scholarly journals Spatiotemporal Trend Analysis of Precipitation Extremes in Ho Chi Minh City, Vietnam During 1980–2017

Author(s):  
Nguyen Trong Quan ◽  
Dao Nguyen Khoi ◽  
Nguyen Xuan Hoan ◽  
Nguyen Ky Phung ◽  
Thanh Duc Dang

Abstract In this study, the spatiotemporal variability of trends in extreme precipitation events in Ho Chi Minh City during the period 1980–2017 was analyzed based on several core extreme precipitation indices (Rx1day, Rx5day, CDD, CWD, R20mm, R25mm, R95p, and SDII). The non-parametric Mann–Kendall and Sen’s slope methods were used to compute the statistical strength, stability, and magnitude of trends in annual rainfall, as well as the extreme precipitation indices. We found that 64% of the stations had statistically significant upward trends in yearly rainfall, with high magnitudes frequently observed in the northern and southern regions of the city. For the extreme precipitation indices, only SDII and R25mm showed dominantly significant trends. Additionally, there were increasing trends in the frequency and duration at the southern and central regions of the city during the study period. Furthermore, El Niño-Southern Oscillation and Pacific Decadal Oscillation positively correlated with the duration and negatively correlated with the intensity and frequency of extreme precipitation. Thus, water management plans should be adjusted appropriately to reduce the severe impacts of precipitation extremes on communities and ecosystems.

2021 ◽  
Author(s):  
Shakti Suryavanshi ◽  
Nitin Joshi ◽  
Hardeep Kumar Maurya ◽  
Divya Gupta ◽  
Keshav Kumar Sharma

Abstract This study examines the pattern and trend of seasonal and annual precipitation along with extreme precipitation events in a data scare, south Asian country, Afghanistan. Seven extreme precipitation indices were considered based upon intensity, duration and frequency of precipitation events. The study revealed that precipitation pattern of Afghanistan is unevenly distributed at seasonal and yearly scales. Southern and Southwestern provinces remain significantly dry whereas, the Northern and Northeastern provinces receive comparatively higher precipitation. Spring and winter seasons bring about 80% of yearly precipitation in Afghanistan. However, a notable declining precipitation trend was observed in these two seasons. An increasing trend in precipitation was observed for the summer and autumn seasons, however; these seasons are the lean periods for precipitation. A declining annual precipitation trend was also revealed in many provinces of Afghanistan. Analysis of extreme precipitation indices reveals a general drier condition in Afghanistan. Large spatial variability was found in precipitation indices. In many provinces of Afghanistan, a significantly declining trends were observed in intensity-based (Rx1-day, RX5-day, SDII and R95p) and frequency-based (R10) precipitation indices. The duration-based precipitation indices (CDD and CWD) also infer a general drier climatic condition in Afghanistan. This study will assist the agriculture and allied sectors to take well-planned adaptive measures in dealing with the changing patterns of precipitation, and additionally, facilitating future studies for Afghanistan.


Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1981 ◽  
Author(s):  
Kang Liang

Precipitation extremes have important implications for regional water resources and ecological environment in endorheic (landlocked) basins. The Hongjian Lake Basin (HJLB), as the representative inflow area in the Ordos Plateau in China, is suffering from water scarcity and an ecosystem crisis; however, previous studies have paid little attention to changes in precipitation extremes in the HJLB. In this study, we investigated the spatio-temporal variations of the core extreme precipitation indices (i.e., PRCTOT, R99p, Rx1day, Rx5day, SDII, R1, R10, CWD, and CDD) recommended by the Expert Team on Climate Change Detection and Indices (ETCCDI), and analyzed the climatic dry–wet regime indicated by these extreme indices during 1960–2014 in the HJLB. The results show that the nine extreme indices had large differences in temporal and spatial variation characteristics. All the nine extreme precipitation indices showed a large fluctuation, both in the whole period and in the three detected different sub-periods, with variation magnitudes of 13%–52%. Most extreme indices had non-significant downward trends, while only the consecutive wet days (CWD) had a significant upward trend. The eight extreme wet indices increased from northwest to southeast, while the consecutive dry days (CDD) had the opposite change direction. Each index had a different trend with different spatial distribution locations and areas. The nine extreme indices revealed that the climate in the HJLB has become a drought since the early 1980s. This was specifically indicated by all four extreme precipitation quantity indices (PRCTOT, R99p, Rx1day, Rx5day) and the extreme intensity index (SDII) declining, as well as the number of heavy precipitation days (R10) decreasing. When the dry–wet variations was divided into the different sub-periods, the climatic dry–wet changes of each index demonstrated more inconsistency and complexity, but most indices in the first sub-period from 1960 to the late 1970s could be regarded as a wet high-oscillation phase, the second sub-period after the early 1980s was a relatively dry low-oscillation phase, and the third sub-period after the late 1990s or early 21st century was a dry medium-oscillation phase. It is worth noting that most extreme indices had an obvious positive linear trend in the third sub-period, which means that in the last 20 years, the precipitation extremes showed an increasing trend. This study could provide a certain scientific reference for regional climate change detection, water resources management, and disaster prevention in the HJLB and similar endorheic basins or inland arid regions.


