Precipitation and temperature changes in eastern India by multiple trend detection methods

Sharma, Chandra Shekhar; Panda, Sudhindra N.; Pradhan, Rudra P.; Singh, Amanpreet; Kawamura, Akira

doi:10.1016/j.atmosres.2016.04.019

Cited by 86 publications

(41 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…When the slope is less than 0, a decreasing trend is seen in the extreme indices, an increasing trend is seen when the slope is greater than 0, and the magnitude of its absolute value reflects the rate at which the extreme indices rise or fall. The statistical significance of the trends was assessed at the 95% confidence level (P<0.05) if |Z|1.96 and at the 99% confidence level (P<0.01) if |Z|2.58 (Sharma et al 2016).…”

Section: Definition Of Extreme Indicesmentioning

confidence: 99%

“…The Pearson correlation analysis method describes the degree of compactness by analyzing the linear relationship magnitude between two variables (Sharma et al 2016, Iqbal and Athar 2017, Ding et al 2018. When the correlation coefficient value is greater than 0, the two variables are positively correlated and are negatively correlated when the coefficient is less than 0.…”

Section: Correlation Analysismentioning

confidence: 99%

See 1 more Smart Citation

Spatiotemporal variations in extreme precipitation and their potential driving factors in non-monsoon regions of China during 1961–2017

Ding

Wang

2019

Environ. Res. Lett.

View full text Add to dashboard Cite

Extreme precipitation events affect the ecological environment and are also important for the sustainable development of regional socioeconomics. Although there are some local studies on extreme precipitation events in which the temporal and spatial variation characteristics of extreme precipitation events in non-monsoon regions (NMRs) are systematically assessed, detailed study on the driving mechanisms of variation are becoming increasingly important. In this study, nine extreme precipitation indices were used to analyze the characteristics of extreme precipitation event spatiotemporal variations in NMRs in China during 1961-2017. The results show that except for the consecutive dry days, which shows a significant decreasing trend (P < 0.01) of −2.33 days/decade, all other indices showed obvious increasing trends, especially the indices of wet day precipitation (PRCPTOT), highest 5 day precipitation (RX5day) and light rain days (R5 mm), with significantly increasing trends (P< 0.01) of 6.80 mm/decade, 0.73 mm/decade and 0.45 days/decade, respectively. In addition, a correlation analysis between altitude, longitude, latitude and extreme precipitation shows that stations at an altitude of more than 3500 m have significant correlations with both extreme precipitation and longitude in NMRs (P< 0.05). In addition, results also indicated that there are significant relationships between extreme precipitation events in NMRs and large-scale ocean-atmosphere circulation patterns (P< 0.05). The rapid increase in extreme precipitation indices over the past 20 years is closely related to the Atlantic Multidecadal Oscillation shift to a warm phase, while the Pacific Decadal Oscillation, El Niño-Southern Oscillation and Summer Monsoon Index show significant correlation with the extreme indices only in certain seasons (P< 0.05).

show abstract

Section: Definition Of Extreme Indicesmentioning

confidence: 99%

Section: Correlation Analysismentioning

confidence: 99%

Spatiotemporal variations in extreme precipitation and their potential driving factors in non-monsoon regions of China during 1961–2017

Ding

Wang

2019

Environ. Res. Lett.

View full text Add to dashboard Cite

show abstract

“…The MK test is often used to detect a step change point in the long-term trend of a time series dataset (Moraes et al, 1998;Li et al, 2016;Zhao et al, 2015). It is suitable for non-normally distributed data and censored data which are not influenced by abnormal values (Yue and Pilon, 2004;Sharma et al, 2016;Yue and Wang, 2004;Gao and Shi, 2016;Zhao et al, 2015). Recently, the MK test has also been used in trend analysis for the time series of atmospheric chemicals, such as persistent organic pollutants, surface ozone (O 3 ), and non-methane hydrocarbon (Zhao et al, 2015;Assareh et al, 2016;Waked et al, 2016;Sicard et al, 2016).…”

Section: Trends and Step Changementioning

confidence: 99%

OMI-measured increasing SO<sub>2</sub> emissions due to energy industry expansion and relocation in northwestern China

