Monthly Maximum Temperature Research Articles

Comparative analysis of temperature and precipitation changes in the city of Shumen for the periods 1971-1980 and 2013-2023

Abstract The main climatic elements and meteorological phenomena in the area of the meteorological observatory in the city of Shumen were studied for the periods 1971-1980 and 2013-2023. A detailed analysis of changes in temperatures and precipitation has been carried out, revealing the trends in their changes. Significant differences in temperature were found between the warm and cold part of the year. For the period 1971-1980, the average January temperatures are from -3.0°C to +2.5°C, and the average June temperatures from +18.4°C to +21.3°C, while for the period 2013-2023 they are, respectively, the average January temperatures from –2.8°C to +5.7°C, and the average June temperatures from +19.1°C to +22.3°C. Temperature analysis reveals warmer months of January and June for the period 2013-2023. The average annual temperature for the period 1971-1980 is +10.73°C., while for the period 2013-2023 it is +12.48°C, i.e. for the second period an increase of 1.75°C is reported. The average maximum monthly temperatures for the city of Shumen for the period 1971-1980 in the summer range from +17.6 to +21.8°C, while for the period 2013-2023 they are from +19.1 to +24.6°C., i.e. for the second period, an increase of about 2°C is reported. The same trend is observed for the average annual temperature amplitudes, which in the period 1971-1980 were from 20°C to 24.4°C, while for the period 2013-2023. are from 19.9°C to 25.8°C. The average annual precipitation for both periods is approximately the same (1971-1980 - 608.64 mm; 2013-2023 - 648.89 mm), but by year in the period 2013-2023 there are very large differences - from 418.4 mm (2019) to 1185.4 mm (2014). Four years of the 2013-2023 period: 2019, 2020, 2022, and 2023 can clearly be identified as years of significant drought. The complex analysis of the climate of the city of Shumen allowed in the final part of the study to draw conclusions about the prevailing types and classes of weather.

Urbanization effects on temperature: 1826–1850

Mean, minimum and maximum monthly temperatures for 58 stations in New York State covering the period 1826–1850 are used to estimate a random effects panel regression. Controlling for latitude, elevation and seasonality, a statistically significant positive effect of population on minimum temperature is detected. At the mean population of 8500, the estimated effect is 0.19 °F (0.105 °C), which is consistent with published estimates for later periods. Mean and maximum temperature effects are +0.06 °F (+0.033 °C) and − 0.05 °F (−0.027 °C), respectively, but are not statistically significant. Microclimate and other unmeasured weather station heterogeneity is captured as a random ‘effects’ distribution variable, a novel treatment. Heat island effects appear to exist at very low levels of population when energy was based on animals and water power, perhaps due to loss of greenspace. Based on these results urbanization could contribute as much as 27.5 % to 41 % of the centennial temperature rise in New York.

The effects of ambient temperature on non-accidental mortality in the elderly hypertensive subjects, a cohort-based study

BackgroundThe association between ambient temperature and mortality has yielded inconclusive results with previous studies relying on in-patient data to assess the health effects of temperature. Therefore, we aimed to estimate the effect of ambient temperature on non-accidental mortality among elderly hypertensive patients through a prospective cohort study conducted in northeastern China.MethodsA total of 9634 elderly hypertensive patients from the Kailuan research who participated in the baseline survey and follow-up from January 1, 2006 to December 31, 2017, were included in the study. We employed a Poisson generalized linear regression model to estimate the effects of monthly ambient temperature and temperature variations on non-accidental mortality.ResultsAfter adjusting for meteorological parameters, the monthly mean temperature (RR = 0.989, 95% CI: 0.984–0.993, p < 0.001), minimum temperature (RR = 0.987, 95% CI: 0.983–0.992, p < 0.001) and maximum temperature (RR = 0.989, 95% CI: 0.985–0.994, p < 0.001) exhibited a negative association with an increased risk of non-accidental mortality. The presence of higher monthly temperature variation was significantly associated with an elevated risk of mortality (RR = 1.097, 95% CI:1.051–1.146, p < 0.001). Further stratified analysis revealed that these associations were more pronounced during colder months as well as among male and older individuals.ConclusionsDecreased temperature and greater variations in ambient temperature were observed to be linked with non-accidental mortality among elderly hypertensive patients, particularly notable within aging populations and males. These understanding regarding the effects of ambient temperature on mortality holds clinical significance for appropriate treatment strategies targeting these individuals while also serving as an indicator for heightened risk of death.