Author(s):  
Ya Huang ◽  
Ling Yi ◽  
Weihua Xiao ◽  
Guibing Hou ◽  
Yuyan Zhou

Abstract Understanding changes in the intensity and frequency of extreme precipitation is vital for flood control, disaster mitigation, and water resource management. In this study, 12 extreme precipitation indices and the best-fitting extreme value distribution were used to analyze the spatiotemporal characteristics of extreme precipitation in the upper reaches of the Hongshui River Basin (UHRB). The possible links between extreme precipitation and large-scale circulation were also investigated. Most extreme precipitation indices increased from west to east in the UHRB, indicating that the eastern region is a humid area with abundant precipitation. The indices for consecutive wet days (CWD) and precipitation events (R0.1) decreased significantly, indicating that the UHRB tends to be dry, with few precipitation events. The probability distribution functions of most extreme precipitation indices, especially that of R0.1, shifted significantly to the left in 1988–2016 compared with 1959–1987, further indicating that the UHRB has experienced a significant drying trend in recent decades. The East Asian summer monsoon and the El Niño–Southern Oscillation/Pacific Decadal Oscillation were confirmed to influence extreme precipitation in the UHRB. These findings are helpful for understanding extreme precipitation variation trends in the UHRB and provide references for further research.


Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 120
Author(s):  
Dao Nguyen Khoi ◽  
Nguyen Trong Quan ◽  
Pham Thi Thao Nhi ◽  
Van Thinh Nguyen

In the context of climate change, the impact of hydro-meteorological extremes, such as floods and droughts, has become one of the most severe issues for the governors of mega-cities. The main purpose of this study is to assess the spatiotemporal changes in extreme precipitation indices over Ho Chi Minh City, Vietnam, between the near (2021–2050) and intermediate (2051–2080) future periods with respect to the baseline period (1980–2009). The historical extreme indices were calculated through observed daily rainfall data at 11 selected meteorological stations across the study area. The future extreme indices were projected based on a stochastic weather generator, the Long Ashton Research Station Weather Generator (LARS-WG), which incorporates climate projections from the Coupled Model Intercomparison Project 5 (CMIP5) ensemble. Eight extreme precipitation indices, such as the consecutive dry days (CDDs), consecutive wet days (CWDs), number of very heavy precipitation days (R20mm), number of extremely heavy precipitation days (R25mm), maximum 1 d precipitation amount (RX1day), maximum 5 d precipitation amount (RX5day), very wet days (R95p), and simple daily intensity index (SDII) were selected to evaluate the multi-model ensemble mean changes of extreme indices in terms of intensity, duration, and frequency. The statistical significance, stability, and averaged magnitude of trends in these changes, thereby, were computed by the Mann-Kendall statistical techniques and Sen’s estimator, and applied to each extreme index. The results indicated a general increasing trend in most extreme indices for the future periods. In comparison with the near future period (2021–2050), the extreme intensity and frequency indices in the intermediate future period (2051–2080) present more statistically significant trends and higher growing rates. Furthermore, an increase in most extreme indices mainly occurs in some parts of the central and southern regions, while a decrease in those indices is often projected in the north of the study area.


