Trends In Maximum Temperatures Research Articles

Analysis of meteorological parameter changes using Mann-Kendall statistical tests in Indian Punjab

Groundwater in Central Punjab is declining at an alarming rate of one meter annually in last two decades and likely to be exhausted up to 300 meter depth in next 2-3 decades as per recent report published in 2018 based upon exhaustive analysis done till 2017 by the relevant agencies (Anonymous, 2018). All the blocks in this zone are over exploited. Rainfall and temperature are predominant meteorological parameters which influence irrigation demand which in turn influences ground water withdrawal; which ultimately influence groundwater depth in the region. Area under rice is increasing due to high returns. So, the trend analysis of these parameters is of paramount importance for sustainability of agriculture in this region. The aim of the present investigation was to study annual trend of precipitation, maximum and minimum temperature and rainfall for 10 locations in Central Punjab during 1998–2019. The effect of rainfall and rice area on groundwater depth has been also studied. To achieve this non-parametric Mann-Kendall and Sen's applied to the data series of annual rainfalls, annual maximum and minimum temperature of the ten selected stations. The nonparametric statistical tests applied to series of annual Tmax revealed an increasing trend in all of the locations of the study area. According to results by Sen’s slope estimator, the increasing trend in annual precipitation series was detected at the Tarantaran, Kapurthala,Ludhiana, Moga, Barnala and Jalandhar, while other stations had negative or no trends.

Spatiotemporal analysis of temperature and precipitation extremes over Bangladesh using a novel gridded observational dataset

This study explores spatial changes in trends of 29 climate extremes indices between 1981 and 2020 in Bangladesh, a country that frequently experiences the impacts of extreme events. This is the first study to examine trends in extreme climate over Bangladesh using a high resolution (0.05° × 0.05°) gridded daily temperature and precipitation data rather than individual stations. Trends in mean daily maximum and minimum temperatures were +0.38 °C and +0.25 °C per decade, respectively, for the last 40 years. The maximum increases in both warm days and nights were 12.75 days per decade with the fastest rate of warming in the eastern part of the country, whereas the maximum decreases in both cold days and nights were 7 days per decade with the western part experiencing the greatest increase in extreme cold. Significant reductions in total precipitation (225 mm per decade) were observed in the major parts of the country. However, the number of very heavy precipitation days (R20mm) showed a statistically significant increase (2.25 days per decade) in the southern coastal areas, with the tendency of more extreme wet days (R30 mm). The maximum decrease in annual total precipitation was 225 mm per decade while the consecutive dry days increased by 12.5 days per decade. While previous studies reported a faster rise in minimum temperature than maximum temperature, this study shows a faster increase in maximum temperature instead of minimum temperature in the study area. Extreme temperature changes were statistically more significant than changes in extreme precipitation. This study also shows statistically significant and consistent spatial trends of extreme temperature and precipitation when using high-resolution gridded observational datasets instead of station data.

TRENDS AND VARIABILITY OF TEMPERATURE TIME SERIES OVER THE KANSHI CATCHMENT IN THE POTOHAR REGION OF PUNJAB-PAKISTAN

The variabilities and changing trends of temperature in the Potohar region have been examined in this study for the period of 1950-2018. Monthly data of mean, maximum and minimum temperature were acquired from Pakistan Meteorological Department (PMD) and slope method was opted to calculate the variation rate of temperature for the period under investigation. The results of the study revealed the rising trend of temperature over the Kanshi catchment in northern Punjab, for the period under study. Trends of maximum temperature significantly increased to a rate of 0.0134 °C/ year, while minimum temperature was also found to have increased at the rate of 0.0334 °C / year. Such high rate of temperacture increase can be attributed to settlement expansion an outcome of rapid urbanization, in Jhelum city. In comparison to maximum temperature (Tmax), the rate of increase of minimum temperature was identified to be more rapid. Correspondingly, a sum of 1 to 2°C increase in minimum temperature was observed, in the study area, for the period under study. The identified temperature changes are anticipated to have adverse consequences particularly for the agriculture and livestock sectors and food security in the region.

