Average Temperature Trend Research Articles

A Determinação do Perfil Climatológico do Município de Santo Antônio de Pádua-RJ e Sua Aplicabilidade na Recuperação de Áreas Degradadas

The municipality of Santo Antonio de Padua, located in the northwest State of Rio de Janeiro-RJ has been and is currently characterized by economic activities highly degrading the environment. As a consequence of process, it is possible to highlight the decline of springs, reduced biodiversity, increased frequency of floods and changes in temperature and water balance, culminating in a process of desertification in the region.The present study was conducted through analysis of historical series of temperature (1980-1995) and (2001-2010) precipitation (1980-1985) and determined the climatic classification of the municipality according to Thornthwaite methodology, which has also been used in calculating the climatic water balance to estimate water availability in the municipality. The present study aimed to investigate the trends of climatic parameters and their impact on the physical environment, as well as its applicability in planning the recovery of degraded lands. According to the analysis of the water balance and the historical series of temperature and rainfall, the region presents marked water deficit during the winter, when there is an upward trend of average monthly temperatures. Knowing the climatological profile has allowed us to define the best methodological alternatives for reforestation of the region, demonstrating the importance of evaluating these parameters in any kind of recovery planning forest.

Observational evidence of temperature trends at two levels in the surface layer

Abstract. Long-term surface air temperatures at 1.5 m screen level over land are used in calculating a global average surface temperature trend. This global trend is used by the IPCC and others to monitor, assess, and describe global warming or warming hiatus. Current knowledge of near-surface temperature trends with respect to height, however, is limited and inadequately understood because surface temperature observations at different heights in the surface layer of the world are rare especially from a high-quality and long-term climate monitoring network. Here we use high-quality two-height Oklahoma Mesonet observations, synchronized in time, fixed in height, and situated in relatively flat terrain, to assess temperature trends and differentiating temperature trends with respect to heights (i.e., near-surface lapse rate trend) over the period 1997 to 2013. We show that the near-surface lapse rate has significantly decreased with a trend of −0.18 ± 0.03 °C (10 m)−1 per decade indicating that the 9 m height temperatures increased faster than temperatures at the 1.5 m screen level and/or conditions at the 1.5 m height cooled faster than at the 9 m height. However, neither of the two individual height temperature trends by themselves were statistically significant. The magnitude of lapse rate trend is greatest under lighter winds at night. Nighttime lapse rate trends were significantly more negative than daytime lapse rate trends and the average lapse rate trend was three times more negative under calm conditions than under windy conditions. Our results provide the first observational evidence of near-surface temperature changes with respect to height that could enhance the assessment of climate model predictions.

Warming trend analysis for the Aji river basin of Rajkot

The historical records of temperature for Aji river basin (Dist. Rajkot) were collected and the monthly seasonal and annual average of daily maximum, minimum and mean temperature were computed for 32 years (1978–2009). The each time series data of temperature were analyzed for the warming trend analysis and based on that the future scenario of climate was projected. Monthly average of maximum temperature was found decreasing, increasing and no significant during 3, 3 and 6 months, respectively, in a year. While that of minimum temperature indicated significantly decreasing trend in 12 months in a year. In fact, the monthly average of daily mean temperature was found decreased in 11 months and insignificant decreasing trend in 1 month. The seasonal average of maximum temperature showed decreasing trend during monsoon and winter and increasing trend in summer season. However, the highly significant decreasing trend in seasonal average minimum temperature was observed during all of three seasons of the year. Seasonal average of dailymean temperature was found in decreasing trend during winter, summer and monsoon. Annual average of daily minimum and meantemperature could be found significantly decreasing by 0.28°C and 0.15°C per year, whereas maximum temperature was found stable. This indicates that there will not be climate change in this region due to warming if the same temperature trend will continue.

