Extreme Rainfall Events in the Macro-Metropolis of São Paulo: trends and connection with climate oscillations

2021 ◽  
Author(s):  
Carolyne B. Machado ◽  
Thamiris L. O. B. Campos ◽  
Sameh A. Abou Rafee ◽  
Jorge A. Martins ◽  
Alice M. Grimm ◽  
...  
Keyword(s):  
Urban Areas ◽  
Extreme Rainfall ◽  
Kendall Test ◽  
Rain Gauge ◽  
Sao Paulo ◽  
Annual Rainfall ◽  
São Paulo ◽  
Wet Season ◽  
Extreme Rainfall Events ◽  
Climatic Indices

AbstractIn the present work, the trend of extreme rainfall indices in the Macro-Metropolis of São Paulo (MMSP) was analyzed and correlated with largescale climatic oscillations. A cluster analysis divided a set of rain gauge stations into three homogeneous regions within MMSP, according to the annual cycle of rainfall. The entire MMSP presented an increase in the total annual rainfall, from 1940 to 2016, of 3 mm per year on average, according to Mann-Kendall test. However, there is evidence that the more urbanized areas have a greater increase in the frequency and magnitude of extreme events, while coastal and mountainous areas, and regions outside large urban areas, have increasing rainfall in a better-distributed way throughout the year. The evolution of extreme rainfall (95th percentile) is significantly correlated with climatic indices. In the center-north part of the MMSP, the combination of Pacific Decadal Oscillation (PDO) and Antarctic Oscillation (AAO) explains 45% of the P95th increase during the wet season. In turn, in southern MMSP, the Temperature of South Atlantic (TSA), the AAO, the El Niño South Oscillation (ENSO) and the Multidecadal Oscillation of the North Atlantic (AMO) better explain the increase in extreme rainfall (R2 = 0.47). However, the same is not observed during the dry season, in which the P95th variation was only negatively correlated with the AMO, undergoing a decrease from the ‘70s until the beginning of this century. The occurrence of rainy anomalous months proved to be more frequent and associated with climatic indices than dry months.

scholarly journals Probabilistic structure of an annual extreme rainfall series of a coastal area of the State of São Paulo, Brazil

2012 ◽  
Vol 32 (3) ◽  
pp. 552-559 ◽  
Author(s):  
Gabriel C. Blain ◽  
Marcelo B. P. de Camargo
Keyword(s):  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Kendall Test ◽  
Sao Paulo ◽  
General Distribution ◽  
São Paulo ◽  
Annual Series ◽  
Serial Correlations ◽  
L Moments ◽  
Probabilistic Structure

This study aimed to describe the probabilistic structure of the annual series of extreme daily rainfall (Preabs), available from the weather station of Ubatuba, State of São Paulo, Brazil (1935-2009), by using the general distribution of extreme value (GEV). The autocorrelation function, the Mann-Kendall test, and the wavelet analysis were used in order to evaluate the presence of serial correlations, trends, and periodical components. Considering the results obtained using these three statistical methods, it was possible to assume the hypothesis that this temporal series is free from persistence, trends, and periodicals components. Based on quantitative and qualitative adhesion tests, it was found that the GEV may be used in order to quantify the probabilities of the Preabs data. The best results of GEV were obtained when the parameters of this function were estimated using the method of maximum likelihood. The method of L-moments has also shown satisfactory results.

scholarly journals Wavelet analysis of rainfall data of the aguapeí -peixe hydrographic basins (state of São Paulo)

2019 ◽  
Vol 41 (1) ◽  
pp. 37753
Author(s):  
Osmar Evandro Toledo Bomfim ◽  
Djane Fonseca da Silva
Keyword(s):  
Wavelet Analysis ◽  
Extreme Rainfall ◽  
Sao Paulo ◽  
Rainfall Data ◽  
São Paulo ◽  
Temporal Scales ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Rainfall Index ◽  
The Pacific

With the use of the Wavelet analysis, this study aimed to detect the dominant oscillations and phenomena that influence the occurrence of extreme rainfall events in the basins of the Aguapeí River and the Peixe River in order to generate information useful to water management. Rainfall data from 18 stations in the State of São Paulo were used, in the period from 1958 to 2013, obtained through the National Water Agency (ANA). The temporal scales that influence the rainfall and the occurrence of extreme events at each rainfall station of the basins were identified, in which the approximately 22-year scale related to the Pacific Decadal Oscillation (PDO) was the dominant in all rainfall stations. The study pointed out that the association of different temporal scales contributes to the increase in the rainfall index, on the other hand, the lack of them relates to years of low rainfall index.

scholarly journals Validation of Satellite Rainfall Estimates over Equatorial East Africa

