Mean Temperature Trends Research Articles

Climate change impact assessment of variations in temperature trends across India: a case study

ABSTRACT Extreme weather events are becoming more severe and frequent worldwide. This study employs the Mann–Kendall test and Thein-Sen estimator for analysing the mean temperature trend in India’s four densely populated metropolitan cities of New Delhi, Kolkata, Mumbai, and Chennai under representative concentration pathways (RCP) 4.5 and 8.5 scenarios. The trend reveals rising temperatures across four Indian regions with the change being more dominant under RCP 8.5 scenario. By the end of the twenty-first century, RCP 4.5 and 8.5 anticipate a significant rise in mean temperature of 6.0°C and 9.0°C in the Western Himalayas, 5.0°C and 7.5°C in East India and 4.0°C and 7.0°C in the Thar Desert’s south-eastern region. Spatio-temporal variation also indicated the influence of heat waves across different regions of India in the late twenty-first century. There should be relevant long-term and short-term policies to mitigate the effect of climate change and optimise the mortality rate caused by heat stress.

Global warming induced spread of the highest human fascioliasis hyperendemic area

BackgroundClimate change is driving the occurrence of several infectious diseases. Within a One Health action to complement the ongoing preventive chemotherapy initiative against human fascioliasis in the Northern Bolivian Altiplano hyperendemic area, field surveys showed a geographical expansion of its lymnaeid snail vector. To assess whether climate change underlies this spread of the infection risk area, an in-depth analysis of the long-term evolution of climatic factors relevant for Fasciola hepatica development was imperative.MethodsWe used monthly climatic data covering at least a 30-year period and applied two climatic risk indices, the water-budget-based system and the wet–day index, both of verified usefulness for forecasting fascioliasis transmission in this endemic area. To reveal the long-term trends of the climatic factors and forecast indices, we applied procedures of seasonal-trend decomposition based on locally weighed regression and trend analysis on the basis of linear models. To further demonstrate the changes detected, we depicted selected variables in the form of anomalies.ResultsThis study revealed a notorious climatic change affecting most of the hyperendemic area, with a strong impact on crucial aspects of the fascioliasis transmission. Trends in maximum and mean temperatures show significant increases throughout the endemic area, while trends in minimum temperatures are more variable. Precipitation annual trends are negative in most of the localities. Trends in climatic risk indices show negative trends at lower altitudes or when farther from the eastern Andean chain. However, monthly and yearly values of climatic risk indices indicate a permanent transmission feasibility in almost every location.ConclusionsWarmer temperatures have enabled lymnaeids to colonize formerly unsuitable higher altitudes, outside the endemicity area verified in the 1990s. Further, drier conditions might lead to an overexploitation of permanent water collections where lymnaeids inhabit, favoring fascioliasis transmission. Therefore, the present preventive chemotherapy by annual mass treatments is in need to widen the area of implementation. This study emphasizes the convenience for continuous monitoring of nearby zones for quick reaction and appropriate action modification.Graphical

Geostatistical evaluation of the impact of climate variability on malaria incidence In the South-West of Nigeria

Malaria remains a significant health concern in Nigeria, particularly in the South-West region. This study assesses the impact of temperature and rainfall on malaria incidence and prevalence in South-West Nigeria using remotely sensed and modelled data sourced from the Malaria Atlas Project and NASA's POWER database covering 2000 to 2020. The study adopts the Geographically Weighted Regression geostatistical model to establish the relationship between malaria and rainfall and temperature in the study area. The result shows a rising oscillating annual mean temperature trend of 0.0088oC/yr-1 from 2000 to 2020. The malaria incidence exceeds 8 million cases annually, peaking in 2020 at almost 10 million cases. The rising trend of malaria incidence highlights the inadequacy of the malaria intervention programmes to meet their goal of reducing malaria incidence by 40% by 2020. The study highlights the spatial variations, with high incidence in urban centres like Lagos and Ibadan metropolises, their satellite towns, as well as other prominent and capital towns including Oshogbo, Ilesa, Akure, Ijebu-Ode and Abeokuta. Contrary to this, the greater malaria prevalence was recorded in less densely populated areas of Oyo state, Imeko-Afon, Odeda, Yewa and Ijebu-Waterside areas in Ogun state as well as Ose and Idanre in Ondo state. The Geographically Weighted Regression equation model shows a strong positive correlation between malaria prevalence and temperature at a significance of 0.76 compared to rainfall which exhibits no association indicating the relevance of temperature as an explanatory indicator of malaria. With the continuous endemicity of malaria in the South-West, malaria management and control efforts should be focused on high-incidence areas in the South-West and Nigeria in general to fulfil the Sustainable Development Goal of Good health and well-being and the eradication of malaria by 2030.

