Analysis of Temporal and Spatial Characteristic of Temperature Change over the Last 45 Years in Northeastern China

2012 ◽  
Vol 518-523 ◽  
pp. 1367-1370 ◽  
Author(s):  
Wei He ◽  
Ren Cang Bu ◽  
Yuan Man Hu ◽  
Zai Ping Xiong ◽  
Miao Liu
Keyword(s):  
Kendall Test ◽  
Northern Region ◽  
Northeastern China ◽  
Spatial Characteristic ◽  
Weighted Interpolation ◽  
Spatiotemporal Trends ◽  
Mean Temperature ◽  
Mann Kendall Test ◽  
Inverse Distance Weighted Interpolation ◽  
Increasing Trends

Based on the temperature datasets from 1961 to 2005 at 96 meteorological stations, the spatiotemporal trends of climate change were analyzed in annual and seasonal timescales, by a linear and regression model, cumulative anomaly method, Mann-Kendall test and inverse distance weighted interpolation methods, in Northeastern China. The results showed that: (1) Both annual and seasonal mean temperature showed increasing trends, the annual mean temperature have rised by 0.07°Cwith a rate of 0.38°C/decade, and the highest increasing rates of temperature occured in the winter (0.53°C/decade) and lowest one was the in the summer (0.23°C/decade). (2) The results of Mann-Kendall test on temperature showed that the annual and seasonal mean temperature significantly increased at 95% of confidence. The climate jump of annual mean temperature took place in 1987, and the climate jumps of spring, summer, autumn and winter mean temperature occurred in 1988, 1993, 1989 and 1981, respectively, and these results were confirmed by the cumulative anomaly curve. (3) The higher the latitude, the more obvious the increasing trend, especially in winter, and therefore the temperature increased in most parts of the Northeastern China.However, the increasing trends in the northern region of the Da Hinggan Moutains and Xiao Hinggan Moutains were the most obvious.

scholarly journals Spatiotemporal Trends and Detection of Changes in Hydrological and Climatic Variables of Modjo River Watershed, Ethiopia

2021 ◽  
Author(s):  
Kokeb Zena Besha ◽  
Tamene Adugna Demissie ◽  
Fekadu Fufa Feyessa
Keyword(s):  
Time Series ◽  
River Flow ◽  
Interpolation Method ◽  
Resource Planning ◽  
Kendall Test ◽  
Precipitation Series ◽  
Weighted Interpolation ◽  
Spatiotemporal Trends ◽  
Distance Weighted ◽  
Inverse Distance Weighted Interpolation

Abstract Understanding hydro-climatic trends in space and time is crucial for water resource planning and management, agricultural productivity and climate change mitigation of a region. This study examined the spatiotemporal variations in precipitation, reference evapotranspiration (ETo) and streamflow in a tropical watershed located in the central highlands of Ethiopia. Temporal trend implications were analyzed using the Mann-Kendall test, and Theil-Sen approach, whereas the inverse distance weighted interpolation method was applied for spatial trend variability analysis. The result showed that a significant decreasing trends in streamflow for the major rainy (Kiremt: Jun - Sept) season and annual time scales. At the same time, the annual and monthly ETo followed significantly increasing trends, but there has been a trendless time series for most of the months and annual mean precipitation series for the period 1986 - 2015. The study indicated that the spatial variability of annual and seasonal precipitation series decreased from north to south and west to east, while this was increased for ETo both for annual and seasonal time series over the study watershed. The contribution of rainfall and mean temperature to streamflow decline was insignificant. It is pointed out that river flow regime is weakly affected by climate changes, hence human activities are stronger in explaining the river flow trends of the watershed. Therefore, urgent calls on the needs for reducing human-induced impacts, and implementing appropriate watershed management, conservation measures and an efficient use of water resources.

scholarly journals Evapotranspiration Intensification Over Unchanged Temperate Vegetation in the Baltic Countries Is Being Driven by Climate Shifts

2021 ◽  
Vol 4 ◽  
Author(s):  
Bruno Montibeller ◽  
Jaak Jaagus ◽  
Ülo Mander ◽  
Evelyn Uuemaa
Keyword(s):  
Land Cover ◽  
Remote Sensing Data ◽  
Kendall Test ◽  
Rate Of Change ◽  
Sen’S Slope ◽  
Baltic Countries ◽  
Spatiotemporal Trends ◽  
Trade Offs ◽  
The Baltic ◽  
Increasing Trends

