Mean Minimum Temperature Research Articles

Identifying climatic and non-climatic determinants of malnutrition prevalence in Bangladesh: A country-wide cross-sectional spatial analysis

Child malnutrition is indisputably a multi-faceted phenomenon. Comprehending the aforesaid crucial issue this paper intended to identify climatic and non-climatic factors for the spatial variation of malnutrition prevalence in Bangladesh. The climatic data on temperature and rainfall are obtained from the WorldClim dataset. We obtained a set of global climate layers that included monthly data on minimum temperature, maximum temperature, mean temperature, and rainfall for the period 1960–1990, at a spatial resolution up to 30 ′onds (~ 1 × 1 km at the equator). The data are extracted at the district level using the zonal-statistics in QGIS. This study performed a spatial lag regression to evaluate association of malnutrition with climate characteristics and other factors. The prevalence of malnutrition exhibited substantial association with temperature and precipitation. Food production, water access, improved sanitation, literacy, road density, solvency ratio and GDP had a significant association with the spatial variation of malnutrition in Bangladesh.

ENSO feedback drives variations in dieback at a marginal mangrove site

Ocean–atmosphere climatic interactions, such as those resulting from El Niño Southern Oscillation (ENSO) are known to influence sea level, sea surface temperature, air temperature, and rainfall in the western Pacific region, through to the north-west Australian Ningaloo coast. Mangroves are ecologically important refuges for biodiversity and a rich store of blue carbon. Locations such as the study site (Mangrove Bay, a World Heritage Site within Ningaloo Marine Park and Cape Range National Park) are at the aridity range-limit which means trees are small in stature, forests small in area, and are potentially susceptible to climate variability such as ENSO that brings lower sea level and higher temperature. Here we explore the relationship between mangrove dieback, and canopy condition with climatic variables and the Southern Oscillation Index (SOI)—a measure of ENSO intensity, through remote sensing classification of Landsat satellite missions across a 29 year period at a north-west Australian site. We find that the SOI, and seasonal mean minimum temperature are strongly correlated to mangrove green canopy (as indicator of live canopy) area. This understanding of climate variations and mangrove temporal heterogeneity (patterns of abundance and condition) highlights the sensitivity and dynamics of this mangrove forest and recommends further research in other arid and semi-arid tropical regions at mangrove range-limits to ascertain the extent of this relationship.

Hibernation behavior of a federally threatened ground squirrel: climate change and habitat selection implications

Abstract Hibernation is an adaptation to survive periods of stress, from food limitation or harsh thermal conditions. A key question in contemporary ecology is whether rare, range-restricted species can change their behavior in response to climate change (i.e., through behavioral plasticity). The northern Idaho ground squirrel, Urocitellus brunneus (A. H. Howell, 1928), is a federally threatened species that hibernates for approximately 8 months per year within the bounds of its small range in central Idaho, USA. Changes in temperature, snow accumulation, and summer precipitation, all brought about as a result of climate change, may reduce survival or fecundity of northern Idaho ground squirrels if they cannot adapt to these climate changes. Hibernating species can respond to climate-change-induced thermal challenges in two ways: change their hibernation physiology and behavior (i.e., emergence date or number of torpor bouts) or alter their environment (i.e., change hibernacula depth or location). We explored a suite of intrinsic and extrinsic factors to document the extent to which they influenced hibernation behavior of northern Idaho ground squirrels. Emergence date was positively associated with snowpack and negatively associated with mean winter temperature. Mean minimum skin temperature was negatively associated with canopy closure and slope of a squirrel’s hibernaculum. Duration of the heterothermal period, number of euthermic bouts, and total time spent euthermic were positively associated with body mass. Immergence date and duration of the longest torpor bout were negatively associated with body mass. Warmer temperatures and less snow accumulation in the winter—caused by climate change—likely will cause altered emergence dates. Our results suggest that any future climate-induced changes in snowfall, ambient temperature, food availability, or habitat likely will impact survival of this rare ground squirrel, because such changes will cause changes in hibernation behavior, percent mass loss during hibernation, and duration of the active season when small mammals are more susceptible to predation.

A time series analysis of the short-term association between climatic variables and acute respiratory infections in Singapore.