Climatic and non-climatic factors driving the livelihood vulnerability of smallholder farmers in Ahafo Ano North District, Ghana

Smallholder farmers in Ahafo Ano North District, Ghana, face multiple climatic and non-climatic issues. This study assessed the factors contributing to the livelihood vulnerability of smallholder farmers in this district by household surveys with 200 respondents and focus group discussions (FGDs) with 10 respondents. The Mann–Kendall trend test was used to assess mean annual rainfall and temperature trends from 2002 to 2022. The relative importance index (RII) value was used to rank the climatic and non-climatic factors perceived by respondents. The socioeconomic characteristics affecting smallholder farmers’ perceptions of climatic and non-climatic factors were evaluated by the binary logistic regression model. Results showed that mean annual rainfall decreased (P>0.05) but mean annual temperature significantly increased (P<0.05) from 2002 to 2022 in the district. The key climatic factors perceived by smallholder farmers were extreme heat or increasing temperature (RII=0.498), erratic rainfall (RII=0.485), and increased windstorms (RII=0.475). The critical non-climatic factors were high cost of farm inputs (RII=0.485), high cost of healthcare (RII=0.435), and poor condition of roads to farms (RII=0.415). Smallholder farmers’ perceptions of climatic and non-climatic factors were significantly affected by their socioeconomic characteristics (P<0.05). This study concluded that these factors negatively impact the livelihoods and well-being of smallholder farmers and socioeconomic characteristics influence their perceptions of these factors. Therefore, to enhance the resilience of smallholder farmers to climate change, it is necessary to adopt a comprehensive and context-specific approach that accounts for climatic and non-climatic factors.

Long-term changes in tropospheric temperature in India: Insights from radiosonde measurements, reanalysis data and CMIP6 model projections

The continuous rise in greenhouse gases (GHGs) in the atmosphere is one of the major factors responsible for the global warming and enhanced tropospheric temperature. In this context, we examine the long-term spatiotemporal changes in the tropospheric temperature (1000–100 hPa) in India using radiosonde measurements and the reanalysis data from European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5), Modern-Era Retrospective analysis for Research and Application Version 2 (MERRA2) and National Center for Environmental Prediction (NCEP) for the period 1980–2020. We also investigate the future projections of tropospheric temperature in the Shared Socio-economic Pathways (SSPs) 2–4.5 and 5–8.5 by using the Coupled Model Intercomparison Project 6 (CMIP6) results for the period 2015–2100 over India. Our analysis shows a significant positive trend (0.01–0.04 °C/yr) in the annual mean temperature in the upper troposphere (500–100 hPa) in India during the period 1980–2020. The warming trends are also noticeable in the middle and lower troposphere of India. Among the regions, the northeast, north central and northwest India exhibit significant warming of about 0.01–0.06 °C/yr in the upper troposphere (500–100 hPa). On the other hand, most regions show a decline in temperature at the tropopause (100 hPa), which is stronger in the interior peninsular, north central and east coast of India, at about −0.05 ± 0.01°C/yr. All reanalysis data show consistent warming and cooling trends in the respective regions as observed from the radiosondes, albeit slight differences in their values. The future high emission scenario of SSP5–8.5 shows a warming trend of about 0.04–0.08 °C/yr at 1000–200 hPa by the end of the century, which is highest at 250 hPa. The increasing trend in tropospheric temperature is a serious concern, which calls for adaptation and mitigation measures to alleviate the impacts of this accelerated warming in India.