Shifts in climate driven by anthropogenic land use and land cover change are expected to alter various land–atmosphere interactions. Evapotranspiration (ET) is one of these processes and plays a fundamental role in the hydrologic cycle. Using gridded reanalysis and remote sensing data, we investigated the spatiotemporal trends of precipitation, temperature, and ET for areas in the Baltic countries Lithuania, Latvia and Estonia where the land cover type had not changed from 2000 to 2018. We focused on ET but investigated the spatiotemporal trends for the three variables at monthly, seasonal, and annual time scales during this period to quantify trade-offs among months and seasons. We used the Mann-Kendall test and Sen’s slope to calculate the trends and rate of change for the three variables. Although precipitation showed fewer statistically significant increasing and decreasing trends due to its high variability, temperature showed only increasing trends. The trends were concentrated in late spring (May, +0.14°C annually), summer (June and August, +0.10°C), and early autumn (September, +0.13°C). For unchanged forest and cropland areas, we found no statistically significant ET trends. However, Sen’s slope indicated increasing ET in April, May, June, and September for forest areas and in May and June for cropland. Our results indicate that during the study period, the temperature changes may have lengthened the growing season, which affected the ET patterns of forest and cropland areas. The results also provide important insights into the regional water balance and complement the findings of other studies.

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 Multi-annual analysis and trends of the temperatures and precipitations in West Anatolia

2017 ◽  
Vol 8 (3) ◽  
pp. 456-473 ◽  
Author(s):  
Turgay Partal
Keyword(s):  
Kendall Test ◽  
Temperature Data ◽  
Significance Level ◽  
Time Frequency ◽  
Pettitt Test ◽  
Frequency Representation ◽  
Mann Kendall Test ◽  
Scale Levels ◽  
Increasing Trends ◽  
Periodic Components

This study has been carried out to analyze the historical precipitation and temperature data for West Anatolia (Turkey) to understand the annual and multi-annual changes. The wavelet transform technique was used for time–frequency representation of the data. The trends in the data were estimated with the non-parametric Mann–Kendall test. A change point in the time series was determined by the Pettitt test. According to the wavelet analysis, some strong short-term periodical events at the scale levels of 1–4 were determined. The application of the Mann–Kendall test resulted with the identification of some decreasing trends in the observed annual precipitations and also in some periodic components, such as in 32 yearly periodic components. As well, 16 yearly periodic components of the temperature data showed very strong increasing trends at the 5% significance level.

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>

scholarly journals Effect of Climatic Factors on the Spread of COVID-19 Pandemic: Evidence from Tunisia

2020 ◽  
pp. 107-121
Author(s):  
Fatma Aribi ◽  
Mongi Sghaier
Keyword(s):  
Confidence Level ◽  
Social Life ◽  
Climatic Factors ◽  
Virus Disease ◽  
Kendall Test ◽  
Climatic Variables ◽  
Health Economy ◽  
Maximum Temperature ◽  
Mean Temperature ◽  
Mann Kendall Test

Since the end of December 2019, the COrona VIrus Disease (COVID-19) is sweeping the world and has caused huge damage to the health, economy, and social life of the communities. Meteorological variables are among the factors influencing the spread of contagious diseases. The aim of this study was to explore the correlation between climatic parameters and COVID-19 spread in Tunisia. To do this, we designed a daily dataset including the number of confirmed and deaths cases, minimum temperature (°C), maximum temperature (°C), mean temperature (°C), rainfall (mm), and wind speed (km/h) during the period of June 27 to October 22, 2020. To investigate the association between climatic variables and COVID-19, the Spearman correlation test was employed. The Mann-Kendall test has been also used to detect the direction of the COVID-19 trend. As many researchers have demonstrated that the incubation period of the ongoing pandemic varies from 1 to 14 days, the correlation of each parameter with COVID-19 was examined on the day of the confirmed cases and deaths, and before 7 and 14 days.  The results showed that out of the five selected climatic variables, four variables were correlated with COVID-19 cases and deaths (statistically significant at a 99% confidence level). A positive correlation of the rainfall with COVID-19 confirmed cases and deaths was observed, the highest was 14 days ago. However, negative correlations were observed for minimum, maximum, and mean temperature, the highest was on the day of the incident. Besides, the Mann-Kendall test showed increasing trends for COVID-19 cases and deaths (statistically significant at a 99% confidence level). The results of this study might be useful to understand the role of climatic factors in the spread of COVID-19 and provide insights for healthcare policymakers to well manage this global pandemic.

scholarly journals Rainfall Dynamics of Terengganu Malaysia and Its Recent Trends Analysis Using the Mann-Kendall Test.

2014 ◽  
Vol 4 (2) ◽  
pp. 372-381 ◽  
Author(s):  
Musa Garba Abdullahi ◽  
Mohd Ekhwan Toriman ◽  
Mohd Barzani Gasim ◽  
Hafizan Juahir
Keyword(s):  
Rainfall Intensity ◽  
Daily Rainfall ◽  
Kendall Test ◽  
Southwest Monsoon ◽  
The State ◽  
Northeast Monsoon ◽  
Monsoon Period ◽  
Mann Kendall Test ◽  
Recent Trends ◽  
Increasing Trends

