Impact of rapid urbanization on microclimate of urban areas of Pakistan

This paper investigates the temporal and spatial variability of the seasonal mean of maximum air temperature in Romania and its links with the large–scale atmospheric circulation. The Romanian data sets are represented by time series at 14 stations. The large‐scale parameters are represented by the observed sea‐level pressure (SLP) and geopotential height at 500 hPa (Z500). The period analysed was 1922–98 for winter and 1960–98 for all seasons. Before analysis, the original temperature data were tested to detect for inhomogeneity using the standard normal homogeneity test. Empirical orthogonal functions (EOFs) were used to analyse the spatial and temporal variability of the local and large‐scale parameters and to eliminate noise from the original data set. The time series associated with the first EOF pattern of the SLP and mean maximum temperature in Romania were analysed from trend and shifts point of view using the Pettitt and Mann–Kendall tests respectively. The covariance map computed using the Z500 and the seasonal mean of maximum temperature in Romania were used as additional methods to identify the large‐scale circulation patterns influencing the local variability.Significant increasing trends were found for winter and summer mean maximum temperature in Romania, with upward shifts around 1947 and 1985 respectively. During autumn, a decreasing trend with a downward shift around 1969 was detected. These changes seem to be real, since they are connected to similar changes in the large‐scale circulation. So, the intensification of the southwesterly circulation over Europe since 1933 overlapped with the enhancement of westerly circulation after the 1940s could be the reason for the change in winter mean maximum temperature. The slight weakening of the southwesterly circulation during autumn could be one of the reasons for the decrease in the regime of the mean maximum temperature for autumn seasons. Additionally, the covariance map technique reveals the influence of the North Atlantic oscillation in winter, East Atlantic Jet in summer and Scandinavian (or Euroasia‐1) circulation pattern in autumn upon mean maximum air temperature. Copyright © 2002 Royal Meteorological Society.

It is generally assumed that rainfall intensity will increase with temperature increase, irrespective of the underlying changes to the average rainfall. This study documents and investigates long-term trends in rainfall intensities, annual rainfall, and mean maximum and minimum temperatures using the Mann–Kendall trend test for nine sites in eastern Australia. Relationships between rainfall intensities at various durations and 1) annual rainfall and 2) the mean maximum and minimum temperatures were investigated. The results showed that the mean minimum temperature has increased significantly at eight out of the nine sites in eastern Australia. Changes in annual rainfall are likely to be associated with changes in rainfall intensity at the long duration of 48 h. Overall, changes in rainfall intensity at short durations (<1 h) positively correlate with changes in the mean maximum temperature, but there is no significant correlation with the mean minimum temperature and annual rainfall. Additionally, changes in rainfall intensity at longer durations (≥1 h) positively correlate with changes in the mean annual rainfall, but not with either mean maximum or minimum temperatures for the nine sites investigated.

Proportion of oleic acid in olive oil as influenced by the dimensions of the daily temperature oscillation