Trends in temperature and precipitation at high and low elevations in the main mountain ranges of the Iberian Peninsula (1894–2020): The Sierra Nevada and the Pyrenees

AbstractThis study describes temperature and precipitation trends in the two National Parks located in the two highest mountain ranges on the Iberian Peninsula: the Sierra Nevada (Sierra Nevada National Park, SN) and the Pyrenees (Aigüestortes i Sant Maurici National Park, ASM). Special focus is placed on analysing disparities between the lowlands and the highlands, as well as the agreement between observational data and grid data (IBERIA01 and E‐OBS). For this purpose, a quality‐controlled and homogeneity‐adjusted database of the daily maximum temperature, minimum temperature and precipitation (SMADS database) has been generated. Regional trends in mean temperature indicate that warming in ASM (0.17°C·decade−1) was greater than in the Sierra Nevada (SN) (0.13°C·decade−1) in the longest joint period, 1930–2020. For annual precipitation, the trends over the past nine decades were negative, although not significantly. Only the summer in SN showed a significant negative trend, which has intensified in recent decades to −13.4%·decade−1 for 1975–2020. A parallel evolution was observed in the annual mean temperature of the highlands (&gt;1500 m) and lowlands (&lt;1500 m) of ASM, with a common trend of 0.17°C·decade−1, while in SN negative elevation‐dependent warming was detected. Differences between lowlands and highlands were also noted in precipitation trends in both mountain ranges: a positive trend in precipitation was found in the lowlands while in the highlands practically null trends (ASM) or decreasing precipitation trends (SN) were detected. The comparison of the Spanish Mountain Adjusted Daily Series (SMADS) results with the IBERIA01 and E‐OBS grid series yielded differences no greater than ±0.2°C·decade−1. No notable differences were detected between the regional trends calculated with observational series or with grid series. These results worsened when the differences in the trends detected in the individual observed temperature series were compared against the corresponding grid series.

Anthropogenic influence on altitudinally amplified temperature change in the Tibetan Plateau

As the highest plateau on the Earth, the Tibetan Plateau (TP) has experienced rapid warming in the last decades, affecting natural ecosystem and water resources extending far beyond the plateau itself. A distinctive characteristic known as elevation-dependent warming (EDW) in the high mountain regions was particularly pronounced in the TP, whereby the magnitude of temperature warming was amplified with increasing altitudes. Different mechanisms have been proposed to explain this phenomenon, however, the link between the root cause of warming, human activities, and the EDW remains poorly understood. Here we used the homogenized observation and simulations by the newest climate models to discern human influence on both mean and extreme temperatures within the region. An optimal fingerprinting method was applied in a vertical space rather than in traditional horizontal space. We found that the long-term trends in mean and extreme temperature amplified with increasing elevation, with larger magnitude of trends at higher elevations. The response to external forcing, primarily driven by human activities, was robustly detected in altitudinal amplification of temperature increase, providing clear evidence of human causes of EDW. As warming increases, the EDW in the region will continue, with more pronounced EDW corresponding to larger magnitude of warming under a high emission scenario. These findings mark the first evidence of human influence on temperature across different vertical altitudes of climate system.

Statistical Analysis for the Detection of Change Points and the Evaluation of Monthly Mean Temperature Trends of the Moulouya Basin (Morocco)

This study examines the spatiotemporal variability of mean monthly temperature in the Moulouya watershed of northeastern Morocco, highlighting associated trends. To this end, statistical methods widely recommended by climate researchers were adopted. We used monthly mean temperature data for the period 1980–2020 from 9 measuring stations belonging to the Moulouya Watershed Agency (ABHM). These stations were rigorously selected, taking into account their reliability, the length of their records, and their geographical position in the basin. In addition, a quality test and homogenization of the temperature series were carried out using the Climatol tool. The results obtained show a significant upward trend in mean monthly temperature, mainly pronounced during the summer months, in the Moulouya watershed. In fact, Z values generally exceeded the 0.05 significance level at all stations during April, May, June, July, August, and October. According to the results of Sen’s slope test, mean monthly temperatures show an annual increase ranging from 0 to 0.13°C. The maximum magnitude of warming is recorded in July, specifically at Oujda Station. On an overall watershed scale, May, August, and July show a rapid warming trend, with average rates of 0.093, 0.086, and 0.08°C per year, respectively. By contrast, the series for the other months show no significant trend. Significant trend change points were also identified at watershed and station scales, mainly around 2000, primarily for accelerated warming of the summer months.