Analysis on Variation Characteristics of Agro-Climatic Resources in Weixian County, China in Recent 54 Years

Based on the daily temperature, precipitation and sunshine data of the National Weather Station of Weixian County, Hebei, China from 1961 to 2014, the average temperature, accumulated temperature, precipitation and sunshine trends of the year and four seasons were analyzed. The results showed an upward trend of the average annual temperature, average annual maximum temperature and average annual minimum temperature and the minimum temperature increase is the largest. The average temperature in summer is decreasing, while the average temperature, maximum temperature and minimum temperature in spring, autumn and winter showed an upward trend. ≥0&#176C accumulated temperature increased by 193.82&#176C for 54 years, and ≥10&#176C accumulated temperature increased 54.59&#176C for 54 years. Weixian County sunshine hours were 119.121 h/10 years to reduce the rate of adverse effects on crop growth; annual precipitation decreased by 116.4 mm for 54 years, the maximum precipitation decreased by 8.2 mm, and the number of annual precipitation decreased 18.6 d, which caused great pressure on groundwater recharge

Chronological Trend of Climate in the Lumle Village Development Committee from Kaski District, Nepal

A study has been conducted to examine how the temperature and precipitation in the Lumle Village Development of Kaski district, Nepal has varied over the thirty years period of 1997-2008. Maximum and minimum temperature and precipitation data were collected from Narayani basin. Maximum and minimum-summer and winter temperatures and precipitation categorized as pre-monsoon, monsoon and post-monsoon were studied with duration of 10 years separately and average annual temperature and precipitation trends of each decade was examined. The trends of temporal variations of temperature and precipitation were analyzed using secular trend of time series analysis with simple linear regression. For almost all decades maximum temperatures were found to be increasing trend whereas most of the minimum temperatures for three decades were found to be decreasing trend except for two events. So, maximum and minimum temperatures were seen increasing trend with average value 0.033 Celsius per year. Extreme temperature event was seen in 2000-2005. Post monsoon precipitation was seen erratic pattern with increasing during first decade and decreasing second and third decades. Pre-monsoon precipitation is constant pattern and trend of precipitation in the first two decades are increasing where as present decade seen decreasing. But average precipitation is increasing trend with rate of 2.5346mm/year because increasing trend of previous two decades outweighs present rate. Extreme drought period was seen in 2005. Actually, it is concluded that Lumle has decreasing trend in total seasonal precipitation and an increasing trend in temperatures. Crossing the Border: International Journal of Interdisciplinary Studies Vol.3(1) 2015: 53-64

On the long-term variability of temperature trends and changes in surface air temperature in Kolkata Weather Observatory, West Bengal, India

the impact of climate change on annual air temperature has received a great deal of attention from clima - tologists worldwide. Many studies have been conducted to illustrate that changes in temperature are becoming evident on a global scale. Air temperature, one of the most important components of climate parameters, has been widely measured as a starting point towards the apprehension of climate change and variability. the main objective of this study is to analyse the temporal variability of mean monthly temperature for the period of 1941 to 2010 (70 years). to detect the magnitude of trend in mean monthly temperature time series, we have used non-parametric test methods such as The Mann-kendall test, often combined with the Theil-Sen's robust estimate of linear trend. Whatever test is used, the user should understand the underlying assumptions of both the technique used to generate the estimates of a trend and the statistical methods used for testing. The results of this analysis reveal that four months - January, February, March and december - indicate a decreasing trend in average temperature, while the remaining eight months have an increasing trend. the magnitude of Mann-Kendall trend statistic Zc for this declining temperature and the magnitude of slope for the months of January, February and december are confirmed at the high significance levels of α = 0.001, 0.01 and 0.1 respectively. Though, the overall trend is positive for monthly as well as seasonally

Spatial variations of aggregate stability in relation to sesquioxides for zonal soils, South-central China

Soil aggregate stability is an important soil property affecting soil functions and erosion. However, there exists some divergence on the relationship between different forms of sesquioxides and aggregate stability, and limited knowledge is available about spatial evolution of aggregate stability under climate conditions (temperature and precipitation) and anthropogenic activities. In this study, the spatial variation and profile distribution of soil aggregate stability and its relation to sesquioxides under cultivation in different zonal soils were investigated. Typical zonal soils in different weathering degrees were selected that were exposed to an increasing trend of annual average temperature and precipitation (from central to south China). These soils contained low organic matter (<3%) and high variation of sesquioxides in different forms (coefficient of variations CVs in 34–104%). Soil free oxides (Fed and Ald) contents showed an increasing trend across the zonal soils with the content of Fed higher than that of Ald. Both amorphous oxides (Feo and Alo) and complex oxides (Fep and Alp) did not present the obvious increasing variation unlike free oxides across the zonal soils. Soil Alp content was higher than Fep content and their complex degrees decreased with soil depth due to complexation with soil organic matter. Soil aggregate stability showed a distinct unimodal trend across the zonal soils and water aggregate stability decreased with soil depth. In general, slaking was the main disruptive force in disaggregation, followed by mechanical breakdown. Multiple stepwise regression analysis showed that complex oxides especially the Alp were strongly related with aggregate stability, synthetically contributing to dry aggregate stability logarithmically and to water stability in a power function. Soil organic matter had a negative effect on dry aggregate stability. Interestingly, it was found that non-complex Fe oxides in amorphous oxides (Feo–Fep) improved water aggregate stability against slaking. More studies are needed to gain more insights into the interaction between soil aggregate stabilization and sesquioxides in future.

