Monotonic Trend Analysis of Temperature Series over Mandya City, Karnataka

2021 ◽  
Vol 9 (VII) ◽  
pp. 1530-1535
Author(s):  
Madhusudhan M S
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Agricultural Sector ◽  
Kendall Test ◽  
Temperature Series ◽  
Maximum Temperature ◽  
Positive Trend ◽  
Significance Level ◽  
Monotonic Trend ◽  
Indirect Impacts

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.

Homogeneity Evaluation of Historical Rainfall and Temperature Series in Mato Grosso

2019 ◽  
pp. 1-7
Author(s):  
Elizangela Selma da Silva ◽  
José Holanda Campelo Júnior ◽  
Francisco De Almeida Lobo ◽  
Ricardo Santos Silva Amorim
Keyword(s):  
Trend Analysis ◽  
Minimum Temperature ◽  
Statistical Tests ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Data Series ◽  
Positive Trend ◽  
Mato Grosso ◽  
Temperature Climate ◽  
Precipitation And Temperature

The homogeneity investigation of a series can be performed through several nonparametric statistical tests, which serve to detect artificial changes or non-homogeneities in climatic variables. The objective of this work was to evaluate two methodologies to verify the homogeneity of the historical climatological series of precipitation and temperature in Mato Grosso state. The series homogeneity evaluation was performed using the following non-parametric tests: Wald-Wolfowitz (for series with one or no interruption), Kruskal-Wallis (for series with two or more interruptions), and Mann-Kendall (for time series trend analysis). The results of the precipitation series homogeneity analysis from the National Waters Agency stations, analyzed by the Kruskal-Wallis and Wald-Wolfowitz tests, presented 61.54% of homogeneous stations, being well distributed throughout Mato Grosso state, whereas those of the trend analysis allowed to identify that 87.57% of the rainfall-gauging stations showed a concentrated positive trend, mainly in the rainy season. Out of the conventional stations of the National Institute of Meteorology of Mato Grosso, seven were homogeneous for the precipitation variable, five for maximum temperature and four stations were homogeneous for minimum temperature. For the trend analysis in the 11 stations, positive trends of random nature were observed, suggesting increasing alterations in the analyzed variables. Therefore, the trend analysis performed by the Mann-Kendall test in the precipitation, and maximum and minimum temperature climate series, indicated that several data series showed increasing trends, suggesting a possible increase in precipitation and temperature values over the years. The results of the Kruskal-Wallis and Wald-Wolfowitz tests for homogeneity presented more than 87% of homogeneous stations.

scholarly journals Trend analysis of seasonal rainfall and temperature pattern in Damota Gale districts of Wolaita Zone, Ethiopia

2021 ◽  
Author(s):  
Elias Bojago ◽  
Dalga YaYa
Keyword(s):  
Trend Analysis ◽  
Meteorological Data ◽  
Statistical Significance ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Temperature Pattern ◽  
Positive Trend ◽  
Annual Minimum Temperature ◽  
Increasing Trend ◽  
Mann Kendall Test

Abstract This paper investigated the recent trends of precipitation and temperature on Damota Gale districts of Wolaita Zone. This study used the observed historical meteorological data from 1987 to 2019 to analyze the trends. The magnitude of the variability or fluctuations of the factors varies according to locations. Hence, examining the spatiotemporal dynamics of meteorological variables in the context of changing climate, particularly in countries where rain-fed agriculture is predominant, is vital to assess climate-induced changes and suggest feasible adaptation strategies. Both rainfall and temperature data for a period of 1987 to 2019 were analyzed in this study. Statistical trend analysis techniques namely Mann–Kendall test and Sen's slope estimator were used to examine and analyze the problems. The long-term trend of rainfall and temperature was evaluated by linear regression and Mann–Kendall test. The temperature was shown a positive trend for both annual and seasonal periods and had a statistical significance of 95%. This study concluded that there was a declining rainfall in the three seasons; spring, summer and winter but in autumn it shows increasing trends and rapid warming, especially in the last 32 years. The detailed analysis of the data for 32 years indicate that the annual maximum temperature and annual minimum temperature have shown an increasing trend, whereas the Damota Gale seasonal maximum and minimum temperatures have shown an increasing trend. The findings of this study will serve as a reference for climate researchers, policy and decision-makers.

scholarly journals Trend analysis of seasonal rainfall and temperature pattern in Damota Gale districts of Wolaita Zone, Ethiopia

