Maximum Air Temperature Research Articles

Analysis of NASA POWER reanalysis products to predict temperature and precipitation in Euphrates River basin

Receiving climate data from observed ground stations is typically difficult and expensive. This study compares observed data from 9 dispersed weather stations across the Euphrates River Basin, Iraq, to NASA POWER reanalysis products for daily, monthly, and annual precipitation, maximum (Tmax), and minimum (Tmin) air temperatures. Results demonstrated well-reliable for each of the NASA POWER products and observed data for all parameters. The coefficient of determination (R2) for precipitation, maximum temperature, and minimum temperature, respectively, ranges from 0.74 to 0.91, 0.74 to 0.94, and 0.72 to 0.95. The respective ranges for the Nash and Sutcliffe efficiencies (NSE) are 0.74 to 0.84, 0.63 to 0.85, and 0.4 to 0.75. Comparatively, the mean bias error (MBE) lies within the ranges of 0.19 to 1.61, −0.53 to +0.03, and +0.37 to +1.5, respectively. For precipitation products, NASA POWER has produced results on three different timescales that are satisfactory. The accuracy of the NASA product was good in humid regions of the west and northwest, but it declined in arid, and semi-arid regions, like the desert. Results demonstrate that NASA POWER can be effective in creating weather data sets in the absence or inaccessibility of ground weather station data.

Influence of Direct-Downscaling and One-Way Nesting on Daily Mean Air Temperature of Egypt Using the RegCM4

Daily mean air temperature (TMP) is an important indicator for a climate change study and it reflects the daily changes of the maximum and minimum air temperature. Downscaling of a General Circulation Model (GCM) to a regional scale is important to ensure accurate simulation of the TMP. To address this issue, a comparison was conducted between Direct Downscaling (DIR) and one-way nesting (NEST) using a Regional Climate Model (RegCM4) in the period 1997-2017 over Egypt. The ERA-Interim reanalysis of 1.5 degrees (EIN15) was used as the atmospheric forcing to downscale the RegCM4 over Egypt, while the fifth generation ECMWF atmospheric reanalysis was used to evaluate the RegCM4 concerning the Total Cloud Cover (CLT), surface short and longwave radiation fluxes (RSDS and RLDS), ground temperature (TS), sensible heat flux (HFSS) and TMP. Results showed that there was no difference between DIR and NEST regarding the CLT and RSDS; while the NEST overestimated the RLDS more than the DIR particularly in the summer and autumn seasons in comparison with ERA5. Furthermore, the difference between DIR and NEST as the NEST overestimated the TS more than DIR in all seasons and in particular the summer and autumn seasons. This noted overestimation propagated to the HFSS explaining the high warm bias in the simulated TMP; which was higher in NEST than DIR. Such findings suggest that DIR was only affected by uncertainty associated with the EIN15. Additionally, this uncertainty was amplified using NEST because the uncertainty of EIN15 first propagated to the mother domain and then from the mother to the nested one. Despite of observed biases, DIR shows promising results more than NEST. Therefore, DIR can be recommended for future climate studies over Egypt.