2021 ◽  
Keyword(s):  
East Africa ◽  
Prediction Models ◽  
Extreme Event ◽  
Weather Prediction ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Annual Rainfall ◽  
Extreme Rainfall Events ◽  
Satellite Rainfall ◽  
Rainfall Estimates

Abstract Rain gauge data sparsity over Africa is known to impede the assessments of hydrometeorological risks and of the skill of numerical weather prediction models. Satellite rainfall estimates (SREs) have been used as surrogate fields for a long time and are continuously replaced by more advanced algorithms and new sensors. Using a unique daily rainfall dataset from 36 stations across equatorial East Africa for the period 2001–2018, this study performs a multi-scale evaluation of gauge-calibrated SREs, namely, IMERG, TMPA, CHIRPS and MSWEP (v2.2 and v2.8). Skills were assessed from daily to annual timescales, for extreme daily precipitation, and for TMPA and IMERG near real-time (NRT) products. Results show that: 1) the SREs reproduce the annual rainfall pattern and seasonal rainfall cycle well, despite exhibiting biases of up to 9%; 2) IMERG is the best for shorter temporal scales while MSWEPv2.2 and CHIRPS perform best at the monthly and annual timesteps, respectively; 3) the performance of all the SREs varies spatially, likely due to an inhomogeneous degree of gauge calibration, with the largest variation seen in MSWEPv2.2; 4) all the SREs miss between 79% (IMERG-NRT) and 98% (CHIRPS) of daily extreme rainfall events recorded by the rain gauges; 5) IMERG-NRT is the best regarding extreme event detection and accuracy; and 6) for return values of extreme rainfall, IMERG and MSWEPv2.2 have the least errors while CHIRPS and MSWEPv2.8 cannot be recommended. The study also highlights; improvements of IMERG over TMPA, the decline in performance of MSWEPv2.8 compared to MSWEPv2.2, and the potential of SREs for flood risk assessment over East Africa.

Sobre a Formação da Mão de Obra Industrial no Brasil e a Imigração Estrangeira - 1890-1930

GEOgraphia ◽  
2009 ◽  
Vol 3 (5) ◽  
pp. 47
Author(s):  
Satiê Mizubuti
Keyword(s):  
Urban Areas ◽  
Rio De Janeiro ◽  
Sao Paulo ◽  
São Paulo ◽  
Agricultural Activities ◽  
Work Relations ◽  
Trade Unionism ◽  
Rural And Urban ◽  
First Republic ◽  
International Demand

Resumo A formação da mão-de-obra no Brasil no decorrer da Primeira República (1890-1930) se fez de forma acelerada e em dois campos simultaneamente no rural e no urbano. No rural, pelo aquecimento da demanda internacional pelo café brasileiro, e, no urbano, pelo início da industrialização, principalmente, nas cidades do Rio de Janeiro e de São Paulo. Tanto nas atividades agrícolas, como nas industriais, a presença e a participação do imigrante estrangeiro foram hegemônicas e decisivas. É preciso considerar que a abolição da escravatura havia ocorrido em 1888, criando um esvaziamento do mercado de trabalho no Brasil. Palavras chave: imigração estrangeira; cafeicultura, industrialização; sindicalismo; relações de trabalho.Resumo Labor formation in Brazil took an accelerated rhythmus during the First Republic (1890-1930) in two fields simultaneously: rural and urban. In the rural sector it was due to an increase in international demand for Brazilian coffee. In the urban areas, meanwhile, the beginning of industrialization, specially in Rio de Janeiro and São Paulo, was the main cause. Not only in the agricultural activities. but also in the industries, the presence and participation of foreign immigrants were decisive. The abolition os slavery in 1888 must be considered as part of this context, as it changed the labour market. Keywords: foreign immigration; coffee growing; industrialization; trade unionism; work relations.

scholarly journals Kecenderungan dan Perubahan Hujan Ekstrem Harian di Pulau Madura

2020 ◽  
Vol 18 (1) ◽  
pp. 89-96
Author(s):  
Ahmad Nur Akma Juangga Fura ◽  
Retno Utami Agung Wiyono ◽  
Indarto Indarto
Keyword(s):  
Flood Hazard ◽  
Parametric Method ◽  
Extreme Rainfall ◽  
Kendall Test ◽  
Random Processes ◽  
Rain Gauge ◽  
Rainfall Trend ◽  
Significance Level ◽  
High Level ◽  
Crossing Test

Madura subject to a high level of flood hazard. One of the main causes of flood is extreme rainfall. Global warming generates changes in the amount of extreme rainfall. This research is conducted to identify and to analyze the trends, changes, and randomness of 24-hour extreme rainfall data on Madura Island. The method used is a non-parametric method which includes the Median Crossing test, the Mann-Kendall test, and the Rank-Sum test at the significance level of α =0.05. The analysis was carried out on 31 rain gauge stations. The recording period observed is between 1991-2015. The results of the analysis show that based on the Median Crossing test, most rainfall stations have data originating from random processes. The result shows also that the maximum 24-hour extreme rainfall trend is significantly decreased in a few locations, while for the majority of other stations have no experience a significant trend.