Acute respiratory infections (ARIs) are among the most common human illnesses globally. Previous studies that examined the associations between climate variability and ARIs or ARI pathogens have reported inconsistent findings. Few studies have been conducted in Southeast Asia to date, and the impact of climatic factors are not well-understood. This study aimed to investigate the short-term associations between climate variability and ARIs in Singapore. We obtained reports of ARIs from all government primary healthcare services from 2005 to 2019 and analysed their dependence on mean ambient temperature, minimum temperature and maximum temperature using the distributed lag non-linear framework. Separate negative binomial regression models were used to estimate the association between each temperature (mean, minimum, maximum temperature) and ARIs, adjusted for seasonality and long-term trend, rainfall, relative humidity, public holidays and autocorrelations. For temperature variables and relative humidity we reported cumulative relative risks (RRs) at 10th and 90th percentiles compared to the reference value (centered at their medians) with corresponding 95% confidence intervals (CIs). For rainfall we reported RRs at 50th and 90th percentiles compared to 0mm with corresponding 95% CIs. Statistically significant inverse S-curve shaped associations were observed between all three temperature variables (mean, minimum, maximum) and ARIs. A decrease of 1.1°C from the median value of 27.8°C to 26.7°C (10th percentile) in the mean temperature was associated with a 6% increase (RR: 1.06, 95% CI: 1.03 to 1.09) in ARIs. ARIs also increased at 23.9°C (10th percentile)compared to 24.9°C of minimum temperature (RR: 1.11, 95% CI: 1.07 to 1.16). The effect of maximum temperature for the same comparison (30.5°C vs 31.7°C) was non-significant (RR: 1.02, 95% CI: 0.99 to 1.05). An increase in ambient temperature to 28.9 °C (90th percentile) was associated with an 18% decrease (RR: 0.82, 95% CI: 0.80 to 0.83) in ARIs. Similarly, ARIs decreased with the same increase to 90th percentile in minimum (RR: 0.84, 95% CI: 0.80 to 0.87) and maximum (RR: 0.89, 95% CI: 0.86 to 0.93) temperatures. Rainfall was inversely associated with ARIs and displayed similar shape in all three temperature models. Relative humidity, on the other hand, exhibited a U-shaped relationship with ARIs. Our findings suggest that lower temperatures increase the risk of ARIs. Anticipated extreme weather events that reduce ambient temperature can be used to inform increased healthcare resource allocation for ARIs.

Disentangling the effects of stand and climatic variables on forest productivity of Chinese fir plantations in subtropical China using a random forest algorithm

A machine learning method called the random forest approach was used to explore the relationship between forest productivity and stand and climate factors. Data was sampled from the long-term spacing trails of Chinese fir plantations in southern China. Results showed that the productivity of Chinese fir plantations increased with increasing value of the Gini coefficient and dominant height (Hd), while it decreased with increasing age (A) and stand basal area (BA). Furthermore, forest productivity was positively correlated with annual precipitation (AP) and summer mean maximum temperature (SMMT); in contrast, it was negatively associated with winter mean minimum temperature (WMMT) and annual heat-moisture index (AHM). Age had the greatest influence on forest productivity compared to a more secondary influence of climate factors. We found that older forests were more vulnerable to climatic stress and the productivity of forests with middle- and high- levels of competition behaved similarly, and was lower than forests with low level of competition intensity. Higher SMMT, AP and lower AHM would enlarge the gap of forest productivity under different levels of stand structure, competition intensity and site quality. Changes in site conditions had little effect on productivity when AP was lower than 1250 mm. Our findings will provide a good framework for Chinese fir plantation management under future climate change.

