Temporal Variation Of Temperature Research Articles

The Influence of Land Cover on Spatio-Temporal Variation of Air Temperature in Grogol District, Central Java – Indonesia

As an urban fringe of Surakarta City-Indonesia, Grogol District is experienced by increasing temperature. The purpose of this study is: 1) to determine the spatial and temporal variations of air temperature in the Grogol District and 2) to determine the difference in air temperature between built-up land cover and non-built-up land cover, particularly rice fields. Air temperature data was obtained by temperature data logger from four sample points on October 27th to December 13th, 2021. Air temperature and land cover data were analyzed by descriptive and inferential statistics as well as spatial interpolation on air temperature data. The result indicates that higher air temperatures are spread over the northern part which is dominated by settlements. Lower air temperatures are found in the southern part which is dominated by rice fields. The temporal variation of air temperature at the four sample points shows almost the same pattern. However, the air temperature was higher in the built-up land cover than in the rice fields. The statistical difference test also showed that there were differences between the two land covers. In conclusion, Grogol District is affected by the urban heat island phenomenon from Surakarta City. This is particularly related to land cover change and increasing population. Therefore, to prevent the increasing temperature, the protection of the open greenspace area should be implemented.

Association of ambient temperature with tuberculosis incidence in Japan: An ecological study

ObjectivesAlthough several studies have investigated the effects of temperature on the incidence of tuberculosis (TB) in a single city or region, few studies have investigated the variations in this association using nationwide data. This study aimed to quantify the association between temporal variations in TB incidence and temperature across Japan. MethodsThe data on the weekly number of newly confirmed TB cases and meteorological variables in 47 Japanese prefectures from 2007 to 2019 were collected. The exposure-response relationships between TB incidence and temperature were quantified using a distributed lag nonlinear model for each prefecture, and estimates from all prefectures were then pooled using a meta-regression model to derive nationwide average associations. ResultsThis study included 335,060 patients with TB. Compared to those with minimum risk temperature on TB incidence (10th percentile at 4.45°C), people who were exposed to the highest temperature concentrations had a 52.0% (relative risk 1.52, 95% confidence interval 1.04-2.23) higher risk for TB incidence at the 99th percentile (30.1°C). Our results also emphasized the heterogeneity of these associations in different prefectures. Conclusions: Strengthening monitoring and public health strategies aimed at controlling temperature-related TB may be more effective when tailored to region-specific meteorological conditions.

Spatial and Temporal Variations in Land Surface Temperature as an Indicator of Learning Comfort Level in Banten Province

Increasing population and rapid development of built-up land can cause an increase in land surface temperature. These changes are often associated with many factors, including changes in land use, and surface parameters, economic development, and vegetation. This research aims to analyze the temperature factor as an indicator of indoor thermal comfort to support the learning process in schools in the Banten Province area. This research uses a spatial temporal approach with descriptive statistical analysis. Based on the results, show that the land surface temperature at each school location in Banten province shows conditions that are not constant. The number of schools with uncomfortable conditions varies from 2019 (89.07%), 2020 (42.65%), 2021 (45.66%), 2022 (82.66%), and 2023 (52.44%). This shows that there has been a decrease in uncomfortable conditions for studying by 36.63% in the last 5 years.

Exploring the impact of tube rotation on the melting performance of multi-tube latent heat storage systems: A numerical investigation

This study explores the impact of tube rotation on the melting performance of a multi-tube latent heat energy storage system through numerical analysis. The system involves a phase change material (PCM) contained within a tube, which absorbs heat from hot water flowing through a tube surrounding the PCM, as well as two tubes enveloped by the PCM. The investigation considers the angle between the line connecting the centers of the two inner tubes and the horizon (α = 0°, 45°, 90°, and 135°), along with the direction of rotation of inner tubes. Results are compared with data from scenarios involving only outer tube rotation and stationary systems. Temporal variations in temperature and liquid fraction contours, along with the temporal evolution of average temperature and average liquid fraction of PCM are presented. It was determined that for each α, the melting performance varied from best to worst across the system configurations as follows: the system with all three rotating tubes, the system with only the outer rotating tube, and the stationary system. The minimum time required to complete PCM melting for cases at α = 0°, 45°, 90°, and 135° is respectively 44.92 %, 42.11 %, 41.32 %, and 40.62 % less than that of the stationary system.