Climate Change Effects on Irrigated Corn Growth in the Lower Mississippi Delta

Abstract In this study, the possible climate change impacts on irrigated corn production in the lower Mississippi delta (LMD) region were analyzed. The observed daily maximum and minimum air temperature, wind speed, relative humidity (RH), and precipitation from 1960 to 2018 were used in the analysis. The length of the growing season, evapotranspiration (ET), and crop yield estimates from the precalibrated Root Zone Water Quality Model (RZWQM) were also used. Trend analyses were performed on growing-season averages for temperature, RH, and wind speed; growing-season totals for precipitation and ET; daily values of minimum and maximum temperature; and averages of RH and wind speed at critical corn growth stages. The last day of spring freezing (LDSF) and days with an average daily air temperature Ta of more than 35°C during corn silking were also included in the analysis. The trend analysis was performed using the modified Mann–Kendall test, Pettitt test, and Sen’s slope at a significance level of p ≤ 0.05. The results from our study pointed out increases in minimum Ta, increases in the number of days with Ta exceeding 35°C during the corn silking stage, increases in RH and decreases in ET, advancement of the LDSF by 2 weeks, and 8% reductions in corn yield that could be attributed to changes in climate. If the observed trends in climate (climate variability and change) and yield reductions continue in the region, it could be challenging to grow the corn crop in the LMD profitably. Significance Statement In recent years, growing corn and soybeans instead of cotton has been gaining popularity in the lower Mississippi delta (LMD) region. Our study is aimed to understand how climate change in the recent past (1960–2018) has affected irrigated corn production in LMD. This will help us to better understand the expected consequences of the future climate. We used observations of daily weather data from 1960 to 2018 and corn yield, water balance, and crop yield results from a computer model designed to simulate corn production. Tools were used to analyze trends and patterns in the data and results. Our analysis pointed out significant changes in weather, water balance, and yield decline for irrigated corn in the LMD.

Rancang bangun mesin pengering buah pinang tipe rotari dengan sumber panas api kompor berbahan bahar oli bekas

This study aims to describe the working system and test the performance of the machine, to find out an overview of reducing the moisture content of betel nut dried with a rotary type betel nut dryer machine with a heat source from a used oil-fueled stove fire. The methods used in the study consist of the design stage and the performance test stage. The design stage was to carry out the construction design process, material selection, and fabrication process. While the performance test stage aims to determine the ability of the machine to carry out the betel nut drying process. The results of the design of the rotary type betel nut dryer machine consist of a heating system and a drive system. The heating system uses heat from the used oil-fueled stove and the drive system uses an electric motor connected to the reducer gearbox to rotate the cylinder of the drying chamber. The maximum air temperature generated during the 7-hour performance test process was 108oC with an air flow speed of 3,8 m/s. The results of the design of the drying machine are able to reduce fruit mass by 5.5 kg with a drying rate of 0.785 kg / hour on wet betel nut. The reduction in the moisture content of dried betel nut is directly proportional to the reduction in mass. During the 7-hour drying process, the moisture content of the betel nut is reduced by 55% with a reduction rate of 7.85% / hour

Historic climate change trends and impacts on crop yields in key agricultural areas of the prairie provinces in Canada: a literature review

The objective of this literature review was to compile research findings on climate change and its impacts on crop production in Prairie Provinces of Canada. Our search strategy included finding primary literature articles from various databases. Seven articles reported increases in average and minimum air temperature over time in the Prairie Provinces of Canada. Increases in maximum air temperature were smaller than that for minimum air temperature. Growing degree days and corn heat units also increased over time, which has allowed for potential expansion of corn growth northwards. While overall increases in average annual precipitation and growing season precipitation have occurred in Canada between 1900 and 2021, western Canada showed increases in some regions but decreases in others. Off-season precipitation and snow cover duration in Canada have decreased since 1950. The number of frost-free days has increased across Canada, on the Prairies and southern Saskatchewan since 1900. Annual snowfall has decreased since 1950 and across Canada the annual maximum snow depth has also decreased. Overall, studies focusing on the Prairie Provinces in Canada have shown accelerated changes in several climate parameters over time, affecting cropping areas and crop yields.

A cold wave of winter 2021 in central South America: characteristics and impacts.

The online version contains supplementary material available at 10.1007/s00382-023-06701-1.

