6 mm, with August receiving the highest amount of rainfall (476 mm), followed by July (407 mm) during the monsoon season. A trend analysis on rainfall over the past 34 years showed an increasing pattern of an average 6.03 mm and 3.6 mm per year in annual and kharif season rainfall, respectively. Agricultural droughts were frequently observed during the early (22-28 Standard Meteorological Week) and late (36-42 SMW) stages of kharif crops. The study also revealed that the station is prone to mild-moderate meteorological droughts of different intensities, including mild,moderate, and severe. To minimize production risks, short duration, low water-requiring, high-value crops such as maize, pulses, oilseeds, and some vegetables are recommended for this region.

Empirical evidence for multi-decadal transients affecting geodetic velocity fields and derived seismicity forecasts in Italy

This study critically examines the use of geodetic strain rates for forecasting long-term earthquake rates in a slow-deforming region such as Italy, challenging the prevailing assumption of their temporal stationarity in interseismic stages for seismic hazard analyses. Typically, earthquake-rate models derived from geodesy assume stationary interseismic loading rates, with stress rates in the upper crust proportional to geodetic strain rates, leading to earthquake rates directly proportional to these strain rate tensors. However, our analysis unveils a pronounced correlation between the epicenters of earthquakes that occurred in the past 60–120 years and areas forecasted for higher future earthquake rates based on geodetic strain rates. This correlation appears weak and scattered in analyses of even older earthquakes. To corroborate our findings, we select the 2009 L’Aquila earthquake (mw = 6.3) to prove that its apparently marginal viscoelastic relaxation significantly alters the time series of adjacent benchmarks for the following ~ 30–60 years, explaining the high correlation between recent earthquakes and strain rate peaks. Our findings require a methodological shift in interpreting geodetic data for earthquake forecasting, emphasizing the two-component (plate-tectonics-driven stationary long-term deformation, and decadal transient viscoelastic relaxation after an earthquake) nature of crustal stress accumulation recorded in geodetic data. We underscore the potential of geodesy-derived forecasts to provide deeper insights into seismic hazards, stressing the importance of acknowledging the long-term temporal variability inherent in geodetic measurements.

Early-life famine exposure may modify the association between long-term temperature variability and cardio-cerebrovascular diseases: a nationwide study

Abstract Background We aimed to evaluate whether the association between long-term temperature variability (TV) and CCVDs was affected by famine exposure in different age stages. &amp;#xD;Methods We used data from the fourth national Urban and Rural Elderly Population survey (2015). Participants were categorized into six groups based on their age at famine exposure (famine exposure under age 5, between ages 5 and 18, and during adulthood) and the severity (severely affected areas versus mildly affected areas) of the Great Chinese Famine (1959-1961) in their province of residence. Mixed-effects logistic regression model was used to quantify the association between long-term TV and the prevalence of CCVDs across six famine-exposed groups.&amp;#xD;Findings A total of 222,179 participants were included. In severely affected areas, the odds ratio (OR) of CCVDs associated with per 1°C increase in 5-year average TV were 1.07 (95% confidence interval [CI]: 1.02, 1.13) for those exposed to famine during adulthood, 1.28 (95% CI: 1.17, 1.40) under the age of 5 years. Urban residence, higher education, increased household income, and more frequent physical activity could mitigate the association between TV and CCVDs, particularly among those exposed to severe famine before the age of 5.&amp;#xD;Conclusion Individuals exposed to famine before the age of 5 are more susceptible to TV-related CCVDs compared to those exposed during adulthood. Our findings highlight the importance of early-life nutrition in lowering susceptibility to CCVDs later in life.

