scholarly journals Correction to “Analysis of variability and trends of extreme rainfall events over India using 104 years of gridded daily rainfall data”

2008 ◽  
Vol 35 (23) ◽  
Author(s):  
M. Rajeevan ◽  
Jyoti Bhate ◽  
A. K. Jaswal
Keyword(s):  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Rainfall Data ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Daily Rainfall Data

ANALYSIS OF EXTREME RAINFALL INDICES IN PENINSULAR MALAYSIA

2016 ◽  
Vol 78 (9-4) ◽  
Author(s):  
Nur Shazwani Muhammad ◽  
Amieroul Iefwat Akashah ◽  
Jazuri Abdullah
Keyword(s):  
East Coast ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Peninsular Malaysia ◽  
Rainfall Data ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Daily Rainfall Data ◽  
Extreme Rain ◽  
Increasing Trends

Extreme rainfall events are the main cause of flooding. This study aimed to examine seven extreme rainfall indices, i.e. extreme rain sum (XRS), very wet day intensity (I95), extremely wet day intensity (I99), very wet day proportion (R95), extremely wet day proportion (R99), very wet days (N95) and extremely wet days (N99) using Mann-Kendall (MK) and the normalized statistic Z tests. The analyses are based on the daily rainfall data gathered from Bayan Lepas, Subang, Senai, Kuantan and Kota Bharu. The east coast states received more rainfall than any other parts in Peninsular Malaysia. Kota Bharu station recorded the highest XRS, i.e. 648 mm. The analyses also indicate that the stations in the eastern part of Peninsular Malaysia experienced higher XRS, I95, I99, R95 and R99 as compared to the stations located in the western and northern part of Peninsular Malaysia. Subang and Senai show the highest number of days for wet and very wet (N95) as compared to other stations. Other than that, all stations except for Kota Bharu show increasing trends for most of the extreme rainfall indices. Upward trends indicate that the extreme rainfall events were becoming more severe over the period of 1960 to 2014. 

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.

scholarly journals TRMM rainfall estimative coupled with Bell (1969) methodology for extreme rainfall characterization

2015 ◽  
Vol 369 ◽  
pp. 163-168 ◽  
Author(s):  
E. Schiavo Bernardi ◽  
D. Allasia ◽  
R. Basso ◽  
P. Freitas Ferreira ◽  
R. Tassi
Keyword(s):  
Temporal Distribution ◽  
Daily Rainfall ◽  
Tropical Rainfall Measuring Mission ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Remote Sensors ◽  
Indirect Measures ◽  
Equation Error ◽  
Convective Cells

Abstract. The lack of rainfall data in Brazil, and, in particular, in Rio Grande do Sul State (RS), hinders the understanding of the spatial and temporal distribution of rainfall, especially in the case of the more complex extreme events. In this context, rainfall's estimation from remote sensors is seen as alternative to the scarcity of rainfall gauges. However, as they are indirect measures, such estimates needs validation. This paper aims to verify the applicability of the Tropical Rainfall Measuring Mission (TRMM) satellite information for extreme rainfall determination in RS. The analysis was accomplished at different temporal scales that ranged from 5 min to daily rainfall while spatial distribution of rainfall was investigated by means of regionalization. An initial test verified TRMM rainfall estimative against measured rainfall at gauges for 1998–2013 period considering different durations and return periods (RP). Results indicated that, for the RP of 2, 5, 10 and 15 years, TRMM overestimated on average 24.7% daily rainfall. As TRMM minimum time-steps is 3 h, in order to verify shorter duration rainfall, the TRMM data were adapted to fit Bell's (1969) generalized IDF formula (based on the existence of similarity between the mechanisms of extreme rainfall events as they are associated to convective cells). Bell`s equation error against measured precipitation was around 5–10%, which varied based on location, RP and duration while the coupled BELL+TRMM error was around 10–35%. However, errors were regionally distributed, allowing a correction to be implemented that reduced by half these values. These findings in turn permitted the use of TRMM+Bell estimates to improve the understanding of spatiotemporal distribution of extreme hydrological rainfall events.

scholarly journals Trend and spatial variability of 1-day extreme rainfall from 1980 - 2015: study at the adminisitrative area of UPT PSDA Pasuruan

2019 ◽  
Vol 8 (1) ◽  
pp. 29
Author(s):  
Indarto Indarto
Keyword(s):  
Spatial Variability ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Statistical Test ◽  
Rainfall Event ◽  
Rainfall Data ◽  
Rainfall Events ◽  
Significance Level ◽  
Main Input ◽  
Crossing Test