<p>The present study aims to analyse future changes in mean maximum and extreme temperature over India using 17 regional climate simulations from  CORDEX-SA experiment RCM ensembles at a spatial resolution of 0.5° x 0.5° for mid-term (2041-2060) and long-term (2081-2099) future under RCP 4.5 and RCP 8.5 scenarios. The regional climate simulations of the three RCM ensembles namely IITM-RegCM4, SMHI-RCA4 and MPI-CSC-REMO2009 were first evaluated against observed seasonal maximum temperature (Mar-Jun) during historical period (1971-2005). The datasets were obtained from CCCR-IITM ESGF data node for the study period. The model performance was assessed using standard performance measure statistics such as mean absolute error, root mean square error, mean bias, percentage bias. The RCMs show warm and cold bias in simulating the climatological mean maximum temperature with mean bias ranging from to 8.43°C(warmest) to -37.29°C (coldest) by CNRM-CM5 RCM of IITM-RegCM4 ensemble and by CSIRO-Mk3.6 RCM of SMHI-RCA4 ensemble respectively over the country. Variance scaling bias correction method was applied to correct the bias associated with the RCMs which significantly reduced the RMSE of RCMs from 11.03 (SMHI-RCA4) and 9.17 (IITM-RegCM4) to around zero after bias correction. Future changes assessed in mean maximum temperature show an increase in the range of 0.5°C to 4.5°C during mid-term (2041-2060) and 0.6°C to 5.84°C long-term (2081-2099) future period while under RCP 8.5 the increase ranges from 0.88° C to 5.40° C for mid-term (2041-2060) and 1.31° C to 12.87° C for long-term (2081-2099) period. The most pronounced increase is observed in the northern, eastern and north-eastern region of the country in which highest rise was simulated by IPSL-CM5A-MR(SMHI-RCA4) in northern region of the country for both the scenarios. The study also analyses changes in different ET-SCI indices as a measure of extreme temperature which have increased multi-fold in the future over the country. The study identifies the regions and magnitude of significant climate change signal expected in the mean maximum and extreme temperature in the future. It enhances the understanding and quantification of inter-model uncertainties within CORDEX-SA experiment RCM simulations. The outcomes of the study have both scientific and societal values in building resilience and informed efforts to avert the severe implications posed by increasing extreme temperature and heat events over India.</p><p> </p><p>Keywords: Future Climate Change, CORDEX-SA, Regional Climate Model, Bias Correction, Extreme weather events</p>

Trends (1961–2003) in daily maximum and minimum temperatures, extremes and variance were found to be spatially coherent across the Asia–Pacific region. The majority of stations exhibited significant trends: increases in mean maximum and mean minimum temperature, decreases in cold nights and cool days, and increases in warm nights. No station showed a significant increase in cold days or cold nights, but a few sites showed significant decreases in hot days and warm nights. Significant decreases were observed in both maximum and minimum temperature standard deviation in China, Korea and some stations in Japan (probably reflecting urbanization effects), but also for some Thailand and coastal Australian sites. The South Pacific convergence zone (SPCZ) region between Fiji and the Solomon Islands showed a significant increase in maximum temperature variability.Correlations between mean temperature and the frequency of extreme temperatures were strongest in the tropical Pacific Ocean from French Polynesia to Papua New Guinea, Malaysia, the Philippines, Thailand and southern Japan. Correlations were weaker at continental or higher latitude locations, which may partly reflect urbanization.For non‐urban stations, the dominant distribution change for both maximum and minimum temperature involved a change in the mean, impacting on one or both extremes, with no change in standard deviation. This occurred from French Polynesia to Papua New Guinea (except for maximum temperature changes near the SPCZ), in Malaysia, the Philippines, and several outlying Japanese islands. For urbanized stations the dominant change was a change in the mean and variance, impacting on one or both extremes. This result was particularly evident for minimum temperature.The results presented here, for non‐urban tropical and maritime locations in the Asia–Pacific region, support the hypothesis that changes in mean temperature may be used to predict changes in extreme temperatures. At urbanized or higher latitude locations, changes in variance should be incorporated. Copyright © 2005 Royal Meteorological Society.

In the backdrop of recent warmer winters over India, temperature series of 174 stations well distributed over the country were statistically analyzed to document the long term variations and trends in monthly mean maximum and minimum temperatures for January to March. From the trend analysis, February month has emerged as the warmer winter month over North India where increase in both maximum (+0.29° C / decade) and minimum (+0.38° C / decade) temperatures is highest with noteworthy increase in maximum temperature at a rate 1.5 times that of the South India averaged increase. Spatially, North India minimum temperature trends for February and March and South India maximum temperature trends for all months are more coherent.
 
 Both day-time and night-time total cloud amounts are increasing significantly over Indo-Gangetic plains and south peninsula and decreasing significantly in central and east India. However increase in temperatures over extreme south peninsula in January and March is difficult to explain on the basis of increase in day-time total cloud amount indicating strong influence of other climatic factors. At the same time, sea surface temperatures of the Arabian Sea and the Bay of Bengal are rising and there is strong positive correlation between land surface temperatures and sea surface temperatures suggesting significant contribution of warmer sea waters which may have important climatic implications over neighbouring regions.