Reconstruction of post-little ice age glacier recession in the Lahaul Himalaya, north-west India

ABSTRACT Understanding past glaciation and deglaciation is vital for assessing present-day glacier dynamics and response to climate change. We focus on reconstructing past glacier fluctuations in Lahaul, north-west India, a region located between arid Ladakh and the humid the Pir-Panjal range. We focus specifically on six glaciers in the Miyar and Thirot catchments of varying size, aspect and debris cover. To reconstruct past terminus fluctuations of these glaciers, we used repeat terrestrial photography and historical archives as data sets and mapped the terminus positions and latero-terminal moraines in the field along with glacier terminus mapping from high to medium resolution satellite images (e.g. Corona, Hexagon, Landsat and LISS IV). Results show that since the little ice age, all the studied glaciers have experienced terminus retreat and area loss, with average values of 1.46 and 0.9 km2, respectively. Precipitation data show a statistically significant decreasing trend during the last century with an increasing trend in annual average maximum (T max) and minimum (T min) temperature. This warming trend is more statistically significant for T min. Although total ice loss at the six studied glaciers is considerable (5.48 km2), this varies both spatially (i.e. from glacier to glacier) and temporally. We attribute this variability to topographic controls such as glacier hypsometry and another non-climatic factor, i.e. varying degree of debris cover.

Rainfall and Temperature Trends and Variability in Arid and Semi-arid Lands of Kitui County, Kenya

A study was carried out to analyse rainfall and temperature trends and variability in selected agro-ecological zones in Kitui County. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) rainfall dataset was used while temperature data was obtained from the Climatic Research Unit gridded Time Series (CRU TS) dataset. The results indicated that there was a non-significant decreasing trend (p<0.05) in average annual rainfall in all the four agro-ecological zones (p<0.05) for a 30-years period (1988-2018) in the study area. A decreasing trend in March-April-May (MAM) seasonal rainfall trend was reported in the arid and semi-arid agro-ecological zones while an increasing trend was recorded in the transitional and semi-humid zones. For the October-November-December (OND) seasonal rainfall, a non-significant decreasing trend was reported in all the four agro-ecological zones. Additionally, a higher annual rainfall variability was recorded in the drier (arid) and wetter (semi-humid) zones compared to that in semi-arid and transitional zones. Moreover, the study established that there was a spatial variation in both MAM and OND seasonal rainfall variability and that rainfall variability was higher in the OND seasonal rainfall than that of the MAM seasonal rainfall in all the agro-ecological zones. With reference to temperature trends, a statistically significant increasing trend in annual and OND seasonal average maximum and minimum temperatures was reported in all the four agro-ecological zones. Further, the study noted a non-significant increasing trend in maximum and minimum temperatures for the MAM season in all the agro-ecological zones. In regard to temperature variability, the study deduced that there was low temperature variability compared to rainfall variability in all the four agro-ecological zones. The study recommends that location-specific rainfall and temperature analysis should guide planning and implementation of adaptation strategies for effective response to climate variability. Keywords: Agro-ecological Zones, Mann-Kendall Test, Coefficient of Variation, CHIRPS, CRU TS DOI: 10.7176/JEES/12-12-05 Publication date: December 31 st 2022

Temperature characteristics and heat load in the City of Dubrovnik

In this study, temperature characteristics and heat load in the city of Dubrovnik are investigated by using temperature data observed at the local meteorological station in Dubrovnik for the period 1961-2019, satellite data collected by LANDSAT5 satellite for the period 2001-2010, and climate indices data obtained from simulations of an urban climate model (MUKLIMO_3) for the period 2001-2010. Trends in daily mean, maximum, minimum, and seasonal temperatures were analysed by using Sen's slope and the Mann-Kendall test. Results reveal rising trends for all of the studied temperature-related elements. However, it is demonstrated that temperature increase is greatest for the summer season with the highest rise for daily maximum temperatures. The same approach was applied to examine trends of climate indices (summer days and tropical nights), which indicates an increase in the number of both summer days and tropical nights. Results of satellite data of average summer land surface temperatures for the period 2001-2010 indicate that urbanised surfaces and bare rock areas heat up more than natural surfaces with vegetation. Climate indices (summer and hot days, warm evenings, and tropical nights) simulated by the urban climate model MUKLIMO_3 also reveal that, on average, in the city of Dubrovnik urbanised surfaces heat up more than natural surfaces with vegetation and that nocturnal heat load is reduced in lower-density built-up areas.

