Long‐term trends in extreme precipitation indices in Ireland

Author(s):  
Ciara Ryan ◽  
Mary Curley ◽  
Séamus Walsh ◽  
Conor Murphy
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.


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.


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.


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.


Agromet ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 41-51
Author(s):  
. Misnawati ◽  
Mega Perdanawanti

Extreme climate events have significant impacts on various sectors such as agriculture, ecosystem, health and energy. The issue would lead to economic losses as well as social problems. This study aims to investigate the trend of extreme precipitation in Sumatera Island based on observed data during 30-year period, 1981–2010. There are ten indices of climate extreme as defined by ETCCDMI, which were tested in this study, including PRCPTOT, SDII, CDD, CWD, R10, R50, R95p, R99p, Rx1day and Rx5day. Then, the trend was analyzed based on the Mann-Kendall statistic, performed on the time series of precipitation data. The result shows that there was positive trend of extreme precipitation found in most stations over Sumatera, either statistically significant or insignificant. In each extreme precipitation indices, the number of observed stations indicating the insignificant change is higher than the significant one. This research also found that some indices including SDII, Rx1day, R50, R95p and R99p, showed a significantly-positive trend followed by a higher intensity of wetter and heavier events of extreme precipitation over Sumatera. On the other hand, the wet spell (CWD) index shows a negative trend (α=0.05).


Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1453 ◽  
Author(s):  
Junnan Xiong ◽  
Zhiwei Yong ◽  
Zegen Wang ◽  
Weiming Cheng ◽  
Yi Li ◽  
...  

The Tibetan Plateau is one of the most vulnerable areas to extreme precipitation. In recent decades, water cycles have accelerated, and the temporal and spatial characteristics of extreme precipitation have undergone dramatic changes across the Tibetan Plateau, especially in its various ecosystems. However, there are few studies that considered the variation of extreme precipitation in various ecosystems, and the impact of El Niño-Southern Oscillation (ENSO), and few researchers have made a quantitative analysis between them. In this study, we analyzed the spatial and temporal pattern of 10 extreme precipitation indices across the Tibetan Plateau (including its four main ecosystems: Forest, alpine meadow, alpine steppe, and desert steppe) based on daily precipitation from 76 meteorological stations over the past 30 years. We used the linear least squares method and Pearson correlation coefficient to examine variation magnitudes of 10 extreme precipitation indices and correlation. Temporal pattern indicated that consecutive wet days (CWD) had a slightly decreasing trend (slope = −0.006), consecutive dry days (CDD), simple daily intensity (SDII), and extreme wet day precipitation (R99) displayed significant increasing trends, while the trends of other indices were not significant. For spatial patterns, the increasing trends of nine extreme precipitation indices (excluding CDD) occurred in the southwestern, middle and northern regions of the Tibetan Plateau; decreasing trends were distributed in the southeastern region, while the spatial pattern of CDD showed the opposite distribution. As to the four different ecosystems, the number of moderate precipitation days (R10mm), number of heavy precipitation days (R20mm), wet day precipitation (PRCPTOT), and very wet day precipitation (R95) in forest ecosystems showed decreasing trends, but CDD exhibited a significant increasing trend (slope = 0.625, P < 0.05). In the other three ecosystems, all extreme precipitation indices generally exhibited increasing trends, except for CWD in alpine meadow (slope = −0.001) and desert steppe (slope = −0.005). Furthermore, the crossover wavelet transform indicated that the ENSO had a 4-year resonance cycle with R95, SDII, R20mm, and CWD. These results provided additional evidence that ENSO play an important remote driver for extreme precipitation variation in the Tibetan Plateau.


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