2021 ◽  
Author(s):  
Elias Bojago ◽  
Dalga Yaya
Keyword(s):  
Trend Analysis ◽  
Meteorological Data ◽  
Statistical Significance ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Temperature Pattern ◽  
Positive Trend ◽  
Annual Minimum Temperature ◽  
Increasing Trend ◽  
Mann Kendall Test

Abstract Background: This paper investigated the recent trends of precipitation and temperature on Damota Gale districts of Wolaita Zone. This study used the observed historical meteorological data from 1987 to 2019 to analyze the trends. The magnitude of the variability or fluctuations of the factors varies according to locations. Hence, examining the spatiotemporal dynamics of meteorological variables in the context of changing climate, particularly in countries where rain fed agriculture is predominant, is vital to assess climate-induced changes and suggest feasible adaptation strategies. Results: Both rainfall and temperature data for period of 1987 to 2019 were analyzed in this study. Statistical trend analysis techniques namely Mann–Kendall test and Sen's slope estimator were used to examine and analyze the problems. The long-term trend of rainfall and temperature was evaluated by linear regression and Mann–Kendall test. The temperature was shown a positive trend for the both annual and seasonal periods and had a statistical significance at 95%.Conclusion: This study concluded that there were a declining rainfall in the three seasons; spring, summer and winter but in autumn it shows increasing trends and rapid warming, especially in the last 32 years. The detailed analysis of the data for 32 years indicate that the annual maximum temperature and annual minimum temperature have shown an increasing trend, whereas the Damota Gale seasonal maximum and minimum temperatures have shown an increasing trend. The findings of this study will serve as a reference for climate researchers, policy and decision makers.

scholarly journals Trend analysis of water quality parameters for the Nisava river

2013 ◽  
Vol 11 (3) ◽  
pp. 199-210 ◽  
Author(s):  
Milan Gocic ◽  
Slavisa Trajkovic
Keyword(s):  
Water Quality ◽  
Trend Analysis ◽  
Kendall Test ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Total Hardness ◽  
Significance Level ◽  
Annual Series ◽  
Annual Time Series ◽  
Annual Time

The data of 12 water quality parameters have been daily monitored at the Nis station on the Nisava River during 2000-2004. The trend analysis was performed on monthly, seasonal and annual time series using the Mann-Kendall test, the Spearman?s Rho test and the linear regression at the 5% significance level. The monthly results showed that significant trends were found only in pH, total hardness, Ca and SO4 data. The results in seasonal series indicated that the significant trends were detected in pH, total hardness, Cl, Ca and SO4 data. In annual series, the trends were insignificant at the 5% significance level.

scholarly journals Innovative Trend Analysis of Precipitation in the Lake Issyk-Kul Basin, Kyrgyzstan

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 332 ◽  
Author(s):  
Yilinuer Alifujiang ◽  
Jilili Abuduwaili ◽  
Balati Maihemuti ◽  
Bilal Emin ◽  
Michael Groll
Keyword(s):  
Trend Analysis ◽  
Resource Planning ◽  
Kendall Test ◽  
Trend Test ◽  
Lake Basin ◽  
Positive Trend ◽  
Monthly Precipitation ◽  
Innovative Trend Analysis ◽  
Mann Kendall Test ◽  
Increasing Trends

The analysis of various characteristics and trends of precipitation is an essential task to improve the utilization of water resources. Lake Issyk-Kul basin is an upper alpine catchment, which is more susceptible to the effects of climate variability, and identifying rainfall variations has vital importance for water resource planning and management in the lake basin. The well-known approaches linear regression, Şen’s slope, Spearman’s rho, and Mann-Kendall trend tests are applied frequently to try to identify trend variations, especially in rainfall, in most literature around the world. Recently, a newly developed method of Şen-innovative trend analysis (ITA) provides some advantages of visual-graphical illustrations and the identification of trends, which is one of the main focuses in this article. This study obtained the monthly precipitation data (between 1951 and 2012) from three meteorological stations (Balykchy, Cholpon-Ata, and Kyzyl-Suu) surrounding the Lake Issyk-Kul, and investigated the trends of precipitation variability by applying the ITA method. For comparison purposes, the traditional Mann–Kendall trend test also used the same time series. The main results of this study include the following. (1) According to the Mann-Kendall trend test, the precipitation of all months at the Balykchy station showed a positive trend (except in January (Zc = −0.784) and July (Zc = 0.079)). At the Cholpon-Ata and Kyzyl-Suu stations, monthly precipitation (with the same month of multiple years averaged) indicated a decreasing trend in January, June, August, and November. At the monthly scale, significant increasing trends (Zc > Z0.10 = 1.645) were detected in February and October for three stations. (2) The ITA method indicated that the rising trends were seen in 16 out of 36 months at the three stations, while six months showed decreasing patterns for “high” monthly precipitation. According to the “low” monthly precipitations, 14 months had an increasing trend, and four months showed a decreasing trend. Through the application of the ITA method (January, March, and August at Balykchy; December at Cholpon-Ata; and July and December at Kyzyl-Suu), there were some significant increasing trends, but the Mann-Kendall test found no significant trends. The significant trend occupies 19.4% in the Mann-Kendall test and 36.1% in the ITA method, which indicates that the ITA method displays more positive significant trends than Mann–Kendall Zc. (3) Compared with the classical Mann-Kendall trend results, the ITA method has some advantages. This approach allows more detailed interpretations about trend detection, which has benefits for identifying hidden variation trends of precipitation and the graphical illustration of the trend variability of extreme events, such as “high” and “low” values of monthly precipitation. In contrast, these cannot be discovered by applying traditional methods.