Climate change is one of the most important issues among researchers, scientists, planners and politicians in the present times. Of all the climatic elements, temperature plays a major role in detecting climatic change brought about by urbanization and industrialization. This paper, therefore, attempts to study the temperature changes at Dehradun city by analyzing the time series data of annual maximum, minimum and mean temperature from 1967 to 2007. Data for the study has been analyzed in three parts by running linear regression and by taking anomalies for the whole period from 1967 to 2007, phase one 1967–1987 and phase two 1988–2007. The study of linear trend indicated increasing trends in annual maximum, annual minimum and annual mean temperatures. During 1967–2007 annual maximum, annual minimum and annual mean temperatures increased about 0.43°C, 0.38°C and 0.49°C, respectively. The analysis of temperature data in two phases also revealed an increase in annual maximum, annual minimum and annual mean temperature. However, temperature increase in second phase was more pronounced in relation to first phase. During second phase (1988–2007) annual maximum, annual minimum and annual mean temperatures increased about 0.42°C, 0.59°C and 0.54°C, respectively. The perceptible increase in temperature during second phase is mainly attributed to urbanization and industrialization process initiated at Dehradun particularly after becoming the state capital of newly carved out state of Uttarakhand since the year 2000. The analysis also highlight significantly the role of extreme vulnerability of rising temperatures at Dehradun and urban population will constantly be affected by the change in the temperature which controls the comfort level of the inhabitants. Also, the rising temperatures in Doon valley are not a healthy signature for crop production and water resources in the region.

Understanding climatic influences on annual basal area growth (ABAG) rates of individual trees is necessary to predict future stand dynamics. We fitted nonlinear ABAG models for shortleaf pine (Pinus echinata Mill.) with climate variables linearly added to the arguments of logistic and exponential multiplicative functions of climate variables as climate modifiers to incorporate 14 growing seasons and 30 month-specific climate variables including standardized precipitation index. Data were collected from permanently established plots in Arkansas and Oklahoma. Six re-measurement events collected between 1985 and 2014 provided five growth periods (GPs) and ABAG models were fitted using a mixed-effects approach. Model performance was evaluated using likelihood ratio tests and fit statistics. Climate variables from GPs expressed as deviations from long-term means that performed better than other candidate variables included (1) month-specific: June mean maximum air temperature (°C) (DTMAX6), and September precipitation (mm) (DPPT9); and (2) growing seasons: mean maximum air temperature (°C) (DGTMAX) and precipitation (mm) (DGPPT). ABAG models fitted with multiplicative climate modifiers provided improved growth predictions compared with models fitted with climate variables linearly added to the argument of a logistic function. There was positive correlation with DGTMAX and negative correlation with DMPPT. In addition, 1°C increase in mean maximum temperature had a greater cumulative effect on ABAG rates of young versus old trees. Fitting ABAG models with climate modifiers are useful for assessing variations in productivity due to climate change in the future.

This study examines changes in annual and seasonal mean (minimum and maximum) temperatures variations in Jordan during the 20th century. The analyses focus on the time series records at the Amman Airport Meteorological (AAM) station. The occurrence of abrupt changes and trends were examined using cumulative sum charts (CUSUM) and bootstrapping and the Mann-Kendall rank test. Statistically significant abrupt changes and trends have been detected. Major change points in the mean minimum (night-time) and mean maximum (day-time) temperatures occurred in 1957 and 1967, respectively. A minor change point in the annual mean maximum temperature also occurred in 1954, which is essential agreement with the detected change in minimum temperature. The analysis showed a significant warming trend after the years 1957 and 1967 for the minimum and maximum temperatures, respectively. The analysis of maximum temperatures shows a significant warming trend after the year 1967 for the summer season with a rate of temperature increase of 0.038°C/year. The analysis of minimum temperatures shows a significant warming trend after the year 1957 for all seasons. Temperature and rainfall data from other stations in the country have been considered and showed similar changes.