Analysis of a piecewise linear trend of average surface temperature in the mathematical model of multifractal dynamics

In this work the model of variations of average annual temperature of the Northern Hemisphere of the Earth is constructed. On its basis, in this research, the main regularities of temporary variability of temperature over the period from 1000 to 2010 have been revealed with the help of application of methods of multi-fractal dynamics. Over the period of 1010 years there were founded 26 periods and for each of them a value of fractal dimension of D was settled. Also, the function of jumps of difference h = D − D0 (where D0 is an equilibrium value of fractal dimension) describing the dynamics of fractal dimension for the period under consideration was constructed. The question of correlation of a historical process and behavior of function h has been discussed. This is the e-book version of the article, published in Russian Journal of Earth Sciences (doi:10.2205/2015ES000551). It is generated from the original source file using LaTeX’s epub.cls class.

Analysis of monthly, seasonal and annual air temperature variability trends in Junagadh (Saurashtra region) of Gujarat

Climatic change is one of the most important issues of present times, therefore, world-wide interest in global warming and climate change has led to numerous trend detection studies. Anthropogenic interference in the environment is one of the greatest causes of the process of climatic change in several regions of the world. This study focuses on the variability and trends of the mean annual, seasonal and monthly surface air temperature in Junagadh (Saurashtra region) of Gujarat, during the period 1980-2011. This study investigated monthly, seasonal and annual climatic variability in Junagadh (Saurashtra region) of Gujarat based on mean maximum, mean minimum and mean air temperatures. One of the main results of this study was the confirmation of a significant warming trend in average temperatures in Junagadh (Saurashtra region) of Gujarat. Analysis of maximum and minimum temperatures revealed a warming trend for the annual and all seasonal series. The warming trend for the summer and winter seasons was statistically significant at P < 0.01 level with a rate of increase of 0.006 C/year and less 0.055C/year. The air temperature time series were analyzed, so that the variability and trends can be described.

A climatic deconstruction of recent drought trends in the United States

We present high spatial-resolution trends of the Palmer drought severity index (PDSI), potential evapotranspiration (PET), and selected climate variables from 1979–2013 for the contiguous United States in order to gain an understanding of recent drought trends and their climatic forcings. Based on a spatial grouping analysis, four regions of increasing (upper Midwest, Louisiana, southeastern United States (US), and western US) and decreasing (New England, Pacific Northwest, upper Great Plains, and Ohio River Valley) drought trends based on Mann–Kendall Z values were found. Within these regions, partial correlation and multiple regression for trends in climate variables and PDSI were performed to examine potential climatic controls on these droughts. As expected, there was a US-wide concurrence on drought forcing by precipitation. However, there was correspondence of recent PET trends with recent drought trends in many regions. For regions with an increase in recent droughts, average air temperature was generally the second most important variable after precipitation in determining recent drought trends. Across the regions where recent drought trends are decreasing, there was no clear ranking of climate-variable importance, where trends in average temperature, specific humidity and net radiation all played significant regional roles in determining recent drought trends. Deconstructing the trends in drought show that, while there are regions in the US showing positive and negative trends in drought conditions, the climate forcings for these drought trends are regionally specific. The results of this study allow for the interpretation of the role of the changing hydroclimatic cycle in recent drought trends, which also have implications for the current and impending results of climate change.