Study on the maximum and longitudinal distribution of ceiling gas temperature in a naturally ventilated tunnel: The effect of longitudinal fire location

The ceiling gas temperature is an important evaluation indicator for determining tunnel fire hazards. The maximum and longitudinal distributions of the ceiling gas temperature are studied numerically with consideration of the effect of longitudinal fire locations, fire heat release rate, tunnel aspect ratio, and total length of the tunnel. Results show that as the fire moves from the middle of the tunnel to the upstream (left opening), the flame tilts to the downstream (right opening) due to the induced longitudinal flow inside the tunnel. The tilting angle increases as the fire approaching the tunnel opening. Correspondingly, the position of the resulting maximum ceiling gas temperature is shifted from right above the fire source to the downstream side. An offset distance is used to quantify this phenomenon and an empirical equation is proposed to calculate this distance. Meanwhile, the resulting maximum ceiling gas temperature decreases. An empirical equation is also proposed to predict the evolutionary trend of maximum ceiling gas temperature under the effect of the longitudinal fire locations. In addition, asymmetric longitudinal distributions of ceiling gas temperature were observed in the upstream and downstream directions. The ceiling gas temperature decays exponentially in both directions with a lower decay rate on the shorter side (the side with a shorter distance between the fire and the nearest opening). Corresponding correlations for related parameters are proposed for the shorter and longer side, respectively.

ANALYSIS OF SEASONAL AND ANNUAL VARIATIONS OF EXTREME TEMPERATURES AND PRECIPITATION IN ETHIOPIA

One of the most serious challenges in the world is climate change. This study examines variations in seasonal and yearly fluctuations in extreme temperatures and precipitation in Ethiopia from 1987 to 2020 using 36 meteorological stations located in various climatic zones. The outcomes of the study demonstrated increased trends in the average annual maximum and minimum temperatures, with values of 0.094∘C and 0.052∘C, respectively. Despite falling trends in the summer, most stations experienced higher winter temperatures than summer. Furthermore, the analysis revealed a trend toward an increase in the number of rain stations over the summer season, while a trend toward a decrease in the amount of precipitation for a number of stations in the winter season; otherwise, large changes expected in the dega (cold), woina dega (cool), and kola (warm) climatic zones during the summer season did not occur. Precipitation activity has been near normal in most dega (cold), woina dega (cool), and kola (warm) climatic zones over the preceding 33 years. However, precipitation in the berha (hot) climatic zone was lower than average, with fluctuating levels noted throughout the year. The average annual precipitation has been decreasing at a rate of 0.146[Formula: see text]mm per year over the past 33 years, indicating that only the winter season has shown a downward (decreasing) trend, while the other three seasons, such as summer, spring, and autumn, have shown growing trends. Furthermore, Ethiopia’s average annual rainfall continues to be on a downward trend (decreasing).

Spatiotemporal trends in mean and extreme climate variables over 1981–2020 in Meki watershed of central rift valley basin, Ethiopia

Understanding the spatiotemporal changes of climate extremes is essential for managing climatic risk. In the present study, trends of annual and seasonal climate variables along with extreme temperature and precipitation were examined in eight climatic stations of Meki watershed, the Central Rift Valley Basin, Ethiopia during the period 1981 to 2020. A set of 20 precipitation and temperature extreme indices were selected and computed in RClimDex package of the R program to detect climate extreme events. The recent method of Innovative trend analysis, the non-parametric Mann–Kendall trend test, and Sen's slope estimator were applied to evaluate trends of the annual and seasonal precipitation and temperature. The result indicates that the annual precipitation has been decreasing in 71% of climatic stations and 43% of these stations showed a significant trend. The annual minimum temperature declined in 75% of the stations, whereas all stations indicated a significant increasing trend in annual mean maximum temperature. The Mann–Kendall test detected a significant increasing and decreasing trend in most of the temperature and precipitation extreme indices respectively. For the temperature extremes, more frequent warm and fewer cold temperature extremes were observed. In more than 75% of the climatic stations, a considerable drying trend was found for the precipitation extreme indices. Besides, stations with significant warming and drying trends were located in the downstream areas of the watershed. Overall, this study proved that the observed warming trend in mean annual temperature contributed to changes in the normal thresholds of extremes. The change in precipitation and temperature extremes have increased the frequency, intensity, and duration of extreme events in most of the stations. Likewise, climate extreme events that occur more frequently with high intensity are likely to exacerbate climatic risks, which require proper planning of risk management strategies in Meki watershed.

