scholarly journals Trend in Extreme Precipitation Indices Based on Long Term In Situ Precipitation Records over Pakistan

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.

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.


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.


2017 ◽  
Author(s):  
Roberto Serrano-Notivoli ◽  
Santiago Beguería ◽  
Miguel Ángel Saz ◽  
Luis Alberto Longares ◽  
Martín de Luis

Abstract. A high-resolution daily gridded precipitation dataset was built from raw data of 12,858 observatories covering a period from 1950 to 2012 in peninsular Spain and 1971 to 2012 in Balearic and Canary Islands. The original data were quality controlled and gaps were filled on each day and location independently. Using the serially-complete dataset, a grid with a 5 x 5 kilometres spatial resolution was constructed by estimating daily precipitation amounts and their corresponding uncertainty at each grid node. Daily precipitation estimations were compared to original observations to assess the quality of the gridded dataset. Four daily precipitation indices were computed to characterize the spatial distribution of daily precipitation and nine extreme precipitation indices were used to describe the frequency and intensity of extreme precipitation events. The use of the total available data in Spain, the independent estimation of precipitation for each day and the high spatial resolution of the grid allowed for a precise spatial and temporal assessment of daily precipitation that are difficult to achieve when using other methods, pre- selected long-term stations or global gridded datasets. SPREAD dataset is publicly available at http://dx.doi.org/10.20350/digitalCSIC/7393.


Atmosphere ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 394 ◽  
Author(s):  
Li Na ◽  
Risu Na ◽  
Jiquan Zhang ◽  
Siqin Tong ◽  
Yin Shan ◽  
...  

As the global climate has changed, studies on the relationship between vegetation and climate have become crucial. We analyzed the long-term vegetation dynamics and diverse responses to extreme climate changes in Inner Mongolia, based on long-term Global Inventory Monitoring and Modelling Studies (GIMMS) NDVI3g datasets, as well as the eight extreme precipitation indices and six extreme temperature indices that are highly correlated with the occurrence of droughts or floods, heat or cold temperature disasters, and vegetation growth in Inner Mongolia. These datasets were analyzed using linear regression analysis, the Hurst exponent index, residual analysis, and the Pearson correlation analysis. The results showed the following: (1) The vegetation dynamical changes exhibited trends of improvement during 1982 to 2015, and 68% of the vegetation growth changes in Inner Mongolia can be explained by climate changes. (2) The extreme precipitation indices exhibited a slight change, except for the annual total wet–day precipitation (PRCPTOT). The occurrence of extreme cold temperatures showed a significant decline, while the occurrence of extreme warm temperatures showed an upward trend in Inner Mongolia. (3) The typical steppe, desert steppe, and forest steppe regions are more sensitive to extreme large precipitation, and the forest regions are more sensitive to extreme warm temperatures. (4) Extreme precipitation exhibits a one-month lagged effect on vegetation that is larger than the same-month effects on the grassland system. Extreme temperature exhibits same-month effects on vegetation, which are larger than the one-month lagged effects on the forest system. Therefore, studies of the relationship between extreme climate indices and vegetation are important for performing risk assessments of droughts, floods, and other related natural disasters.


2021 ◽  
Author(s):  
Monika Lakatos ◽  
Olivér Szentes

<p>The warming climate evokes increasing frequency of extreme precipitation in some region. Analysis of long-term measurements could support the better understanding of the processes that cause extreme precipitation events.</p><p>Automatic stations replaced the ombrometer in many places in Hungary, particularly from the late 1990s. The change of the measurement practice do not allow simply merging the data recorded form the registering paper in the past and the recent 10 minutes measurements.   The most intense 5, 10, 20, 30, 60, 180 min sub-totals per rainfall events were recorded from the ombrometer registering paper before atomization, typically until 1993. By contrast, the 10 min precipitation sum from the AWSs are stored in the meteorological database of the Hungarian Meteorological Service from automatization. In order to join together the older and the AWS measurements it was necessary to develop a method to make this possible. Therefore we downscaled the 10 min data in time. The sampling of the AWSs is one minute, although the 1-minute data are available only for some stations in the digital database.  We applied a linear regression model to downscale the 10-miniute data for 1 min. After this, we can derive the most intense sub-totals per events from the AWS data as if they have been measured with the ombrometers.</p><p>Thereby a set of sub-daily precipitation indices defined in the INTENSE project (https://research.ncl.ac.uk/intense/aboutintense/ can be computed for longer data series. Some of the indices specified in INTENSE project describes the maximum rainfall totals and timing, the intensity, duration and frequency of heavy precipitation, frequency of rainfall above specific thresholds and some of them is related to diurnal cycle. A few of these indices are analysed for long data series to detect the sub-daily precipitation changes in Hungary.</p>


2012 ◽  
Vol 5 (4) ◽  
pp. 852 ◽  
Author(s):  
Carlos Antonio Costa dos Santos ◽  
Leydson Galvincio Dantas ◽  
Maria M. M. S. Melo ◽  
Elder G. dos Santos

The objective of this study was to analyze the trends in seven annual extreme indices of precipitation for Idaho, USA. The analyses were conducted for 35 meteorological stations, during the period from 1970 to 2006, a high quality and a fairly long-term dataset. The analyses of precipitation indices presented large spatial variability and few statistically significant trends. Thus it is not possible to conclude that significant changes in precipitation have occurred in this region during the past few decades.Keywords:Climate change, global warming, environmental impact Tendências nos Índices Extremos de Precipitação Diária sobre Idaho - USA  RESUMO O objetivo deste estudo foi analisar as tendências em sete índices anuais extremos de precipitação para Idaho, EUA. As análises foram conduzidas para 35 estações meteorológicas, durante o período de 1970 a 2006, com dados de alta qualidade e longo prazo. As análises dos índices de precipitação apresentaram alta variabilidade espacial e poucas tendências estatisticamente significativas. Logo, não é possível concluir que ocorreram mudanças significativas na precipitação nesta região durante as últimas décadas. Palavras - chave: Mudanças climáticas, aquecimento global, impacto ambiental


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.


Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 150
Author(s):  
Congxuan Kang ◽  
Zujiang Luo ◽  
Wen Zong ◽  
Jian Hua

The urbanization process is the hallmark of the population’s economic activities and land-use types, including population-, economic-, and landscape-urbanization. The question of how to classify the stations into urbanized and suburbanized stations is important for detecting the contribution rates of urbanization to precipitation extremes. This study used the fuzzy c-means clustering method to classify different urbanized level stations by population, economy, and impervious surface in the Suzhou-Wuxi-Changzhou urban agglomeration. Based on the change trends of six extreme precipitation indices, the contribution rates of urbanization to the precipitation extremes were estimated. The results show that the increasing indices were the intensity indices, while the decreasing indices were the duration indices during 1980–2015. Moreover, high urbanization tended to have a higher contribution to the most extreme precipitation indices, especially the intensity indices, than urbanization in the medium-size cities, indicating the urbanization leads to the phenomenon of extreme precipitation enhancement. The results of the three kinds of classification methods were different, especially the classification by the impervious area. This paper investigated the spatiotemporal changes in precipitation extremes and the contribution of urbanization to extreme precipitation, which will provide support for the development of urban agglomeration in the future.


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