Thermal performance assessment of the coaxial pipe evacuated tube solar air heater in Bilaspur climatic conditions

The present era finds the implementation of small-scale solar thermal applications to overcome emissions caused by fossil fuels. In this connection, a forced convection co-axial pipe evacuated tube solar air heater is fabricated and examined under various operating parameters and in Bilaspur Chhattisgarh climatic conditions in the months from October 2021 to March 2022. The performance parameters under consideration were outlet air temperature, collector efficiency, exergy efficiency, and overall system efficiency. The experiments have been performed for different mass flow rates 9.36, 15.84, 18.36, 22.32, and 26.28 kg/h of air. The ambient air temperature varied in the range of 20.8 °C to 41.6 °C. The air temperature at the inlet of the heater varies from 28.4 °C to 66.7 °C. The maximum outlet air temperature and temperature rise recorded were 82.9 °C and 37.2 °C in the month of March and February, respectively, for the low mass flow rate of 9.36 kg/h. It was observed that the maximum collector efficiency, exergy efficiency, and overall system efficiency were achieved as 82.95%, 6.4%, and 81.92%, respectively, for a moderate mass flow rate of 15.84 kg/h. All the performance parameters seem to be strongly dependent on the solar intensity and were found to be highest when the intensity was at its peak value. It is found that the increase in mass flow rates beyond 15.84 kg/h tends to decrease the temperature rise as well as the efficiency of the solar heater. No significant temperature rise is observed for a mass flow rate beyond 26.28 kg/h. The study finds that the fabricated setup can effectively produce a low to moderate temperature range (40 °C–80 °C) and can be used for domestic as well as small-scale industrial applications.

Measurement and evaluation of ambient temperature distribution in Mubi town, Adamawa State, Nigeria

This paper is based on measurement of ambient (air) temperature distribution in Lamurde, Mubi South local government area, Nigeria. HTC-2 digital LCD thermometer and hygrometer electronic meter manufactured by Shenzhen Oway Technology Co. Limited Guangdong, China was used to collect data in the study area and compared with the National Aeronautics and Space Administrative (NASA) values. The results of the research revealed the maximum air temperature of 29.30oC against 33.70oC (NASA). Instat 3 and Microsoft Excel statistical package were used to analyze the data obtained. The results of T-test revealed p value of 0.0009 which is considered as extremely significant at 95% confidence interval and F-test showed that f (0.08) ≤ F (0.42) which revealed that there is no significant difference between the two data because it has 75% correlation coefficient. The study concluded that the data obtained could be used for research purpose and recommended that other sophisticated equipment should be used to validate the data.

Use of Geostatistics as a Tool to Study Spatial-Temporal Dynamics of Leucoptera coffeella in Coffee Crops

Coffee is considered one of the most important commercial commodities globally, and in 2020, it moved to a global market of USD 102.02 billion. However, the attack of pests in coffee production can cause significant economic losses. Leucoptera coffeella is a critical pest in coffee-producing countries, with productivity losses reaching 87%. The knowledge of the spatial distribution patterns of L. coffeella is essential to developing an efficient sampling and control plan. Moreover, it allows us to target for control specific locations/seasons where L. coffeella occurrence is at its highest density before reaching the economic injury level. Therefore, our objective in this study was to determine the spatial distribution of L. coffeella in coffee crops through geostatistical analysis. Data on the population density of L. coffeella were collected over four years on a farm with 18 center pivots located in the Brazilian Cerrado. The presence of L. coffeella was recorded in all 18 pivots during the entire time of the study (2016 to 2020). The highest densities were from July to November. These high densities of L. coffeella positively correlated with maximum air temperatures and wind speed. It was also verified to negatively correlate with minimum air temperatures and rainfall. The surrounding vegetation does not affect the pest densities. The pest hotspots appeared in different pivots and different locations inside pivots. Furthermore, L. coffeella showed an aggregated distribution pattern. For three years, the colonization started at the edge of the crop. The sampling should be performed equidistant as the pest is distributed equally in all directions. The information found in this study provides valuable information to initiate timely management and control methods in coffee crops with a high incidence of L. coffeella, thus reducing production costs and the harmful effects of pesticide use.

Long-term annual climate trends around the Breton Plots area, Alberta: is there any evidence of local climate change?