Human activity drives establishment, but not invasion, of non‐native plants on islands

Island ecosystems are particularly susceptible to the impacts of invasive species. Many rare and endangered species that are endemic to islands are negatively affected by invasions. Past studies have shown that the establishment of non‐native species on islands is related to native plant richness, habitat heterogeneity, island age, human activity, and climate. However, it is unclear whether the factors promoting establishment (i.e. the formation of self‐sustaining populations) also promote subsequent invasion (i.e. spread and negative impacts). Using data from 4308 non‐native plant species across 46 islands and archipelagos globally, we examined which biogeographic characteristics influence established and invasive plant richness using generalized linear models nested within piecewise structural equation models. Our results indicate that anthropogenic land use (i.e. human modification) is strongly associated with establishment but not invasion, that climate (maximum monthly temperature) is strongly associated with invasion but not establishment, and that habitat heterogeneity (represented by maximum elevation and island area) is strongly associated with both establishment and invasion. Island isolation explains native plant richness well, but is not associated with established and invasive plant richness, likely due to anthropogenic introductions. We conclude that anthropogenic land use on islands is likely to be a proxy for the number of introductions (i.e. propagule pressure), which is more important for establishment than invasion. Conversely, islands with more diverse habitats and favorable (warm) climate conditions are likely to contain more available niche space (i.e. ‘vacant niches') which create opportunities for both establishment and invasion. By evaluating multiple stages of the invasion process, we differentiate between the biogeographic characteristics that influence plant establishment (which does not necessarily lead to ecological impacts) versus those that influence subsequent plant invasion (which does lead to negative impacts).

Effect of climate on emergency department admissions for renal colic: a comparative analysis of sedentary and non-sedentary lifestyles.

To investigate the impact of climate and seasonal variations on emergency department (ED) admissions for renal colic, while specifically comparing the differences between individuals with sedentary and non-sedentary lifestyles. A retrospective, single center study was conducted. Between the years 2017- 2020, medical records of patients admitted to the ED with renal colic, found to harbor ureteric stones on CT scans, were examined. Data on patients' occupational activities was collected through telephone questionnaires. Patients were categorized into two groups: sedentary and active. Precise weather data was obtained from the Israeli Meteorological Service website. The monthly average daily maximum temperatures were calculated. In the final sample of 560 participants, 285 were in the sedentary group, and 275 were in the active group. The study population consisted of 78.1% males and 21.9% females, with consistent gender ratios in both occupational groups. Prevalence of uric acid stones was higher in the sedentary group (p < 0.05). While there was a slight increase in admissions during the summer, seasonal distribution did not significantly differ among occupational groups. The study found no significant differences in admissions across different temperature ranges. Both groups exhibited a pattern of increased referrals during the summer and reduced referrals in the colder winter months. The baseline data revealed notable differences between the sedentary and active groups, particularly in the prevalence of uric acid stones. Climate factors, including temperature and seasonal variations, had limited impact on ED admissions for renal colic in patients with kidney stones, irrespective of their sedentary or active lifestyles. Both groups exhibited similar admission patterns, with a higher rate of admissions during the summer and a lower rate of admissions during the winter.

Analysis of a Plant’s Response to Climate Change Factors Through the Use of Herbarium Records: Collinsia violacea Nutt. (Plantaginaceae).

Climate change has resulted in various changes to the phenology of species, and some of these changes have been documented through the use of herbarium specimens. Understanding how plants react to changes in the environment can give scientists insight into how plants have been responding and will respond to the continuing consequences of climate change as well as how to approach biodiversity conservation. In this study, herbarium records of Collinsia violacea Nutt. ranging from 1895 to 2014 were utilized to show the trends of the first and peak flowering dates with regard to various geographic and climatic variables using regression analysis. The results from simple linear regression analyses showed a trend of the flowering times for first and peak flowering dates occurring earlier over the years; however, the relationship was not significant. The multiple linear regression full model for first flowering indicated increases in latitude, longitude, and mean monthly temperatures were associated with delayed flowering while increases in monthly minimum and maximum temperatures were associated with earlier flowering. The full model for peak flowering showed that peak flowering was delayed with increases in latitude, longitude, and maximum monthly temperature. The reduced models, with highly correlated variables removed, indicated significant delays in first flowering and peak flowering with increases in latitude, longitude, and mean monthly temperature, but no significant relationship between monthly precipitation and flowering time. Further research is needed to fully understand the implications of these changes.