Socioecological conditions predict degu social instability and provide limited cues to forecast subsequent breeding conditions

Permanent changes in group membership may result in detrimental fitness effects on both group residents and immigrants. Factors associated with this form of social instability are rarely documented. We used a 15-year dataset on degus, a social and short-lived species, to test the hypothesis that physical condition and socioecological factors experienced during breeding are associated with social instability in terms of group individual membership (hypothesis 1). We also tested the hypothesis that these factors represent potential cues for individuals to predict social instability conditions during subsequent breeding (i.e., exhibiting autocorrelation) (hypothesis 2). Social instability in degu group membership was ubiquitous. Social instability increased with increasing ectoparasite load but decreased with increasing food abundance, increasing degu density, increasing mean minimum temperature, and increasing number of female group members. Of these conditions, degu density during winter exhibited autocorrelation. Finally, overall predictability of ecological conditions varied from low to high within a 5–6-year period. These findings indicate that socioecological conditions experienced by the breeding adults and their developing offspring predict within-year social instability (hypothesis 1) and provide some limited cues to individuals to predict similar conditions during the subsequent breeding event (hypothesis 2). Permanent changes in the adult composition of social groups (social instability) can have significant impacts on the fitness of group members. Determining the ecological and social conditions associated with social instability and whether individuals can anticipate social instability in adulthood can inform socioecological theory. In the communally rearing rodent, Octodon degus, social instability during breeding is ubiquitous and impacts the fitness of adult males and females differently. We determined that social instability in degu groups during breeding is associated with local ecological conditions (ambient temperature, ectoparasite loads, abundance of food, population density) and the social environment (number of adult females). Of the ecological variables, only population density exhibited autocorrelation. These results are important because they imply limited ecological cues available for the offspring to anticipate social instability conditions as adults.

Climate change impacts and transformative adaptation strategies among farming households in the City of Koronadal, Philippines

Farmers in the Roxas mountain range, City of Koronadal used to have bountiful harvests during the time when the city was still free from climate-related hazards. However, this situation has recently changed due to the increasing climate-related risk events. Moreover, localized baseline scientific climate information is limited to foster the development of appropriate adaptations and policies toward climate-resilient communities. This study assessed the climate trends and the changes, impacts, and adaptation strategies of farm households in five barangays in the Roxas mountain range, Koronadal City, South Cotabato. The study conducted household surveys with 265 respondents, focus group discussions, and key informant interviews. In using Mann-Kendall test statistics, time series analysis and one-way analysis of variance, the findings from 1981 to 2012 show increasing trends with significant changes (p <0.01) in mean minimum temperature, increasing by 0.74 °C for three decades. In contrast, mean maximum temperature showed a decreasing trend with an average decrease of 0.65 °C, p <0.01). In three decadal periods, an average increase of 0.04 °C in monthly mean temperature was observed. Rainfall patterns during the same period also show significant changes in the months of June (p <0.01), August, and December (p <0.05); these findings suggest that climate change occurred. Floods, landslides, and droughts were experienced by the communities, which had devastating socioeconomic and environmental impacts. The existing adaptation strategies are just stop-gap solutions that address the effects of climate change but do not consider the root causes. To consider future changes in climate patterns, the socioeconomic and political structure and processes of the communities need to change; this can be achieved if multifaceted drivers of climate change hazards and their impacts are appropriately and immediately addressed. Some grassroot-level transformative adaptation strategies identified in the study consist of socioeconomic facets, specifically, investment in children’s education, financial management, family planning, and development of alternative on-farm and nonfarm livelihood options. The environmental aspect, which includes promoting agroforestry system, water impoundment technologies, and advanced early warning system, were also considered.

Comparison of gridded temperature dataset of IMD and Sheffield over India

Climate modelling and prediction studies play crucial role in identifying suitable mitigation techniques to minimize or avoid adverse consequences of climate extremes. The accurate spatially and temporally distributed temperature and rainfall dataset are key components in climate prediction studies. Reanalysis datasets provide better spatial and temporal coverage than observational datasets; therefore, reanalysis datasets are widely used for global and regional studies. However, before using the reanalysis dataset in climate modelling studies, it is crucial to compare the robustness and accuracy of the reanalysis dataset with the observational dataset. In this study, daily gridded maximum and minimum temperature datasets of Indian Meteorological Department (IMD) (1°?×?1°) and Sheffield (0.25°×0.25°) are compared using 62-years data i.e 1951-2012. The comparison is based on differences in spatial distribution pattern, probability distribution functions plots and box-plots of the respective gridded dataset. The spatial distribution of grid-wise averaged maximum and minimum temperature dataset generally compare well across pan India in both IMD and Sheffield; however, the significant differences are observed over western Himalaya (WH) and northeast (NE) region. The probability distribution of the pooled mean minimum temperature dataset of IMD is found significantly different from Sheffield using the two-sample Kolmogorov-Smirnov (KS) test. This study will be helpful for researchers who are planning to use Sheffield gridded temperature dataset for climate modelling studies.