Downscaled Climate Change Projections in Urban Centers of Southwest Ethiopia Using CORDEX Africa Simulations

Projections of future climate change trends in four urban centers of southwest Ethiopia were examined under a high Representative Concentration Pathways (RCP8.5) scenario for near- (2030), mid- (2050), and long-term (2080) periods based on high-resolution (0.220) Coordinated Regional Climate Downscaling Experiment (CORDEX) for Africa data. The multi-model ensemble projects annual maximum and minimum temperatures increasing by 0.047 °C per year (R2 > 0.3) and 0.038 °C per year (R2 > 0.7), respectively, with the rates increased by a factor of 10 for decadal projections between the 2030s and 2080s. The monthly maximum temperature increase is projected to be 1.41 °C and 2.82 °C by 2050 and 2080, respectively. In contrast, the monthly minimum temperature increase is projected to reach +3.2 °C in 2080. The overall seasonal multi-model ensemble average shows an increment in maximum temperature by +1.1 °C and +1.9 °C in 2050 and 2080, with the highest change in the winter, followed by spring, summer, and autumn. Similarly, the future minimum temperature is projected to increase across all seasons by 2080, with increases ranging from 0.4 °C (2030s) to 3.2 °C (2080s). All models consistently project increasing trends in maximum and minimum temperatures, while the majority of the models projected declining future precipitation compared to the base period of 1971–2005. A two-tailed T-test (alpha = 0.05) shows a significant change in future temperature patterns, but no significant changes in precipitation were identified. Changes in daily temperature extremes were found in spring, summer, and autumn, with the largest increases in extreme heat in winter. Therefore, our results support proactive urban planning that considers suitable adaptation and mitigation strategies against increasing air temperatures in urban centers in southwest Ethiopia. Future work will examine the likely changes in temperature and precipitation extremes.

Appraisal of historical trends in maximum and minimum temperature using multiple non-parametric techniques over the agriculture-dominated Narmada Basin, India.

In this study, the long-term trends in climatological parameters, viz., maximum temperature (TMAX) and minimum temperature (TMIN), are determined over 68 years (i.e., June 1951 to May 2019) using the gridded observation datasets (1° × 1° spatial resolution) of India Meteorological Department over the Narmada river basin, India. Multiple non-parametric techniques, viz., modified Mann-Kendall (MMK), Sen's slope (SS), and Spearman's rho (SR) tests, are used to determine monthly, seasonal, and annual trends over individual grids. The trends are also analyzed for the climatic variables spatially averaged over the entire basin to draw general conclusions on historical climate change. The results reveal a significant spatiotemporal variation in trends of TMAX and TMIN over the basin. In general, both the parameters are found to be increasing. Furthermore, the hottest months (April and May) have become hotter, and the coldest month (January) has become colder, implying a higher probability of increasing temperature extremes. Furthermore, the entire duration of 68 years is divided into two epochs of 34 years, i.e., 1951-1984 and 1985-2018, and the trend analysis of TMAX and TMIN is also carried out epoch-wise to better understand/assess the signals of climate change in recent years. In general, a relatively higher warming trend was observed in the latter epoch. As a majority of the basin area is dominated by agricultural lands, the implications of the temperature trends and their impacts on agriculture are succinctly discussed. The information reported in this study will be helpful for proper planning and management of water resources over the basin under the changing climatic conditions.