Cryosphere and land cover influence on stream water quality in Central Asia's glacierized catchments

This work helps address recent calls for systematic water quality assessment in Central Asia and considers how nutrient and salinity sources, and transport, affect water quality along the continuum from the cryosphere to the lowland plains. Spatial and, for the first time, temporal variations in stream water pH, temperature, electrical conductivity, and nitrate and phosphate concentrations are presented for four catchments (485–13,500 km2), all with glaciers and major urban areas. The catchments studied were: Kaskelen (Kazakhstan), Ala-Archa (Kyrgyzstan), Chirchik (Uzbekistan) and the Kofarnihon (Tajikistan). Measurements were made in cryosphere, stream water, groundwater, reservoir and lake samples over a 22-month period at fortnightly intervals from 35 sites. The results highlight that glacier, permafrost and rock glacier outflows were primary and secondary nitrate sources (>1 mg N L−1) to the headwaters, and there were major increases in salinity and nitrate concentrations where rivers receive inputs from agriculture and settlements. Overall, the water quality complied with national and World Health Organization standards, however there were pollution hot-spots with shallow urban groundwaters contaminated with nitrate (>11 mg N L−1) and stream electrical conductivity above 800 μS cm−1 in some agricultural areas indicative of high salinity. Phosphate concentrations were generally low (<0.06 mg P L−1) throughout the catchments, though elevated (>0.2 mg P L−1) in urban areas due to effluent contamination. A melt water dilution effect along the main river channels was discernible, in the electrical conductivity and nitrate concentration seasonal dynamics, 100 s of km from the headwaters. Thus, the input of relatively clean water from the cryosphere is an important regulator of main channel water quality in the urban and farmed lowland plains adjacent to the Tien Shan and Pamir. Improved sewage treatment is needed in urban areas.

Effects of internal waves on bottom thermal structures and turbulent mixing in the Xisha Islands

Using velocity and high-resolution temperature mooring data from the fore-reef slope of Yongxing Island in the northwest South China Sea (water depth of 69 m), we examine the effects of internal waves on the temporal variations in temperature, bottom mixed layer (BML) and turbulent mixing. The diurnal tide is found to be the dominant tidal force and the baroclinic tide is highly active, which would account for the 11 d abnormal spring-neap cycle in the barotropic tidal current. During the ebb period (tidal elevation decreases), the bottom diurnal baroclinic current transports cold water upslope, resulting in a decrease in temperature, and vice versa during the flood period. The BML thickness Hbml widely varies around 1.5m, approximately 2% of the water depth. The bottom turbulent mixing is not so active, indicated by the bulk dissipation Eɛ of 10 mWm−2 and turbulent diffusivity κz of 2×10−4m2s−1. Both Hbml and Eɛ approximate a log-normal distribution, demonstrating strong intermittency. The high-frequency (ω) internal bores can increase Hbml by four times and enhance the turbulent mixing by one order, which should be responsible for the slow cascade of Hbml(∼ω−1.5) and Eɛ(∼ω−1.0). In the downslope phase, Hbml is about 30% thicker, and turbulent mixing is enhanced by 3 times stronger than those in the upslope phase. It is revealed that under the forcing of internal waves, turbulent mixing corresponds to a thick BML with Hbml∼〈κz〉0.25, and stratification (N) has a significantly negative correlation with the development of BML, Hbml∼〈N〉−1.8.

Association of temporal variation of land surface temperature and vegetation cover at the Mount Babor forest area, Algeria: a geospatial modeling approach

Association of temporal variation of land surface temperature and vegetation cover at the Mount Babor forest area, Algeria: a geospatial modeling approach

Temporal Variations in Land Surface Temperature within an Urban Ecosystem: A Comprehensive Assessment of Land Use and Land Cover Change in Kharkiv, Ukraine