The objective of this research was to investigate the long-term trends in historical climate variables using the data collected near the classical Breton Plots (Alberta, Canada) and to determine if the data show any evidence of local climate change. The climate data used for the study were obtained from the Alberta Climate Information Service for the years 1901–2020. Various parametric statistical analyses were conducted to determine if monotonic trends occurred in the climate variables over time, and the analyses were conducted on the annual data as well as the 30 year climate normals. Large fluctuations in annual climate variables occurred, but a positive linear trend was observed in the average annual and growing season minimum air temperatures over time. Between 1901 and 2020 the annual minimum air temperature average increased at a rate of 0.3 °C for every 10 years. During the winter periods (December, January, and February, inclusive) from 1901 to 2020, the minimum air temperature average increased at an even higher rate of 0.5 °C every 10 years. Overall, the 30 year climate normals for minimum and maximum air temperatures increased for most seasons. The rates of increase were largest over the winter period, at 0.5 °C every 10 years for minimum air temperature and at 0.3 °C every 10 years for maximum air temperature. Strong linear increases occurred over time for growing degree days, number of frost-free days, total annual precipitation, growing season precipitation, and off-season precipitation.

Eco-friendly management of wheat stripe rust through application of Bacillus subtilis in combination with plant defense activators

Stripe rust (SR) caused byPuccinia striiformisWestend. f. sp.triticiErikss (Pst) is one of the most important and destructive disease of wheat worldwide. In Pakistan, stipe rust appeared as epidemic and is causing huge losses to wheat production. However, wheat breeding programs are not sufficiently advanced to cope with the recently emergedPuccinia striiformisstrains. Under this scenario, current research was carried out for safe, effective and sustainable management of stripe rust of wheat. Seven wheat varieties include Sehar-06, Galaxy-13, Abdul Sattar-02, Faisalabad-08, Johar-16, TD-1 and Ujala-16 were planted at research farm of Muhammad Nawaz Shareef University of Agriculture, Multan, Pakistan during November 2019–20 and 2020–21 to determine their response toward Puccinia striiformis. The fungicide Tilt®, propiconazole, (T2) at the rate of 3 mL per 1500 mL water was used while the Bacillus subtilis (T1) was added at rate of 0.25 mL/1500 mL water with 15 g of dextrose, 0.25 g of chitosan and 0.25 g of salicylic acid in 1500 mL water to make a fine suspension. Our results showed that T1 reduced the disease effectively up to (8.18%) followed by T2 (10.7%) as compared to T0 (23.8%). The correlation between minimum air temperature, relative humidity and disease severity was highly significant while with maximum air temperature it was negatively non-significant. Also, wind speed, solar radiation and rainfall showed non-significant correlation with disease severity. After treatment, application of T1 and T2, minimum air temperature expressed a significant correlation with disease severity on varieties Sehar-2006, Galaxy-13 and Abdul Sattar-02 while non-significant correlation with disease severity on varieties Faisalabad-08, Johar-16, TD-1 and Ujala-16. Similarly, maximum air temperature, relative humidity, wind speed and solar radiation showed non-significant correlation with disease severity while rain fall was negatively non-significant. The current study showed that Bacillus subtilis is an ecofriendly management of stripe rust and its combination with plant defense activators enhance the efficacy and suppress disease. This management strategy is an innovative, and the results obtained will be helpful for better, ecofriendly and effective management of disease.

Cooling energy saving by vegetation planting in high-density districts: Evaluation using the coupled simulation

Urban vegetation is an important factor for urban heat island mitigation, which also contributes to indoor cooling energy reduction. In this study, a one-way coupled simulation method which linked the ENVI-met and Energyplus models was developed to evaluate the impacts of urban vegetation on micro-climate parameters and the building cooling energy consumptions. The simulation results from 27 cases (three typical scenarios with nine vegetation configurations) under extreme hot weather in the summer of Xi'an city, China were compared and analyzed. Compared to that in high-rise blocks, the vegetation in low-rise blocks showed a larger potential at cooling-energy saving. The maximum air temperature reduction around the buildings reached to 0.40 °C, the maximum mean radiant temperature reduction reached to 1.78 °C, and the sensible cooling load of some thermal zones dropped by 2.13%. Although the overall effect of vegetation on decreasing the district cooling load is positive, the evaporation effect and the limited area of vegetation cooling may induce a limited rate on the cooling energy saving, especially in the high-rise blocks. This study provides a method for evaluating the potential of environmental and energy-saving benefits of vegetation planting in different urban blocks, and the result is valuable for planners to balance the costs and benefits of green configurations.