Analysis of the annual pollen integral in Albuquerque, New Mexico, shows a negative trend with temperatures for Juniper, Cottonwood, Elm, and Mulberry

The goal of this study is to determine if the annual pollen integral (APIn) for the top tree allergens in the City of Albuquerque is correlated with meteorological variables. This analysis would be the first of its kind for this area. We used 17 consecutive years from 2004 to 2020 and data collected by the city of Albuquerque using a Spore Trap (Burkard) volumetric air sampler in a location designed to represent a typical desert environment. The pollen studied include Juniper, Elm, Ash, Cottonwood, and Mulberry. We found a negative linear correlation with early summer temperatures of the previous year and APIn for Elm, Cottonwood, and Mulberry, and early fall temperatures for Juniper. Linear regression models developed for Elm, Cottonwood, and Mulberry used the monthly mean maximum temperature for the month of June of the prior year as the independent variable to yield a R squared statistic (R2) of 0.88, 0.91 and 0.78, respectively. For Juniper, the average monthly mean minimum temperature for the previous September and October served as the independent variable and yielded the R2 value of 0.80. We also observed a positive trend for the annual maximum temperature over time and a negative trend for the total APIn. Summers in New Mexico are hot and dry, and they may be getting hotter and drier because of climate change. Our analysis predicts that climate change in this area may lead to reduced allergies if temperatures continue to increase and if precipitation patterns remain the same.

Adaptive neuro fuzzy inference system (ANFIS) machine learning algorithm for assessing environmental and socio-economic vulnerability to drought: a study in Godavari middle sub-basin, India

Climate change has increased the frequency of drought occurrence in various parts of the world. Drought as a complex phenomenon causes severe impacts on ecological and socio-economic status. Short-term and long-term occurrences of drought have made many regions vulnerable globally. This paper makes an attempt to assess drought vulnerability in Godavari Middle Sub-basin of India. Twenty-four site specific socio-economic and environmental factors were identified based on the extensive literature review. Drought frequency was assessed using standardized precipitation index (SPI). These datasets were divided into training (70%) and testing (30%) data. Frequency ratio (FR) model was utilized to establish relationship among drought conditioning factors and drought frequency. Weights obtained from the FR model were used as input to the adaptive neuro-fuzzy inference systems (ANFIS) model. Drought vulnerability results were validated using the testing data and receiver operating characteristic (ROC). The accuracy of ANFIS models for 1-month (0.957), 3-months (0.882), 6-months (0.964) and 12-months (0.938) showed high suitability of ANFIS model for the assessment of drought vulnerability. The findings revealed that very low normalized difference vegetation index (NDVI) and increasing trend of highest maximum and mean maximum temperature were major environmental factors which influenced high drought vulnerability in the sub-basin. High proportion of area under fallow land, high infant mortality rate (IMR) and moderate literacy rate were identified as major socio-economic factors making watersheds vulnerable during short and long-term droughts. Largest area of the sub-basin was found under high vulnerability for 3-months, followed by 6-months and 12-months droughts. Thus, the study calls for policy intervention towards lessening the impact of drought in highly vulnerable watersheds.

Changes in the means of temperatures and rainfall of the period 1981-2010 with respect to mean values of 1951-80 over the Indian stations

In this paper, the changes in monthly and annual means of maximum temperature, minimum temperature and rainfall at well distributed 178 stations of India for the period 1981-2010 as compared to the respective means of 1951-80, are determined and analysed. To test the significant differences at the station, Student’s t test has been applied.
 Increasing trend in monthly and annual mean maximum temperature is found at most places of southern and western regions of India. There is a decrease in maximum temperature in Indo-Gangetic Plains (IGP) region in January to June months. Significant rise in maximum temperature in all months except August is found at more places in southern part (south of 20° N) of India than northern part(north of 20° N). Significant fall in the temperature is found at a few places of the country. The same trend is found in annual maximum temperature. Minimum temperature has increased at most places of the country in all months except April to June where in it decreased over northern, central and eastern regions. During November to March months, minimum temperature increased more at most places of northern part of the country. Annual minimum temperature has increased at most places of the country except over UK, Significant fall in minimum temperature is observed at some places of the country.
 There is a less change in monthly rainfall all over the country. Annual rainfall slightly decreased at most places of the country except Meghalaya, WB and Kerala where it increased. There is a significant fall in annual rainfall at some places of the country.

