Temperature and Rainfall Partial Trends in Oxford, 1870-2019

Author(s):  
Eyüp Şişman ◽  
Burak KIZILÖZ

Abstract In this study, the trends and stabilities of temperature and precipitation hydro-meteorology time series recorded since 1870 in Oxford city of England were analyzed in detail. The Innovative Triangular Trend Analysis (ITTA) method has been inspired to identify and analyze the trends and stabilities of the selected time series. To compare the results obtained by the above-mentioned method, the Classical Mann Kendall (MK) method has been applied to each series determined for ITTA design. Thanks to the innovative design of ITTA which is preferred by the Classic MK and Sen slope methods, the trends of time series could be analyzed in detail. In this study, the first draft structure has been improved with the help of ± 5-±10 % percentage change levels which were added to the ITTA method, and thus more objective evaluations about the trend magnitudes in time series is possible. For the same draft, the monotonic trend slopes which were found by the classical MK were also calculated through the Sen slope method. The data trends could explain in more detail with the help of the draft used in this study, compared to the studies in the literature. Climate change, which has been the most important factor in trend formation in recent years, has been taken into consideration while determining the design series. The thirty-year period up to 2019, a year in which the climate change was felt much more, constitutes the most important reference years for the analysis beginning from 1990, a year in which the climate change effects started to emerge. When the data trends of one hundred fifty years are examined for the different sub-time series, it is seen that the temperature increase in during1990-2019 period is much higher than the past hundred and twenty years, according to the analysis results. The highest average precipitation occurred in the 1990–2019 and 1900–1929 periods, and their amounts and patterns are nearly similar.

2018 ◽  
Vol 11 (2) ◽  
pp. 420-433 ◽  
Author(s):  
Adem Yavuz Sönmez ◽  
Semih Kale

Abstract The main purpose of this study was to estimate possible climate change effects on the annual streamflow of Filyos River (Turkey). Data for annual streamflow and climatic parameters were obtained from streamflow gauging stations on the river and Bartın, Karabük, Zonguldak meteorological observation stations. Time series analysis was performed on 46 years of annual streamflow data and 57 years of annual mean climatic data from three monitoring stations to understand the trends. Pettitt change-point analysis was applied to determine the change time and trend analysis was performed to forecast trends. To reveal the relationship between climatic parameters and streamflow, correlation tests, namely, Spearman's rho and Kendall's tau were applied. The results of Pettitt change-point analysis pointed to 2000 as the change year for streamflow. Change years for temperature and precipitation were detected as 1997 and 2000, respectively. Trend analysis results indicated decreasing trends in the streamflow and precipitation, and increasing trend in temperature. These changes were found statistically significant for streamflow (p < 0.05) and temperature (p < 0.01). Also, a statistically significant (p < 0.05) correlation was found between streamflow and precipitation. In conclusion, decreasing precipitation and increasing temperature as a result of climate change initiated a decrease in the river streamflow.


2018 ◽  
Vol 16 (1) ◽  
pp. 87-102 ◽  
Author(s):  
Jiban Mani Poudel

Satellite images, repeated photography, temperature and precipitation data, and other proxy scientific evidences support the claim that climate is changing rapidly in Nepal, including in the Trans-Himalayan regions of the country. Climate change in the Trans-Himalayan region of Nepal is altering the existing relations of functional socio-ecological system for generations. This ethnographic assessment of Nhāson village looks at the disturbance posed by climate change to the social and ecological relationship in reference to livestock management practices. It focuses on two thematic areas of communities’ verbalisation of issues and challenges faced by the mountain herders in the climate change context. This paper is the product of ethnographic study between the years 2012 and 2014 in Nhāson. The locals’ attachment to environment and witnesses of change is capable of telling the story on the disturbance of climate change in the social and ecological systems, contextually. The stories gathered during walking, herding, travelling, watching and observing of the places are “real stories” with insights into the past climate variability and fluctuation which is critically valuable to understand the environmental phenomena at times when scientific evidences are not sufficient. Ethnographic study can contribute in documenting the place and cultural specific stories as a powerful evidence to climate change and its impact on grounded social and ecological systems.


2018 ◽  
Vol 64 (No. 3) ◽  
pp. 139-147 ◽  
Author(s):  
Khaleghi Mohammad Reza

The present study tends to describe the survey of climatic changes in the case of the Bojnourd region of North Khorasan, Iran. Climate change due to a fragile ecosystem in semi-arid and arid regions such as Iran is one of the most challenging climatological and hydrological problems. Dendrochronology, which uses tree rings to their exact year of formation to analyse temporal and spatial patterns of processes in the physical and cultural sciences, can be used to evaluate the effects of climate change. In this study, the effects of climate change were simulated using dendrochronology (tree rings) and an artificial neural network (ANN) for the period from 1800 to 2015. The present study was executed using the Quercus castaneifolia C.A. Meyer. Tree-ring width, temperature, and precipitation were the input parameters for the study, and climate change parameters were the outputs. After the training process, the model was verified. The verified network and tree rings were used to simulate climatic parameter changes during the past times. The results showed that the integration of dendroclimatology and an ANN renders a high degree of accuracy and efficiency in the simulation of climate change. The results showed that in the last two centuries, the climate of the study area changed from semiarid to arid, and its annual precipitation decreased significantly.