Canopy buffering effects against climatic extremes of deciduous broad‐leaved forests are higher on calcareous than siliceous bedrocks

Forest ecosystems can buffer understorey microhabitats and provide refuges for understorey species in a warming world. These effects are dependent on forest complexity and management. However, the roles of soils and bedrock types are less known although they also may affect forest complexity. We assessed differences in buffering effects of deciduous broad‐leaved forests from calcareous and siliceous soils in the temperate climate of south‐west France predicted to become dryer with climate change. We transplanted during dry and wet years, without and with neighbours (herbaceous and shrubs from forest understories and gaps), six species in gaps and dense forests of the two soil types. Target species originated from contrasting light availabilities and the two soil types. We measured transplant survival, light transmission, air temperature and vapour pressure deficit (VPD) in all treatments. Forest structure and soil parameters were also quantified on both bedrocks. Forest structure complexity was higher and light transmission lower on calcareous than siliceous soils. Relative air humidity was higher and maximum air temperature and VPD lower in the understorey of calcareous than siliceous forests, while soil nutrients and moisture were lower in siliceous soils. We found strong direct facilitation of transplants from shaded habitats by calcareous forest canopies during dry years. Facilitation of forest canopies was much weaker on siliceous bedrocks, during wet years and for species from sunny habitats. Facilitative responses were less obvious but still observed in the presence of understorey neighbours. Calcareous forests showed a stronger buffering ability than siliceous ones due to both higher facilitative effects of calcareous woody dominants and lower survival in calcareous gaps during dry years. Considering that the two forest types were old forests with similar management histories, differences in buffering ability between them were likely due to differences in forest complexity and composition induced by differences in soil types.

Streamflow Composition and the Contradicting Impacts of Anthropogenic Activities and Climatic Change on Streamflow in the Amu Darya Basin, Central Asia

Abstract Transboundary rivers are often the cause of water-related international disputes. One example is the Amu Darya River, with a catchment area of 470 000 km2, which passes through five countries and provides water resources for 89 million people. Intensified human activities and climate change in this region have altered hydrological processes and led to water-related conflicts and ecosystem degradation. Understanding streamflow composition and quantifying the change impacts on streamflow in the Amu Darya basin (ADB) are imperative to water resources management. Here, a degree-day glacier-melt scheme coupled offline with the Variable Infiltration Capacity hydrological model (VIC-glacier), forced by daily precipitation, maximum and minimum air temperature, and wind speed, is used to examine streamflow composition and changes during 1953–2019. Results show large differences in streamflow composition among the tributaries. There is a decrease in the snowmelt component (−260.8 m3 s−1) and rainfall component (−30.1 m3 s−1) at Kerki but an increase in the glacier melt component (160.0 m3 s−1) during drought years. In contrast, there is an increase in the snowmelt component (378.6 m3 s−1) and rainfall component (12.0 m3 s−1) but a decrease in the glacier melt component (−201.8 m3 s−1) during wet years. Using the VIC-glacier and climate elasticity approach, impacts of human activities and climate change on streamflow at Kerki and Kiziljar during 1956–2015 are quantified. Both methods agree and show a dominant role played by human activities in streamflow reduction, with contributions ranging 103.2%–122.1%; however, the contribution of climate change ranges from −22.1% to −3.2%.

