Increasing Trend of Synoptic Activity and Its Relationship with Extreme Rain Events over Central India

Abstract The nature of the increasing frequency of extreme rainfall events (ERE) in central India is investigated by relating their occurrence to synoptic activity. Using a long record of the paths and intensities of monsoon synoptic disturbances, a synoptic activity index (SAI) is defined whose interannual variation correlates strongly with that in the number of ERE, demonstrating a strong connection between these phenomena. SAI furthermore shows a rising trend that is statistically indistinguishable from that in ERE, indicating that the increasing frequency of ERE is likely attributable to a rising trend in synoptic activity. This synoptic activity increase results from a rising trend in relatively weak low pressure systems (LPS), and it outweighs a declining trend in stronger LPS.

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An Intuitive Metric to Quantify and Communicate Tropical Cyclone Rainfall Hazard

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-19-0075.1 ◽

2020 ◽

Vol 101 (2) ◽

pp. E206-E220

Author(s):

Christopher D. Bosma ◽

Daniel B. Wright ◽

Phu Nguyen ◽

James P. Kossin ◽

Derrick C. Herndon ◽

...

Keyword(s):

Human Life ◽

Regional Scale ◽

Extreme Rainfall ◽

Precipitation Forecast ◽

Communication Tool ◽

Accurate Identification ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Extreme Rain ◽

Rain Events

Abstract Recent tropical cyclones (TCs) have highlighted the hazards that TC rainfall poses to human life and property. These hazards are not adequately conveyed by the commonly used Saffir–Simpson scale. Additionally, while recurrence intervals (or, their inverse, annual exceedance probabilities) are sometimes used in the popular media to convey the magnitude and likelihood of extreme rainfall and floods, these concepts are often misunderstood by the public and have important statistical limitations. We introduce an alternative metric—the extreme rain multiplier (ERM), which expresses TC rainfall as a multiple of the climatologically derived 2-yr rainfall value. ERM allows individuals to connect (“anchor,” in cognitive psychology terms) the magnitude of a TC rainfall event to the magnitude of rain events that are more typically experienced in their area. A retrospective analysis of ERM values for TCs from 1948 to 2017 demonstrates the utility of the metric as a hazard quantification and communication tool. Hurricane Harvey (2017) had the highest ERM value during this period, underlining the storm’s extreme nature. ERM correctly identifies damaging historical TC rainfall events that would have been classified as “weak” using wind-based metrics. The analysis also reveals that the distribution of ERM maxima is similar throughout the eastern and southern United States, allowing for both the accurate identification of locally extreme rainfall events and the development of regional-scale (rather than local-scale) recurrence interval estimates for extreme TC rainfall. Last, an analysis of precipitation forecast data for Hurricane Florence (2018) demonstrates ERM’s ability to characterize Florence’s extreme rainfall hazard in the days preceding landfall.

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Observed Link of Extreme Hourly Precipitation Changes to Urbanization over Coastal South China

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-18-0284.1 ◽

2019 ◽

Vol 58 (8) ◽

pp. 1799-1819 ◽

Cited By ~ 24

Author(s):

Mengwen Wu ◽

Yali Luo ◽

Fei Chen ◽

Wai Kin Wong

Keyword(s):

