Trends of precipitation extremes during 1960–2008 in Xinjiang, the Northwest China

Jiang, Feihong; Hu, R. J.; Wang, Shaoping; Zhang, Yanwei; Li, Tong

doi:10.1007/s00704-012-0657-3

Cited by 83 publications

(66 citation statements)

References 44 publications

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“…(1) if only 1 day has missing data, the missing data are replaced by the average value of the same day in all selected years; (2) if consecutive two or more days have missing data, the missing data are processed by simple linear correlation between the station and its neighbours (distance <100 km) (Jiang et al, 2012). Furthermore, homogenization was done for the daily precipitation dataset of these selected meteorological stations to avoid Hussain and Lee, 2013), based on these heavy and torrential precipitation thresholds obtained by Table 2 which are extreme precipitation thresholds for NAR, China, extreme precipitation indices showed in Table 3 are defined.…”

Section: Datamentioning

confidence: 99%

Spatial coherence of variations in seasonal extreme precipitation events over Northwest Arid Region, China

Wang

Jiang

Ding

2015

Intl Journal of Climatology

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Daily precipitation data covering the period of 1961-2009 from 72 stations in Northwest Arid Region, China, are analysed to investigate coherent subregions of variations in extreme precipitation events. First, four extreme precipitation indices, i.e. number of heavy precipitation days (DPh), precipitation intensity above heavy precipitation (IPh), number of torrential precipitation days (DPt), and precipitation intensity above torrential precipitation (IPt), were defined and analysed seasonally. Then rotated empirical orthogonal function (REOF) technique is used to identify the coherent subregions of these seasonal extreme precipitation indices and related trends. The results indicate that the number of coherent subregions of DPh, IPh, DPt, and IPt is 6, 5, 14, and 10 for spring; 4, 18, 6, and 6 for summer; 15, 8, 10, and 8 for autumn; and 7, 7, 2, and 5 for winter, respectively. Attribute shifts of underlying surfaces should be an important driving factor behind changes of extreme precipitation events. Intensity variations of heavy and torrential precipitation are the main reason behind significant changes of extreme precipitation, especially intensity variations of the heavy precipitation. The highest increasing magnitude of IPh is 584% (10a) −1 which is found in summer in the west parts of the Southern Xinjiang, the middle Tianshan Mountains, and the west parts of the Junggar Basin in the Northern Xinjiang. The findings of this study are potentially relevant for the development of human understanding of hydrological cycle responses in arid regions to regional and global climate changes, particularly in terms of extreme weather extremes.

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Section: Datamentioning

confidence: 99%

Spatial coherence of variations in seasonal extreme precipitation events over Northwest Arid Region, China

Wang

Jiang

Ding

2015

Intl Journal of Climatology

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“…In Brazil, some studies can be cited, such as: Santos et al (2012a), who applied to the part of Northern Brazil, including the North, Northeast, Midwest and part of the Southeast; Santos et al (2012b) applied to Manaus; Pinheiro, Graciano and Severo (2013) in southern Brazil; Santos et al (2012c) applied to the city of Rio Claro, São Paulo; Wang et al (2012Wang et al ( , 2013 and Jiang et al (2013) applied to China, and Santos et al ( , 2012d) who applied to Utah and Idaho, USA.…”

Section: Punctual Rainfall Indicesmentioning

confidence: 99%

Influence of oceanic-atmospheric interactions on extreme events of daily rainfall in the Sub-basin 39 located in Northeastern Brazil

Salgueiro¹,

Montenegro

Pinto

et al. 2016

RBRH

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Changes in extreme precipitation have been observed in regions where frequent rainfalls occur over short periods of time followed by prolonged droughts, creating, as a result, new watershed scenarios. Recent studies have attributed such occurrences to possible climate changes. This paper analyzes the correlation between extreme events recorded in the Sub-basin 39, located in Northeastern Brazil, and the anomalies caused by sea surface temperature -SST and the atmospheric systems operating in the region. Pearson correlation coefficients have been used combined with the variables analyzed. For such, trends in precipitation have been obtained by using the method of least squares together with linear regression and the Student's t test. The results obtained have demonstrated that due to the geographical position of the region investigated, both maximum extreme events (areas with positive trends) and minimum extreme events (areas with negative trends) are more dependent on the Dipole Atlantic than on the effects of El Niño Southern Oscillation -ENOS.Keywords: Climate change; Maximum precipitation; Minimum precipitation; Influence on TSM. RESUMOAs alterações nos extremos pluviométricos estão sendo observadas em várias localidades, com uma frequência maior de chuvas intensas concentradas em poucos dias e estiagens mais prolongadas, passando a caracterizar novos cenários nas bacias hidrográficas. Estudos específicos vêm atribuindo tais ocorrências às possíveis modificações climáticas. Este artigo analisou a relação existente entre os eventos extremos registrados na Sub-bacia 39, localizada no Nordeste do Brasil, com as anomalias das Temperaturas da Superfície do Mar (TSM) e os sistemas atmosféricos atuantes na região, utilizando os coeficientes de correlação de Pearson entre as variáveis analisadas. Para isso, as tendências da precipitação foram obtidas utilizando o Método dos Mínimos Quadrados, associado à regressão linear e o teste t de Student. Os resultados evidenciaram que devido à posição geográfica da região estudada, tanto os eventos extremos máximos (áreas com tendências positivas) como os eventos extremos mínimos (áreas com tendências negativas) são bem mais dependentes do Dipolo do Atlântico do que das influências do El Niño/Oscilação Sul -ENOS.Palavras-chave: Mudanças climáticas; Precipitações máximas; Precipitações mínimas; Influência de TSM.

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“…In general, extreme precipitation is defined as annual total precipitation with daily precipitation > 95th percentile, named P95, which is one of the thirteen extreme precipitation indices introduced by the ETCCDI (the Expert Team on Climate Change Detection and Indices) [10,11]. Recent research indicates that extreme precipitation in Xinjiang also exhibits increasing trends [12][13][14][15][16], consistent with regional and global studies [17][18][19]. Global warming has been projected to lead to large increases in extreme precipitation [20][21][22][23][24].…”

Section: Introductionmentioning

confidence: 99%

Possible Causes for Spatial and Temporal Variation of Warm Season Precipitation in Xinjiang from 1960–2014

et al. 2017

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Abstract:In this work, rain totals from 1960-2014, obtained during the warm season (May to October) from 52 meteorological stations, over Xinjiang, China were classified as either light, moderate, or heavy rain in two sub-regions (northern and southern). Spatial and temporal trends for rain amounts and days for the three rain classes were determined. All light, moderate, and heavy rain amounts displayed increasing trends over the two sub-regions. Furthermore, heavy rain amounts contributed the most to changes in total rain amounts. Light rain days in northern Xinjiang significantly decreased, in contrast to increasing light rain days in southern Xinjiang and moderate and heavy rain days within two sub-regions. Results obtained from correlation and relative weights analyses implied that lower-tropospheric specific humidity was the main factor responsible for light rain day trends in Xinjiang. Increasing temperatures were not found to have a significant effect.

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Trends of precipitation extremes during 1960–2008 in Xinjiang, the Northwest China

Cited by 83 publications

References 44 publications

Spatial coherence of variations in seasonal extreme precipitation events over Northwest Arid Region, China

Spatial coherence of variations in seasonal extreme precipitation events over Northwest Arid Region, China

Influence of oceanic-atmospheric interactions on extreme events of daily rainfall in the Sub-basin 39 located in Northeastern Brazil

Possible Causes for Spatial and Temporal Variation of Warm Season Precipitation in Xinjiang from 1960–2014

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