The impact of meteorological parameters on the scrub typhus incidence in Baoshan City, western Yunnan, China.

Scrub typhus has become widespread across various regions in China in recent decades, causing a considerable burden on residents. While meteorological variables significantly impact the spread of scrub typhus, there is insufficient quantitative evidence illustrating this association in known high-endemic areas. A distributed lag non-linear model was applied to explore the relationship between meteorological parameters and scrub typhus incidence from 2010 to 2019 in Baoshan City, western Yunnan Province, China. High monthly mean (20°C) and maximum (30°C) temperatures were associated with a peak risk of scrub typhus in the current month. Higher minimum temperatures and higher relative humidity were followed by increasing cumulative risks over the ensuing 3 months. Higher precipitation was followed by increasing cumulative risk over the ensuing 2-month period, peaking at around 30 cm. The non-linear lag associations between meteorological parameters and scrub typhus incidence suggest that higher monthly minimum temperature and relative humidity could be associated with an increased risk of scrub typhus in the subsequent several months, while warm temperature is more likely to impact the occurrence of scrub typhus in the current month.

ClimateDT: A Global Scale-Free Dynamic Downscaling Portal for Historic and Future Climate Data

Statistical downscaling of climate data has been widely described in the literature, with the aim of improving the reliability of local climatic parameters from coarse-resolution (often &gt;20 km) global datasets. In this article, we present ClimateDT, a dynamic downscaling web tool for monthly historical and future time series at a global scale. The core of ClimateDT is the 1 km 1981–2010 climatology from CHELSA Climate (version 2.1), where the CRU-TS layers for the period 1901-current are overlayed to generate a historic time series. ClimateDT also provides future scenarios from CMIP5 using UKCP18 projections (rcp2.6 and rcp8.5) and CMIP6 using 5 GCMs, also available on the CHELSA website. The system can downscale the grids using a dynamic approach (scale-free) by computing a local environmental lapse rate for each location as an adjustment for spatial interpolation. Local predictions of temperature and precipitation obtained by ClimateDT were compared with climate time series assembled from 12,000 meteorological stations, and the Mean Absolute Error (MAE) and the explained variance (R2) were used as indicators of performance. The average MAEs for monthly values on the whole temporal scale (1901–2022) were around 1.26 °C for the maximum monthly temperature, 0.80 °C for the average monthly temperature, and 1.32 °C for the minimum monthly temperature. Regarding monthly total precipitation, the average MAE was 19 mm. As for the proportion of variance explained, average R2 values were always greater than 0.95 for temperatures and around 0.70 for precipitation due to the different degrees of temporal autocorrelation of precipitation data across time and space, which makes the estimation more complex. The elevation adjustment resulted in very accurate estimates in mountainous regions and areas with complex topography and substantially improved the local climatic parameter estimations in the downscaling process. Since its first release in November 2022, more than 1300 submissions have been processed. It takes less than 2 min to calculate 45 locations and around 8 min for the full dataset (512 records).

The new record of drought and warmth in the Amazon in 2023 related to regional and global climatic features