This study aims to analyze trends,  shift and spatial variability of extreme-rainfall in the area of UPT PSDA Pasuruan. The daily rainfall data from 64 stations from 1980 until 2015 were used as main input. The 1-day extreem rainfall data is determined as the maximum annual of 24-hour rainfall events.  The statistical  analysis using Mann-Kendall, Rank-Sum, and Median Crossing Test using significance level α = 0,05. The spatial variability of extrem rainfall data is described using average annual 24-hour rainfall during the periods of record. Each station is represented by one value. The values are then interpolated using IDW interpolation methods to maps the spatial variability of extreem rainfall event.  The results show the value of statistical test for each stations that show the existing  trend, shift, or randomness of data. The result also produce thematic maps show the spatial variability of extreme rainfall and the value of each trend.

Extreme rainfall events during and following heatwaves

2021 ◽  
Author(s):  
Christoph Sauter ◽  
Christopher White ◽  
Hayley Fowler ◽  
Seth Westra
Keyword(s):  
Natural Hazards ◽  
Rainfall Intensity ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Rainfall Extremes ◽  
Average Rainfall ◽  
Time Of Year ◽  
The Impact

<p>Heatwaves and extreme rainfall events are natural hazards that can have severe impacts on society. The relationship between temperature and extreme rainfall has received scientific attention with studies focussing on how single daily or sub-daily rainfall extremes are related to day-to-day temperature variability. However, the impact multi-day heatwaves have on sub-daily extreme rainfall events and how extreme rainfall properties change during different stages of a heatwave remains mostly unexplored.</p><p>In this study, we analyse sub-daily rainfall records across Australia, a country that experiences severe natural hazards on a frequent basis, and determine their extreme rainfall properties, such as rainfall intensity, duration and frequency during SH-summer heatwaves. These properties are then compared to extreme rainfall properties found outside heatwaves, but during the same time of year, to examine to what extent they differ from normal conditions. We also conduct a spatial analysis to investigate any spatial patterns that arise.</p><p>We find that rainfall breaking heatwaves is often more extreme than average rainfall during the same time of year. This is especially prominent on the eastern and south-eastern Australian coast, where frequency and intensity of sub-daily rainfall extremes show an increase during the last day or the day immediately after a heatwave. We also find that although during heatwaves the average rainfall amount and duration decreases, there is an increase in sub-daily rainfall intensity when compared to conditions outside heatwaves. This implies that even though Australian heatwaves are generally characterised by dry conditions, rainfall occurrences within heatwaves are more intense.</p><p>Both heatwaves and extreme rainfall events pose great challenges for many sectors such as agriculture, and especially if they occur together. Understanding how and to what degree these events co-occur could help mitigate the impacts caused by them.</p>

Extreme rainfall and drought events in Tamil Nadu, India

2020 ◽  
Vol 80 (3) ◽  
pp. 175-188
Author(s):  
R Rajkumar ◽  
CS Shaijumon ◽  
B Gopakumar ◽  
D Gopalakrishnan
Keyword(s):  
Tamil Nadu ◽  
Daily Rainfall ◽  
India Meteorological Department ◽  
Extreme Rainfall ◽  
Drought Severity ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Significance Level ◽  
Spatio Temporal ◽  
Temporal Dimensions

In the present study, we examined the exposure of the Tamil Nadu region, India, to droughts and extreme rainfall events using the Standardised Precipitation Evapotranspiration Index (SPEI) and a classification scheme based on daily rainfall. We used high-resolution temperature and rainfall observations from the India Meteorological Department for the period 1951-2016. The robustness of the results was tested using the Mann-Kendall trend (M-K) test and the Kolmogorov-Smirnov (K-S) test. During the study period, there were statistically significant increasing trends in drought area (90% significance level), maximum drought intensity (99% significance level) and maximum drought severity (99% significance level) over the Tamil Nadu region. There has also been an increase in the frequency and intensity of heavy rainfall events in recent years. The spatio-temporal dimensions of this study suggest an increasing exposure of this semi-arid, rain shadow region to severe droughts and extreme rainfall events in recent decades. The results provide sufficient grounds to substantiate the necessity of immediate interventions at the policy level.

scholarly journals The impact of atmospheric rivers on rainfall in New Zealand

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jingxiang Shu ◽  
Asaad Y. Shamseldin ◽  
Evan Weller
Keyword(s):  
New Zealand ◽  
Austral Summer ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Detection Algorithm ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Atmospheric Rivers ◽  
Hydrological Hazards ◽  
The Impact