Global hourly land surface air temperature datasets: inter‐comparison and climate change

ABSTRACTThe land surface air temperature (LSAT) is one of the fundamental parameters to represent heat transfer and to modulate the moisture cycle between land and atmosphere. Here, we quantify the spatiotemporal characteristics of four newly developed hourly temperature products by merging reanalysis with in situ data Climatic Research Unit (CRU). Overall, LSATs from different hourly products are consistent with each other, and their differences are generally smaller in magnitude than biases between hourly products and monthly averaged daily maximum and minimum temperature data from CRU. While the true monthly mean (using hourly values) and the monthly mean (of daily maximum and minimum temperatures) and their seasonality [as represented by the (July–January) differences] differ, their trends agree with each other very well. The polar amplification ratio of average temperature trend north of 65°N to that over global land (excluding Greenland and Antarctica) is also similar among different products, with the annual ratio of around 1.7. The ratio in summer (June–August) is always smaller than the annual value for different periods among all products. Based on the probability distribution functions from the monthly anomalies of different variables, the coldest tenth percentile of temperature in each decade overall increases with time, while the warmest tenth percentile does not vary much from 1950–1979, followed by a rapid increase from 1980–2009. These results and additional sensitivity tests suggest that the 4‐h LSAT products can be widely used for climate analysis, model evaluation, and offline land surface modelling from 1948–2009.

Influence of Sunspots on Global Mean Surface Temperature

The influence of variations in solar activity on earth's surface temperature is a key question in climate-change attribution. On the basis of natural cyclic sea surface temperatures and the annual mean daily sunspot number as a proxy for variability in solar influence on the energy retained by the planet, a predictive equation derived from well-understood physical principles proves capable of reproducing observed anomalies in annual global mean surface temperature since before 1900 with 90% accuracy (R2 = 0.9049). This accuracy results even where a zero-contribution from changes in greenhouse-gas concentrations is assumed. Here we show that the cumulative influence of the unusually elevated solar activity in the 64 years 1941–2005, as calculated using the time-integral of sunspot number anomalies (with a proxy factor) might have been a primary cause of the global warming observed through 2001. After 2001 the low solar activity is consistent with the observed flat average global temperature trend. The physically-based predictive equation, with the widely-projected decline in solar activity, moderated by the substantial effective thermal capacitance of the planet, especially the oceans, projects a downtrend steeper than 0.1K/decade.

A model for global diversity in response to temperature change over geological time scales, with reference to planktic organisms.

There are strong propositions in the literature that abiotic factors override biotic drivers of diversity on time scales of the fossil record. In order to study the interaction of biotic and abiotic forces on long term changes, we devise a spatio-temporal discrete-time Markov process model of macroevolution featuring population formation, speciation, migration and extinction, where populations are free to migrate. In our model, the extinction probability of these populations is controlled by latitudinally and temporally varying environment (temperature) and competition. Although our model is general enough to be applicable to disparate taxa, we explicitly address planktic organisms, which are assumed to disperse freely without barriers over the Earth's oceans. While rapid and drastic environmental changes tend to eliminate many species, generalists preferentially survive and hence leave generalist descendants. In other words, environmental fluctuations result in generalist descendants which are resilient to future environmental changes. Periods of stable or slow environmental changes lead to more specialist species and higher population numbers. Simulating Cenozoic diversity dynamics with both competition and the environmental component of our model produces diversity curves that reflect current empirical knowledge, which cannot be obtained with just one component. Our model predicts that the average temperature optimum at which planktic species thrive best has declined over the Neogene, following the trend of global average temperatures.

Statistical inquiry into the causes of global temperature changes

Observed changes in average global temperatures over time have led to two general avenues of discussion in the environmental literature. The scientific community has concentrated on the statistical detection of global warming and the determination of biological and industrial factors causing average world temperatures to rise. A second avenue of thought considers the issue of economic abatement by attempting to measure the pecuniary costs of global warming and the elimination of factors influencing this problem. This paper concentrates not on developing an economic model of global warming and environmental damage, but rather on examining the problem from a purely statistical vantage point. Utilising annual data from 1950 to 1991 and optimally determined vector auto regression specifications, it is shown that general industrial growth and greenhouse gas emission levels statistically cause a persistent increase in average global temperatures. In addition, this analysis shows that increasing average world temperatures have a statistically significant negative causal impact on agricultural productivity. Given that global warming is a long–term process culminating from decades of industrial activity, statistically significant causal results derived in this paper using short term data are interesting. Statistical results suggest that trends in average temperatures respond to short–run fluctuations in industrial activity and population growth.