In 2023 Amazonia experienced both historical drought and warm conditions. On October 26th 2023 the water levels at the port of Manaus reached its lowest record since 1902 (12.70 m). In this region, October monthly maximum and minimum temperature anomalies also surpassed previous record values registered in 2015 (+ 3 °C above the normal considering the 1981–2020 average). Here we show that this historical dry and warm situation in Amazonia is associated with two main atmospheric mechanisms: (i) the November 2022–February 2023 southern anomaly of vertical integrated moisture flux (VIMF), related to VIMF divergence and extreme rainfall deficit over southwestern Amazonia, and (ii) the June–August 2023 downward motion over northern Amazonia related to extreme rainfall deficit and warm conditions over this region. Anomalies of both atmospheric mechanisms reached record values during this event. The first mechanism is significantly correlated to negative sea surface temperature (SST) anomalies in the equatorial Pacific (November–February La Niña events). The second mechanism is significantly correlated to positive SST anomalies in the equatorial Pacific, related to the impacts of June–September El Niño on the Walker Circulation. While previous extreme droughts were linked to El Niño (warmer North Tropical Atlantic SST) during the austral summer (winter and spring), the transition from La Niña 2022–23 to El Niño 2023 appears to be a key climatic driver in this record-breaking dry and warm situation, combined to a widespread anomalous warming over the worldwide ocean.

Floristic diversity of vascular plants in the Mimouna Forest (north-western Algeria)

In arid and semi-arid areas, wild vegetation is a very important natural resource and provides various ecosystem services, such as environmental adjustment functions. It is therefore important to manage and protect plant diversity in these areas. We investigated the Mimouna Forest in the Algerian Saida Province, characterized by a Mediterranean-type climate with maximum average monthly temperature of 27.1°C, minimum of 8.3°C and annual rainfall of 345 mm. We described and analysed the species diversity of vascular plants in this area. The floristic inventory was carried out using a subjective sampling method. This allowed us to identify 93 species belonging to 80 genera and 33 botanical families. The major families were the Asteraceae (16%) and Poaceae (14%). The analysis of plant life-forms showed the dominance of therophytes (36%) and hemicryptophytes (28%). On the phytogeographic level, the prevailing chorological elements were of Mediterranean affinity (54% in total). Endemic taxa accounted for 9% of the flora. The Shannon index was moderately high (3.62) and 13% of the recorded species were rare, including 5 protected by Algerian law.

On the existence of multiple states of low flows in catchments in southeast Australia

This study investigates whether low flow events in a catchment exhibit a possibility of switching regimes. If this happens, it can result in a catchment experiencing a flow anomaly that is even more extreme than what was historically considered a conventional low flow event. A Hidden Markov Modeling approach was used to identify shifts in the intensity of low flow events in catchments in southeast Australia. We found very strong evidence of low flow intensity exhibiting two distinct states (viz., a normal and an intensified state) for several catchments, providing convincing reasons to believe that low flows can and have undergone regime changes. The periods when the catchments exist in an intensified low flow state were associated with higher maximum and average monthly temperature (Δ≈+2.1,+1°C, respectively) and lower precipitation (Δ≈−25mm, a decline of 30%) compared to periods when these exist in their normal state.

Climate Change’s Impacts on Drought in Upper Zab Basin, Iraq: A Case Study

Iraq has a semiarid and desert climate. Also, it is predicted to be more susceptible to global warming effects. In the present study, daily climatic data from the past and projected future of the Upper Zab Basin, located in northern Iraq and considered an example of arid and semiarid climate conditions, were simulated using LARS-WG 6.0, i.e., a stochastic weather generator. The model also estimated daily rainfall and temperature. Using the RCP4.5 and RCP8.5 main emission scenarios, the future climate throughout the current century was estimated utilizing the MIROC5, CanESM2, HadGEM2-ES, ESM1-M, and CSIRO-Mk3.6.0 general circulation models (GCMs). This estimation was performed considering the significant uncertainty of future climate estimates. The model, constructed using thirty years' worth of historical data, was validated using climate data from the Upper Zab Basin in northern Iraq (1990–2021). According to the data, the average monthly maximum temperature will decline by 2.15–6.20 °C under RCP4.5 and 1.81–6.10 °C under RCP8.5 by the end of the twenty-first era for the corresponding upstream and downstream sub-basins. Precipitation projections from all GCMs showed varying patterns. Given that some models, like CanESM2, expected a rise in precipitation, while others, like MIROC5, forecasted a future with no change in precipitation or a falling trend, which illustrates the significant level of uncertainty in precipitation forecast when only one model was utilized. Also, the downstream sub-basin suffered the most during the 1999–2000 and 2007–2008 droughts, with average RDIst values of -1.97 and -1.64, respectively. However, the upstream sub-basin had moderate to severe droughts in 1999–2000 and 2007–2008, with average RDIst values of -0.81 and -1.84, respectively. The water available in the research location will be significantly impacted by variations in rainfall and temperature.