Atmosphere ◽  
2021 ◽  
Vol 12 (11) ◽  
pp. 1522
Author(s):  
Xiaoxia Yang ◽  
Juan Wu ◽  
Jia Liu ◽  
Xuchun Ye

In this study, 11 extreme precipitation indices were selected to examine the spatiotemporal variation of extreme precipitation in the Poyang Lake Basin during 1960–2017. The responses of extreme precipitation indices to El Nino/Southern Oscillation (ENSO) events of different Pacific Ocean areas were further investigated. The results show that the temperature in the Poyang Lake Basin has increased significantly since the 1990s, and the inter-decadal precipitation fluctuated. Most extreme precipitation indices showed an increasing trend with abrupt changes occurring around 1991. Spatially, most of the extreme precipitation indices decreased from northeast to southwest. The increasing trend of most indices in the center and south of the basin was relatively prominent. The linear correlations between the extreme precipitation indices and Nino 1 + 2 were the most significant. On the timescale of 2–6 years, a common oscillation period between the extreme precipitation of the basin and the four ENSO indices can be observed. After 2010, the positive correlation between the precipitation of the Poyang Lake Basin and the SST (sea surface temperature) anomalies in the equatorial Pacific increased significantly. Additionally, annual total wet–day precipitation in most areas of the Poyang Lake Basin increased with varying degrees in warm ENSO years. The results of this study will improve the understanding of the complex background and driving mechanism of flood disasters in the Poyang Lake Basin.


2014 ◽  
Vol 18 (2) ◽  
pp. 709-725 ◽  
Author(s):  
A. Casanueva ◽  
C. Rodríguez-Puebla ◽  
M. D. Frías ◽  
N. González-Reviriego

Abstract. A growing interest in extreme precipitation has spread through the scientific community due to the effects of global climate change on the hydrological cycle, and their threat to natural systems' higher than average climatic values. Understanding the variability of precipitation indices and their association to atmospheric processes could help to project the frequency and severity of extremes. This paper evaluates the trend of three precipitation extremes: the number of consecutive dry/wet days (CDD/CWD) and the quotient of the precipitation in days where daily precipitation exceeds the 95th percentile of the reference period and the total amount of precipitation (or contribution of very wet days, R95pTOT). The aim of this study is twofold. First, extreme indicators are compared against accumulated precipitation (RR) over Europe in terms of trends using non-parametric approaches. Second, we analyse the geographically opposite trends found over different parts of Europe by considering their relationships with large-scale processes, using different teleconnection patterns. The study is accomplished for the four seasons using the gridded E-OBS data set developed within the EU ENSEMBLES project. Different patterns of variability were found for CWD and CDD in winter and summer, with north–south and east–west configurations, respectively. We consider physical factors in order to understand the extremes' variability by linking large-scale processes and precipitation extremes. Opposite associations with the North Atlantic Oscillation in winter and summer, and the relationships with the Scandinavian and East Atlantic patterns as well as El Niño/Southern Oscillation events in spring and autumn gave insight into the trend differences. Significant relationships were found between the Atlantic Multidecadal Oscillation and R95pTOT during the whole year. The largest extreme anomalies were analysed by composite maps using atmospheric variables and sea surface temperature. The association of extreme precipitation indices and large-scale variables found in this work could pave the way for new possibilities regarding the projection of extremes in downscaling techniques.


Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 797 ◽  
Author(s):  
Asher Samuel Bhatti ◽  
Guojie Wang ◽  
Waheed Ullah ◽  
Safi Ullah ◽  
Daniel Fiifi Tawia Hagan ◽  
...  

Assessing the long-term precipitation changes is of utmost importance for understanding the impact of climate change. This study investigated the variability of extreme precipitation events over Pakistan on the basis of daily precipitation data from 51 weather stations from 1980-2016. The non-parametric Mann–Kendall, Sen’s slope estimator, least squares method, and two-tailed simple t-test methods were used to assess the trend in eight precipitation extreme indices. These indices were wet days (R1 ≥1 mm), heavy precipitation days (R10 ≥ 10 mm), very heavy precipitation days (R20 ≥ 20 mm), severe precipitation (R50 ≥ 50 mm), very wet days (R95p) defining daily precipitation ≥ 95 percentile, extremely wet days (R99p) defining daily precipitation ≥ 99 percentile, annual total precipitation in wet days (PRCPTOT), and mean precipitation amount on wet days as simple daily intensity index (SDII). The study is unique in terms of using high stations’ density, extended temporal coverage, advanced statistical techniques, and additional extreme indices. Furthermore, this study is the first of its kind to detect abrupt changes in the temporal trend of precipitation extremes over Pakistan. The results showed that the spatial distribution of trends in different precipitation extreme indices over the study region increased as a whole; however, the monsoon and westerlies humid regions experienced a decreasing trend of extreme precipitation indices during the study period. The results of the sequential Mann–Kendall (SqMK) test showed that all precipitation extremes exhibited abrupt dynamic changes in temporal trend during the study period; however, the most frequent mutation points with increasing tendency were observed during 2011 and onward. The results further illustrated that the linear trend of all extreme indices showed an increasing tendency from 1980- 2016. Similarly, for elevation, most of the precipitation extremes showed an inverse relationship, suggesting a decrease of precipitation along the latitudinal extent of the country. The spatiotemporal variations in precipitation extremes give a possible indication of the ongoing phenomena of climate change and variability that modified the precipitation regime of Pakistan. On the basis of the current findings, the study recommends that future studies focus on underlying physical and natural drivers of precipitation variability over the study region.