South China ◽

Extreme Rainfall ◽

Rapid Urbanization ◽

Extreme Rainfall Events ◽

Convective Initiation ◽

Rainfall Events ◽

Hourly Precipitation ◽

Urban Cluster ◽

Wide Range ◽

Extreme Rain

AbstractUnderstanding changes in subdaily rainfall extremes is critical to urban planners for building more sustainable and resilient cities. In this study, the hourly precipitation data in 1971–2016 from 61 rain gauges are combined with historical land-use change data to investigate changes in extreme hourly precipitation (EXHP) in the Pearl River delta (PRD) region of South China. Also, 120 extreme rainfall events (EXREs) during 2011–16 are analyzed using observations collected at densely distributed automatic weather stations and radar network. Statistically significant increase of hourly precipitation intensity leads to higher annual amounts of both total and extreme precipitation over the PRD urban cluster in the rapid urbanization period (about 1994–2016) than during the preurbanization era (1971 to about 1993), suggesting a possible link between the enhanced rainfall and the rapid urbanization. Those urbanization-related positive trends are closely related to more frequent occurrence of abrupt rainfall events with short duration (≤6 h) than the continuous or growing rainfall events with longer duration. The 120 EXREs in 2011–16 are categorized into six types according to the originating location and movement of the extreme-rain-producing storms. Despite the wide range of synoptic backgrounds and seasons, rainfall intensification by the strong urban heat island (UHI) effect is a clear signal in all the six types, especially over the inland urban cluster with prominent UHIs. The UHI thermal perturbation probably plays an important role in the convective initiation and intensification of the locally developed extreme-rain-producing storms during the daytime.

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ANALYSIS OF EXTREME RAINFALL INDICES IN PENINSULAR MALAYSIA

Jurnal Teknologi ◽

10.11113/jt.v78.9677 ◽

2016 ◽

Vol 78 (9-4) ◽

Cited By ~ 2

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.

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Precipitation Nowcasting with Orographic Enhanced Stacked Generalization: Improving Deep Learning Predictions on Extreme Events

Atmosphere ◽

10.3390/atmos11030267 ◽

2020 ◽

Vol 11 (3) ◽

pp. 267 ◽

Cited By ~ 7

Author(s):

Gabriele Franch ◽

Daniele Nerini ◽

Marta Pendesini ◽

Luca Coviello ◽

Giuseppe Jurman ◽

...

Keyword(s):

Deep Learning ◽

Extreme Rainfall ◽

Superior Performance ◽

Short Term ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Severe Thunderstorms ◽

Extreme Rain ◽

Novel Method ◽

Rain Rates

One of the most crucial applications of radar-based precipitation nowcasting systems is the short-term forecast of extreme rainfall events such as flash floods and severe thunderstorms. While deep learning nowcasting models have recently shown to provide better overall skill than traditional echo extrapolation models, they suffer from conditional bias, sometimes reporting lower skill on extreme rain rates compared to Lagrangian persistence, due to excessive prediction smoothing. This work presents a novel method to improve deep learning prediction skills in particular for extreme rainfall regimes. The solution is based on model stacking, where a convolutional neural network is trained to combine an ensemble of deep learning models with orographic features, doubling the prediction skills with respect to the ensemble members and their average on extreme rain rates, and outperforming them on all rain regimes. The proposed architecture was applied on the recently released TAASRAD19 radar dataset: the initial ensemble was built by training four models with the same TrajGRU architecture over different rainfall thresholds on the first six years of the dataset, while the following three years of data were used for the stacked model. The stacked model can reach the same skill of Lagrangian persistence on extreme rain rates while retaining superior performance on lower rain regimes.

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Mesoscale and Synoptic Environment in Three Orographically Enhanced Rain Events on the Coast of Santa Catarina (Brazil)

Weather and Forecasting ◽

10.1175/waf-d-15-0003.1 ◽

2016 ◽

Vol 31 (5) ◽

pp. 1529-1546

Author(s):

M. Laura Guimarães Rodrigues ◽

Rita Yuri Ynoue

Keyword(s):

Extreme Rainfall ◽

Heavy Rain ◽

The United States ◽

Santa Catarina ◽

Local Networks ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Unstable Environment ◽

Slow Moving ◽

Rain Events

Abstract In this study three cases of extreme rainfall events are analyzed in Florianopolis, Santa Catarina (SC), on Brazil’s coast, lying between the mountains and the South Atlantic Ocean in southeastern South America. The largest rainfall totals, 200–300 mm in 12–24 h, resulted in flash floods. ECMWF 6-hourly 1.5° × 1.5° data were used to determine the synoptic fields and quasigeostrophic forcing, along with observational data from local networks, for subsynoptic analyses. In case C1, during May 2010, there was a frontal passage. In C2 and C3 (January 2008 and February 1979, respectively) the coastline separated a ridge over the continent from a trough over the sea at the surface, with an atmosphere of low baroclinicity predominating at 500 hPa. All three events were characterized by postfrontal conditions; the presence of an anticyclone over the sea, centered at 35°–40°S; and slow-moving or quasi-stationary midlevel cyclones over the continent, at 27 °S. The circulation generated in the cyclone resulted in strong (10 m s−1) and persistent low-level east-northeast winds along the coast of SC, favoring the influx of heat and humidity on days with heavy rain. The upward motion at 850 hPa was concentrated over the affected areas and stronger than that at 500 hPa. Even so, the moist air that reached the mountain in a conditionally unstable environment rose only to middle levels. The features presented were similar to those observed for orographic rain events in Europe and the United States.