Heavy precipitating events in satellites and rain-gauge products over the Sahel

2021 ◽  
Author(s):  
Sidiki Sanogo ◽  
Philippe Peyrillé ◽  
Romain Roehrig ◽  
Françoise Guichard ◽  
Ousmane Ouedraogo
Keyword(s):  
Burkina Faso ◽  
West African Monsoon ◽  
Extreme Rainfall ◽  
Rain Gauge ◽  
Reference Dataset ◽  
Extreme Rainfall Events ◽  
Microwave Sensor ◽  
Sahel Region ◽  
Distribution Intensity ◽  
Rain Gauge Network

<p>The Sahel has experienced an increase in the frequency and intensity of extreme rainfall events over the recent decades. These trends are expected to continue in the future. However the properties of these events have so far received little attention. In the present study, we define a heavy precipitating event (HPE) as the occurrence of daily-mean precipitation exceeding a given percentile (e.g., 99<sup>th</sup> and higher) over a 1°x1° pixel and examine their spatial distribution, intensity, seasonality and interannual variability. We take advantage of an original reference dataset based on a rather high-density rain-gauge network over Burkina Faso (142 stations) to evaluate 22 precipitation gridded datasets often used in the literature, based on rain-gauge-only measurements, satellite measurements, or both. Our reference dataset documents the HPEs over Burkina Faso. The 99<sup>th</sup> percentile identifies events greater than 26 mm d<sup>-1</sup> with a ~2.5 mm confidence interval depending on the number of stations within a 1°x1° pixel. The HPEs occur in phase with the West African monsoon annual cycle, more frequently during the monsoon core season and during wet years. The evaluation of the gridded rainfall products reveals that only two of the datasets, namely the rain-gauge-only based products GPCC-DDv1 and REGENv1, are able to properly reproduce all of the HPE features examined in the present work. A subset of the remaining rainfall products also provide satisfying skills over Burkina Faso, but generally only for a few HPE features examined here. In particular, we notice a general better performance for rainfall products that include rain-gauge data in the calibration process, while estimates using microwave sensor measurements are prone to overestimate the HPE intensity. The agreement among the 22 datasets is also assessed over the entire Sahel region. While the meridional gradient in HPE properties is well captured by the good performance subset, the zonal direction exhibit larger inter-products spread. This advocates for the need to continue similar evaluation with the available rain-gauge network available in West Africa, both to enhance the HPE documentation and understanding at the scale of the region and to help improve the rainfall dataset quality.</p>

scholarly journals Space-time cluster analysis of American visceral leishmaniasis in Bauru, São Paulo State, Brazil

2012 ◽  
Vol 28 (10) ◽  
pp. 1949-1964 ◽  
Author(s):  
Vanessa Aparecida Feijó de Souza ◽  
Luiz Ricardo Paes de Barros Cortez ◽  
Ricardo Augusto Dias ◽  
Marcos Amaku ◽  
José Soares Ferreira Neto ◽  
...  
Keyword(s):  
Visceral Leishmaniasis ◽  
Urban Areas ◽  
Sao Paulo ◽  
Space Time ◽  
São Paulo ◽  
Prevention Measures ◽  
Paulo State ◽  
Positive Tendency ◽  
São Paulo State ◽  
The City

A space-time analysis of American visceral leishmaniasis (AVL) in humans in the city of Bauru, São Paulo State, Brazil was carried out based on 239 cases diagnosed between June 2003 and October 2008. Spatial analysis of the disease showed that cases occurred especially in the city's urban areas. AVL annual incidence rates were calculated, demonstrating that the highest rate occurred in 2006 (19.55/100,000 inhabitants). This finding was confirmed by the time series analysis, which also showed a positive tendency over the period analyzed. The present study allows us to conclude that the disease was clustered in the Southwest side of the city in 2006, suggesting that this area may require special attention with regard to control and prevention measures.

scholarly journals Extreme Rainfall in the Mediterranean: What Can We Learn from Observations?