Why the lower stratosphere cools when the troposphere warms

Observational data have long suggested that in the tropics, when the troposphere locally warms, the lower stratosphere locally cools. Here, the observed anti-correlation between tropospheric and lower stratospheric temperature is confirmed-the lower stratosphere cools by approximately 2 degrees per degree of warming in the mid-troposphere. This anti-correlation is explained through a recently proposed theory holding that there is a quasi-balanced response of the stratosphere to tropospheric heating [J. Lin, K. Emanuel, Tropospheric thermal forcing of the stratosphere through quasi-balanced dynamics. J. Atmos. Sci. (2024).]. The local-scale anti-correlation between tropospheric and lower stratospheric temperature also holds when considering climate change-where the troposphere has been anomalously warming relative to the zonal mean, the lower stratosphere has been anomalously cooling, and vice versa. This suggests that zonally asymmetries in tropospheric temperature trends will be reflected in that of the lower stratospheric temperature trends. The zonally asymmetric trends are also found to be comparable in magnitude to the mean temperature trends in the lower stratosphere, highlighting the importance of the pattern of warming. The results and proposed theory suggest that in addition to forcing via wave-dissipation, the lower stratosphere can also be subject to direct forcing by the troposphere, through quasi-steady, quasi-balanced dynamics.

Warm Arctic–Cold Eurasia pattern driven by atmospheric blocking in models and observations

In recent decades, Arctic-amplified warming and sea-ice loss coincided with a prolonged wintertime Eurasian cooling trend. This observed Warm Arctic–Cold Eurasia pattern has occasionally been attributed to sea-ice forced changes in the midlatitude atmospheric circulation, implying an anthropogenic cause. However, comprehensive climate change simulations do not produce Eurasian cooling, instead suggesting a role for unforced atmospheric variability. This study seeks to clarify the source of this model-observation discrepancy by developing a statistical approach that enables direct comparison of Arctic-midlatitude interactions. In both historical simulations and observations, we first identify Ural blocking as the primary causal driver of sea ice, temperature, and circulation anomalies consistent with the Warm Arctic–Cold Eurasia pattern. Next, we quantify distinct transient responses to this Ural blocking, which explain the model-observation discrepancy in historical Eurasian temperature. Observed 1988–2012 Eurasian cooling occurs in response to a pronounced positive trend in Ural sea-level pressure, temporarily masking long-term midlatitude warming. This observed sea-level pressure trend lies at the outer edge of simulated variability in a fully coupled large ensemble, where smaller sea-level pressure trends have little impact on the ensemble mean temperature trend over Eurasia. Accounting for these differences bring observed and simulated trends into remarkable agreement. Finally, we quantify the influence of sea-ice loss on the magnitude of the observed Ural sea-level pressure trend, an effect that is absent in historical simulations. These results illustrate that sea-ice loss and tropospheric variability can both play a role in producing Eurasian cooling. Furthermore, by conducting a direct model-observation comparison, we reveal a key difference in the causal structures characterizing the Warm Arctic–Cold Eurasia Pattern, which will guide ongoing efforts to explain the lack of Eurasian cooling in climate change simulations.

Limited reversal of regional climate signals in overshoot scenarios

Without stringent reductions in emission of greenhouse gases in the coming years, an exceedance of the 1.5 °C temperature limit is increasingly likely. This has given rise to so-called temperature overshoot scenarios, in which the global mean surface air temperature exceeds a certain limit (i.e. 1.5 °C above pre-industrial levels) before bringing temperatures back below that limit. Despite their prominence in the climate mitigation literature, the implications of an overshoot for local climate impacts is still understudied. Here we present a comprehensive analysis of implications of an overshoot for regional temperature and precipitation changes as well as climate extremes indices. Based on a multi-model comparison from the Coupled Model Intercomparison Project we find that temperature changes are largely reversible in many regions, but also report significant land–ocean and latitudinal differences after an overshoot. For precipitation, the emerging picture is less clear. In many regions the drying or wetting trend is continued throughout the overshoot irrespective of a change in the global mean temperature trend with resulting consequences for extreme precipitation. Taken together, our results indicate that even under a reversal of global mean temperature increase, regional climate changes may only be partially reversed in the decades after peak warming. We thus provide further evidence that overshooting of a warming level implies considerable risks on the regional level.