Impact of long-term temperature shifts on activated sludge microbiome dynamics and micropollutant removal

Micropollutants removal efficiency strongly vary across different aerobic wastewater treatment plants, resulting in their frequent detection in surface and ground waters. Seasonal temperature variation is a major factor influencing plant performance, but it is still unclear how prolonged periods of temperature change impact microbiome and micropollutant biotransformation. This work investigates the effect of long-term temperature variation on the microbial dynamics in an activated sludge system, and the impact on micropollutant biotransformation. Sequencing batch reactors were used as model system and 4–40 °C temperature range was studied. 16S rRNA amplicon sequencing showed that temperature drives microbial structure (gDNA) and activity (RNA), rather than time, and this was stronger below 15 °C and above 25 °C. The microbial community was richest and more diverse at 20 °C, while rarer and more specific taxa became predominant over time, at more extreme temperatures. This suggested that less abundant taxa might be responsible for maintaining the biotransformation capability in the activated sludge at extreme temperatures. Micropollutant biotransformation rates mostly deviated from the classic Arrhenius model below 15 °C and above 25 °C, indicating that prolonged exposure to temperature changes leads to temperature-induced taxonomic shifts, resulting in the emerging of different sets of biotransformation pathways over different temperature ranges.

Assessing the durability performance of high belite cement incorporating fly ash under long-term temperature variations

The widespread use of ordinary Portland cement (OPC), which has a significant carbon footprint, greatly contributes to the climate crisis. High belite cement (HBC) is renowned for its low-carbon characteristics, resulting in an evident reduction in both energy consumption and CO2 emissions. Fly ash (FA), an industrial solid waste material, is commonly employed in the construction of mass concrete structures. This combination facilitates the adoption of cleaner and more ecologically sustainable construction manufacturing processes. The durability of structures constructed from HBC and FA has not been fully demonstrated due to their exposure to constantly changing atmospheric conditions. In order to unravel this issue, a comparative investigation was carried out through laboratory acceleration testing, aiming to evaluate the macro- and micro-mechanical properties, chemical compositions, and micro-morphology of HBC and OPC with FA under a rapid temperature changing cycle (RTC) within 5–45°C. The findings reveal the mechanism of deterioration under RTC, including the phase transformation of C–S–H, the propagation of micro-cracks, the coarsening of the pore structure, and the loss of toughness. FA alleviates the reduction in toughness, but also undermines the mechanical properties. Additionally, it was noted to undergo pozzolanic reaction, residual hydration and carbonation during RTC. Regarding OPC, the inclusion of FA within a specific dosage range (0–30%) has a beneficial impact on compressive strength. However, as for HBC, the presence of FA entirely exhibits a detrimental effect on service performance.

April–September minimum temperature reconstruction based on Sabina tibetica ring-width chronology in the central eastern Tibetan Plateau, China

Minimum temperatures have remarkable impacts on tree growth at high-elevation sites on the Tibetan Plateau, but the shortage of long-term and high-resolution paleoclimate records inhibits understanding of recent minimum temperature anomalies. In this study, a warm season (April–September) reconstruction is presented for the past 467 years (1550–2016) based on Sabina tibetica ring-width chronology on the Lianbaoyeze Mountain of the central eastern Tibetan Plateau. Eight warm periods and eight cold periods were identified. Long-term minimum temperature variations revealed a high degree of coherence with nearby reconstructions. Spatial correlations between our reconstruction and global sea surface temperatures suggest that warm season minimum temperature anomalies in the central eastern Tibetan Plateau were strongly influenced by large-scale ocean atmospheric circulations, such as the El Niño-Southern Oscillation and the Atlantic Multidecadal Oscillation.

Long-term temperature variability and death among stroke patients: A cohort study in central Shandong province, China