Evaluation of Satellite-Based Air Temperature Estimates at Eight Diverse Sites in Africa

High resolution satellite and reanalysis-based air temperature estimates have huge potential to complement the sparse networks of air temperature measurements from ground stations in Africa. The recently released Climate Hazards Center Infrared Temperature with Stations (CHIRTS-daily) dataset provides daily minimum and maximum air temperature estimates on a near-global scale from 1983 to 2016. This study assesses the performance of CHIRTS-daily in comparison with measurements from eight ground stations in diverse locations across Africa from 1983 to 2016, benchmarked against the ERA5 and ERA5-Land reanalysis to understand its potential to provide localized temperature information. Compared to ERA5 and ERA5-Land, CHIRTS-daily maximum temperature has higher correlation and lower bias of daily, annual mean maximum and annual extreme maximum temperature. It also exhibits significant trends in annual mean maximum temperature, comparable to those from the station data. CHIRTS-daily minimum temperatures generally have higher correlation, but larger bias than ERA5 and ERA5-Land. However, the results indicate that CHIRTS-daily minimum temperature biases may be largely systematic and could potentially be corrected for. Overall, CHIRTS-daily is highly promising as it outperforms ERA5 and ERA5-Land in many areas, and exhibits good results across a small, but diverse set of sites in Africa. Further studies in specific geographic areas could help support these findings.

Machine learning-based assessment of long-term climate variability of Kerala.

Studies on historical patterns of climate variables and climate indices have attained significant importance because of the increasing frequency and severity of extreme events worldwide. While the recent events in the tropical state of Kerala (India) have drawn attention to the catastrophic impacts of extreme rainfall events leading to landslides and loss of human lives, a comprehensive and long-term spatiotemporal assessment of climate variables is still lacking. This study investigates the long-term trend analysis (119years) of climate variables at 5% significance level over the state using gridded datasets of daily rainfall (0.25° × 0.25° spatial resolution) and temperature (1° × 1° spatial resolution) at annual and seasonal scales (south-west monsoon, north-east monsoon, winter and summer). Five trend analysis techniques including the Mann-Kendall test (MK), three modified Mann-Kendall tests and innovative trend analysis (ITA) test were performed in the study. It is evident from the trend analysis results that more than 83% of grid points were showing negative trends in annual and south-west monsoon season rainfall series (at a mean rate of 39.70mm and 28.30mm per decade respectively). All the trend analysis tests identified statistically significant increasing trends in mean and maximum temperature at annual and seasonal scales (0.10 to 0.20°C/decade) for all grids. The K-means clustering algorithm delineated 59 grid points into five clusters for annual rainfall, illustrating a clear geographical pattern over the study area. There is a clear gradient in rainfall distribution and concentration inside the state at annual as well as seasonal scales. The majority of annual rainfall is concentrated in a few months of the year. That may lead the state vulnerable to water scarcity in non-rainy seasons.

Potential climate change impact assessment on the hydrology of the Lake Tana Basin, Upper Blue Nile River Basin, Ethiopia

The recent climate change is manifested by human activities, such as increasing global temperature, anomalous rainfall, and extreme fluctuations in the hydrological cycle noticed in different regions of the earth. This study assesses the hydrological changes of Lake Tana Basin under future climatic changes. The study used Statistical Downscaling Model (SDSM) to project future climate change. The basin's hydrology was assessed using the Soil and Water Assessment Tool (SWAT). The SWAT was driven by the outputs of SDSM and calibrated against observed river flow. The results indicate that the maximum and minimum temperature trends are generally in line with the global trends, whereas the precipitation shows an inconsistent pattern. The predictive results from the RCP8.5 radiative forcing scenarios indicate that during the wet season (dry season), the evapotranspiration, streamflow, and base flow will tend to increase by 14.9%, 9.7%, and 20.9% (70.1%, 2.8%, and 16.7%) respectively by the year 2090s. The streamflow curve for the Lake Tana basin's under future climate change shows a steep slope, and stream discharge is highly variable, particularly the surface runoff. This study indicates that although climate change seems uncertain for the study area, preparedness is warranted to avoid the aggravation of soil erosion, water stress and scarcity, and often floods/droughts.