scholarly journals Tropical rainfall trend and stationarity analysis

2020 ◽  
Vol 20 (7) ◽  
pp. 2471-2483
Author(s):  
Chun Kang Ng ◽  
Jing Lin Ng ◽  
Yuk Feng Huang ◽  
Yi Xun Tan ◽  
Majid Mirzaei
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
River Basin ◽  
Spatial Scales ◽  
Kendall Test ◽  
Temporal Analysis ◽  
Northern Region ◽  
Rainfall Series ◽  
Kelantan River Basin ◽  
Temporal And Spatial

Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.

TREND ANALYSIS OF RAINFALL, TEMPERATURE AND RUNOFF DATA: A CASE STUDY OF RANGOON WATERSHED IN NEPAL

2017 ◽  
Vol 5 (3) ◽  
pp. 21-38 ◽  
Author(s):  
Amar Bahadur Pal ◽  
Deepak Khare ◽  
Prabhash Kumar Mishra ◽  
Lakhwinder Singh
Keyword(s):  
Trend Analysis ◽  
Research Work ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Original Research ◽  
Positive Trend ◽  
Sen’S Slope ◽  
Z Value ◽  
Trend Direction

Purpose: The study has been carried out to investigate and assess the significance of the potential trend of three variables viz. rainfall, temperature and runoff over the Rangoon watershed in Dadeldhura district of Nepal.Methodology: In this study, trend analysis has been carried out on monthly, seasonal and annual basis using the data period between 1979 to 2010 for rainfall and temperature and 1967 to 1996 for runoff. Mann-Kendall test and Sen’s slope estimate test were applied to identify the existing trend direction and Sen’s slope estimator test were used to detect the trend direction and magnitude of change over time.Main findings: The most important findings are, i) There is warming trends over the Rangoon watershed as Mann-Kendall statistic (Z-value) for most of the maximum temperature values are positive, ii) Rainfall and runoff affected by fluctuations every year though the annual rainfall showing a rising trend whereas runoff showing a falling trend. The rainfall seasonal trend analysis indicates that monsoon and post-monsoon period showed a positive rainfall trend with z statistics of +1.93, and +1.12 respectively, whereas pre-monsoon and winter seasons showed a negative trend with z statistics of -1.02, and -0.54 respectively. However, the annual rainfall in the Rangoon watershed showed a positive trend with a z value of +1.70.Importance of this study: This case study has been undertaken to investigate the trends of important climatic variables viz. rainfall, temperature which have a direct impact on the agriculture of the region.Originality / Novelty of study: This is an original research work undertaken under the M. Tech programme during 2016-17 at IIT Roorkee by the scholar Er. Amar Bahadur Pal from Nepal. 

Analysis of the extreme heat events in Iran

2017 ◽  
Vol 9 (4) ◽  
pp. 418-432 ◽  
Author(s):  
Hojjatollah Yazdanpanah ◽  
Josef Eitzinger ◽  
Marina Baldi
Keyword(s):  
Trend Analysis ◽  
Heat Wave ◽  
Heat Waves ◽  
Temporal Variations ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Daily Maximum ◽  
Positive Trend ◽  
Content Type ◽  
Hot Days

