Detection of Approximate Potential Trend Turning Points in Temperature Time Series (1941-2010) for Asansol Weather Observation Station, West Bengal, India

Chatterjee, Soumendu; Bisai, Dipak; Khan, A. R.

doi:10.4236/acs.2014.41009

Cited by 24 publications

(21 citation statements)

References 11 publications

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“…A positive significant correlation between NDVI and Soil temperature, NDII, and ET, which is also represented as in Figures 7 and 8, indicates that soil moisture, soil temperature, and evapotranspiration play a significant role in vegetation health in the HiP. The significant but negative correlation between Niño3.4 and NDVI confirms the notion that ENSO variability plays a role in the climatic conditions of southern Africa [35,52]. [66].…”

Section: Correlations Statistics and Mann-kendall Testsupporting

confidence: 64%

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Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought

Mbatha

Xulu

2018

Climate

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The variability of temperature and precipitation influenced by El Niño-Southern Oscillation (ENSO) is potentially one of key factors contributing to vegetation product in southern Africa. Thus, understanding large-scale ocean-atmospheric phenomena like the ENSO and Indian Ocean Dipole/Dipole Mode Index (DMI) is important. In this study, 16 years (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017) of Moderate Resolution Imaging Spectroradiometer (MODIS) Terra/Aqua 16-day normalized difference vegetation index (NDVI), extracted and processed using JavaScript code editor in the Google Earth Engine (GEE) platform was used to analyze the vegetation response pattern of the oldest proclaimed nature reserve in Africa, the Hluhluwe-iMfolozi Park (HiP) to climatic variability. The MODIS enhanced vegetation index (EVI), burned area index (BAI), and normalized difference infrared index (NDII) were also analyzed. The study used the Modern Retrospective Analysis for the Research Application (MERRA) model monthly mean soil temperature and precipitations. The Global Land Data Assimilation System (GLDAS) evapotranspiration (ET) data were used to investigate the HiP vegetation water stress. The region in the southern part of the HiP which has land cover dominated by savanna experienced the most impact of the strong El Niño. Both the HiP NDVI inter-annual Mann-Kendal trend test and sequential Mann-Kendall (SQ-MK) test indicated a significant downward trend during the El Niño years of 2003 and 2014-2015. The SQ-MK significant trend turning point which was thought to be associated with the 2014-2015 El Niño periods begun in November 2012. The wavelet coherence and coherence phase indicated a positive teleconnection/correlation between soil temperatures, precipitation, soil moisture (NDII), and ET. This was explained by a dominant in-phase relationship between the NDVI and climatic parameters especially at a period band of 8-16 months. Climate 2018, 6, 95 2 of 24The influence of drought on vegetation varies in the spatial and temporal scales, and these are projected to increase with climate change [6,7]. This behavior affects wildlife, particularly in semi-arid and arid environments where herbivory is strongly restricted by vegetation extent and water availability [8]. In the north-east part of KwaZulu-Natal, South Africa, for example, droughts are becoming a recurrent and prominent feature [9,10], affecting vegetation, water and wildlife resources notably in the Hluhluwe-iMfolozi Park (HiP), the oldest proclaimed game reserve in Africa, as reported in this paper. Furthermore, these impacts have potential consequences that could incapacitate this game reserve's support of its specialist grazers such as rhinos [11].Understanding the association between vegetation productivity and climatic variables such as precipitation and temperature has, therefore, become a high priority. To address this, spatiotemporal tools that can integrate climate data with other information of interest are required....