Our current understanding of the repercussions stemming from long-term temperature variability (TV) within the broader context of global climate change remains considerably limited. This study aims to investigate the influence of long-term temperature variability on the probability of death and mortality among stroke patients. For this study, a sample of stroke patients aged 40 years and above between 2016 and 2019 was taken from five districts/counties in central Shandong Province. We calculated the standard deviation (SD) of the annual mean daily temperature and the annual mean diurnal temperature range (DTR) obtained from the baseline survey to express the long-term TV. To assess the link between TV exposure and mortality among stroke patients, we utilized the Cox proportional hazards regression method. This statistical method allowed us to estimate the adjusted hazard ratio (HR) and 95 % confidence interval (CI) with regard to the risk of mortality. For stroke patients, there was a correlation between a 1 °C rise in the SD of temperature and an elevated risk of mortality (HR: 1.18, 95 % CI: 1.08–1.29). Additionally, each 1 °C increase in the DTR was associated with a further increase in the risk of death (HR: 1.69, 95 % CI: 1.59–1.79). In patients diagnosed with ischemic and hemorrhagic stroke, DTR was found to be positively associated with the risk of death. Temperature SD was found to be positively associated with the risk of death only in patients with ischemic stroke. Persistent exposure to TV was strongly linked to mortality risk among individuals with stroke. By devoting increased attention to TV, these organizations can develop strategies to mitigate its adverse effects on public health.

Spatiotemporal analysis of seasonal trends in land surface temperature within the distribution range of Moringa peregrina (Forssk.) in Southern and Southeastern Iran.

Temperature fluctuations and related factors are among the main causes of climate change. Understanding the temporal and spatial variations in temperature can shed light on how species respond to climate change. Plants generally persist in suitable microclimates in response to environmental change; however, examining long-term temperature variations within a species' range can be challenging using field observations. Thermal remote sensing, on the other hand, provides multi-scale time-series data with good coverage and regularity to overcome the challenges associated with field observations in environmental monitoring. Although changes in land surface temperature (LST) affect climate, hydrological processes, land-atmosphere interactions, and ecological activities, this metric has not received much research attention. This study aimed to analyze changes in habitat suitability and microclimatic conditions for Moringa peregrina. Seasonal changes in LST within the distribution range of the species were also investigated. To this aim, mean seasonal LST was computed in Google Earth Engine using the daily MODIS/006/MYD13A2 product from 2003 to 2023. Subsequently, a binary habitat suitability map was created based on the true skill statistic (TSS). The Mann-Kendall test was used to analyze seasonal LST trends. Major trends in LST were quantified based on the z-score, and compatibility with habitat suitability was evaluated via GAP analysis and the Kappa index. Seasonal temperature trends were evaluated by comparing each season with the following season using binary comparison. Landforms at presence points were regarded as microclimates and the sensitivity of microclimates to LST was evaluated using two methods: Principal component analysis (PCA) was used to quantify seasonal LST heterogeneity and the random forest (RF) approach was used to evaluate the effect of environmental parameters on habitat suitability within microclimates. The Kappa index revealed a weak overlapping between suitable / unsuitable habitat and the surfaces affected by the trend of changes. Moreover, the suitable habitat of Moringa peregrina in spring, autumn and winter is spatially overlapped by areas that have shown an increasing LST trend, and the presence points have not experienced an increasing temperature trend only in the summer. The findings show that the analysis of seasonal trends in LST provides insights into the effect of LST on habitat suitability and the condition of vegetation. The current study clearly shows that seasonal changes have had a significant impact on the distribution and habitat suitability of M. peregrina, particularly during summer and winter. Improved habitat suitability and range expansion were observed throughout the year. The study also highlights the role of landforms in regulating temperature. Landforms such as local ridges with minimal temperature fluctuations and regions near the Oman Sea were identified as potential future habitats due to favorable humidity conditions.

Extreme value analysis of precipitation and temperature over Jammu &amp; Kashmir and Ladakh in western Himalaya, India

Climate change has become a major issue for the world today. Small changes in the climate in the Himalayan region can have a significant impact on the delicate ecosystem, which is very sensitive to such changes. Recent investigations into climate change in the Western Himalayas have provided compelling evidence that these regions are especially susceptible to a wide variety of catastrophic occurrences. In the current scenario, the threat posed by climate change to human existence in Jammu and Kashmir (J&amp;K), as well as the region of Ladakh, has grown more tangible and evident. Temperature and precipitation statistics could be used to observe this regional climatic shift. This study analyses and forecasts long-term spatio-temporal variations in precipitation and temperature using a century-long dataset from 1901 to 2002 over 14 districts of Jammu and Kashmir and Ladakh. The Augmented Dickey-Fuller (ADF) test and the Kwiatkowski-Phillips-Schmidt-Shin (KPSS) test of stationarity on the data show that the time series is stationary. Extreme Value Theory (EVT), which is an outstanding statistical method to interpret the records for the estimation of the future probability of the occurrence of extremes, is utilised in this study. Further, precipitation and temperature extremes are forecasted for 50, 80, 100, 120, 200, 250, 300, and 500 year return periods respectively and results reveal that the districts- Jammu, Rajouri, Leh, Srinagar, Baramulla and Poonch will be more prone to extreme weather events phenomenon.