Impact of aerosol concentration on elevation‐dependent warming pattern in the mountains of Nepal

AbstractGreater warming rates in the mountain areas (higher elevations) compared to other parts of the world have drawn the attention of the scientific community in recent years. In this study, we first analyzed elevation‐dependent warming (EDW) patterns based on maximum temperature trends along the south–north temperature gradients of Nepal and then focused on influencing factors of EDW. Nonparametric statistical test was used to identify the warming trend (1970–2016) in each meteorological station along the altitude gradients. Furthermore, aerosol optical depth data was used to observe aerosol concentrations in different seasons across Nepal. Overall, the EDW trend was found positive on the mean annual and seasonal cycle in the study area. It was observed that there was more significant positive correlation of warming rates with altitude below the middle parts of the Lower Hills while a less pronounced correlation above it. This different behavior is attributed to high aerosol concentration on the lower part of this region.

Spatio-Statistical Analysis of Temperature and Trend Detection in Baluchistan, Pakistan

The assessment of temperature variability in any region of the world is important for prior planning in the context of current climate change. The mean monthly, seasonal and annual temperature data of nine meteorological stations was analysed in this study to determine the temperature variability and trend in Baluchistan province, Pakistan. The non-parametric Mann–Kendall and Sen’s slope estimator were applied to investigate the temperature trend pattern in the study Temperature data from the relevant meteorological stations (met-stations) were collected for this purpose from the Pakistan Meteorological Department and the National Center for Environmental Information. The result revealed an increasing significant trend (IST) in the mean annual temperature at Dalbandin, Kalat, Quetta, Zhob and Gawadar meteorological stations. While the seasonal minimum, maximum and mean temperature showed trend fluctuations in winter, spring and autumn seasons. In the seasonal analysis, the increasing trend has been detected in most of the meteorological stations (Dalbandin, Kalat, Quetta, Zhob, Khuzdar, Lasbella, Gawadar) in all four seasons. Whereas in Sibi met-station, a decreasing significant trend (DST) was recorded in summer (minimum, maximum and mean) and the met-station Barkhan recorded decreasing trend in maximum temperature in the autumn season. The Baluchistan province is totally spread over an arid and semiarid area of Pakistan where temperature fluctuations further aggravate the deprived agriculture and sparse natural vegetation.

Climatic Trends of Variable Temperate Environment: A Complete Time Series Analysis during 1980–2020

The western Himalayan region is susceptible to minor climate changes because of its fragile ecology, which might threaten the valley’s prestigious ecosystems and socio-economic components. The Himalayas’s local climate and weather are vulnerable to and interlinked with world-scale climatic changes since the region’s hydrology is predominantly dominated by snow and glaciers. The Himalayas, notably the Jammu and Kashmir region in the western Himalayas, has clearly shown distinct and robust evidence of climate change. This study used observed data to examine the climatic variability and trends of change in precipitation and temperature for the Kashmir valley between 1980 and 2020. Gulmarg, Pahalgam, Kokernag, Qazigund, Kupwara, and Srinagar (Shalimar) meteorological stations in the Kashmir valley were studied in detail for long- and short-term as well as localized fluctuations in temperature and precipitation. The annual temperature and precipitation fluctuations were calculated using Sen’s slope approach, and the sloping trend was determined using linear regression. The research showed statistically insignificant growing trends in maximum and minimum temperatures throughout the Kashmir valley. The average annual temperature in the Kashmir valley increased by 1.55 °C during the last 41 years (from 1980 to 2020), with a higher rise in maximum and minimum temperature by 2.00 and 1.10 °C, respectively. However, precipitation showed a non-significant decreasing trend concerning time series analysis over 1980 to 2020 in Kashmir valley. Results of annual average maximum temperature at all the stations revealed that Pahalgam (2.2 °C), Kokernag (1.8 °C), and Kupwara (1.8 °C) displayed a steep upsurge and statistically significant trends; however, annual average minimum temperature followed an increasing trend from 1980 to 2020 at all the stations except Shalimar. However, non-significant declining trends in precipitation were recorded at all the locations in Kashmir valley. This changing pattern of temperature and precipitation could have significant environmental consequences, affecting the western Himalayan region’s food security and ecological sustainability.