Spatial analysis of the temperature trends in Serbia during the period 1961–2010

The spatial analysis of annual and seasonal temperature trends in Serbia during the period 1961–2010 was carried out using mean monthly data from 64 meteorological stations. Change year detection was achieved using cumulative sum charts. The magnitude of trends was derived from the slopes of linear trends using the least square method. The same formalism of least square method was used to assess the statistical significance of the determined trends. Maps of temperature trends were generated by applying a spatial regression method to visualize the detected tendencies. The obtained results indicate a negative temperature trend for the period before the change year except for winter and a more pronounced positive trend after the change year. Besides being more pronounced, the vast majority of trends after the change year were also clearly statistically significant. Our estimate of the average temperature trend over Serbia is in agreement with those obtained at the global and European scale. Calculated global autocorrelation statistics (Moran’s I) indicate an apparent random spatial pattern of temperature trends across the Serbia for both periods before and after the change year.

Assessment of forced responses of the Australian Community Climate and Earth System Simulator (ACCESS) 1.3 in CMIP5 historical detection and attribution experiments.

The Australian Community Climate and Earth System Simulator (ACCESS) coupled climate model version 1.3 participated in phase five of the Coupled Model Intercomparison Project (CMIP5) with an initial contribution of high priority experiments. Further standard experiments have since been conducted with ACCESS1.3, including an ensemble of three simulations for the historical period (1850-2005) forced with time-evolving natural and anthropogenic forcings. Additional ensembles of simulations have been conducted for the same period with subsets of known forcings, including with natural forcings only ('historicalNat') and with greenhouse gas forcings only ('historicalGHG'). In this study, we describe this ACCESS1.3 contribution to CMIP5 and assess several key aspects of ACCESS1.3 forced responses in these experiments against observations and an ensemble of participating CMIP5 models, consisting of 40 realisations from ten models. Overall, ACCESS1.3 historical experiments demonstrate skill in simulating the global and regional metrics assessed that is comparable to the CMIP5 multi-model ensemble utilised. Global annual average temperature and precipitation trends simulated with ACCESS1.3 (0.05-0.07 K/decade; -0.007 to -0.0004 mm day /decade) largely lie within the CMIP5 ensemble window (0.06 - 0.18 K/decade; -0.01 to 0.009 mm day /decade) and near those observed (0.10 K/decade; -0.0007 to -0.001 mm day-1/decade) over the 1950-2005 period. For the ACCESS1.3 historicalNat and historicalGHG experiments, simulated temperature trends are also predominately within the CMIP5 multi-model ensemble range. Similarly, ACCESS1.3 (-0.07 to -0.12 K) and the CMIP5 models (-0.03 to -0.21 K) largely capture the composited observed decrease in global temperature (-0.04 K) following three major late 20th century volcanic eruptions. However, like all global climate models, ACCESS1.3 has deficiencies that should be considered. In particular, one of most notable features of ACCESS1.3 historical simulations is the reduced warming trend over the period 1950-2005 that is evident in all ACCESS1.3 realisations at the global-scale for Australia, relative to both observations and the CMIP5 multi-model mean. This appears to be related to the overly strong response to increases in anthropogenic aerosols. Overall, these historical period experiments using ACCESS1.3 with various forcings are useful for inclusion with other CMIP5 models for studies aimed at detecting and attributing climatic changes. -1 -1

Atmospheric circulation as a factor for air temperatures in Bulgaria

The research period is 1950–2012, and includes data for air temperatures in 21 Bulgarian stations. Two circulation indices, covering the same period and showing west–east or south–north directions of transport of air masses, were calculated. Statistical methods were used in the study. The results show a significant positive trend in average annual air temperatures in almost the entire territory of Bulgaria with the exception of its eastern-northeastern part. The warming occurs mainly in March, June and July, with some stations having significant positive values also in January, May and August. The zonal index reveals an insignificant increase of western transport of air masses in the cold half of the year (October–April) and strengthening of the eastern transport in the rest of the year. The meridional index shows an increase of the northern transport of air masses over the entire year and this is particularly visible in March, June, August and September. Correlation coefficients indicate that atmospheric circulation has leading role in determination of air temperatures during the period from November to April. Western transport of air masses leads to higher temperatures in spring, autumn and winter and to lower temperatures in summer. The influence of ENSO on atmospheric circulation over Bulgaria is weak, with a time lag of 2 months. El Nino is associated with increased western and northern transport of air masses, while La Nina is associated with increased eastern and southern transport of air masses over southeastern Europe.