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Section: Correlations Statistics and Mann-kendall Testsupporting

confidence: 64%

“…Additionally, in this study, a 95% confidence level was considered, which means critical limit values are ±1.96. This method has been successfully utilized in studies of trends detection in temperature [52,53] and precipitation [51,53,54].…”

Section: Mann-kendall Testmentioning

confidence: 99%

Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought

Mbatha

Xulu

2018

Climate

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“…Determination of beginning, change, and abrupt changes in the trend in long time data series is also important in climate studies. Sequential Mann Kendall technique is becoming popular for the determination of start of trend and abrupt change in trends [28][29][30].…”

Section: Introductionmentioning

confidence: 99%

Trend Change Study of Climate Variables in Xin’anjiang-Fuchunjiang Watershed, China

Zaman¹,

Fang²,

Mehmood³

et al. 2015

Advances in Meteorology

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This study emphasizes the precipitation and the maximum and minimum temperature trend and presents the results of study in temporal and spatial scales, after performing statistical analysis of the Xin’anjiang-Fuchunjiang watershed. Statistical Mann Kendall and Theil Sen techniques were used to determine the trend and its magnitude, respectively, and for determining the start and abrupt change in the trend, Sequential Mann Kendall test has been performed. Furthermore, statistical tests were performed to determine the overall trend in the area at a regional basis. For the removal of the serial effect of the data, prewhitening technique is applied. In this study, statistical tests were performed at 1901–2013 precipitation and temperature series and then after detection of the change year precipitation data were divided into two different scenarios of 1901–1960 period and 1961–2013 period. The results showed that precipitation trend is insignificant while maximum and minimum temperature have increased during 1901–2013 period except for some stations of autumn and summer seasons.

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“…The annual average, maximum, and minimum precipitations were 477.3 mm, 816.9 mm (1967), and 266.5 mm (1972). UF and UB are standardized statistical series which can be written as Equations (4) and (5) in the M-K test [61]. When the UF curve and the UB curve intersect in the confidence zone, the cross point indicates that it is an abrupt point [61].…”

Section: Design Of the Climate Scenariosmentioning

confidence: 99%

“…When the UF curve and the UB curve intersect in the confidence zone, the cross point indicates that it is an abrupt point [61].…”

Section: Design Of the Climate Scenariosmentioning

confidence: 99%

Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China

Jin

Zhu

Zhao

et al. 2016

Water

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Abstract:The assessment of water resource responses to climate change is required in water resource planning and management, protecting environmental quality, and managing watersheds. This study modeled surface runoff and baseflow responses to variations in precipitation (0%, ±10%, and ±20%) and temperature (0 • C, ±1 • C, and ±2 • C) in 25 types of scenarios in the Lanhe Watershed (1140 km 2 ), which possesses the typical hydrological and meteorological characteristics of the Loess Plateau in China. The study is based on the Soil and Water Assessment Tool (SWAT), which was calibrated and validated using the coefficient of determination (R 2 ), Nash-Suttcliffe (Ens), and Percent bias (PBIAS), using the observed streamflow of Shangjingyou Station, a unique gauging station in the study area. The model was calibrated with daily streamflow, from 1967 to 1996, and then validated from 1997 to 2011. R 2 , Ens, and PBIAS were 0.95 and 0.84, 0.78 and 0.72, and 0.6% and −9.1% in annual and monthly calibration periods, 0.90 and 0.78, 0.74 and 0.67, and 22.1% and 18.8% in annual and monthly validation periods, and the overall performance ratings was "satisfactory". The assessment indicates that surface runoff is likely to be more affected than baseflow when altering temperatures and precipitation, and the noticeable changes of surface and baseflow are from June to September and October to November, respectively. Results also indicate that surface runoff and baseflow are very sensitive to the projected reduction in temperature, rather than to an increase of temperature, while precipitation is a constant. In turn, when the temperature is a constant, the surface runoff is sensitive to the projected increase in precipitation and the baseflow is sensitive to the decrease in precipitation.

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Detection of Approximate Potential Trend Turning Points in Temperature Time Series (1941-2010) for Asansol Weather Observation Station, West Bengal, India

Cited by 24 publications

References 11 publications

Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought

Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought

Trend Change Study of Climate Variables in Xin’anjiang-Fuchunjiang Watershed, China

Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China

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