2020 ◽  
Author(s):  
Shivanand Mandraha ◽  
Sujata Ray

<p>The occurrence of extreme precipitation events is a severe concern to any nation due to its socio-economic impacts. In this study, spatiotemporal variability of precipitation extremes was analyzed over the Indian sub-continent using the quantile perturbation method (QPM). QPM is a non-parametric method that requires very few assumptions. The gridded data of precipitation with 0.5 × 0.5-degree resolution CRU (Climate Research Unit, University of East Anglia, UK) and 117 years (1901-2017) data set has been used. The result shows that the initial decade (1910s to 1940s) and the recent decade (1990s to 2000s) are the decades when significant anomalies found in most of India. The northeast part of India shows positive anomalies while the central region and northern region show negative anomalies in the 1910s. In the period of 1930-1940s central India shows positive anomalies, and the northern region shows negative anomalies. Significant positive anomalies found in the west part of southern India in the period of 1950-1960s. In the period of 1960-2000s, the northern region shows positive anomalies. Indo-Gangetic plain and central India have negative anomalies while the western part shows positive anomalies in the 2000s in most of the grid. To partially address the reason behind the perturbation correlation analysis has been applied between extreme precipitation anomaly and Indian Ocean Dipole. Results show a moderately negative correlation found in most of the eastern and north-eastern regions of India, while a positive correlation found in some northern and southern parts of India. Analysis suggests that Indian Ocean sea surface temperature might be the main driver for the decadal perturbations in precipitation extremes.</p>


2012 ◽  
Vol 573-574 ◽  
pp. 395-399
Author(s):  
Yong Wang ◽  
Yuan Yuan Ding ◽  
Qi Long Miao

Based on the daily precipitation data in Northeast China (NE China) from 1961 to 2010, six extreme precipitation indices (RX1day, Rx5day, R10mm, R20mm, R95T, and R99T) in NE China were calculated, and the temporal and spatial characteristics of extreme precipitation events were analyzed. The main results are summarized as follows: Except R99T, other extreme precipitation indicators all show the decreasing trend. All indicators are not significant. From the spatial distribution of extreme precipitation indicators, extreme precipitation indicators have different change situations in various regions, and the decreasing trends are dominant. This shows that the climate has become dry in NE China. It is important to forecast and reduce the climate induced flood risks and provide information for rational countermeasures.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Dan Zhang ◽  
Wensheng Wang ◽  
Shuqi Liang ◽  
Shunjiu Wang

Climate extremes have attracted widespread attention for their threats to the natural environment and human society. Based on gauged daily precipitation from 1963 to 2016 in four subregions of the Jinsha River Basin (JRB), four extreme precipitation indices developed by the Expert Team on Climate Change Detection and Indices (ETCCDI) were employed to assess the spatiotemporal variations of extreme precipitation events. Results show the following: (1) Max one-day precipitation amount (RX1day), max consecutive five-day precipitation amount (RX5day), precipitation on very wet days (R95p), and number of heavy precipitation days (R10mm) showed increasing trends in four subregions except for the decline of R10mm in the southeastern and RX5day in the midsouthern. Extreme precipitation has become more intense and frequent in most parts of the JRB. (2) In space, the four extreme precipitation indices increased from the northwest to the southeast. Temporal trends of extreme precipitation showed great spatial variability. It is notable that extreme precipitation increased apparently in higher elevation areas. (3) The abrupt change of extreme precipitation in the northwestern, midsouthern, and southeastern mainly appeared in the late 1990s and the 2000s. For the midnorthern, abrupt change mainly occurred in the late 1980s. This study is meaningful for regional climate change acquaintance and disaster prevention in the JRB.


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