Flowering Phenology of Eastern Filbert Blight-resistant Hazelnut Accessions in New Jersey

Hazelnuts (Corylus sp.) are monoecious and wind-pollinated with reproduction limited by a sporophytic self-incompatibility system. They flower during the winter and are dichogamous with the dates of flowering ranging from December to March in New Jersey depending on the genotype, geographic location, and year. Successful, consistent nut production depends on both genetic compatibility and the appropriate timing of flowering between pollinizing and nut-producing cultivars. While the disease eastern filbert blight (EFB), caused by Anisogramma anomala, has severely limited past hazelnut production in the eastern United States, resistant and tolerant genotypes are now available for testing. However, little is known of their flowering phenology in this region. In this study, the flower and budbreak phenology of 19 different EFB-resistant and EFB-tolerant hazelnut accessions was evaluated over 4 years, and the results compared with air temperature data collected during bloom. Results showed that the accessions followed a similar progression of bloom each year (both staminate and pistillate flowers), which allowed their placement into early-, mid-, and late-flowering groups. However, the date of bloom and duration of bloom, especially for pollen shed, differed each year, largely corresponding to average air temperature trends. Confirming previous reports from other cold regions, it was shown that consistently colder average temperatures delayed bloom until later in the winter, which then led to a compressed period of flowering once temperatures warmed. In contrast, relatively warm temperatures over the season led to earlier flowering as well as a significant lengthening of the duration of bloom, similar to responses reported in Mediterranean climates. Our study documents hazelnut flowering phenology under New Jersey’s variable winter climate, and the results provide a benchmark for selecting suitable pollenizers and breeding parents for future nut production, flowering research, and/or genetic improvement in this region.

Temperature Extremes from Canadian Regional Climate Model (CRCM) Climate Change Projections

Future climate projections of extreme events can help forewarn society of high-impact events and allow the development of better adaptation strategies. In this study a non-stationary model for Generalized Extreme Value (GEV) distributions is used to analyze the trend in extreme temperatures in the context of a changing climate and compare it with the trend in average temperatures.The analysis is performed using the climate projections of the Canadian Regional Climate Model (CRCM), under an IPCC SRES A2 greenhouse gas emissions scenario, over North America. Annual extremes in daily minimum and maximum temperatures are analyzed. Significant positive trends for the location parameter of the GEV distribution are found, indicating an expected increase in extreme temperature values. The scale parameter of the GEV distribution, on the other hand, reveals a decrease in the variability of temperature extremes in some continental regions. Trends in the annual minimum and maximum temperatures are compared with trends in average winter and summer temperatures, respectively. In some regions, extreme temperatures exhibit a significantly larger increase than the seasonal average temperatures.The CRCM projections are compared with those of its driving model and framed in the context of the Coupled Model Intercomparison Project, phase 3 (CMIP3) Global Climate Model projections. This enables us to establish the CRCM position within the CMIP3 climate projection uncertainty range. The CRCM is validated against the HadEX2 dataset in order to assess the CRCM representation of temperature extremes in the present climate. The validation is also framed in the context of CMIP3 validation results. The CRCM cold extremes validate better and are closer to the driving model and CMIP3 projections than the hot extremes.

Analysis of Temperature Trends in Sutluj River Basin, India

Surface air temperature is an important climatic variable that drives the hydrological cycle. Precipitation and runoff production are impacted by surface air temperature changes and are, therefore, important for water resources planning, irrigation and agriculture. Focusing on the Sutlej Basin in the Himalayan region, the present research is aimed at utilizing observational evidence to evaluate the response of the region to global warming through investigation of temperature trends. Trends in long-term average annual and seasonal surface air temperature, and several temperature indices at eight stations in the Sutlej River basin have been examined using Mann-Kendall non-parametric test. Six stations exhibited increasing trends in annual average maximum temperature with two being statistically significant. The trends in annual average minimum temperature were mixed; three of eight stations exhibited statistically significant decreasing trends. Some higher elevation stations exhibited clear warming trends both in maximum and minimum temperatures. Analysis of seasonal temperature data indicated that the warming was more pronounced in winter and spring than in summer and autumn. Trends in temperature indices considered in this paper were predominantly increasing. The predominant pattern of increased warming in the basin could have implications for water availability as the snow and glacier melt contribution to annual runoff at Bhakra reservoir is estimated at 59%. The analysis shows that even within a small area, there is variability in the magnitude and direction of historic temperature trends. Some of these variations could be partially attributed to data reliability.