Mapping Fluctuations of Hispar Glacier, Karakoram, using Normalized Difference Snow Index (NDSI) and Normalized Difference Principal Component Snow Index (NDSPCSI)

Investigation of the fluctuations in the snow-covered area of the major glaciers of the Karakoram range is essential for proper water resource management in Pakistan, since its glaciers are responding differently to the rising temperatures. The objective of this paper is to map snow covered area of Hispar glacier in Hunza river basin for the years 1990, 2010 and 2018. Two techniques, (NDPCSI) Normalized Difference Principal Component Snow Index and (NDSI) Normalized Difference Snow Index were used. Hispar glacier of the Hunza basin has lost 114 km2 of its ice cover area, during the last 28 years, with an alarming annual retreat rate of 1.67 km2 of glacier ice from 1990 to 2018. Hunza basin experienced a +1°C rise in both mean minimum and mean maximum temperature during 2007 to 2018.as a result, Karakorum ice reserves have been affected by rising temperature of the region. Due to temperature rise, retreat of snowcovered area of Hispar, Karakoram mountain range shows a shift in the cryospheric hazard zone.

Impact of Rainfall Variability on Rural Tea Roads in Kericho, Kenya

Climate variability is a global phenomenon that is posing a threat to the infrastructure and agricultural sector. Intense precipitation often results in the deterioration of rural road infrastructure resulting in inaccessibility. Rainfall and temperature data from 1989 to 2019 was obtained from Kenya Meteorological Department. Data on Greenleaf and cost of repairs and maintenances are from selected tea factories managed by Kenya Tea Development Agency. Data on perception is based on a questionnaire survey of 398 randomly selected tea farmers. Results show that climate variability is experienced in Kericho (p < 0.005). There is a varsity variation in mean maximum temperatures F(0.05, 29) ꞊ 5.564 (p ꞊ 0.009) and mean minimum temperature F(29) =8.503 (p ꞊ 0.000). However, the linear regression analysis shows that rainfall has decreased (y ꞊ 2.5476x - 40.778) while the temperature has increased (y ꞊ 0.028x - 0.4473). There is a significant positive correlation between the amount of rainfall and cost of repairs and maintenances for five factories (r ꞊ 0.122, r = 0.046, r = 0.029, r = 0.255) except one (r = -.261, p ꞊ .466). Therefore, the climate has significantly varied from 1989-2019 and heavy rains occur periodically that damage rural tea roads, thus impacting negatively on tea transportation. There is a need, therefore, for heavy investment of emergency funds for repair and maintenance of rural tea roads based on rainfall variability and heavy rain return period pattern.

Effect of encased concrete on section temperature gradient of corrugated steel web box girder

Thirty-two temperature sensors, a solar radiation sensor, wind speed, and direction sensor were installed on the bridge for the field monitoring of structural temperature, solar radiation, and wind. The frequency was set at 60 min for 211 days. Empirical equations were used to predict the maximum vertical and lateral temperature gradients, and the daily maximum and minimum mean temperatures of the corrugated steel web box girder. The results showed that the temperature gradient of the corrugated steel web box girder was closely related to the temperature gradient of air. The vertical maximum temperature gradient occurred at 4 pm. The height of the box girder had a significant effect on the accuracy of the predicted vertical maximum temperature gradient. Compared with the section without encased concrete, the maximum temperature gradient of the encased concrete section was reduced by 10.48%. Encased concrete showed minimal effect on both the vertical and lateral temperature gradient of the top plate part, however, the effect on the vertical temperature gradient of the haunch reduced by 17.19%. The maximum temperature gradient of corrugated steel with a composite encased concrete section was 4.12°C, which was less than that of the section without encased concrete at 5.06°C. The encased concrete had a significant effect on the maximum temperature gradient of corrugated steel web with a 26.99% deviation.