Remote sensing technologies are critical for analyzing the escalating impacts of global climate change and increasing urbanization, providing vital insights into land surface temperature (LST), land use and cover (LULC) changes, and the identification of urban heat island (UHI) and surface urban heat island (SUHI) phenomena. This research focuses on the nexus between LULC alterations and variations in LST and air temperature (Tair), with a specific emphasis on the intensified SUHI effect in Kharkiv, Ukraine. Employing an integrated approach, this study analyzes time-series data from Landsat and MODIS satellites, alongside Tair climate records, utilizing machine learning techniques and linear regression analysis. Key findings indicate a statistically significant upward trend in Tair and LST during the summer months from 1984 to 2023, with a notable positive correlation between Tair and LST across both datasets. MODIS data exhibit a stronger correlation (R2 = 0.879) compared to Landsat (R2 = 0.663). The application of a supervised classification through Random Forest algorithms and vegetation indices on LULC data reveals significant alterations: a 70.3% increase in urban land and a decrement in vegetative cover comprising a 15.5% reduction in dense vegetation and a 62.9% decrease in sparse vegetation. Change detection analysis elucidates a 24.6% conversion of sparse vegetation into urban land, underscoring a pronounced trajectory towards urbanization. Temporal and seasonal LST variations across different LULC classes were analyzed using kernel density estimation (KDE) and boxplot analysis. Urban areas and sparse vegetation had the smallest average LST fluctuations, at 2.09 °C and 2.16 °C, respectively, but recorded the most extreme LST values. Water and dense vegetation classes exhibited slightly larger fluctuations of 2.30 °C and 2.24 °C, with the bare land class showing the highest fluctuation 2.46 °C, but fewer extremes. Quantitative analysis with the application of Kolmogorov-Smirnov tests across various LULC classes substantiated the normality of LST distributions p &gt; 0.05 for both monthly and annual datasets. Conversely, the Shapiro-Wilk test validated the normal distribution hypothesis exclusively for monthly data, indicating deviations from normality in the annual data. Thresholded LST classifies urban and bare lands as the warmest classes at 39.51 °C and 38.20 °C, respectively, and classifies water at 35.96 °C, dense vegetation at 35.52 °C, and sparse vegetation 37.71 °C as the coldest, which is a trend that is consistent annually and monthly. The analysis of SUHI effects demonstrates an increasing trend in UHI intensity, with statistical trends indicating a growth in average SUHI values over time. This comprehensive study underscores the critical role of remote sensing in understanding and addressing the impacts of climate change and urbanization on local and global climates, emphasizing the need for sustainable urban planning and green infrastructure to mitigate UHI effects.

Simulation analysis of thermal insulation performance of diesel engine piston based on PEO and La2Zr2O7 thermal barrier coating

In this research, we explored the application of ‘thermal swing’ thermal barrier coatings (TBCs) in diesel engines, aiming to surpass the performance of conventional TBCs. Traditional TBCs often suffer from limitations like consistently high surface temperatures and a delayed response to sudden variations in cylinder temperatures, which adversely impact engine efficiency. To overcome these challenges, plasma electrolytic oxidation (PEO) technology was employed to engineer TBCs with the sought-after ‘thermal swing’ feature. Comparative simulations were conducted to assess the thermal characteristics of PEO coatings on pistons, in contrast to standard La2Zr2O7 coatings. The steady-state thermal analysis revealed that PEO coatings maintained a lower peak temperature compared to La2Zr2O7 coatings under similar thermal insulation conditions, indicating a superior ability of the PEO coatings in heat dissipation and in sustaining lower surface temperatures.In the transient thermal analysis, focusing on temporal temperature variations, the PEO coatings exhibited a markedly quicker and more robust response to cylinder temperature fluctuations. This indicates that PEO coatings are highly effective in adapting swiftly to temperature changes, thereby contributing to enhanced engine performance. Additionally, the PEO coating demonstrated a notable reduction in the end temperature (TE), which is crucial for mitigating the heating effect on intake gas, in comparison to La2Zr2O7 coatings with equivalent thermal insulation properties. However, it was observed that this advantage significantly decreased when the PEO coating thickness surpassed 0.3 mm. Drawing from these observations, it is concluded that PEO coatings hold several thermal advantages over La2Zr2O7 coatings, particularly in terms of thermal load management and responsiveness to in-cylinder temperature shifts. These benefits are most pronounced when the PEO coating maintains a thickness below 0.3 mm.

ANALYSIS OF CLIMATE CHANGE EFFECT ON EXTREME PRECIPITATION EVENT IN CONSTANTINE ALGERIA

Extreme precipitation events are critical climatic indicators that offer substantial insights into climate change and its variability. This study aims to investigate whether climate change has impacted precipitation frequencies in the Constantine region of Algeria, known for its semi-arid climate with hot-dry summers and cold-wet winters. Temporal variations of monthly air temperature and precipitation were analyzed from 1981 to 2014. Statistical analysis identified a threshold for estimating monthly extreme precipitation during the period from 1981 to 2005 using the Gumbel distribution method. Additionally, a climatic projection of precipitation for return periods of 50 (t = 50) and 100 (t = 100) years was conducted to forecast extreme precipitation values in the future. The results indicate a gradual increase in precipitation levels during the study period, with values generally remaining below extreme thresholds. This suggests no significant escalation in the occurrence of extreme precipitation events. Furthermore, the findings highlight that climate change has had a more pronounced impact on altering air temperature than on influencing extreme precipitation trends.