Evaluation of climate change impact on plants and hydrology

Climate change (CC) is the menace of the hour impacting every facet of human existence. Regional CC and its impact studies are crucial in that they contribute to global change. The current study aims to investigate the prevalence of CC in Charsadda, Pakistan and its impact on vegetation and hydrology of the region to understand microclimate variability contribution to global CC. Utilizing local climate data for 20 years (2001–2020), Modified Mann-Kendall and Sen’s Slope statistics were employed to determine monthly and seasonal trends in climate variables. Significant changing climate variables were regressed on Moderate resolution Imaging Spectroradiometer (MODIS) satellite dataset viz. normalized difference vegetation index (NDVI). Due to the prominent climate factor impacting vegetation, NDVI was further correlated to MODIS land surface temperature (LST). Floods being the conspicuous climate calamity were mapped for 2005 and 2010 using satellites Landsat 5 and 7 dataset viz. normalized difference water index (NDWI) with flood risk assessment by watershed delineation. The findings revealed significant (p &amp;lt; 0.05) variability in climate variables (average monthly and summer maximum temperature, and average monthly and summer precipitation) that are driving CC and impacting vegetation and hydrology in the region. Temperature and solar radiation affect NDVI adversely while precipitation and relative humidity has positive impact on vegetation. NDVI varied greatly spatiotemporally, often increasing but worsening in some areas (Shabqadar, Abazai, Palai and Charsadda city with NDVI = 0.1–0.3) of the study region as a result of extreme weather events. Temporally, NDVI improved with an overall positive trend with a stage (2007–2016) of noticeable zigzag fluctuation. Spatial grids with higher LST (&amp;gt;40°C) were either devoid of or with sparse NDVI (&amp;lt;0.3) presenting global warming as peril to vegetation. NDWI maps (2005, 2010 floods) indicate that after floods wreaked havoc on the region altering the vegetation pattern revealing heavy irregular precipitation as the next to temperature in jeopardizing vegetation of the region. Lower elevation regions along the Swat and Kabul Rivers with a greater risk of flooding were identified by watershed delineation. The study suggests that local governments and stakeholders implement CC mitigation strategies and plans for vegetation restoration, flood alerts with post-flood management for regional sustainable development.

Analyses of Climate Variability and Trends in the Oil Palm Belt of Ghana

The current production of oil palm in Africa has been severely limited by long periods of drought and perennial floods due to the increased rates of climate change. The study was aimed at assessing the climatic variability trends in 7 major Oil Palm growing areas (Benso, Mpohor, Bogoso, Twifo Praso, Kade, Juabeng and Brewaniese) located in the oil palm belt in Ghana spanning the semideciduous and the wet evergreen rainforest zones of Ghana using 30 years of historical weather data (1993-2022). The data was analysed to evaluate the extent of seasonal changes in weather over the 30-year period using the Statistical Package for Social Sciences (SPSS 20.0 version), using descriptive statistics and time series analysis. Trend analysis was conducted using the non-parametric Mann-Kendall (MK) and Sen’s slope estimator tests. A seasonal trend in rainfall was observed at all sites with maximum levels observed between May and July as well as a minor rainy season in September to Mid-November. The Mann-Kendall trend analysis showed a generally increasing trend at most stations in rainfall, temperature and solar radiation. A generally increasing trend in annual rainfall was observed from 1993-2022 with significant trends at Mpohor and Juabeng. The trend was higher in the moist evergreen rainforest zone than in the semi-deciduous rainforest zone. An average increase of 6.7 mm/yr in rainfall trend was observed for the period. An increasing trend in monthly maximum, minimum and mean temperatures were also observed. Significant increases in mean temperatures were observed at Bogoso (0.022°C/yr), Benso (0.018°C/yr), Juabeng (0.011°C/yr) and Mpohor (0.017°C/yr). The trend in mean annual solar radiation was generally not significant except in Benso where the mean solar radiation increased at the rate of 0.044 MJ/day. Higher drought levels in the first half year combined with very heavy rains later in the year are features of the ongoing climate change menace.