2013 ◽  
Vol 14 (3) ◽  
pp. 906-922 ◽  
Author(s):  
N. Rebora ◽  
L. Molini ◽  
E. Casella ◽  
A. Comellas ◽  
E. Fiori ◽  
...  
Keyword(s):  
Extreme Rainfall ◽  
Flash Floods ◽  
Rain Gauge ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Life Threatening ◽  
The Mediterranean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ground Effects

Abstract Flash floods induced by extreme rainfall events represent one of the most life-threatening phenomena in the Mediterranean. While their catastrophic ground effects are well documented by postevent surveys, the extreme rainfall events that generate them are still difficult to observe properly. Being able to collect observations of such events will help scientists to better understand and model these phenomena. The recent flash floods that hit the Liguria region (Italy) between the end of October and beginning of November 2011 give us the opportunity to use the measurements available from a large number of sensors, both ground based and spaceborne, to characterize these events. In this paper, the authors analyze the role of the key ingredients (e.g., unstable air masses, moist low-level jets, steep orography, and a slow-evolving synoptic pattern) for severe rainfall processes over complex orography. For the two Ligurian events, this role has been analyzed through the available observations (e.g., Meteosat Second Generation, Moderate Resolution Imaging Spectroradiometer, the Italian Radar Network mosaic, and the Italian rain gauge network observations). The authors then address the possible role of sea–atmosphere interactions and propose a characterization of these events in terms of their predictability.

Towards pluvial flooding hazard assessment in an urban environment

2021 ◽  
Author(s):  
Omar Seleem ◽  
Maik Heistermann ◽  
Axel Bronstert
Keyword(s):  
Urban Areas ◽  
Extreme Rainfall ◽  
Likelihood Method ◽  
Runoff Generation ◽  
Topographic Wetness Index ◽  
Extreme Rainfall Events ◽  
Flooding Hazard ◽  
Pluvial Flooding ◽  
Elevation Model ◽  
Spatial Window

<p>Urban pluvial floods are considered as a ubiquitous hazard. The increase in intensity and frequency of extreme rainfall events, combined with high population density makes urban areas vulnerable to pluvial flooding. Pluvial floods could occur anywhere depending on the existence of minimal areas for surface runoff generation and concentration. Detailed hydrologic and hydrodynamic simulations are computationally expensive and resource-intensive. This study applies two computationally inexpensive approaches to identify risk areas for pluvial flooding. One approach uses common GIS operations to detect flood-prone depressions from a high-resolution 1m x 1m Digital Elevation Model (DEM), to identify contributing catchments, and to represent runoff concentration by a fill-spill-merge approach. The second approach employs GIS to identify pluvial flood-prone hotspots in terms of the topographic wetness index (TWI).  Based on the exceedance of a TWI threshold, flood-prone areas are identified using a maximum likelihood method. The threshold is estimated by comparing the TWI to inundation profiles from a two-dimensional (2D) hydrodynamic model (TELEMAC 2D), calculated for various rainfall depths within a given spatial window. The two approaches are applied to two flooding hotspots in Berlin, which have been repeatedly subject to pluvial flooding in the last decades and the outputs are compared against the detailed output from TELEMAC 2D. </p>

scholarly journals Spatial Heterogeneity Analysis of Short-Duration Extreme Rainfall Events in Megacities in China

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3364 ◽  
Author(s):  
Qi Zhuang ◽  
Shuguang Liu ◽  
Zhengzheng Zhou
Keyword(s):  
Spatial Heterogeneity ◽  
Short Duration ◽  
Urban Areas ◽  
Spatial Association ◽  
Extreme Rainfall ◽  
Flood Frequency ◽  
Flood Frequency Analysis ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Design Storm

Given the fact that researchers require more specific spatial rainfall information for storm flood calculation, hydrological risk assessment, and water budget estimates, there is a growing need to analyze the spatial heterogeneity of rainfall accurately. This paper provides insight into rainfall spatial heterogeneity in urban areas based on statistical analysis methods. An ensemble of short-duration (3-h) extreme rainfall events for four megacities in China are extracted from a high-resolution gridded rainfall dataset (resolution of 30 min in time, 0.1° × 0.1° in space). Under the heterogeneity framework using Moran’s I, LISA (Local Indicators of Spatial Association), and semi-variance, the multi-scale spatial variability of extreme rainfall is identified and assessed in Shanghai (SH), Beijing (BJ), Guangzhou (GZ), and Shenzhen (SZ). The results show that there is a pronounced spatial heterogeneity of short-duration extreme rainfall in the four cities. Heterogeneous characteristics of rainfall within location, range, and directions are closely linked to the different urban growth in four cities. The results also suggest that the spatial distribution of rainfall cannot be neglected in the design storm in urban areas. This paper constitutes a useful contribution to quantifying the degree of spatial heterogeneity and supports an improved understanding of rainfall/flood frequency analysis in megacities.

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