Construction of yield loss indicators for cold vortex, light-temperature-water combined stress during the flowering period of rice in Northeast China.

The construction of a yield loss evaluation index for the cold vortex type light-temperature-water composite adversity during rice flowering period in Northeast China is important for elucidating the impacts of cold vortex type composite disasters on rice yield loss in middle and high latitude areas. Moreover, it can provide meteorological support to ensure safe production of high-quality japonica rice in China and contribute to regional disaster reduction and efficiency improvement. By combining growth period data, meteorological data, and yield data, we delineated and constructed the composite stress occurrence index of cold vortex type light-temperature-water at the flowering stage of japonica. We analyzed the relationship between factors causing disasters and yield structure, as well as the relationship between different yield structures and yield by employing BP neural network method. We further dissected the processes involved in the causation of combined disasters. Based on the K-means clustering method and historical typical disaster years, we quantified the critical thresholds and disaster grades, and established an evaluation index and model for assessing yield loss caused by combined stress from cold vortex type light-temperature-water. Finally, we examined the spatial and temporal variations of low temperature, abundant rainfall, and reduced sunlight during the flowering period in the three provinces of Northeast China. Results showed that the critical thresholds for light, temperature, and water stress index during the flowering stage of mild, moderate, and severe cold vortex types were [0, 0.21), [0.21, 0.32), and [0.32, 0.64], respectively. The rates of yield loss were [0, 0.03), [0.03, 0.08), and [0.08, 0.096], respectively. Based on the verification results of a total of 751 samples in 11 random years from 1961 to 2020, the percentage of stations for which the production reduction grade, as calculated by the composite index developed in this study, aligning with the actual production reduction grade was 63.7%, consistently exceeding 58.0% annually. Moreover, the proportion of sites with a similarity or difference level of 1 stood at 88.3%, surpassing 85.0% in each year. The index could effectively assess the extent of rice yield loss caused by cold vortex disasters in Northeast China.

Variability in surface CO2 flux: Implication for monitoring surface emission from geothermal fields

In the last decade the international push for the development of various renewable energy and the increase of the carbon tax for emitters, has put high enthalpy geothermal on a hot seat. Anthropic geothermal emissions in volcanic areas are not negligible due to the inherent nature of their volcanic setting but are counted regardless, similarly to a gas or coal power plant, despite their non-fossil carbon origin. Natural volcanic emissions are however poorly constrained due to the lack of field scale soil CO2 flux assessments. In this study, we analyse the temporal and spatial variations of soil CO2 flux and soil temperature in the Taupō region, Taupō Volcanic Zone, New Zealand, in the light of seasonal variation, field utilisation, and seismicity. Fortnightly monitoring between 2019 and 2023 at 8 sites across the Tauhara and Wairakei geothermal fields provides insight into changes of seasonal variations and geothermal activities. To understand the broader distribution of natural degassing and to compare the CO2 flux over decades, we repeated the CO2 flux survey between 2019 and 2023 and compared to previous results at Karapiti, Wairakei geothermal field (2004, 2018), Ring of Fire, Tauhara geothermal field (2006), and Rotokawa geothermal field (2003, 2011). Similar emissions but a change in the spatial distribution at Tauhara geothermal field suggests that human surface development has affected permeability in the shallow subsurface. In contrast, a similar spatial distribution of flux, but higher emissions, at Karapiti, Wairakei indicates the recovery or modification of reservoir pressure. Finally, a decrease of total emission flux of the natural geothermal features at Rotokawa coincides with the decrease of CO2eq emissions at the power stations. This study showcases the complexity and uncertainties of natural CO2 emission calculations and provides recommendations for future monitoring studies.

Evaporation of acoustically levitated ouzo droplets

An ouzo droplet is a multicomponent liquid comprising ethanol, water, and anise oil, each possessing distinct thermophysical properties, volatility, and mutual miscibility. Evaporation leads to the complex physicochemical process of coupled mass and heat transfer, spontaneous emulsification, and liquid–liquid phase separation, known as the ouzo effect. An acoustically levitated ouzo droplet undergoes five characteristic stages of evaporation based on temporal temperature variation. Such levitated droplet shows a significantly longer lifespan upon evaporation because of the thermal isolation in air, as well as a drastic initial cooling. Sessile droplets, on the other hand, have heat transferred from the surroundings via the substrate to replenish latent heat of vaporization. A conductive substrate thus helps the droplet to stay close to the ambience and a shorter lifespan. A rudimentary theoretical model based on dimensional analysis is developed and shows consistency with measurements.