Unveiling climate change impacts on agricultural sustainability: insights from the united states

Climate change poses significant threats to agricultural systems, necessitating a comprehensive understanding of its impact for effective adaptation strategies. This study examines the influence of climate change on agriculture in the United States, primarily focusing on temperature shifts and precipitation variations. Utilizing historical data and climate projections, we analyse trends in mean temperature and precipitation patterns from 1950 to 2020. The results indicate a noteworthy increase in annual mean temperature over the years, attributed to climate change. This rise in temperature has multifaceted implications, including heat stress in crops and exacerbation of drought conditions. The study also explores the complex relationship between precipitation patterns and climate change, highlighting regional variations and potential shifts in future precipitation trends. By projecting data under SSP 1-1.9 emission scenario, we assess potential changes in mean temperatures, hot days, and precipitation for 2040-2059 periods. In conclusion, this study sheds light on the interplay between climate change and agricultural systems, emphasizing the need for adaptive strategies to secure food production and mitigate potential risks. The findings underscore the urgency of proactive measures to safeguard agricultural sustainability and resilience in the face of evolving climatic conditions.

Assessing the vulnerability of flash floods to climate change in arid zones: Amman–Zarqa Basin, Jordan

Abstract The objective of this study was to evaluate the sensitivity of flash floods to future climate change in the Amman–Zarqa Basin, Jordan. Historical daily rainfall and temperature data from 1970 to 2018 were collected, along with projected daily data derived from general circulation models (GCMs) forecast spanning 2019–2060. The methodology involved analyzing historical and model forecast data, conducting trend analysis, mapping changes in land use, estimating runoff volume, selecting indicators, assigning their weights through the analytical hierarchy process, and generating vulnerability maps. Analysis of precipitation trends revealed a 14.61% decrease in total annual rainfall over the past 48 years; however, future projections indicate a 5.26% increase. Downstream sub-catchments in the arid portion are projected to receive higher rainfall, while upstream sub-catchments are expected to experience a substantial decline, resulting in an overall reduction in runoff. Moreover, our findings demonstrate a rising trend in mean temperature, which is expected to persist. Remote sensing data indicate a 14.76% expansion of urban areas, indicative of rapid population growth. Although no highly vulnerable sub-catchments were identified, downstream sub-catchments 8 and 9 exhibited moderate vulnerability to flash floods, which can be attributed to the increase in rainfall and insufficient stormwater infrastructure.

ТЕКУЩИЕ ТРЕНДЫ ПРИПОВЕРХНОСТНОЙ ТЕМПЕРАТУРЫ ВОЗДУХА В АНТАРКТИДЕ ПО ДАННЫМ РЕАНАЛИЗА И НАЗЕМНЫХ СТАНЦИЙ

This study utilizes monthly-mean records of near-surface air temperature from ground-based stations in Antarctica spanning the time period of 1980 to 2022 to estimate temperature trends in the region. Analysis of in situ data confirms the prevailing warming tendencies over the continent, with positive trends observed at 11 out of the 18 examined stations. Annual mean temperature trends reach 0.40 °C/decade, with the most significant warming observed in the Antarctic Peninsula, West Antarctica, and Inner Antarctica. Relatively weaker and mixed temperature trends occurred in the coastal areas of East Antarctica. Throughout the year, the spring season exhibited the most consistent upward trends across the continent. Comparing current temperature trends with earlier estimates has revealed increased warming at most Antarctic stations in recent years. Four widely used reanalysis datasets – ERA5, JRA55, MERRA2, and CFSR – were examined to evaluate their ability to reproduce the observed temperature trends in situ. Among these four datasets temperature trends inferred from ERA5 provided the best fit to the station data. However, even in ERA5, the uncertainty in trend estimates was comparable to the magnitude of trend variation between stations. This suggests a limited ability of available reanalysis datasets to accurately reproduce the spatial distribution and patterns of temperature trends across the continent.

Long-term air temperature trends in North Cyprus

The Eastern Mediterranean region is a major climate change hotspot. The island of Cyprus is likely to face increases in the frequency and intensity of hotter weather conditions and heatwaves in the near future. Studies conducted on the long-term temperature changes in Cyprus are very limited. Here, we present an updated and most detailed assessment of the maximum, minimum, mean and diurnal temperature series in North Cyprus for the period 1975–2021. Data obtained from the meterological stations of North Cyprus have been analysed using Mann–Kendal (MK) test and Theil–Sen slope estimator. Overall the mean minimum temperature trend (Tmin) showed the highest warming rate 0.61 (0.24 ≤ Tmin ≤ 0.99)°C decade−1 followed by the mean temperature trend (Tmean) 0.38 (0.29 ≤ Tmean ≤ 0.50) °C decade−1 and the mean maximum temperature trend (Tmax) 0.28 (0 ≤ Tmax ≤ 0.50) °C decade−1. The magnitude of the warming trend observed in the overall mean minimum temperature of North Cyprus 0.61 °C decade−1, is one of the fastest warming trends reported in the literature. A negative association was detected between the direction of prevailing winds of North Cyprus and the magnitude of increase in the mean temperature trends of the locations with coastal Mediterranean climate, which has pointed out the importance of prevailing winds regarding their cooling effect in coastal areas. The diurnal temperature range trend of North Cyprus indicates an apparent decrease (− 0.33 °C decade−1). The warming impact of urban heat island effect was detected in temperature trends of Nicosia in the Mesaoria plain. The information provided here is invaluable to consider in any climate assessment and adaptation plan in Cyprus. If the current warming trend persists into the future, it will devastatingly impact all sectors and natural systems in the region.