Diurnal temperature range as a key predictor of plants’ elevation ranges globally

A prominent hypothesis in ecology is that larger species ranges are found in more variable climates because species develop broader environmental tolerances, predicting a positive range size-temperature variability relationship. However, this overlooks the extreme temperatures that variable climates impose on species, with upper or lower thermal limits more likely to be exceeded. Accordingly, we propose the ‘temperature range squeeze’ hypothesis, predicting a negative range size-temperature variability relationship. We test these contrasting predictions by relating 88,000 elevation range sizes of vascular plants in 44 mountains to short- and long-term temperature variation. Consistent with our hypothesis, we find that species’ range size is negatively correlated with diurnal temperature range. Accurate predictions of short-term temperature variation will become increasingly important for extinction risk assessment in the future.

Thermal structure of two deep boreholes in the Siljan Ring, Central Sweden, and palaeoclimatic implications

Heat-flow data from deep boreholes are of particular value as a number of factors, including climatic surface temperature variations, may disturb subsurface thermal conditions, especially at shallow depths. This study provides thermal results from two boreholes, Gravberg-1 and Stenberg-1, drilled to large depths in the Siljan Ring impact structure, Baltic Shield, Central Sweden. Taking several high-resolution temperature logs to a depth of more than 5000 m in Gravberg-1 and close to 2000 m in Stenberg-1, and up to a long time after drilling, ensures high-quality deep temperature data. A good-quality thermal conductivity profile was determined from mineralogical composition and radiogenic heat production from a spectral gamma-ray log. The observations show overall thermal conductive profiles with local non-conductive temperature variations. Observed present-day near-surface heat flow (depth range 200–500 m) in Gravberg-1 is 47 mW/m2 (std. dev. 1.5 mW/m2). From observed deep background heat flow, considering heat production, the equivalent steady-state, unperturbed heat flow is estimated at 66–68 mW/m2. Data from Stenberg-1 provide similar results. The observed reduction of heat flow at near-surface level by about 20 mW/m2 is interpreted as originating from long-term palaeoclimatic temperature variations. During the last glacial period, the area was, to varying degree, both ice-free and covered by the Fennoscandian ice sheet. Thermal modelling, with a ground-surface mean-temperature increase by 12±2 °C from glacial to post-glacial time, shows consistency between observed and modelled heat flow perturbations for the full depth range of observations. Heat flow perturbations may be significant to depths of about 2000 m. These results show that, uncorrected for palaeoclimate, depending on depths of measurements, observed continental heat flow values might be markedly underestimated. This applies to Northern Europe and, likely, to many other areas as well.

Exploring temperature dynamics in Madhya Pradesh: a spatial-temporal analysis.

Understanding the dynamics of temperature trends is vital for assessing the impacts of climate change on a regional scale. In this context, the present study focuses on Madhya Pradesh state in Central Indian region to explore the spatial-temporal distribution patterns of temperature changes from 1951 to 2021. Gridded temperature data obtained from the Indian Meteorological Department (IMD) in 1° × 1° across the state are utilised to analyse long-term trends and variations in temperature. The Mann-Kendall (MK) test and Sen's slope (SS) estimator were used to detect the trends, and Pettitt's test was utilised for change point detection. The analysis reveals significant warming trends in Madhya Pradesh during the study period during specific time frames. The temperature variables, such as the annual mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin), consistently increase, with the most pronounced warming observed during winter. The trend analysis reveals that the rate of warming has increased in the past few years, particularly since the 1990s. However, Pettitt's test points out significant changes in the temperature, with Tmean rising from 25.46 °C in 1951-2004 to 25.78 °C in 2005-2021 (+0.33 °C), Tmax shifting from 45.77 °C in 1951-2010 to 46.24 °C in 2011-2021 (+0.47°C), and Tmin increasing from 2.65 °C in 1951-1999 to 3.19 °C in 2000-2021 (+0.46 °C). These results, along with spatial-temporal distribution maps, shed important light on the alterations and variations in monthly Tmean, Tmax, and Tmin across the area, underlining the dynamic character of climate change and highlighting the demand for methods for adaptation and mitigation.