Purpose The purpose of this paper is to assess the spatial and temporal variations of extreme hot days (H*) and heat wave frequencies across Iran. Design/methodology/approach The authors used daily maximum temperature (Tmax) data of 27 synoptic stations in Iran. These data were standardized using the mean and the standard deviation of each day of the year. An extreme hot day was defined when the Z score of daily maximum temperature of that day was equal or more than a given threshold fixed at 1.7, while a heat wave event was considered to occur when the Z score exceeds the threshold for at least three continuous days. According to these criteria, the annual frequency of extreme hot days and the number of heat waves were determined for all stations. Findings The trend analysis of H* shows a positive trend during the past two decades in Iran, with the maximum number of H* (110 cases) observed in 2010. A significant trend of the number of heat waves per year was also detected during 1991-2013 in all the stations. Overall, results indicate that Iran has experienced heat waves in recent years more often than its long-term average. There will be more frequent and intense hot days and heat waves across Iran until 2050, due to estimated increase of mean air temperature between 0.5-1.1 and 0.8-1.6 degree centigrade for Rcp2.6 and Rcp8.8 scenarios, respectively. Originality/value The trend analysis of hot days and heat wave frequencies is a particularly original aspect of this paper. It is very important for policy- and decision-makers especially in agriculture and health sectors of Iran to make some adaptation strategies for future frequent and intense hot days over Iran.

scholarly journals Cuantificación e interpolación de tendencias locales de temperatura y precipitación en zonas alto andinas de Cundinamarca y Boyacá (Colombia)

2010 ◽  
Vol 11 (2) ◽  
pp. 173 ◽  
Author(s):  
Edwin Rojas ◽  
Blanca Arce ◽  
Andrés Peña ◽  
Francisco Boshell ◽  
Miguel Ayarza
Keyword(s):  
Production Systems ◽  
Hydrological Cycle ◽  
Kendall Test ◽  
Maximum Temperature ◽  
Positive Trend ◽  
Weighted Interpolation ◽  
Weather Patterns ◽  
Statistical Confidence ◽  
Temperature And Precipitation ◽  
Inverse Distance Weighted Interpolation

<p>El cambio en el patrón climático global no sólo afecta la temperatura, sino el ciclo hidrológico con mayores variaciones en los ambientales locales. Con el fin de cuantificar las tendencias de temperatura máxima, mínima y precipitación media, se realizó un análisis no-paramétrico de las series de tiempo de 31 estaciones meteorológicas ubicadas en zonas alto andinas de Cundinamarca y Boyacá, con registros de 1985 a 2008. Se calcularon las tendencias de cambio de las variables climáticas para cada una de las estaciones mediante el método de estimación de pendiente de Sen y se utilizó la prueba de Mann- Kendall para determinar el nivel de confianza de dichas tendencias. La temperatura máxima mostró tendencias positivas con niveles de confianza significativa (&gt;90%) en la mayoría de estaciones climáticas. Para la temperatura mínima, la tendencia positiva fue detectada en menor número de estaciones pero con mayores niveles de confianza estadística (12 estaciones superaron el 95%). La precipitación mostró tendencias significativas (&gt;90%) sólo en siete de las 31 estaciones analizadas (seis de ellas fueron positivas y una negativa). Se utilizó el método de interpolación de distancia inversa ponderada (IDW) para generar los mapas de la distribución espacial de las tendencias. Mediante validación cruzada se encontró que el IDW tiene un mejor ajuste para la precipitación que para la temperatura. Se concluye que el cambio climático tiene manifestaciones muy locales en términos del comportamiento de las temperaturas y la precipitación para la zona de estudio, lo que podría generar impactos específicos sobre los sistemas productivos de la región.</p><p> </p><p><strong>Quantization and interpolation of local trends in temperature and precipitation in the high Andean areas of Cundinamarca and Boyaca (Colombia)</strong></p><p>Change in global weather patterns affects not only temperature, but also the hydrological cycle with greater variations in local environments. In order to quantify trends in maximum temperature and minimum and average precipitation, we performed a nonparametric analysis of time series of 31 meteorological stations located in the high Andes of Cundinamarca and Boyaca, with records from 1985 to 2008. We calculated the changing trends of climatic variables for each of the stations with the Sen slope estimator and we used the Mann-Kendall test to determine the confidence level of such trends. The maximum temperature showed positive trends with significant confidence levels (&gt; 90%) in most seasons. For the lowest temperature, the positive trend was detected in fewer stations but with higher levels of statistical confidence (12 stations exceeded 95%). Rainfall showed significant trends (&gt; 90%) in only seven of the 31 stations analyzed (six of them were positive and one negative). We used the method of inverse distance weighted interpolation (IDW) to generate maps of the spatial distribution of the trends. Cross validation found that IDW has a better fit for precipitation than for temperature. We conclude that climate change manifests very local expressions in terms of the behavior of temperatures and precipitation for the study area, which could lead to specific impacts on production systems in the region.</p>

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