Population Exposure Changes to Mean and Extreme Climate Events Over Pakistan and Associated Mechanisms.

The increasing prevalence of warmer trends and climate extremes exacerbate the population's exposure to urban settlements. This work investigated population exposure changes to mean and extreme climate events in different Agro-Ecological Zones (AEZs) of Pakistan and associated mechanisms (1979-2020). Spatiotemporal trends in mean and extreme temperatures revealed significant warming mainly over northern, northeastern, and southern AEZs. In contrast, mean-to-extreme precipitation changes showed non-uniform patterns with a significant increase in the northeast AEZs. Population exposure to mean (extreme) temperature and precipitation events increased two-fold during 2000-2020. The AEZs in urban settlements (i.e., Indus Delta, Northern Irrigated Plain, and Barani/Rainfall) show a maximum exposure to extreme temperatures of about 70-100×106 (person-days) in the reference period (1979-1999), which increases to 140-200×106 person-days in the recent period (2000-2020). In addition, the highest exposure to extreme precipitation days also increases to 40-200×106 person-days during 2000-2020 than 1979-1999 (20-100×106) person-days. Relative changes in exposure are large (60%-90%) for the AEZs across northeast Pakistan, justifying the spatial population patterns over these zones. Overall, the observed changes in exposure are primarily attributed to the climate effect (50%) over most AEZs except Northern Irrigated Plain for R10 and R20 events, where the interaction effect takes the lead. The population exposure rapidly increased over major AEZs of Pakistan, which could be more vulnerable to extreme events due to rapid urbanization and population growth in the near future.

Effects of atmospheric aerosols on heat stress over South Asia

The recent trend in global mean temperature is expected to increase the frequency, duration, and intensity of heat waves and heat stress all around the world, especially over the Indian subcontinent. To investigate the plausible mechanisms and implications of meteorological feedback of aerosol forcing on heat stress over South Asia, simulations using a regional climate model (RegCM4) coupled with aerosols were carried out from 2015 to 2019. Generally, extreme heat days are observed mainly over the central and western Indo-Gangetic plains (IGPs) during May. The two heat-humidity indices, wet-bulb temperature (WBT) and heat index (HI), showed moderate effects due to aerosol forcing despite the high aerosol loading during the pre-monsoon. The inclusion of aerosols leads to surface cooling (a reduction in maximum surface temperature), with the highest impact over western India (WI) and the IGP. However, this surface cooling due to aerosols is compensated by an increase in near-surface relative humidity (RH), leading to an increase in WBT and HI. This compensating effect of RH on WBT and HI is greater in WI than that in eastern India. Regional heterogeneity in aerosol-induced changes in heat stress has a strong dependence on land-atmosphere interactions. This study clearly shows that aerosol-induced changes in RH play a decisive role in the assessment of heat stress, which answers the link between the prevalence of high heat stress conditions despite high aerosol loading (surface cooling) over the Indian region.

Estimating Daily Temperatures over Andhra Pradesh, India, Using Artificial Neural Networks