2021 ◽  
Author(s):  
Zekai Sen

Abstract Trend identification procedures are employed to determine the systematic monotonic trend lines in a given hydro-meteorological time series records for depiction of time dependent changes in the form of increase or decrease. Different methodologies are proposed for such identifications, but most of them require restrictive assumptions such as the normal (Gaussian) probability distribution, serial independence and long sample sizes. In order to relieve especially the serial independence requirement pre-whitening and over-whitening procedures are suggested, but they cannot render a serially dependent series into completely independent structure. In this paper, a new trend methodology is proposed on the basis of crossing features along any given straight-line within the given time series and the one with the maximum crossing number is the searched trend component. This approach does not require any restrictive assumption. Contrary to the previous trend algorithms, the suggested crossing empirical trend analysis (CETA) yields not a single trend, but a set of trends at different levels within the variation range of hydro-meteorological time series records. In this paper for the sake of brevity only three levels are considered at 10%, 50% and 90% risk levels. The comparison of the CETA approach is presented with the classical and frequently used method of Mann-Kendall (MK) trend identification procedure based on the Sen’s slope calculation. For small serial correlation coefficients and normal probability distribution (PDF) function cases CETA and classical technique yield almost the same trend line within +5% error band limits. The application of this methodology is presented for monthly and annual discharge records of Danube River and annual precipitation records from seven geographical regions of Turkey.


2017 ◽  

The effects of climate change have been observed on agricultural lands in the Caribbean. Climate change effects include shifts in temperature and precipitation, which can manifest as water scarcity or excess, above normal temperatures, sea level rise, as well as frequent tropical storms.


2021 ◽  
Vol 14 (1) ◽  
pp. 117
Author(s):  
Davide De Santis ◽  
Fabio Del Frate ◽  
Giovanni Schiavon

Evaluation of the impact of climate change on water bodies has been one of the most discussed open issues of recent years. The exploitation of satellite data for the monitoring of water surface temperatures, combined with ground measurements where available, has already been shown in several previous studies, but these studies mainly focused on large lakes around the world. In this work the water surface temperature characterization during the last few decades of two small–medium Italian lakes, Lake Bracciano and Lake Martignano, using satellite data is addressed. The study also takes advantage of the last space-borne platforms, such as Sentinel-3. Long time series of clear sky conditions and atmospherically calibrated (using a simplified Planck’s Law-based algorithm) images were processed in order to derive the lakes surface temperature trends from 1984 to 2019. The results show an overall increase in water surface temperatures which is more evident on the smallest and shallowest of the two test sites. In particular, it was observed that, since the year 2000, the surface temperature of both lakes has risen by about 0.106 °C/year on average, which doubles the rate that can be retrieved by considering the whole period 1984–2019 (0.053 °C/year on average).


2009 ◽  
Vol 1 (1) ◽  
pp. 77-90 ◽  
Author(s):  
Marian Melo ◽  
Milan Lapin ◽  
Ingrid Damborska

Abstract In this paper methods of climate-change scenario projection in Slovakia for the 21st century are outlined. Temperature and precipitation time series of the Hurbanovo Observatory in 1871-2007 (Slovak Hydrometeorological Institute) and data from four global GCMs (GISS 1998, CGCM1, CGCM2, HadCM3) are utilized for the design of climate change scenarios. Selected results of different climate change scenarios (based on different methods) for the region of Slovakia (up to 2100) are presented. The increase in annual mean temperature is about 3°C, though the results are ambiguous in the case of precipitation. These scenarios are required by users in impact studies, mainly from the hydrology, agriculture and forestry sectors.


Author(s):  
Umut Okkan ◽  
Gul Inan

This study aims to discuss the potentials of machine learning methods such as artificial neural network (ANN), least squares support vector machine (LSSVM), and relevance vector machine (RVM) in downscaling of simulations of a general circulation model (GCM) for monthly temperature and precipitation of the Demirkopru Dam located in the Aegean region of Turkey. The predictors are obtained from ERA-Interim re-analysis data. The best performed downscaling model is integrated into European Centre Hamburg Model (ECHAM5) with A2 future scenario. The results are then discussed to assess the probable climate change effects on temperature and precipitation.


Author(s):  
Madhusudhan M S

Climate change is mostly driven by global warming. Climate change is one of the most critical long-term development issues, particularly for developing countries like India. India is one of the world's most climatically diverse countries, making it sensitive to climatic change and impacting the livelihoods of millions of people who rely on agriculture. Temperature and its fluctuation have direct and indirect impacts on crop development in the agricultural sector. Understanding the temperature and its variability in a changing environment would aid in improved decision-making and suggest feasible adaption strategies. The present study focuses on temperature trend analysis in Mandya city, Karnataka, India. The analysis was carried out through the non-parametric Mann-Kendall test and Sen's slope estimator. The findings demonstrate that, there has been a rising trend in temperature in the study area over the last 30 years as a result of climate change. From the analysis, there is a significant positive trend for all the seasons considered for the significance level of 90%, 95% and 99%. The magnitude of the increasing trend will be in the range of 0.46 °C/year for the average time series. Also, there will be an average increase of 0.07 °C/year for the various scenarios considered in Mandya city for the Maximum temperature series.


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