Assessing the Climate Tendency over the Yangtze River Delta, China: Properties, Dry/Wet Event Frequencies, and Causes

Wu, Yanjie; Xu, Yu

doi:10.3390/w12102734

Cited by 2 publications

(4 citation statements)

References 35 publications

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“…Furthermore, significant positive anomalies were observed in the 2010s at the annual time scale and in the flood season, with anomalies higher than 20%. The YRD has, indeed, experienced several severe floods around 1991, 1999 and 2015 (Liu et al 2008;Wu & Xu 2020). Also, there are high anomalies of annual precipitation exhibited around 1961, 1975, 1982, 1991 and 1998, and low anomalies around 1966, 1980, 1986, 1995 and 2006.…”

Section: Resultsmentioning

confidence: 98%

“…High values were found in the 2010s in the northern region and the mid-2000s in the northern region. Generally, the increasing and decreasing trend of annual average precipitation dominated in the southern and northern regions of the YRD (Hu et al 2016;Wu & Xu 2020). The total wetness events were detected in 1962-1963, 1973-1975, 1990-1992, 1998-2000, 2003-2006, 2010 and 2015-2016.…”

Section: Spatial Patterns Of Precipitationmentioning

confidence: 94%

“…On the annual scale, significant negative anomalies were found in 23, 13 and 12 stations (53.49, 30.23 and 27.91% of the total) around the years 1968, 1978 and 2005, respectively. On the other hand, significant positive anomalies were found in 7, 6, 10 and 18 stations (16.28, 13.95, 23.26 and 41.86% of the total) around the years 1976, 1991, 1998-2002 and 2014, respectively. In the YRD, large-scale extremely dry events mainly happened in the late 1960s, the late 1970s and the 2000s assessed by the SPI method (Wu & Xu 2020). Meanwhile, several similar periods with significant positive/negative anomalies were also detected in flood and non-flood seasons.…”

Section: Spatial Trends Of Precipitationmentioning

confidence: 98%

“…The extreme wetness events mainly happened in the south of the Yangtze River. Meanwhile, large-scale extremely dry events mainly happened in the 1960s, the late 1970s and the 2000s (Wu & Xu 2020).…”

Section: Spatial Patterns Of Precipitationmentioning

confidence: 99%

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Change patterns of precipitation anomalies and possible teleconnections with large-scale climate oscillations over the Yangtze River Delta, China

Zhao

et al. 2022

Journal of Water and Climate Change

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In view of the key factor in regional hydrological processes and water resource management, the temporal patterns of precipitation anomalies and oscillations were detected by the Quantile Perturbation Method (QPM) and the Singular Spectrum Analysis (SSA) Method, and the spatial patterns were identified using the Principal Component Analysis (PCA) Method. In addition, the teleconnections and lagged influence with large-scale climate oscillations in the Yangtze River Delta (YRD) of China from 1957 to 2016 were also analyzed. Results showed that, temporally, the main oscillations of precipitation were all found to be 2, 7–11 and 3–4 years in the annual and seasonal scales. Precipitation quantiles are subject to strong temporal oscillations at (multi-)decadal time scales, with high and low anomalies at specific periods. Spatially, the whole region could be divided into two main sub-regions in annual and seasonal scales, respectively. Among the selected large-scale climate oscillations, the Pacific Decadal Oscillation (PDO) have a stronger influence on precipitation in March, July and September, but significant correlations were detected in more than 18% of the total stations. These stations mainly in the southeast regions. The North Pacific index (NP) controlled the precipitation in February (13.95% of the total stations) and October (37.21% of the total stations) in the north region. Generally, the indicators of the Southern Oscillation index (SOI) and Oceanic Niño 4 SST Index (ONI) had the strongest influence in regional precipitation variations, but significant correlations were detected in more than 20% of the total stations in March, September, October and November. Also, large-scale climate oscillations have a delayed way on precipitation. Among the oscillations, the Arctic Oscillation (AO) and North Atlantic Oscillation (NAO) showed that significant cross-correlations on precipitation were 0 and 3–5 months, respectively. NP showed significant cross-correlations with precipitation in many stations when the lag time was 0–3 months. Generally, the PDO, SOI and ONI have a greater influence in the south region, mainly with the lag time of 0–3, 2–3 and 1–5 months, respectively. The results will provide a basis for taking relevant measures to deal with problems of meteorological disaster and water supplement under climate change.

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Section: Resultsmentioning

confidence: 98%

Section: Spatial Patterns Of Precipitationmentioning

confidence: 94%

Section: Spatial Trends Of Precipitationmentioning

confidence: 98%

Section: Spatial Patterns Of Precipitationmentioning

confidence: 99%

See 2 more Smart Citations

Change patterns of precipitation anomalies and possible teleconnections with large-scale climate oscillations over the Yangtze River Delta, China

Zhao

et al. 2022

Journal of Water and Climate Change

Self Cite

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Spatial-Temporal Variations of Extreme Precipitation Characteristics and Its Correlation with El Niño-Southern Oscillation during 1960–2019 in Hubei Province, China

Wang

Tang

et al. 2022

Atmosphere

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Extreme precipitation could result in many disasters, such as floods, drought, and soil erosion, further bringing severe economic loss. Based on the daily precipitation records during 1960–2019 of 26 stations obtained from the National Meteorological Science Data Center of China, 10 extreme precipitation indices (EPIs: annual total precipitation (PRCPTOT), max-1-day precipitation amount (RX1day), max-5-day precipitation amount (RX5day), number of heavy rain days (R10), number of very heavy rain days (R10), simple daily intensity index (SDII), consecutive dry days (CDD), continued wet days (CWD), very wet days (R95p) and extremely wet days (R99p)) were chosen and used to analyze the spatial-temporal variation of extreme precipitation within Hubei province, China, which is an important industrial and agricultural base in China. Finally, the correlation between El Niño-Southern Oscillation and EPIs was analyzed by cross-wavelet analysis. Results showed that the annual EPIs varied obviously during 1960–2019, and CWD decreased significantly (p < 0.05). The chosen EPIs were higher in eastern and southwestern Hubei compared to other regions, and RX1day, RX5day, R95p, and R99p were increased in most regions. The spatial-temporal variations of spring and summer EPIs were more obvious than those on an annual scale. In summer, all EPIs except CDD should increase in the near future. More attention should be paid to Wuhan, Enshi, and Macheng, where the RX1day, RX5day, R95p, and R99p will increase in these regions. Finally, the RX1day and R10 were positively correlated with MEI (p < 0.05), while the RX5day, CDD, CWD, and R99p were negatively correlated with MEI (p < 0.05). The extreme precipitation events within Hubei were affected by the El Niño-Southern Oscillation. The results could provide a possible driving factor for precipitation prediction and natural hazard prevention within Hubei province, China.

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Assessing the Climate Tendency over the Yangtze River Delta, China: Properties, Dry/Wet Event Frequencies, and Causes

Cited by 2 publications

References 35 publications

Change patterns of precipitation anomalies and possible teleconnections with large-scale climate oscillations over the Yangtze River Delta, China

Change patterns of precipitation anomalies and possible teleconnections with large-scale climate oscillations over the Yangtze River Delta, China

Spatial-Temporal Variations of Extreme Precipitation Characteristics and Its Correlation with El Niño-Southern Oscillation during 1960–2019 in Hubei Province, China

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