The incidence of asthma attributable to temperature variability: An ecological study based on 1990–2019 GBD data

BackgroundAsthma, the second leading cause of death from chronic respiratory diseases, is associated with climate change, especially temperature changes. It is currently unclear about the relationship between long-term temperature variability and the incidence of asthma on a global scale. MethodsWe used asthma incidence, demographic and socioeconomic data from the Global Burden of Disease (GBD) Results Database, and environmental and geographical statistics from TerraClimate between 1990 and 2019 to determine the association between maximum temperature variability and asthma incidence. We also predicted the incidence of heat-related asthma in the future (2020−2100) under four shared socioeconomic pathways (SSPs: 126, 245, 370, and 585). ResultsBetween 1990 and 2019, the global median incidence of asthma was 402.0 per 100,000 with a higher incidence (median: 1380.3 per 100,000) in children under 10 years old. We found that every 1 °C increase in maximum temperature variability increased the risk of asthma globally by 5.0 %, and the effect was robust for individuals living in high-latitude areas or aged from 50 to 70 years. By 2100, the average incidence of asthma is estimated to be reduced by 95.55 %, 79.32 %, and 40.02 % under the SSP126, SSP245, and SSP370 scenarios, respectively, compared to the SSP585 at latitudes >60°. ConclusionOur study provides evidence that maximum temperature variability is associated with asthma incidence. These findings suggest that implementing stricter mitigation and adaptation strategies may be importment in reducing asthma cases caused by climate change.

Conodont size in time and space: Beyond the temperature-size rule

The temperature-size rule (TSR) states that ectotherms mature at smaller adult body size in warmer conditions. Such a rule may have the potential to explain size response of fossil organisms to past temperature variations, but its validity in deep time has been seldom tested. The generality of this rule was investigated here by compiling data documenting the size record of three conodont genera (Palmatolepis, Ancyrodella and Polygnathus) at different spatial and temporal scales during the Late Frasnian and the Famennian, characterized by short- and long-term temperature variations. Statistical models were used to investigate the relationship between conodont size and oxygen isotope values, considered as paleotemperature proxies. Comparison of evolutionary models further allowed to test alternative modes of size variation such as stasis or punctuation.The TSR was not validated as a general rule explaining size variation in these fossil records, being only observed as a large-scale geographic trend during a time-slice. The only strong support for temperature being the driver of temporal variations was found regarding the size of Palmatolepis during the Kellwasser period, but the relationship was reverse to the expectation of the TSR. The absence of general TSR pattern is probably due to the interference of many other factors (demography and mortality patterns, temperature tolerance, size reduction due to stress) whose relative importance may depend on the time interval and the genus considered. Rather than a correlation with environmental proxies, evolutionary models suggested the occurrence of a synchronous shift in Palmatolepis size around 369 Ma (Palmatolepis termini conodont Zone) in several outcrops, raising questions about the environmental forcing beyond this shift. Departures from the expected TSR may thus provide relevant insights into the complex interplay of physical, tectonic and eco-evolutionary processes impacting size evolution in deep time.