Assessment of observed temperature trend patterns of Bhubaneswar city, India with special prominence on future projections using SimCLIM climate model and farmer’s perception

&lt;p&gt;Temperature dynamics is a widely recognized indicator of the global warming phenomenon. Changes in temperature patterns in Bhubaneswar, India, were assessed by examining the monthly minimum and maximum temperature data for 60 years (1956–2015) sourced from the Indian Meteorological Department. SimCLIM climate change risk assessment software was used for projecting the temperature regime for four different representative concentration pathways. Further, a survey of 112 farmers was conducted to understand their perceptions of temperature variations in and around Bhubaneswar city using a multi-stage sampling technique. Mann–Kendall statistics and linear regression were used to analyze the monthly temperature data and trend detection. The study reveals a change of +4%,-4.44%, and +1.09% in the mean monthly maximum, minimum, and annual temperature. The results of the future projection show a temperature change of 0.81°C for RCP 2.6, 1.12°C for RCP 4.5, 1.03°C for RCP 6.0, and 1.54°C for RCP 8.5 for the year 2050. Confirming the analysis findings, most of the interviewed farmers also perceived increasing temperatures and decreasing precipitation in and around the city. The study outcome of temperature trend analysis and future projections will be helpful for farmers and policymakers in formulating adaptation strategies to climate change.&lt;/p&gt;&#x0D;

Boosting the energy output of an On-Grid solar PV system using a novel techniques

Two techniques have been used in this study to boost energy output of an on-grid PV system. Boosting energy output is achieved by educating the PV solar system performance parameters. Planar concentrators and cooling are two techniques used to boost energy output. The current solar PV system is placed in Baghdad/Al-Taji. This work includes improving the following performance parameters: performance ratio (PR), array efficiency, array yield, electrical energy, as well as solar irradiation. All of these improvements are accomplished by improving solar irradiance using planar concentrators (made of aluminum metal) and cooling (via water). The monthly daily average of energy produced for enhanced and reference PV modules is 14.2 kWh and 11.1 kWh, respectively. The monthly daily average of the array yield to the enhanced PV modules and reference PV modules is 7.14 kWh/kWp and 5.61 kWh/kWp, respectively. The monthly daily average of solar irradiation to the enhanced and reference PV modules is 7.71kWh/m2 and 6.101kWh/m2, respectively. The monthly daily average efficiency and performance ratio of the enhanced and reference PV modules are 14.3% &amp; 93.6%, and 13.9% &amp; 91.1%, respectively. The maximum average monthly temperatures of the enhanced and reference PV modules are in July, at 48.5OC and 57.4OC respectively, where the ambient air temperature is 42.1OC. The novel aspect of this work is the successful optimization of the performance (PR) parameters of an on-grid PV system using the new equations. Besides from designing a novel system to improve the performance of solar PV modules of the second generation (CIGS).

Environmental factors associated with incidence of developmental dysplasia of the hip: a systematic review and meta-analysis

BackgroundEstablished associated factors for DDH include female sex, breech presentation, family history, congenital malformations, oligohydramnios, and maternal hyperthyroidism. However, evidence for environmental factors that may contribute to DDH is limited and inconsistent.MethodsA systematic review of medical literature was conducted to collect data on environmental factors, including latitude, longitude, average yearly precipitation, average yearly temperature, minimum monthly temperature, and maximum monthly temperature, from all institutions that published articles on DDH. Univariate linear regression analysis was used to examine the correlation between environmental factors and DDH incidence, while multiple regression analysis was conducted to identify significant associated factors for DDH incidence.ResultsData from a total of 93 unique manuscripts were analyzed, revealing a significant negative correlation between DDH incidence and temperature, including average yearly temperature (r = -0.27, p = 0.008), minimum monthly temperature (r = -0.28, p = 0.006), and maximum monthly temperature (r = -0.23, p = 0.029). Additionally, there was a significant positive correlation between DDH incidence and latitude (r = 0.27, p = 0.009), and a significant negative correlation between DDH incidence and average yearly precipitation (r = -0.29, p = 0.004). In the final multiple regression analysis, temperature, including average yearly temperature, minimum monthly temperature, and maximum monthly temperature, were identified as significant associated factors for DDH incidence.ConclusionThe findings of this study suggest an association between cold weather and DDH incidence. Further research should explore the link between cold weather and DDH incidence, offering insights into potential interventions for cold climates.