Prediction Model for Reference Crop Evapotranspiration Based on the Back-propagation Algorithm with Limited Factors

The precise estimation of reference crop evapotranspiration (ETO) is vital for regional and irrigation water resource management. It is also beneficial to the rational allocation of regional water resources and alleviates the disparity between water supply and demand. This study accurately estimates the ETO of 14 meteorological stations in southern China. Five neural network models (extreme learning machine [ELM], back-propagation neural network [BP], ant colony optimization [ACO]-BP, bird swarm algorithm [BSA]-BP, and cat swarm optimization [CSO]-BP) were introduced to predict ETO with limited factors using different methods. The results demonstrated that models involving T (average, maximum, and minimum air temperature), sunshine duration (n), and relative humidity (RH) exhibited the highest accuracy of all studied combinations; the role of T, n, RH, wind speed (U2) and average atmospheric pressure (AP) regarding ETO gradually decreased. These three biological heuristic algorithms (ACO, BSA, and CSO) each significantly enhanced the capability of the BP model. The accuracy and computational cost of the CSO-BP model are better than those built by other algorithms. Therefore, it is strongly recommended to use the CSO-BP model for ETO estimation in southern China. This result serves as a reference for a more accurate estimation of ETO for future irrigation decision-making and water resource management in southern China.

Towards Thermal-Aware Workload Distribution in Cloud Data Centers Based on Failure Models

Increasing workload conditions lead to a significant surge in power consumption and computing node failures in data centers. The existing workload distribution strategies focused on either thermal awareness or failure mitigation, overlooking the impact of node failures on the energy efficiency of cloud data centers. To address this issue, a new holistic model is built to characterize the impacts of workloads, computing and cooling costs, heat recirculation, and node failure on the energy efficiency of cloud data centers. Leveraging such a holistic model, we propose a novel thermal-aware workload distribution strategy called <i>HGSA</i> that takes node failure into accountand can improve the energy efficiency of cloud data centers. Our empirical findings confirm that (i) faulty nodes lead to a large rise in power consumption, and (ii) failure locations play a vital role in the power consumption of data centers. Experimental results unveil that HGSA is adroit at making near-optimal decisions in workload distribution strategies. In particular, HGSA cuts down the minimum inlet temperature by 5.2 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> -15 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , improves the maximum air temperature of a Computer Room Air Conditioner (CRAC) model by 4.2 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> -26.5 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> , lowers the cooling cost by 15.4 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> -50 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> compared to the existing solutions. Furthermore, HGSA cuts back the total power consumption by 0.65 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> -78 <inline-formula><tex-math notation="LaTeX">$\%$</tex-math></inline-formula> .

A simple method for the estimation of minimum and maximum air temperature monthly mean maps using MODIS images in the region of Murcia, Spain

Air temperature records are acquired by networks of weather stations which may be several kilometres apart. In complex topographies the representativeness of a meteorological station may be diminished in relation to a flatter valley, and the nearest station may have no relation to a place located near it. The present study shows a simple method to estimate the spatial distribution of minimum and maximum air temperatures from MODIS land surface temperature (LST) and normalized difference vegetation index (NDVI) images. Indeed, there is a strong correlation between MODIS day and night LST products and air temperature records from meteorological stations, which is obtained by using geographically weighted regression equations, and reliable results are found. Then, the results allow to spatially interpolate the coefficients of the local regressions using altitude and NDVI as descriptor variables, to obtain maps of the whole region for minimum and maximum air temperature. Most of the meteorological stations show air temperature estimates that do not have significant differences compared to the measured values. The results showed that the regression coefficients for the selected locations are strong for the correlations between minimum temperature with LSTnight (R2 = 0.69–0.82) and maximum temperature with LSTday (R2 = 0.70–0.87) at the 47 stations. The root mean square errors (RMSE) of the statistical models are 1.0 °C and 0.8 °C for night and daytime temperatures, respectively. Furthermore, the association between each pair of data is significant at the 95% level (p&lt;0.01).