Analysis of Maximum and Minimum Temperature in Qilian Mountainous, Northwest China

As one of the key elements of climate change, the temperature changes can affects the energy balance and hydrological cycle. The variations and trend of mean annual maximum temperature (Tmax) and minimum temperature (Tmin) were analyzed by using linear regress for 44 stations inside and surrounding the Qilian Mountains for period of 1960-2017. The results have shown that the variations of mean annual Tmax and Tmin have significant increasing in whole study regions. The warming trend of mean annual Tmix is higher than that of Tmax. Both the trend of mean annual Tmax and Tmin in the southern slope is warmer than those in the northern slope of Qilian Mountains. In spring, the warming trend of Tmax is significantly weaker inside than that outside the Qilian Mountains. For all seasons, the trend of Tmax and Tmin is the highest in winter, and is weakest in spring.

Layered self‐resistance electric heating to cure thick carbon fiber reinforced epoxy laminates

AbstractCuring of thick carbon fiber reinforced thermosetting composite laminates has been a major challenge due to the undesired through‐thickness temperature gradient. In this paper, a novel layered self‐resistance electric heating (L‐SRE) method to cure thick laminates was proposed. The thick laminate was divided into multiple independent sub‐layers, and the temperature of each sub‐layer was controlled individually. The experiment's results revealed that L‐SRE was able to achieve highly homogeneous temperature distribution filed through‐thickness both in rapid heating and exothermic reaction stages. The maximum temperature difference of dwell stage for L‐SRE process was less than 4.0°C, and the L‐SRE process that had an optimized thickness of each sub‐layer achieved the minimum mean temperature deviation of 2.1°C, which was 88.46% lower than that of the oven process. By using the optimized L‐SRE method, the maximum value of crosslink thermal overshoot was 12.2°C (32.5°C for oven curing). Different layered temperature control strategies were explored, and the lowest energy consumption of 309.7 Wh (19.82% of oven process) was achieved by using the single‐power pulsed heating. The method proposed in this paper provided a new solution for high‐quality and energy‐efficient curing of thick laminates.

Effect of latitude on maize kernel weight and grain yield across China

AbstractLatitude influences maize kernel weight (KW) and grain yield by variation in climatic conditions such as temperature and solar radiation. In this study, the major aim is to examine the spatial variation in 1,000‐KW and grain yield of the same maize hybrids and to further understand the differences in the response of 1,000‐KW and maize grain yield to climatic factors under a wide range of latitude. For this purpose, we conducted field experiments at 17 different locations in the North maize region (NM) and Huanghuaihai maize region (HM) of China between 33°35′ N and 46°48′ N latitude from 2013 to 2016. The extensively used five maize hybrids (Xianyu 335, Zhengdan 958, Denghai 11, Nonghua 101, and Zhongdan 909) in China were chosen for these experiments. Based on the findings of this study, the maize 1,000‐kernel weight and yield were found to be significantly influenced by the latitude. The maximum average grain yield of five hybrids was observed (12.25 Mg ha–1) at 43°58′ N latitude. Whereas the maximum 1,000‐KW of five hybrids was weighted (362.08 g) at the latitude of 41°48′ N, respectively. Five hybrids showed similar trends with latitudes. Among all the climatic factors, mean minimum temperature (Tm) and accumulated solar radiation (Ra) were mainly responsible for the variations of 1,000‐KW and maize grain yield. Based on the obtained results of this research, it was also found that Xianyu 335 had higher yield potential, especially at high latitude.

Evaluation of climate change impact on extreme temperature variability in the Blue Nile Basin, Ethiopia

Abstract. Climate change raises important issues concerning hydrological engineering. The impact of climate change on important river basins should be investigated rigorously. Extreme temperature variability has a direct impact on the hydrological cycle, especially the evaporation component. In this paper, spatial and temporal patterns of changes in extreme temperatures were investigated using 10 meteorological stations' data for the period 1950–2018 in the Blue Nile Basin. Long-term trends in the Blue Nile Basin annual and monthly temperatures were investigated. The statistical significance of the trend was calculated by applying the Mann–Kendall (MK) test. The analysis of data was performed using the coefficient of variance and anomaly index. The results showed that the annual maximum and minimum temperatures were increasing significantly with a magnitude of 0.037 and 0.025 ∘C per decade respectively in the period from 1950 to 2018. The result of the Mann–Kendall analysis test revealed a marked increase in the mean maximum and minimum temperature trends over time during the study period (the minimum temperature rate is more evident than the maximum). The long-term anomalies of mean annual minimum temperature revealed the interannual variability while the trend after 1977 was higher than the long-term average, which is proof of the warming trend's existence during the last two decades of the 20th century.