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Performance of NCUM global weather modeling system in predicting the extreme rainfall events over the central India during the Indian summer monsoon 2016

Modeling Earth Systems and Environment ◽

10.1007/s40808-017-0387-8 ◽

2017 ◽

Vol 3 (4) ◽

pp. 1409-1419 ◽

Cited By ~ 4

Author(s):

Sourabh Shrivastava ◽

Prasanta Kumar Bal ◽

Raghavendra Ashrit ◽

Kuldeep Sharma ◽

Abhishek Lodh ◽

...

Keyword(s):

Summer Monsoon ◽

Indian Summer Monsoon ◽

Central India ◽

Extreme Rainfall ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Weather Modeling

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The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

Journal of Engineering and Scientific Research ◽

10.23960/jesr.v1i1.7 ◽

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.

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CLIMATOLOGY OF EXTREME RAINFALL EVENTS IN EASTERN AND NORTHERN SANTA CATARINA STATE, BRAZIL: PRESENT AND FUTURE CLIMATE

Brazilian Journal of Geophysics ◽

10.22564/rbgf.v31i3.314 ◽

2013 ◽

Vol 31 (3) ◽

pp. 413 ◽

Cited By ~ 3

Author(s):

André Becker Nunes ◽

Gilson Carlos Da Silva

Keyword(s):

Climate Model ◽

Climate Modeling ◽

Linear Trend ◽

Extreme Rainfall ◽

Eastern Region ◽

Santa Catarina ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

History Of ◽

Santa Catarina State

ABSTRACT. The eastern region of Santa Catarina State (Brazil) has an important history of natural disasters due to extreme rainfall events. Floods and landslides are enhancedby local features such as orography and urbanization: the replacement of natural surface coverage causing more surface runoff and, hence, ﬂooding. Thus, studies of this type of events – which directly inﬂuence life in the towns – take on increasing importance. This work makes a quantitative analysis of occurrences of extreme rainfall events in the eastern and northern regions of Santa Catarina State in the last 60 years, through individual analysis, considering the history of ﬂoods ineach selected town, as well as an estimate through to the end of century following regional climate modeling. A positive linear trend, in most of the towns studied, was observed in the results, indicating greater frequency of these events in recent decades, and the HadRM3P climate model shows a heterogeneous increase of events for all towns in the period from 2071 to 2100.Keywords: ﬂoods, climate modeling, linear trend. RESUMO. A região leste do Estado de Santa Catarina tem um importante histórico de desastres naturais ocasionados por eventos extremos de precipitação. Inundações e deslizamentos de terra são potencializados pelo relevo acidentado e pela urbanização das cidades da região: a vegetação nativa vem sendo removida acarretando um maior escoamento superﬁcial e, consequentemente, em inundações. Desta forma, torna-se de suma importância os estudos acerca deste tipo de evento que inﬂuencia diretamente a sociedade em geral. Neste trabalho é realizada uma análise quantitativa do número de eventos severos de precipitação ocorridos nas regiões leste e norte de Santa Catarina dos últimos 60 anos, por meio de uma análise pontual, considerandoo histórico de inundações de cada cidade selecionada, além de uma projeção para o ﬁm do século de acordo com modelagem climática regional. Na análise dos resultados observou-se uma tendência linear positiva na maioria das cidades, indicando uma maior frequência deste tipo de evento nas últimas décadas, e o modelo climático HadRM3P mostra um aumento heterogêneo no número de eventos para todas as cidades no período de 2071 a 2100.Palavras-chave: inundações, modelagem climática, tendência linear.

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