The present study is about the analysis of mean maximum and mean minimum temperatures carried out on annual, seasonal, and monthly timescales examining the data from 15 meteorological stations in Bangladesh for the period 1961–2008. Various spatial and statistical tools were used to display and analyze trends in temperature data. ArcGIS was used to produce the spatially distributed temperature data by using Thiessen polygon method. The nonparametric Mann–Kendall test was used to determine whether there is a positive or negative trend in data with their statistical significance. Sen’s method was also used to determine the magnitude of the trends. The results reveal positive trends in annual mean and mean maximum temperatures with 95 % significance. Trend test reveals that the significant positive trend is found in June to November in case of mean maximum temperature, but according to the mean minimum temperature, the situation is different and a significant positive trend was found from November to February. The analysis of the whole record reveals a tendency toward warmer years, with significantly warmer summer periods and slightly colder winters. These warming patterns may have important impacts on energy consumption, water supply, human health, and natural environment in Bangladesh.

Agriculture is the mainstay of Ethiopian economy. Developing country like Ethiopia suffers from climate change, due to their limited economic capability to build irrigation projects to combat the trouble. This study generates climate change in rift valley basins of Ethiopia for three time periods (2020s, 2055s and 2090s) by using two emission scenarios: SRA1B and SRB1 for faster technological and environmental extreme respectively. First, outputs of 15 General Circulation Models (GCMs) under two emission scenarios (SRA1B and SRB1) are statistically downscaled by using LARS-WG software. Probability assessment of bounded range with known distributions is used to deal with the uncertainties of GCMs’ outputs. These GCMs outputs are weighted by considering the ability of each model to simulate historical records. The study result indicates that LARS-WG 5.5 version model is more uncertain to simulate future mean rainfall than generating maximum and minimum mean temperatures. GCMs weight difference for mean rainfall is 0.83 whereas weight difference for minimum and maximum mean temperatures is 0.09 among GCMs models. The study results indicate minimum and maximum temperatures absolute increase in the range of 0.34˚C to 0.58˚C, 0.94˚C to 1.8˚C and 1.42˚C to 3.2˚C and 0.32˚C to 0.56˚C, 0.91˚C to 1.8˚C and 1.34˚C to 3.04˚C respectively in the near-term (2020s), mid-term (2055s) and long-term (2090s) under both emission scenarios. The expected rainfall change percentage during these three time periods considering this GCMs weight difference into account ranges from -2.3% to 7%, 0.375% to 15.83% and 2.625% to 31.1% in the same three time periods. In conclusion, the study results indicate that in coming three time periods, maximum and minimum temperature and rainfall increase is expected in rift valley of basins of Ethiopia.

Understanding the impact of climate change on water resources is important for developing regional adaptive water management strategies. This study investigated the impact of climate change on water resources in the Yarmouk River Basin (YRB) of Jordan by analyzing the historical trends and future projections of temperature, precipitation, and streamflow. Simple linear regression was used to analyze temperature and precipitation trends from 1989 to 2017 at Irbid, Mafraq, and Samar stations. The Statistical Downscaling Model (SDSM) was applied to predict changes in temperature and precipitation from 2018 to 2100 under three Representative Concentration Pathway (RCP) scenarios (i.e., RCP2.6, RCP4.5, and RCP8.5), and the Soil and Water Assessment Tool (SWAT) was utilized to estimate their potential impact on streamflow at Addasiyia station. Analysis of data from 1989 to 2017 revealed that mean maximum and minimum temperatures increased at all stations, with average rises of 1.62°C and 1.39°C, respectively. The precipitation trends varied across all stations, showing a significant increase at Mafraq station, an insignificant increase at Irbid station, and an insignificant decrease at Samar station. Historical analysis of streamflow data revealed a decreasing trend with a slope of −0.168. Significant increases in both mean minimum and mean maximum temperatures across all stations suggested that evaporation is the dominant process within the basin, leading to reduced streamflow. Under the RCP scenarios, projections indicated that mean maximum temperatures will increase by 0.32°C to 1.52°C, while precipitation will decrease by 8.5% to 43.0% throughout the 21st century. Future streamflow projections indicated reductions in streamflow ranging from 8.7% to 84.8% over the same period. The mathematical model results showed a 39.4% reduction in streamflow by 2050, nearly double the SWAT model’s estimate under RCP8.5 scenario. This research provides novel insights into the regional impact of climate change on water resources, emphasizing the urgent need to address these environmental challenges to ensure a sustainable water supply in Jordan.