Effects of rainfall, temperature and topography on malaria incidence in elimination targeted district of Ethiopia

BackgroundClimate and environmental factors could be one of the primary factors that drive malaria transmission and it remains to challenge the malaria elimination efforts. Hence, this study was aimed to evaluate the effects of meteorological factors and topography on the incidence of malaria in the Boricha district in Sidama regional state of Ethiopia.MethodsMalaria morbidity data recorded from 2010 to 2017 were obtained from all public health facilities of Boricha District in the Sidama regional state of Ethiopia. The monthly malaria cases, rainfall, and temperature (minimum, maximum, and average) were used to fit the ARIMA model to compute the malaria transmission dynamics and also to forecast future incidence. The effects of the meteorological variables and altitude were assessed with a negative binomial regression model using R version 4.0.0. Cross-correlation analysis was employed to compute the delayed effects of meteorological variables on malaria incidence.ResultsTemperature, rainfall, and elevation were the major determinants of malaria incidence in the study area. A regression model of previous monthly rainfall at lag 0 and Lag 2, monthly mean maximum temperature at lag 2 and Lag 3, and monthly mean minimum temperature at lag 3 were found as the best prediction model for monthly malaria incidence. Malaria cases at 1801–1900 m above sea level were 1.48 times more likely to occur than elevation ≥ 2000 m.ConclusionsMeteorological factors and altitude were the major drivers of malaria incidence in the study area. Thus, evidence-based interventions tailored to each determinant are required to achieve the malaria elimination target of the country.

Effects of Lime and Compost on Acidic Soil Amelioration and Grain Yield of Maize at Jimma, Southwestern Ethiopia

Maize is the third important cereal crop globally after wheat and rice. Though it is consumed in all regions of Ethiopia, the crop is used as stable food in western and south western part of the country. However, Soil acidity and nutrients depletion are serious limitations in maize productivity improvement. Now a day, increasing maize production through expansion of cultivable land is no more possible. Productivity of the crop on less fertile acidic soils can be improved by integrated use of soil amendments like lime, compost as well as farm yard manure and proper fertilizer management. In Ethiopia, integrated approach of soil fertility management is attractive prime importance these days. The objective of this study is to evaluate effects of manure (FYM),compost, and their interactions with lime and inorganic fertilizers on soil properties and maize productivity . The experiment was conducted for consecutive cropping seasons 2010-2013 at Melko Jima Agricultural Research Center,. The Center is found in South Western Ethiopia; in Oromiya National Regional State and located at 7°40'47"N latitude and 36°49'47"E longitude. The mean maximum and minimum temperature of the Center are 26.2 and 11.3°C respectively. The elevation of the Center is 1,753m above sea level and it receives 1,529.5mm average annual Rainfall. The design was RCB design with three replications. Combinations of organic, inorganic fertilizers and lime significantly (P < 0.05) influenced maize grain yield in all cropping seasons. The result also revealed that in the first cropping season, recommended NP gave significantly higher yield than other combinations. On the other hand, recommended NP + recommended lime resulted in significantly higher grain yield than other combinations in 2011 and 2012 cropping seasons. It is shown that application of organic, inorganic fertilizers and lime significantly affected soil properties such as pH, exchangeable acidity, available phosphorus organic carbon content and cation exchange capacity. Accordingly, the use of compost alone, compost and lime significantly improved soil reaction in relation to other combinations. However the use of N and P and its combinations with organic fertilizer and lime did not improve soil pH. This indicates the soil acidity aggravate effect of ammoniac fertilizes. Compost, together N and P, compost with lime as well as half of compost, lime and recommended N and P significantly lowered exchangeable acidity of the soil. The use of compost alone and as well as compost and lime simultaneously significantly increased available P in soil solution relative to other combinations. It was also observed that application of compost alone and simultaneously with lime improved CEC and organic carbon stack of the soil. Generally, the use of integrated compost, manure , lime and in directly and indirect improving soil chemical and physical properties. provide significant quantities of available nitrogen, P, Mo and B, and more favorable conditions for microbial mediated reactions. Integrate use of lime, organic nutrient sources and inorganic fertilizers are beneficial in improving maize productivity and ameliorating properties of acid soil. Keywords: C ompost, Exchangeable acidity, FYM, Lime, P fertilizer, Soil pH DOI: 10.7176/JNSR/12-3-03 Publication date: February 28 th 2021