Temporal and Spatial Variations of Sea Temperature in the Suez Gulf, Egypt

Temporal and Spatial Variations of Sea Temperature in the Suez Gulf, Egypt

Temporal-Spatial Variations Analysis of Surface Temperature in Kalimantan Region for The Period of 2010 - 2020

Surface temperature information is important to study because it affects other climate parameters and has an impact on various sectors. This study aims to analyze the temporal and spatial variations of maximum surface temperature on Kalimantan Region during the period 2010 to 2020. The data used is Surface Maximum Temperature (SMT) in the form of a 0.5o x 0.5o grid from the Climate Prediction Center (CPC) NOAA PCL. The results of the temporal analysis showed that the highest monthly SMT values occurred in May (32.00o C) and September (31.75o C). While the lowest monthly SMT values were found in January (30.88o C) and July (31.40o C). The results of the annual SMT trend analysis show that the surface temperature in the Kalimantan Region has increased at an average rate of 0.03°C per year. This value is higher than the increase in global surface temperature (~0.02°C per year). Based on the results of spatial analysis, it was known that the distribution of SMT on Kalimantan Region tends to be stable in the range of 25o C to 35o C throughout the year. Spatial analysis of SMT in 2011 showed that low values (25o - 31o C) dominated South Kalimantan Province , while high values (33°C - 35°C) dominated West Kalimantan Province. The results of the 2019 SMT spatial analysis revealed a similar pattern to 2011. However, there was a significant increase in temperature compared to 2011, especially in the high SMT values observed in West Kalimantan and East Kalimantan Provinces.

Spatial and Temporal Variations of Temperature in the Punjab Province, Pakistan

Identifying the temperature change at a regional level is one of the essential parameters to determine theintensity of climate change. The current investigation provides an examination of changing trends of temperature in thePunjab province from 1970 to 2019. Sen's slope estimator method is applied to monthly data of mean temperature(Tmean), maximum temperature (Tmax), and minimum temperature (Tmin) to calculate the rate of temperature change.Statistical methods were used to find out the level of significance in terms of negative or positive trends to examine thevariability among various weather observatories. Moreover, predicted values have also been observed for a detailedanalysis of temperature variability and trends. Significant and pronounced changes in the mean temperature (T mean)are distinguished all over the Punjab regions with an increasing trend from North to South Punjab. In the case ofmaximum temperature (Tmax), a faster rate of rising in temperature is observed over the Southern and Western regionsof Punjab. In contrast, the minimum temperature (Tmin) shows an increasing trend in Central Punjab. The findingsprovide detailed insight to policymakers for the planning of mitigating efforts and adaptation strategies in response toclimate change.

Effects of protection and temperature variation on temporal stability in a marine reserve network.

Understanding the drivers of ecosystem stability has been a key focus of modern ecology as the impacts of the Anthropocene become more prevalent and extreme. Marine protected areas (MPAs) are tools used globally to promote biodiversity and mediate anthropogenic impacts. However, assessing the stability of natural ecosystems and responses to management actions is inherently challenging due to the complex dynamics of communities with many interdependent taxa. Using a 12-year time series of subtidal community structure in an MPA network in the Channel Islands (United States), we estimated species interaction strength (competition and predation), prey species synchrony, and temporal stability in trophic networks, as well as temporal variation in sea surface temperature to explore the causal drivers of temporal stability at community and metacommunity scales. At the community scale, only trophic networks in MPAs at Santa Rosa Island showed greater temporal stability than reference sites, likely driven by reduced prey synchrony. Across islands, competition was sometimes greater and predation always greater in MPAs compared with reference sites. Increases in interaction strength resulted in lower temporal stability of trophic networks. Although MPAs reduced prey synchrony at the metacommunity scale, reductions were insufficient to stabilize trophic networks. In contrast, temporal variation in sea surface temperature had strong positive direct effects on stability at the regional scale and indirect effects at the local scale through reductions in species interaction strength. Although MPAs can be effective management strategies for protecting certain species or locations, our findings for this MPA network suggest that temperature variation has a stronger influence on metacommunity temporal stability by mediating species interactions and promoting a mosaic of spatiotemporal variation in community structure of trophic networks. By capturing the full spectrum of environmental variation in network planning, MPAs will have the greatest capacity to promote ecosystem stability in response to climate change.