et al. 2017

View full text Add to dashboard Cite

Abstract. The rapid growth of economy makes China the largest energy consumer and sulfur dioxide (SO 2 ) emitter in the world. In this study, we estimated the trends and step changes in the planetary boundary layer (PBL) vertical column density (VCD) of SO 2 from 2005 to 2015 over China measured by the Ozone Monitoring Instrument (OMI). We show that these trends and step change years coincide with the effective date and period of the national strategy for energy development and relocation in northwestern China and the regulations in the reduction of SO 2 emissions. Under the national regulations for the reduction of SO 2 emissions in eastern and southern China, SO 2 VCD in the Pearl River Delta (PRD) of southern China exhibited the largest decline during 2005-2015 at a rate of −7 % yr −1 , followed by the North China Plain (NCP) (−6.7 % yr −1 ), Sichuan Basin (−6.3 % yr −1 ), and Yangtze River Delta (YRD) (−6 % yr −1 ). The Mann-Kendall (MK) test reveals the step change points of declining SO 2 VCD in 2009 for the PRD and 2012-2013 for eastern China responding to the implementation of SO 2 control regulation in these regions. In contrast, the MK test and regression analysis also revealed increasing trends of SO 2 VCD in northwestern China, particularly for several "hot spots" featured by growing SO 2 VCD in those large-scale energy industry bases in northwestern China. The enhanced SO 2 VCD is potentially attributable to increasing SO 2 emissions due to the development of large-scale energy industry bases in energy-abundant northwestern China under the national strategy for the energy safety of China in the 21st century. We show that these largescale energy industry bases could overwhelm the trends and changes in provincial total SO 2 emissions in northwestern China and contribute increasingly to the national total SO 2 emissions in China. Given that northwestern China is more ecologically fragile and uniquely susceptible to atmospheric pollution than the rest of China, increasing SO 2 emissions in this part of China should not be overlooked and merit scientific research.

show abstract

“…Over the past few years, many studies have been conducted worldwide to assess the changing trends in temperature and rainfall for different countries such as the USA, Africa, India, Norwegian Arctic, Nepal, Northwestern Himalaya [10,[12][13][14][15], using different statistical models and methods.…”

Section: Introductionmentioning

confidence: 99%

Investigating Snow Cover and Hydrometeorological Trends in Contrasting Hydrological Regimes of the Upper Indus Basin

2018

View full text Add to dashboard Cite

Abstract:The Upper Indus basin (UIB) is characterized by contrasting hydrometeorological behaviors; therefore, it has become pertinent to understand hydrometeorological trends at the sub-watershed level. Many studies have investigated the snow cover and hydrometeorological modeling at basin level but none have reported the spatial variability of trends and their magnitude at a sub-basin level. This study was conducted to analyze the trends in the contrasting hydrological regimes of the snow and glacier-fed river catchments of the Hunza and Astore sub-basins of the UIB. Mann-Kendall and Sen's slope methods were used to study the main trends and their magnitude using MODIS snow cover information (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) and hydrometeorological data. The results showed that in the Hunza basin, the river discharge and temperature were significantly (p ≤ 0.05) decreased with a Sen's slope value of −2.541 m 3 ·s −1 ·year −1 and −0.034 • C·year −1 , respectively, while precipitation data showed a non-significant (p ≥ 0.05) increasing trend with a Sen's slope value of 0.023 mm·year −1 . In the Astore basin, the river discharge and precipitation are increasing significantly (p ≤ 0.05) with a Sen's slope value of 1.039 m 3 ·s −1 ·year −1 and 0.192 mm·year −1 , respectively. The snow cover analysis results suggest that the Western Himalayas (the Astore basin) had a stable trend with a Sen's slope of 0.07% year −1 and the Central Karakoram region (the Hunza River basin) shows a slightly increasing trend with a Sen's slope of 0.394% year −1 . Based on the results of this study it can be concluded that since both sub-basins are influenced by different climatological systems (monsoon and westerly), the results of those studies that treat the Upper Indus basin as one unit in hydrometeorological modeling should be used with caution. Furthermore, it is suggested that similar studies at the sub-basin level of the UIB will help in a better understanding of the Karakoram anomaly.

show abstract

Precipitation and temperature changes in eastern India by multiple trend detection methods

Cited by 86 publications

References 36 publications

Spatiotemporal variations in extreme precipitation and their potential driving factors in non-monsoon regions of China during 1961–2017

Spatiotemporal variations in extreme precipitation and their potential driving factors in non-monsoon regions of China during 1961–2017

OMI-measured increasing SO<sub>2</sub> emissions due to energy industry expansion and relocation in northwestern China

Investigating Snow Cover and Hydrometeorological Trends in Contrasting Hydrological Regimes of the Upper Indus Basin

Contact Info

Product

Resources

About

Precipitation and temperature changes in eastern India by multiple trend detection methods

Cited by 86 publications

References 36 publications

Spatiotemporal variations in extreme precipitation and their potential driving factors in non-monsoon regions of China during 1961–2017

Spatiotemporal variations in extreme precipitation and their potential driving factors in non-monsoon regions of China during 1961–2017

OMI-measured increasing SO&lt;sub&gt;2&lt;/sub&gt; emissions due to energy industry expansion and relocation in northwestern China

Investigating Snow Cover and Hydrometeorological Trends in Contrasting Hydrological Regimes of the Upper Indus Basin

Contact Info

Product

Resources

About

OMI-measured increasing SO<sub>2</sub> emissions due to energy industry expansion and relocation in northwestern China