Change in mean and extreme temperature at Yingkou station in Northeast China from 1904 to 2017

The understanding of centennial trends of extreme temperature has been impeded due to the lack of early-year observations. In this paper, we collect and digitize the daily temperature data set of Northeast China Yingkou meteorological station since 1904. After quality control and homogenization, we analyze the changes of mean and extreme temperature in the past 114 years. The results show that mean temperature (Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) all have increasing trends during 1904–2017. The increase of Tmin is the most obvious with the rate of 0.34 °C/decade. The most significant warming occurs in spring and winter with the rate of Tmean reaching 0.32 °C/decade and 0.31 °C/decade, respectively. Most of the extreme temperature indices as defined using absolute and relative thresholds of Tmax and Tmin also show significant changes, with cold events witnessing a more significant downward trend. The change is similar to that reported for global land and China for the past six decades. It is also found that the extreme highest temperature (1958) and lowest temperature (1920) records all occurred in the first half of the whole period, and the change of extreme temperature indices before 1950 is different from that of the recent decades, in particular for diurnal temperature range (DTR), which shows an opposite trend in the two time periods.

Impact of lake surface changes on climate fluctuation within a lake‐affected region

Wetlands are one of the most important aquatic ecosystems that are vulnerable to various factors, including human activity or natural events such as drought. Remote sensing technology is an effective technique for managing and monitoring changes in these ecosystems caused by natural events and human activities. The present study evaluated the effects of changes at Bakhtegan Lake on six climatic parameters in its surrounding environments. Landsat satellite imagery was used to monitor changes in the Bakhtegan Lake surface during times of maximum extent in the period from 2000 to 2015. Support vector machine (SVM) classification was applied to extract the characteristics of the lake surface. Then, the distance of 80 km from the lakeshore was identified as the environment of its influence on the surrounding land, which was divided into three buffers from 0 to 25, 26–55 and 56–80 km. The results showed that a higher accuracy than the index for extracting lake area was achieved using the SVM classification method. Additionally, the climate parameters of mean annual precipitation, relative humidity, and percentage of cloud cover significantly influenced (0.001) lake surface changes in buffer one, indicating the highest impact among all climatic parameters. In buffer two, the significance level of the precipitation parameter decreased to about 0.05, and the annual mean minimum temperature was significantly lower (0.05); however, the mean annual minimum and maximum temperatures were not significant

Near future climate change projections with implications for the agricultural sector of three major Mediterranean islands

The paper presents the analysis of a sub-set of high-resolution bias-adjusted simulations from the EURO-CORDEX initiative, in order to examine the changes in the mean climate and the extremes in three Mediterranean islands, namely, Sicily, Crete and Cyprus, in the near future (2031–2060) compared to the present climate (1971–2000), under two future scenarios, i.e. RCP4.5 and RCP8.5. The analysis entails commonly used climatic indices of interest related to the islands’ agricultural sector. The results indicate robust increases for both the mean maximum and minimum temperatures on a seasonal basis, as well as for the temperature related extremes under both climate scenarios. On the contrary, the changes in precipitation are less pronounced as the changes in the seasonal precipitation are not found statistically significant for the three islands under both scenarios. The projected warming combined with the projected unchanged precipitation pattern in the future, especially in spring and summer, might expose the crops to conditions with a negative impact on the plants’ phenology, leading to implications on crop production and quality. The results presented here might be the basis for the development of an adaptation strategy specifically targeted on the three islands but also replicable to other Mediterranean islands.