Experimental study of air cargo temperature variations and its impact on mango quality

An air cargo supply chain for fresh mango was investigated from Thailand to France. Measurements of air temperature, air relative humidity, and fruit (peel) temperature were conducted using thermo-hygrometer data loggers in cartons. In a Unit Load Device (ULD) containing 148 cartons, twenty-seven instrumented cartons were placed at different positions to observe spatial and temporal temperature variations during 12 h cruising. At the destination, mango quality attributes were assessed at different time-points during 15-day storage at 16.1 °C and 21.6 °C. Throughout the supply chain, fruit temperatures ranged from 16.6 °C to 30.5 °C. During cruising, fruit temperatures in upper cartons remained almost constant, whereas base carton temperatures continuously decreased from 26.1 °C to 18.1 °C. Because of a short cruising period in comparison to a storage duration at the destination and proper ambient temperature condition during the experiment, carton position in the ULD had no discernible impact on fruit quality during storage. Fruit stored at 16.1 °C preserved superior fruit quality compared to 21.6 °C storage. For the same storage temperature, better quality of fruits stored in Thailand demonstrated the impact of air shipment on product degradation. The measured temperature and relative humidity evolutions were used as input parameters of a mass loss evolution model. A comparison with the measured data exhibited good agreement (RMSE < 1.8 % mass loss). Considering 10 % mass loss as a critical value, this model allows an estimation of the product shelf life based on a supply chain scenario.

Investigation of the Spatial and Temporal Variation of Temperature and Water Vapor in Lower Troposphere Using the Combined Backward Raman Scattering LiDAR and Lateral Scanning Raman Scattering LiDAR

Investigation of the Spatial and Temporal Variation of Temperature and Water Vapor in Lower Troposphere Using the Combined Backward Raman Scattering LiDAR and Lateral Scanning Raman Scattering LiDAR

Spatiotemporal analysis of seasonal trends in land surface temperature within the distribution range of Moringa peregrina (Forssk.) in Southern and Southeastern Iran.

Temperature fluctuations and related factors are among the main causes of climate change. Understanding the temporal and spatial variations in temperature can shed light on how species respond to climate change. Plants generally persist in suitable microclimates in response to environmental change; however, examining long-term temperature variations within a species' range can be challenging using field observations. Thermal remote sensing, on the other hand, provides multi-scale time-series data with good coverage and regularity to overcome the challenges associated with field observations in environmental monitoring. Although changes in land surface temperature (LST) affect climate, hydrological processes, land-atmosphere interactions, and ecological activities, this metric has not received much research attention. This study aimed to analyze changes in habitat suitability and microclimatic conditions for Moringa peregrina. Seasonal changes in LST within the distribution range of the species were also investigated. To this aim, mean seasonal LST was computed in Google Earth Engine using the daily MODIS/006/MYD13A2 product from 2003 to 2023. Subsequently, a binary habitat suitability map was created based on the true skill statistic (TSS). The Mann-Kendall test was used to analyze seasonal LST trends. Major trends in LST were quantified based on the z-score, and compatibility with habitat suitability was evaluated via GAP analysis and the Kappa index. Seasonal temperature trends were evaluated by comparing each season with the following season using binary comparison. Landforms at presence points were regarded as microclimates and the sensitivity of microclimates to LST was evaluated using two methods: Principal component analysis (PCA) was used to quantify seasonal LST heterogeneity and the random forest (RF) approach was used to evaluate the effect of environmental parameters on habitat suitability within microclimates. The Kappa index revealed a weak overlapping between suitable / unsuitable habitat and the surfaces affected by the trend of changes. Moreover, the suitable habitat of Moringa peregrina in spring, autumn and winter is spatially overlapped by areas that have shown an increasing LST trend, and the presence points have not experienced an increasing temperature trend only in the summer. The findings show that the analysis of seasonal trends in LST provides insights into the effect of LST on habitat suitability and the condition of vegetation. The current study clearly shows that seasonal changes have had a significant impact on the distribution and habitat suitability of M. peregrina, particularly during summer and winter. Improved habitat suitability and range expansion were observed throughout the year. The study also highlights the role of landforms in regulating temperature. Landforms such as local ridges with minimal temperature fluctuations and regions near the Oman Sea were identified as potential future habitats due to favorable humidity conditions.