In the recent past, Andhra Pradesh (AP) has experienced increasing trends in surface air mean temperature (SAT at a height of 2 m) because of climate change. In this paper, we attempt to estimate the SAT using the GFDL-ESM2G (Geophysical Fluid Dynamics Laboratory Earth System Model version 2G), available from the Coupled Model Intercomparison Project Phase-5 (CMIP5). This model has a mismatch with the India Meteorological Department (IMD)’s observations during April and May, which are the most heat-prone months in the state. Hence, in addition to the SAT from the model, the present paper considers other parameters, such as mean sea level pressure, surface winds, surface relative humidity, and surface solar radiation downwards, that have influenced the SAT. Since all five meteorological parameters from the GFDL-ESM2G model influence the IMD’s SAT, an artificial neural network (ANN) technique has been used to predict the SAT using the above five meteorological parameters as predictors (input) and the IMD’s SAT as the predictand (output). The model was developed using 1981–2020 data with different time lags, and results were tested for 2021 and 2022 in addition to the random testing conducted for 1981–2020. The statistical parameters between the IMD observations and the ANN estimations using GFDL-ESM2G predictions as input confirm that the SAT can be estimated accurately as described in the analysis section. The analysis conducted for different regions of AP reveals that the diurnal variations of SAT in the IMD observations and the ANN predictions over three regions (North, Central, and South AP) and overall AP compare well, with root mean square error varying between 0.97 °C and 1.33 °C. Thus, the SAT predictions provided in the GFDL-ESM2G model simulations could be improved statistically by using the ANN technique over the AP region.

Evaluation and Projection of Climate Change in the Second Songhua River Basin Using CMIP6 Model Simulations

The aim of this study is to evaluate the performance of the Global Climate Model (GCM) of the Coupled Model Intercomparison Project Phase 6 (CMIP6) in historical simulations of temperature and precipitation. The goal is to select the best performing GCMs for future projection of temperature and precipitation in the Second Songhua River Basin under multiple shared socioeconomic pathways (SSPs). Interannual variability skill (IVS) and Taylor diagrams are used to evaluate the spatiotemporal performance of GCMs against temperature and precipitation data published by the China Meteorological Science Commons during 1956–2016. In addition, five relatively independent models are selected to simulate the temperature and precipitation for 2021–2050 using Hierarchical Clustering. The selected models are CMCC-ESM2, EC-Earth3-Veg-LR, IPSL-CM6A-LR, MIROC-ES2L, and MPI-ESM1-2-HR. The projected results find that SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios show an increasing trend of future annual mean temperature and precipitation. However, for annual precipitation, there is a mixed state of increase and decrease among different models on the seasonal scale. In general, future temperature and precipitation changes still show a trend of growth and uneven distribution in the Second Songhua River Basin, which may be further accelerated by human activities.

Examining the past 120 years’ climate dynamics of Ethiopia

Climate change is one of the environmental threats around the globe. However, this change is not uniform throughout the world, both spatially and temporally. This study, therefore, examined the spatiotemporal (annual and seasonal) variability and trends of rainfall and temperature over Ethiopia from 1901 to 2020. Monthly rainfall and temperature (maximum, minimum, and mean) data were extracted from the latest version of the Climatic Research Unit (CRU 4.05) dataset. Using long-term seasonal rainfall patterns and pixel-based correlation techniques, five homogeneous rainfall zones were identified. The rainfall and temperature from CRU were validated using observed data from 235 and 145 meteorological stations, respectively. The results revealed that inter-seasonal rainfall and temperature variabilities are more pronounced than interannual variabilities in all rainfall zones. Only 19% (215,700 km2) and 3% (33, 900 km2) of the country’s total area experienced statistically significant (α = 0.05) decreasing and increasing trends of rainfall, respectively from 1901 to 2020. A statistically significant decreasing trend in rainfall with time was observed during the summer in only one zone that received rainfall in all months. A precipitation concentration index analysis revealed that the country exhibited a moderate to strongly irregular annual and seasonal rainfall distribution, except during the summer when the rainfall distribution was uniform. There was hence a high degree of rainfall seasonality throughout the study period. In addition to the devastating 1984 nationwide drought, Ethiopia also experienced local droughts for a number of 10 to 20 years. Unlike rainfall, there was a significant (α = 0.05) spatiotemporal increasing trend of temperature over the country. The spatial and temporal increasing trend of mean temperature over 120 years ranged from 0.24oC to 1.92oC and 0.72oC to 1.08oC, respectively. This increasing trend was higher in two zones located in the western and northwest parts of Ethiopia and the inflection points occurred after the 1970s in all zones. It is noteworthy that the maximum temperature increased at a lower rate than the minimum temperature. The warming trends and changes in rainfall patterns are likely to increase the frequency of climate extreme events and impact ecosystem services. This study suggests that climate change-sensitive zones require more attention and further study to enhance awareness of climate change in Ethiopia and facilitate adaptation to climate change and inform actions to mitigate adverse effects.