Estimating the potential distribution of yellow spotted stink bug (Erthesina fullo) using ecological niche models

AbstractInvasive insect species threaten the productivity of ecosystems worldwide, and ecological niche models can be used to predict distributions of invaders and guide management efforts. Ecological niche models can also aid monitoring for invasive species that are globally distributed. One such species is the yellow spotted stink bug (Erthesina fullo Thunberg), a polyphagous pest native to Asia that has established in Europe and South America and threatens specialty crops. Here, we used ecological niche models to predict the potential distribution of E. fullo, and created a website to display predictions. We show that E. fullo has peak occurrence probability in areas with annual mean temperatures around 20°C, and that the occurrence probability increases as maximum monthly temperature reaches up to 38°C. The likelihood of occurrence decreased as annual precipitation increased, but increased with greater precipitation in the wettest and driest months. This suggests E. fullo is most suited to regions that are warm and dry and where most precipitation occurs across only a few months, such as southern North America, central and southern South America, southern Europe, southern Africa, and central and eastern Australia. Given that E. fullo is a highly mobile hitchhiking insect that travels through cargo and other containers to new areas, the potential spread of this species into new regions should be carefully monitored.

Investigating the correlation between extreme temperature events and the increasing frequency of power outages in the Northern Territory of Australia

It has been claimed that the grid of the Northern Territory of Australia suffers from more frequent blackouts because of the increasing occurrence of extreme events. However, the temperature oscillations have not changed since the time measurements started to be collected at the end of 1800. The time series of the monthly maximum and highest temperatures for the two locations of the Northern Territory of Australia which are spanning 140 years shows temperature extremes are not worsening, being the records detrended. The increasing power outages have many other causes. Some are natural such as cyclones, winds, or lightning. Others are human such as equipment failure, animal or human interference, overload, and maintenance or upgrade. One reason for the more frequent power outages is the reduced resilience of the grid forced to accept a growing share of non-dispatchable, intermittent, and irregular solar energy without appropriate energy storage. Their occurrence may be lessened by improving the resilience of the grid by providing adequate energy storage. The study contributes to the understanding of the complex factors influencing power outages and highlights the importance of resilient grid infrastructure.

Climate Variability and Glacier Evolution at Selected Sites Across the World: Past Trends and Future Projections

AbstractThe availability of freshwater from glaciers and snowmelt is of vital importance for people and ecosystems in the context of global climate change. Here, we focus on 25 glaciers located in different climates and latitudes and investigate their recent (1958–2020) and future projected trends (2020–2050 and 2070–2100) in monthly precipitation (Pr), maximum and minimum temperatures, ice mass loss, and their relationships with cloud properties. The study sites are located in Temperate Europe (France), the Inner (Ecuador, Venezuela, and Colombia) and Outer Tropics (Bolivia and Peru), Central America (Mexico), tropical Southeast Asia (Indonesia), Equatorial Africa (Uganda), and the Southern dry and Patagonian Andes (Chile and Argentina). The climate analyses are based on TerraClimate data (Monthly Climate and Climatic Water Balance for Global Terrestrial Surfaces) and 28 CORDEX (Coordinated Regional Climate Downscaling Experiment) climate simulations. Our findings reveal that, extrapolating current glacier volume change trends, almost half of the studied glaciers are likely to vanish (95%–100% volume loss) by 2050, with widespread warming and drying trends since 1958. A shift toward wetter conditions at Pico Humboldt (Venezuela) and Martial Este (Argentina) identifiable in the CORDEX simulation will very likely not have a limiting impact on glacier mass loss owing to increasing temperatures, which will raise the elevation of the rain/snow limit. Our results provide useful new information to better understand glacier‐climate relationships and future scenarios dominated by ice mass loss trends across the globe. These findings suggest serious consequences for future water availability, which exacerbate the vulnerability of local populations and ecosystems.