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Abstract Temperature variability may have direct and indirect impacts on the environments of the Accra and Kumasi Metropolises in Ghana. This study analysed temperature and trends in temperature in both cities using in-situ measurements from one meteorological station in both cities from 1986 to 2015. The temperature indices were computed using the RClimdex package from the Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). The temperature time series was pre-whitened before the Mann–Kendall trend and Sen’s slope estimator analysis were applied. Initial analysis revealed minimal variation in temperature in both cities. The results from the analysed temperature indices revealed an increase in warm days and a general rise in the minimum temperature compared to maximum temperatures. Mann Kendall and Sen’s slope revealed significant trends in the annual and seasonal (dry and wet seasons) in minimum temperature in both cities. These might lead to an increased rate of heat-stressed diseases and an overall rise in urban warming in both cities. The analysis of temperature, indices and trends provided comprehensive insights into the temperature of Accra and Kumasi. The results highlight the essence of evaluating temperature indices and trends in light of Climate Change concerns. It is recommended that urban green and blue spaces should be incorporated into land use plans as these policy directions can aid regulate the temperature in both cities.

In order to analyze the changing pattern of rainfall in one of the important district in Kerala, this study concentrated on a crucial meteorological variable: precipitation. Agriculture in this region depends on rain, but because it occurs erratically and without warning, it has an adverse impact on the cropping system and the availability of natural water resources. Non-parametric analysis was used to determine the monthly, seasonal, and annual rainfall variability (trend and slope magnitude) from rainfall data spanning 30 years (1989-2018) on a monthly basis. To determine the strength of a trend for time series data, the Mann-Kendall (MK) Test for monotonic analysis of trend and non-parametric Sen's Slope Estimator were utilized. The past 30 years have been used to create monthly, seasonal, and yearly precipitation trends. The 30-year monthly data was used to generate monthly, seasonal, and yearly precipitation trends. The results of the statistical analysis of the entire reference time series data shows that the trend appears to be primarily positive (growing), both on an annual and seasonal scale. There was a decreasing tendency in the spring, pre-monsoon, and post-monsoon seasons. Individually, the seven months of January through February show a growing tendency, whereas the remaining five months of March through December show a declining trend with 99% and 95% confidence levels, respectively, the annual total rainfall and monsoon seasons demonstrated a positive significant increasing trend.

Aerosols are an inextricably linked component of the atmosphere. Nowadays the study of aerosols has attracted the attention of the world community due to the increasing concerns over air pollution and climate change. Aerosol optical depth (AOD) is the measure of aerosols distributed within the atmospheric column from the Earth's surface to the top of the atmosphere. This study was conducted to examine the trend in AOD between latitudes 22° and 24.62° N, and longitudes 83.26° and 87.01° E, covering the entire part of the Indian state of Jharkhand. Mann–Kendall (MK) trend test and Sen’s slope estimator model were used to examining the trend over 18 years (period: 2000–2017) AOD data obtained from satellite-based sensor namely MODIS. The highest AOD was observed in the north-eastern part, while the lowest was observed in the state’s southwestern part. The mean relative percentage change (RPC) analysis showed that the AOD increased from 20 to 60%. Jharkhand State comprises various sub-regions; all the sub-regions, including major cities, have shown a remarkable positive trend. In particular, Dhanbad, Sahibganj, Chaibasa, Jamshedpur, Ranchi, and Hazaribagh demonstrate statistically significant positive trends (99% confidence level). It was observed that the highest positive trend (0.1228) and the lowest negative trend (−0.02587) were in Sahibganj and Gumla districts, respectively. This study revealed a statistically robust significant correlated pattern of AOD with the variability of meteorological factors.

Recently, trend detection in ambient air pollutants has received a lot of interest, particularly in relation to climatic changes. Air pollutants data that were acquired from monitoring stations from 2015 to 2021 were used in the current investigation. The direction and size of the monotonic trend were determined using the Mann-Kendall test and Sen's slope estimator. The findings showed that there was significant fluctuation in different parameters over time. According to the study, SO2 and NO2 indicate a slightly increasing tendency with approximate annual concentrations of 6mg/m3 and 40mg/m3, respectively, whereas PM2.5 shows a decreasing trend with an approximate annual concentration of 130mg/m3. For all of Odisha's districts, PM10 exhibits no trend, with annual concentrations of about 90mg/m3. The study found that while NO2, PM2.5, and PM10 concentrations were significantly over the standard allowed limits while SO2 concentrations were significantly below them. Specific actions are needed to reduce these pollutants' emissions in Odisha.