This study investigated the pattern and trends of the daily rainfall data in Terengganu Malaysia based on seasonal rainfall indices. The statistics of rainfall indices were calculated in terms of their means for seven stations in Terengganu Malaysia for the period 2000 to 2012. The findings indicate that the trend in the study area has no significant changes in stations (1, 4 and 6) while station (2, 3, 5 and 7) shows significant changes and southwest monsoon had the greatest impact on the whole stations, particularly in characterizing the rainfall pattern of the area. During this season, the study area could be considered as the wettest region since all rainfall indices tested are higher than in other neighboring state of the Peninsula. Otherwise, the northwest of the area is denoted as the driest part of the state during the northeast monsoon period. The northwest of the state is less influenced by the northeast monsoon because of the existence of the Titiwangsa Range, which blocks some part of the region from receiving heavy rainfall. On the other hand, it is found that the areas with lowlands are strongly characterized by the northeast monsoonal flow.The results of the Mann-Kendall test, shows that, trends of the total amount of rainfall during the southwest monsoon decrease at some of the stations. The rainfall intensity increases in contrast, increasing trends in the total amount of rainfall were observed at three stations during the northeast monsoon, which give rise to the increasing trend of rainfall intensity. The results for the combined stations in both seasons indicate that there are no significant changes in trends during the extreme events for the Terengganu Malaysia. However, a smaller number of significant trends were found for extreme intensity. 

scholarly journals Spatio-Temporal Analysis of Drought Indicated by SPEI over Northeastern China

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 908 ◽  
Author(s):  
Lei Ye ◽  
Ke Shi ◽  
Hairong Zhang ◽  
Zhuohang Xin ◽  
Jing Hu ◽  
...  
Keyword(s):  
Water Resource Management ◽  
Kendall Test ◽  
Temporal Analysis ◽  
Northeastern China ◽  
Jilin Province ◽  
Liaoning Province ◽  
Songhua River ◽  
Liaohe River ◽  
Spatio Temporal ◽  
Increasing Trends

Drought is a natural extreme climate event which occurs in most parts of the world. Northeastern China is one of the major agricultural production areas in China and also a typical vulnerable climate zone. To understand the spatio-temporal characteristics of drought over northeastern China, we first assessed the trends of precipitation and temperature. Drought events were then characterized by Standardized Precipitation Evapotranspiration Index over various temporal scales. The Trend Free Prewhitening Mann–Kendall test and distinct empirical orthogonal function, were used to investigate the trends and spatio-temporal patterns of droughts. The results indicate precipitation increasing trends are mostly detected in Heilongjiang and Jinling provinces, however, the majority of the trends are insignificant. Temperature increasing trends are detected over the entire northeastern China and most of them are significant. Decreasing drought trends are observed in Heilongjiang province and some bordering area in Jilin province, whereas increasing trends are noticed in Liaoning province and some bordering area in Jilin province. Two main sub-regions of drought variability—the Liaohe River Plain and the Second Songhua River basin (LS region), and the Songnen Plain and the Lesser Hinggan Mountains (SL region) are identified, and the detected droughts for the two sub-regions correspond well with recorded drought loss. The results will be beneficial for regional water resource management and planning, agriculture production, and ecosystem protection in northeastern China.

scholarly journals Time Series Modelling of Monthly Temperature and Reference Evapotranspiration for Navsari (Gujarat), India

2019 ◽  
pp. 1-13
Author(s):  
D. K. Dwivedi ◽  
P. K. Shrivastava
Keyword(s):  
Time Series ◽  
Reference Evapotranspiration ◽  
Kendall Test ◽  
Trend Detection ◽  
Positive Trend ◽  
Monthly Temperature ◽  
Mean Temperature ◽  
Time Series Modelling ◽  
Mann Kendall Test ◽  
Past Data

Time series modelling has been proved its usefulness in various fields including meteorology, hydrology and agriculture. It utilizes past data and extracts useful information from them to build up a model which could simulate various processes. The prior knowledge of evapotranspiration could help in estimating the amount of water required by the crops that is useful for optimizing design of irrigation systems. In this study, the time series modelling of monthly temperature and reference evapotranspiration has been carried out utilizing past data of 35 years (1983-2017) to assist decision makers related to agriculture and meteorology. 30 years (1983-2012) of temperature and evapotranspiration data were used for training and remaining 5 years of data (2013-2017) were used for validation. The monthly evapotranspiration was estimated using Penman-Monteith FAO-56 method. Mann-Kendall test was used at 5% significant level for identifying trend component in mean temperature. The time series of temperature and evapotranspiration was made stationary for modelling the stochastic components using ARIMA (Autoregressive Integrated Moving Average) model. In order to check the normality of residuals, the Portmantaeu test was applied. The time series models for temperature and evapotranspiration which were validated for 5 years (2013-2017) and further deployed for forecasting of 5 years (2018-2022). It was found that for modelling temperature and reference evapotranspiration for Navsari, seasonal ARIMA (1,0,0)(0,1,1)12 and seasonal ARIMA (1,0,1)(1,1,2)12 were found to be appropriate models respectively. Mann Kendall test used for trend detection in monthly mean temperature revealed that October and November months had significant positive trend. Negative trend was observed only in the month of June.

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