Extensive analyses of trends in mean annual and mean seasonal minimum and maximum temperatures and relative humidity were examined for Bawku East, northern Ghana, for the period 1961 to 2012. Mean monthly maximum and minimum temperatures were used to analyse and establish recent temperature trends on an annual and seasonal basis. The year was divided into rainy and dry seasons for the seasonal trends. Mean monthly relative humidity at 6 am and 3 pm from 1961 to 2012 were considered to show recent trends in humidity since temperature and humidity interact to determine the heat exposure for outdoor workers. Regression analysis was used to illustrate trends and calculate mean yearly and seasonal rate of change. A Durbin-Watson statistical test was employed to verify autocorrelation of the residuals of the trend models and none was detected. Results showed a gradual and statistically significant rise in both mean minimum and mean maximum temperatures at two stations (Manga and Garu). There was an inconsistent pattern of trend observed at the third station (Binduri). Declining trends in relative humidity were observed at 6 am and 3 pm at seasonal and annual levels at Binduri and Garu, while there was a rising trend in relative humidity at Manga. The importance of this study hinges on the linkage between heat exposure (temperature and air humidity) and human health in the wake of climate change on outdoor farmers in developing countries who spend many hours doing manual work in the heat. On the whole, the rising temperature has impacted on ecosystem services in the study area.

Temporal and spatial variability of temperature in Emilia-Romagna is described using daily maximum and minimum temperature at 40 stations covering the period 1958 to 2000. Before use, data were quality controlled and tested for inhomogeneity using standard techniques. First, a description of climatological values of maximum and minimum temperature and of their temporal variability is given. Then, frequency of extreme events in temperature is described using 4 indices: 10th percentile of minimum temperature, 90th percentile of maximum temperature, number of frost days and heat wave duration. These indices are based on daily temperature and were computed for all seasons. For each season and each index, the magnitude of trends was estimated by linear regres- sion, while statistical significance was evaluated by Kendall's τ. The analysis reveals the presence of an increase in mean maximum and minimum temperature, especially during winter and summer. Trends were significant in the plain and hill area. Similar tendencies were also observed in the 10th percentile of daily minimum temperature in both seasons, accompanied by a reduction in the num- ber of frost days during winter. Positive trends were detected in the 90th percentile of daily maximum temperature during winter, spring and summer, leading to an increase in the heat wave duration index. These results were significant over almost the whole region, summer being the season charac- terised by the greatest number of stations with significant trends. The spatial variability of frequency of extreme events was analysed using cluster techniques. Finally, the relationship between winter frequency of extreme temperature events in Emilia-Romagna and large-scale Euro-Atlantic circula- tion patterns is briefly described. The results show the presence of significant values of correlation with some of the patterns considered, namely the Eastern Atlantic and European Blocking pattern.

The present paper is an analysis of mean maximum and minimum temperatures carried out on monthly, seasonal and annual time-scales examining the data collected at 171 meteorological stations over a region in the North West of Spain (Castilla y Leon) for the period 1961–1997. Various statistical tools were used to detect and describe significant trends in these data. The magnitude of the trends was derived from the slopes of the regression lines using the least squares method, and the statistical significance was determined by means of the non-parametric Mann-Kendall test. The pattern obtained is quite similar for mean maximum and minimum temperatures with increases in all months of the year, and in the annual series. The seasonal series corresponding to winter and summer also followed this same pattern. Spring and autumn were found to be more irregular. Because maximum temperature increased at a higher rate than minimum temperature in this period, an increase in the annual diurnal temperature range (DTR) was observed. The correlation between the North Atlantic Oscillation (NAO) and the regional maximum and minimum temperatures and DTR series for the period 1961–1997 have also be studied in this paper.