ОПЫТНО-АНАЛИТИЧЕСКОЕ ОПРЕДЕЛЕНИЕ КРИТИЧЕСКИХ ТЕМПЕРАТУРНЫХ ТОЧЕК ТЕПЛИЦЫ

In greenhouse, soil is the main heat accumulator, and its rational use is a very urgent task, which can be successfully solved only with full automation of the transfer of the missing thermal energy. To do this, it is enough to determine the following parameters in the greenhouse: the maximum daily temperatures of air and soil inside and outside, the distribution of temperature maxima during the day, the relative position and time of balancing the temperatures of the air and soil half-space in the greenhouse in the morning and in the evening, or the point of reversal of the heat flow. The temperature parameters were determined experimentally over a continuous 11 days, then approximated to third-order polynomial equations with a reliability of 0.92 ... 0.96, and analytical studies were carried out on them. The daily temperature maxima were calculated by equating the first derivatives to zero and solving the quadratic equation. The daily points of heat reversal to the soil and from the soil in time were determined by solving the system of equations for changing the temperature of the soil and the air half-space inside the greenhouse (points of intersection of the graphs). Similarly, from the system of equations, critical points were determined in the time of transition of the temperature of the air half-space inside the greenhouse to the negative zone (t=0ºC). The same method was used to calculate the optimal temperatures in the greenhouse or the moments in time of switching on and off the heat source, for which topt was introduced into the system of equations for each cultivated plant. A differentiated heating system for the greenhouse is proposed in terms of soil heat consumption, which consists in ensuring the minimum supply of additional heat during the daytime optimum and the maximum at nighttime minimum points.

Mapping and Analysis of Monthly Average Maximum and Minimum Air Temperature Distribution of Muğla Province in Geographic Information Systems (GIS) Environment with IDW Method

Muğla province, which is located in Southwest Anatolia and has a surface area of 13,338 km2, generally has a mountainous and rough terrain. In this study, it is aimed to map and analyze the distribution of monthly and annual maximum and minimum average temperature values of Muğla province by using the Inverse Distance Weighted (IDW) interpolation method. For this purpose, meteorological data of 13 stations of the General Directorate of Meteorology in Muğla and the stations of Gölhisar, Bozdoğan, Kaş, Elmalı, which are close to the borders of the province, were used. The average values of the annual and monthly maximum and minimum temperatures of these stations were transferred to the ArcGIS environment with the help of Geographic Information Systems (GIS) and their distribution was mapped with the IDW method. According to these maps, the highest average annual temperature in Muğla is in Milas and its surroundings, while the lowest is the provincial borders in the northeast of Muğla center and Seydikemer district. These two places are followed by Datça district, which is located on a long peninsula. The places with the highest annual minimum average temperatures are around Datça and Marmaris districts, while the lowest is the Burdur provincial border in the northeast of Kavaklıdere and Seydikemer. The maximum average temperature in the province is July (between 41.6-41.1°C in Milas and Köyceğiz), and the lowest is January (between 14-17°C in Muğla center and Kavaklıdere). The minimum average temperatures in the province are highest in June (between 37.7-34.6°C in Marmaris), and the lowest in January (between -7.9 and -6.6°C in Kavaklıdere). Elevation conditions, maritime influence and aspect conditions, and the intrusion of thermal pressure areas, especially in summer, have been effective in the distribution of maximum and minimum average temperature values in the province. These values may also vary depending on time during the year

Air temperature Distribution of Different Features and Urban Typology Blocks of Putrajaya City (Malaysia)

The study examines the effects of heat islands on Putrajaya City and evaluates the planned city features effect since climate policies were not deliberatively considered during the planning process. The aim of this study is to explore the effect of air temperature on the different urban forms and residential areas in the completed construction precincts of Putrajaya Boulevard. The investigation was performed using a mobile survey method with a data logger three times a day, during the morning, noon, and afternoon time, for three days during the hottest month in July 2012. It was found that there is no significant difference in variation of the air temperature between the different city features, and urban typology blocks, and the maximum air temperature was 37 °C. Hence, the temperature has remained constant since before the city was built. Therefore, the climate aspect was not considered during the planning process for reducing the temperature and improving environmental comfort. It is, therefore, necessary to establish a strategy and policy that will reduce the high air temperature before the master plan is completed.