scholarly journals Spatiotemporal characteristics of extreme precipitation at multiple timescales over Northeast China during 1961–2014

2017 ◽  
Vol 8 (3) ◽  
pp. 535-556 ◽  
Author(s):  
X. J. Yang ◽  
Z. X. Xu ◽  
W. F. Liu ◽  
Lin Liu
Keyword(s):  
Extreme Precipitation ◽  
Northeast China ◽  
Agricultural Drought ◽  
Crop Failure ◽  
Growing Period ◽  
Daily Precipitation Data ◽  
Extreme Precipitation Indices ◽  
Precipitation Anomalies ◽  
Precipitation Indices ◽  
Increasing Trends

Few studies of extreme precipitation have been conducted in Northeast China, particularly at multi-timescales. We aim to enhance the understanding of changes and variability in extreme precipitation over the past 54 years (1961–2014) in this region. We have investigated the potential relationship among extreme precipitation, climate and agricultural drought focusing on several timescales in this region. Thirteen extreme precipitation indices at seasonal, annual, and growing-period scales were estimated on the basis of daily precipitation data from 70 meteorological stations. The results indicate that all extreme precipitation indices that reflect the features of extreme wet events showed increasing trends in spring, and the trends of these indices were almost negative for the other timescales. Spatially, the frequency, duration and intensity of extreme wet events decreased gradually from south to north. The range of influence and the duration of extreme dry events increased continuously in Northeast China. In Northeast China, extreme precipitation was more easily influenced by the polar climate than the monsoon. Furthermore, correlation between the extreme precipitation indices and comprehensive crop failure ratios of agricultural drought disasters (C index) confirmed that agricultural drought was heavily influenced by precipitation anomalies in this area.

Spatial and Temporal Variations of Extreme Precipitation Events in Northeast China

2012 ◽  
Vol 573-574 ◽  
pp. 395-399
Author(s):  
Yong Wang ◽  
Yuan Yuan Ding ◽  
Qi Long Miao
Keyword(s):  
Extreme Precipitation ◽  
Northeast China ◽  
Temporal Variations ◽  
Ne China ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Temporal And Spatial Characteristics ◽  
Precipitation Events

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.

scholarly journals Spatial and Temporal Patterns of the Extreme Precipitation across the Tibetan Plateau (1986–2015)

Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1453 ◽  
Author(s):  
Junnan Xiong ◽  
Zhiwei Yong ◽  
Zegen Wang ◽  
Weiming Cheng ◽  
Yi Li ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Extreme Precipitation ◽  
Temporal Pattern ◽  
Alpine Meadow ◽  
The Tibetan Plateau ◽  
Desert Steppe ◽  
Trend Slope ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Increasing Trends

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.

Spatiotemporal Changes in Precipitation Extremes over Canada and Their Teleconnections to Large-Scale Climate Patterns

2019 ◽  
Vol 20 (2) ◽  
pp. 275-296 ◽  
Author(s):  
Yang Yang ◽  
Thian Yew Gan ◽  
Xuezhi Tan
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Specific Humidity ◽  
Climate Indices ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Climate Patterns ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Precipitation Events

Abstract In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results reveal statistically significant positive trends for most extreme precipitation indices, which means that extreme precipitation of Canada has generally become more severe since the mid-twentieth century. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominated the central Canadian Prairies. In addition, strong teleconnections are found between extreme precipitation and climate indices, but the effects of climate patterns differ from region to region. Furthermore, complex interactions of climate patterns with synoptic atmospheric circulations can also affect precipitation variability, and changes to the summer and winter extreme precipitation could be explained more by the thermodynamic impact and the combined thermodynamic and dynamic effects, respectively. The seasonal CAPE, specific humidity, and temperature are correlated to Canadian extreme precipitation, but the correlations are season dependent, which could be positive or negative.

Understanding Precipitation Characteristics of Afghanistan at Provincial Scale

2021 ◽  
Author(s):  
Shakti Suryavanshi ◽  
Nitin Joshi ◽  
Hardeep Kumar Maurya ◽  
Divya Gupta ◽  
Keshav Kumar Sharma
Keyword(s):  
Extreme Precipitation ◽  
Asian Country ◽  
Annual Precipitation ◽  
Precipitation Pattern ◽  
Precipitation Trend ◽  
Extreme Precipitation Events ◽  
Changing Patterns ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Precipitation Events

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.

scholarly journals Trend of Extreme Precipitation over Sumatera Island for 1981-2010

Agromet ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 41-51
Author(s):  
. Misnawati ◽  
Mega Perdanawanti
Keyword(s):  
Extreme Precipitation ◽  
Ecosystem Health ◽  
The Other ◽  
Economic Losses ◽  
Positive Trend ◽  
Climate Extreme ◽  
Precipitation Data ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices ◽  
Climate Events

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).

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