Background: The aim of this research was to assess the Humidex (HD) trends as a thermal discomfort index by analyzing meteorological data during a 30-year period of summertime in Iran. Methods: For this purpose, data regarding average temperature and relative humidity were collected daily from 40 different synoptic meteorological stations during a 30-year statistical period (1985-2014). The HD index was calculated based on temperature and relative humidity according to an equation introduced by Masterton and Richardson. The Mann-Kendall and Sen’s slope tests were performed to analyze the changing trend of the HD. Results: Based on the findings, in 72% of the meteorological stations, the HD followed an upward trend, so that 40% of them was statistically significant. The changing trends in temperature during summertime throughout the studied years fluctuated greatly but generally, in many regions such as the arid, semi-arid, and humid regions, this trend was mostly incremental. Also, the changing trends in relative humidity in all regions was decremental throughout the years under study. Conclusion: The changing trend of the HD, which is based on temperature and humidity, was incremental in arid and semi-arid regions and decremental in the Mediterranean and humid regions.

Rainfall is the most important fundamental physical parameter among the climate, as this parameter determines the environmental condition of the particular region, which affects the agricultural productivity. Global warming or climate change, is one of the most important worldwide issues discussed among scientists and researchers. One of the consequences of climate change is the alteration of rainfall patterns and an increase in temperature. The drastic changes in rainfall pattern showed a significant impact on society, and therefore its up-to-date information is needed to estimate the spatial distribution and variability at all points of the territory. In this paper, a study on trend analysis of rainfall data observed at Anasi, Haliyal, Kadra, and Supa rain gauge stations in Karnataka, India, was carried out. For this purpose, the annual 1-day maximum rainfall (AMR) and annual total rainfall (ATR) series were generated from the daily rainfall data and used in trend analysis. A non-parametric Mann-Kendall (MK) test was applied to evaluate the presence of significant trend in AMR and ATR, while the rate of significant trend was computed by Sen's slope estimator (SSE). The MK test results indicated that there is a decreasing trend in AMR series of Anasi, Haliyal, Kadra, and Supa. The study showed that the rate of decreasing trend in the AMR series of Anasi, Haliyal, Kadra, and Supa is computed as 1.4 mm/year, 0.1 mm/year, 0.6 mm/year, and 0.2 mm/year, respectively. For the ATR series, the rate of decreasing trend for Anasi was computed as 23.8 mm/year, whereas 11.2 mm/year for Supa, whereas the rate of increasing trend was 4.3 mm/year for Haliyal and 2.2 mm/year for Supa. This paper illustrated the application of the MK test and SSE for analyzing the trend in AMR and ATR of Anasi, Haliyal, Kadra, with Supa and the results obtained from the study. [ABSTRACT FROM AUTHOR]

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We observed the effect of the La Niña phenomenon on the concentration of water vapor and ozone in the Indonesian region. This aims to the value of water vapor and ozone concentrations due to the La Niña phenomenon using Microwave Limb Sounder (MLS) data from 2004-2022. The La Niña phenomenon was chosen because during La Niña, the sea surface temperature in Indonesia is warmer than normal, thus increasing the evaporation of sea water which result is an increase in the concentration of water vapor in the atmosphere. Concentration values are observed at altitudes of (25.7;30.5;35.3;40.1) km because there are trends in water vapor and ozone concentrations at these altitudes. The La Niña phenomenon is used to see anomalies in water vapor and ozone concentrations from their normal state. La Niña phenomenon is observed based on the ONI index. We found that during La Niña, the water vapor concentration increased from its normal state while the ozone concentration decreased from its normal state. These two concentration values were used to find trends using Mann Kendall and Sen's Slope methods. We found that the trend of water vapor concentration is statistically significant while the trend of ozone concentration is the opposite.

Understanding the spatiotemporal dynamics of climatic conditions within a region is paramount for informed rural planning and decision-making processes, particularly in light of the prevailing challenges posed by climate change and variability. This study undertook an assessment of the spatial and temporal patterns of rainfall trends across various agro-ecological zones (AEZs) within Wolaita, utilizing data collected from ten strategically positioned rain gauge stations. The detection of trends and their magnitudes was facilitated through the application of the Mann–Kendall (MKs) test in conjunction with Sen's slope estimator. Spatial variability and temporal trends of rainfall were further analyzed utilizing ArcGIS10.8 environment and XLSTAT with R programming tools. The outcomes derived from ordinary kriging analyses unveiled notable disparities in the coefficient of variability (CV) for mean annual rainfall across distinct AEZs. Specifically, observations indicated that lowland regions exhibit relatively warmer climates and lower precipitation levels compared to their highland counterparts. Within the lowland AEZs, the majority of stations showcased statistically non-significant positive trends (p > 0.05) in annual rainfall, whereas approximately two-thirds of midland AEZ stations depicted statistically non-significant negative trends. Conversely, over half of the stations situated within highland AEZs displayed statistically non-significant positive trends in annual rainfall. During the rainy season, highland AEZs experienced higher precipitation levels, while the south-central midland areas received a moderate amount of rainfall. In contrast, the northeast and southeast lowland AEZs consistently received diminished rainfall across all seasons compared to other regions. This study underscores the necessity for the climate resilient development and implementation of spatiotemporally informed interventions through implementing region-specific adaptation strategies, such as water conservation measures and crop diversification, to mitigate the potential impact of changing rainfall patterns on agricultural productivity in Wolaita.