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).

scholarly journals Bias correction of gauge-based gridded product to improve extreme precipitation analysis in the Yarlung Tsangpo-Brahmaputra River Basin

2019 ◽  
Author(s):  
Xian Luo ◽  
Xuemei Fan ◽  
Yungang Li ◽  
Xuan Ji
Keyword(s):  
River Basin ◽  
Bias Correction ◽  
Extreme Precipitation ◽  
Precipitation Data ◽  
Brahmaputra River ◽  
Spatial Coverage ◽  
Extreme Precipitation Indices ◽  
Precipitation Analysis ◽  
Precipitation Indices ◽  
Yarlung Tsangpo

Abstract. Critical gaps in the amount, quality, consistency, availability, and spatial distribution of rainfall data limit extreme precipitation analysis, and the application of gridded precipitation data are challenging because of their considerable biases. This study corrected Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) in the Yarlung Tsangpo-Brahmaputra River Basin (YBRB) using two linear and two nonlinear methods, and assessed their influence on extreme precipitation indices. The results showed that the original APHRODITE data tended to underestimate precipitation during the summer monsoon season, especially in the topographically complex Himalayan belt. Bias correction using complementary rainfall observations to add spatial coverage in data-sparse regions greatly improved the performance of extreme precipitation analysis. Although all methods could correct mean precipitation, their ability to correct the wet-day frequency and coefficient of variation were substantially different, leading to considerable differences in extreme precipitation indices. Generally, higher-skill bias-corrected APHRODITE data are expected to perform better than those corrected by lower-skill approaches. This study would provide reference for using gridded precipitation data in extreme precipitation analysis and selecting bias-corrected method for rainfall products in data-sparse regions.

scholarly journals Identifying hydro-meteorological events from precipitation extremes indices and other sources over northern Namibia, Cuvelai Basin

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Frans C. Persendt ◽  
Christopher Gomez ◽  
Peyman Zawar-Reza
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Economic Losses ◽  
Precipitation Data ◽  
Rainfall Station ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Dry Spell ◽  
Flood Disasters ◽  
Precipitation Indices

Worldwide, more than 40% of all natural hazards and about half of all deaths are the result of flood disasters. In northern Namibia flood disasters have increased dramatically over the past half-century, along with associated economic losses and fatalities. There is a growing concern to identify these extreme precipitation events that result in many hydro-meteorological disasters. This study presents an up to date and broad analysis of the trends of hydrometeorological events using extreme daily precipitation indices, daily precipitation data from the Grootfontein rainfall station (1917–present), regionally averaged climatologies from the gauged gridded Climate Research Unit (CRU) product, archived disasters by global disaster databases, published disaster events in literature as well as events listed by Mendelsohn, Jarvis and Robertson (2013) for the data-sparse Cuvelai river basin (CRB). The listed events that have many missing data gaps were used to reference and validate results obtained from other sources in this study. A suite of ten climate change extreme precipitation indices derived from daily precipitation data (Grootfontein rainfall station), were calculated and analysed. The results in this study highlighted years that had major hydro-meteorological events during periods where no data are available. Furthermore, the results underlined decrease in both the annual precipitation as well as the annual total wet days of precipitation, whilst it found increases in the longest annual dry spell indicating more extreme dry seasons. These findings can help to improve flood risk management policies by providing timely information on historic hydro-meteorological hazard events that are essential for early warning and forecasting.

scholarly journals Bias correction of a gauge-based gridded product to improve extreme precipitation analysis in the Yarlung Tsangpo–Brahmaputra River basin

2020 ◽  
Vol 20 (8) ◽  
pp. 2243-2254
Author(s):  
Xian Luo ◽  
Xuemei Fan ◽  
Yungang Li ◽  
Xuan Ji
Keyword(s):  
River Basin ◽  
Bias Correction ◽  
Extreme Precipitation ◽  
Precipitation Data ◽  
Brahmaputra River ◽  
Extreme Precipitation Indices ◽  
Precipitation Analysis ◽  
Precipitation Indices ◽  
Yarlung Tsangpo ◽  
Local Intensity

Abstract. Critical gaps in the amount, quality, consistency, availability, and spatial distribution of rainfall data limit extreme precipitation analysis, and the application of gridded precipitation data is challenging because of their considerable biases. This study corrected Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) estimates in the Yarlung Tsangpo–Brahmaputra River basin (YBRB) using two linear and two nonlinear methods, and their influence on extreme precipitation indices was assessed by cross-validation. Bias correction greatly improved the performance of extreme precipitation analysis. The ability of four methods to correct wet-day frequency and coefficient of variation were substantially different, leading to considerable differences in extreme precipitation indices. Local intensity scaling (LOCI) and quantile–quantile mapping (QM) performed better than linear scaling (LS) and power transformation (PT). This study would provide a reference for using gridded precipitation data in extreme precipitation analysis and selecting a bias-corrected method for rainfall products in data-sparse regions.

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 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.

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