AbstractThis study quantifies the impact of atmospheric rivers (ARs) on rainfall in New Zealand. Using an automated AR detection algorithm, daily rainfall records from 654 rain gauges, and various atmospheric reanalysis datasets, we investigate the climatology of ARs, the characteristics of landfalling ARs, the contribution of ARs to annual and seasonal rainfall totals, and extreme rainfall events between 1979 and 2018 across the country. Results indicate that these filamentary synoptic features play an essential role in regional water resources and are responsible for many extreme rainfall events on the western side of mountainous areas and northern New Zealand. In these regions, depending on the season, 40–86% of the rainfall totals and 50–98% of extreme rainfall events are shown to be associated with ARs, with the largest contributions predominantly occurring during the austral summer. Furthermore, the median daily rainfall associated with ARs is 2–3 times than that associated with other storms. The results of this study extend the knowledge on the critical roles of ARs on hydrology and highlight the need for further investigation on the landfalling AR physical processes in relation to global circulation features and AR sources, and hydrological hazards caused by ARs in New Zealand.

scholarly journals Avaliação do padrão hidroclimático e da erosividade no Sertão de Pernambuco

2019 ◽  
Vol 12 (5) ◽  
pp. 1757
Author(s):  
Mariana Caroline Gomes de Lima ◽  
Thais Emanuelle Monteiro Dos Santos Souza ◽  
Valéria Sandra de Oliveira Costa ◽  
Carlos Eduardo Santos De Lima ◽  
Josimar Vieira Dos Reis ◽  
...  
Keyword(s):  
Extreme Rainfall ◽  
Rainfall Data ◽  
Data Series ◽  
High Susceptibility ◽  
Strategic Information ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Agricultural Potential ◽  
Erosivity Index ◽  
Intermediate Pattern

A erosão hídrica é um dos grandes problemas que atingem regiões com potenciais agrícolas e áreas com propensão para deslizamento de terras. A chuva é considerada o fator climático que exerce maior influência no processo erosivo, especialmente nos trópicos por causa da sua distribuição temporal, espacial, características físicas e duração. Este trabalho teve como objetivo determinar o padrão hidrológico e o índice de erosividade  no sertão Pernambucano, visando contribuir com informações estratégicas para gestão agrícola e ambiental na região. Foram utilizados dados pluviométricos horários de 2000 a 2017 localizados no município de Petrolina, disponibilizados pela (APAC). A partir dos dados da precipitação, utilizou-se o aplicativo Climap 3.0 para avaliar os eventos extremos de precipitação e o padrão hidrológico, bem como determinou-se por meio de equações o índice de erosividade para a região. No período analisado os maiores valores da precipitação ocorreram entre os meses de janeiro e abril e identificou-se 8 anos consecutivos de seca na região. Os resultados apontam que houve tendências significativas nas séries de dados, a erosividade foi considerada fraca a moderada em sua maioria, e o padrão hidrológico mais frequente foi o padrão intermediário, resultando uma alta suscetibilidade dos solos da região em sofrer erosão hídrica.Evaluation of hydroclimatic pattern and erosivity Sertão of Pernambuco A B S T R A C T Water erosion is one of major problems affecting regions with agricultural potential and landslide-prone areas. Rain is considered the climatic factor that exerts greatest influence on erosive process, especially in tropics because its temporal, spatial distribution, physical characteristics and duration. This work purpose to determine  hydrological pattern and erosivity index in Pernambucano Sertão,  to contribute with strategic information for agricultural and environmental management in region. Rainfall data from 2000 to 2017 located in city of Petrolina, provided by (APAC) were used. From the rainfall data, the Climap 3.0  was used to evaluate the extreme rainfall events and  hydrological pattern, as well  to determine through equations the erosivity index for  region. During  analyzed period the highest rainfall values occurred between January and April and 8 consecutive years of drought were identified in region. The results indicate that there were significant trends in data series, erosivity was considered weak to moderate mostly, and most frequent hydrological pattern was the intermediate pattern, resulting in high susceptibility of region's soils to water erosion.Keywords: climate variability, hydrological pattern, extreme indexes.

Simulated changes in daily rainfall intensity due to the enhanced greenhouse effect: implications for extreme rainfall events

1992 ◽  
Vol 8 (2) ◽  
pp. 83-102 ◽  
Author(s):  
H B Gordon ◽  
P H Whetton ◽  
A B Pittock ◽  
A M Fowler ◽  
M R Haylock
Keyword(s):  
Greenhouse Effect ◽  
Rainfall Intensity ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Extreme Rainfall Events ◽  
Rainfall Events
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