Climatology of the Mount Brown South ice core site in East Antarctica: implications for the interpretation of a water isotope record

Abstract. Water stable isotope records from ice cores (δ18O and δD) are a critical tool for constraining long-term temperature variability at high latitudes. However, precipitation in Antarctica consists of semi-continuous small events and intermittent extreme events. In regions of high accumulation, this can bias ice core records towards recording the synoptic climate conditions present during extreme precipitation events. In this study we utilise a combination of ice core data, reanalysis products, and models to understand how precipitation intermittency impacts the temperature records preserved in an ice core from Mount Brown South in East Antarctica. Extreme precipitation events represent only the largest 10 % of all precipitation events, but they account for 52 % of the total annual snowfall at this site, leading to an overrepresentation of these events in the ice core record. Extreme precipitation events are associated with high-pressure systems in the mid-latitudes that cause increased transport of warm and moist air from the southern Indian Ocean to the ice core site. Warm temperatures associated with these events result in a +4.8 ∘C warm bias in the mean annual temperature when weighted by daily precipitation, and water isotopes in the Mount Brown South ice core are shown to be significantly correlated with local temperature when this precipitation-induced temperature bias is included. The Mount Brown South water isotope record spans more than 1000 years and will provide a valuable regional reconstruction of long-term temperature and hydroclimate variability in the data-sparse southern Indian Ocean region.

Interannual climate variability improves niche estimates for ectothermic but not endothermic species

Climate is an important limiting factor of species’ niches and it is therefore regularly included in ecological applications such as species distribution models (SDMs). Climate predictors are often used in the form of long-term mean values, yet many species experience wide climatic variation over their lifespan and within their geographical range which is unlikely captured by long-term means. Further, depending on their physiology, distinct groups of species cope with climate variability differently. Ectothermic species, which are directly dependent on the thermal environment are expected to show a different response to temporal or spatial variability in temperature than endothermic groups that can decouple their internal temperature from that of their surroundings. Here, we explore the degree to which spatial variability and long-term temporal variability in temperature and precipitation change niche estimates for ectothermic (730 amphibian, 1276 reptile), and endothermic (1961 mammal) species globally. We use three different species distribution modelling (SDM) algorithms to quantify the effect of spatial and temporal climate variability, based on global range maps of all species and climate data from 1979 to 2013. All SDMs were cross-validated and accessed for their performance using the Area under the Curve (AUC) and the True Skill Statistic (TSS). The mean performance of SDMs using only climatic means as predictors was TSS = 0.71 and AUC = 0.90. The inclusion of spatial variability offers a significant gain in SDM performance (mean TSS = 0.74, mean AUC = 0.92), as does the inclusion of temporal variability (mean TSS = 0.80, mean AUC = 0.94). Including both spatial and temporal variability in SDMs shows the highest scores in AUC and TSS. Accounting for temporal rather than spatial variability in climate improved the SDM prediction especially in ectotherm groups such as amphibians and reptiles, while for endothermic mammals no such improvement was observed. These results indicate that including long term climate interannual climate variability into niche estimations matters most for ectothermic species that cannot decouple their physiology from the surrounding environment as endothermic species can.

Air Temperature Variability of the Northern Mountains in the Czech Republic

Analysis of a long-term temperature variability of mountains has been neglected for a long time. Here we homogenised and reconstructed four temperature series (1961–2020) of selected mountain stations situated above 1000 m representing the area of northern Moravian mountain ridges (the Czech Republic) and their spatiotemporal variability was examined. A statistically significant increase of 10-year linear trends of annual (0.26–0.38), summer/winter half-year and seasonal mean temperatures were found at most stations. Summer (JJA) was detected as the season with the highest mean temperature increase between 1961–1990 and 1991–2020 normal periods (1.5 °C). From the spatial point of view, the climate conditions were becoming warmer faster in higher elevations compared to the lower ones. At all stations, a statistically significant decrease in ice and frost days was observed (−9.1–19.9 and −9.5–16.3, respectively). Moreover, it was proved that the temperature series of a newly established Vysoká hole station are representative enough and comparable with measurements of other meteorological stations in the studied region. This research provided valuable insight into the temperature variability of mountain ridges and the results completed our sparse knowledge about temperature changes in the mountain regions in Central Europe.