Ranking of daily precipitation extreme events over oil pipelines in Rio de Janeiro

2021 ◽  
Author(s):  
ICF Amaral ◽  
RS Libonati ◽  
ACPA Palmeira ◽  
AM Ramos
Keyword(s):  
Extreme Events ◽  
Rio De Janeiro ◽  
Daily Precipitation ◽  
Precipitation Extreme ◽  
Oil Pipelines

Estimating return periods for daily precipitation extreme events over the Brazilian Amazon

2015 ◽  
Vol 126 (3-4) ◽  
pp. 585-595 ◽  
Author(s):  
Eliane Barbosa Santos ◽  
Paulo Sérgio Lucio ◽  
Cláudio Moisés Santos e Silva
Keyword(s):  
Extreme Events ◽  
Daily Precipitation ◽  
Brazilian Amazon ◽  
Precipitation Extreme ◽  
Return Periods

scholarly journals RANKING OF DAILY SATELLITE-DERIVED PRECIPITATION EXTREMES FOR THE ORBIG PIPELINE IN RIO DE JANEIRO

2020 ◽  
Vol XLII-3/W12-2020 ◽  
pp. 505-508
Author(s):  
I. C.F. Amaral ◽  
R. S. Libonati ◽  
A. C. P. A. Palmeira
Keyword(s):  
Rio De Janeiro ◽  
Daily Precipitation ◽  
False Alarms ◽  
Oil Pipeline ◽  
News Reports ◽  
Rainfall Index ◽  
Extreme Precipitation Events ◽  
Statistical Ranking ◽  
Summer Time ◽  
Precipitation Events

Abstract. The present work was motivated by the occurrence of vast damage caused by intense rainfalls in the state of Rio de Janeiro and the great importance of the oil pipelines for the economy by using remote sensing multisatellite dataset from the GPM 3-IMERG-HHE product from 06/2000 to 06/2019, along the ORBIG pipeline located between the municipalities of Angra dos Reis and Duque de Caxias, RJ. A statistical ranking method has been applied to classify extreme daily precipitation events over the region. An event is classified as extreme by considering the total affected area and its intensity, based on the daily normalized anomaly calculated from the climatology data. The results show that in cold front events the oil pipeline region is hit more spatially with high accumulations of daily precipitation. However, in thermal instability precipitation, despite affecting locally, it has also shown extreme precipitation events, highlighting that in the 10 largest cases there were no false alarms, according to records found in news reports and rainfall indexes. It was also noted that during summer time there were more extreme cases. In conclusion, this study served to indicate places and times of higher rainfall index regardless of whether the region has a dense population or not.

scholarly journals Identificação das causas climáticas dos eventos extremos e dos impactos dos ENOS Canônico e Modoki nas macrorregiões de Alagoas

2021 ◽  
Vol 14 (4) ◽  
pp. 1880-1897
Author(s):  
Djane Fonseca Da Silva ◽  
Pedro Fernandes de Souza Neto ◽  
Silvania Donato da Silva ◽  
Maria José da Silva Lima ◽  
Iara Bezerra da Silva Cavalcante ◽  
...  
Keyword(s):  
Extreme Events ◽  
El Niño ◽  
Daily Precipitation ◽  
El Nino ◽  
The State ◽  
La Niña ◽  
Eastern Region ◽  
Equatorial Pacific Ocean ◽  
La Nina ◽  
Daily Precipitation Data

Anomalies of sea surface temperature that occur in some regions of the Equatorial Pacific Ocean are being studied because their cause different impacts and originate in different ways, are the ENOS, Modoki and Canonical. The objective of this work is to identify the climatic causes of the extreme events that occurred in the macro-regions of Alagoas, and at the same time, to compare the effects of ENOS Canonical and Modoki and their classes on the macro-regions of Alagoas. The daily precipitation data for 21 municipalities in the State of Alagoas were obtained through the National Water Agency from 1963 to 2014. EN Modoki and low promoted an increase in rainfall in the Eastern region. EN Fortes, on the other hand, caused a decrease in rainfall in the Sertão. Canonical LN events caused a significant increase in rainfall in the three macro-regions, but the effect was better in LN Forte. During the phases of the Atlantic Dipole, the negative phase generated positive SPI across the state, and in the positive phase, there was a decrease in SPI in the East, and a negative SPI record in Sertão and Agreste. The climatic causes of the extreme events were the combination of semiannual, interannual scales, scale between 1-2 years of ENOS, scale of ENOS extended and scale of 11 years (Dipole and sunspots), potentiating the local total rainfall, and for cases of drought , your absence. It was found, through cluster analysis, similarity between the SPIs of La Niña low and La Niña Canonical, and between El Niño Canonical is linked to El Niño Forte. Mathematically, the categories of El Niño and La Niña strong and weak showed better correlations with ENOS Modoki and Canonical, suggesting a pattern for Alagoas.

scholarly journals Assessment of climate variations in temperature and precipitation extreme events over Iran

2015 ◽  
Vol 126 (3-4) ◽  
pp. 775-795 ◽  
Author(s):  
M. Soltani ◽  
P. Laux ◽  
H. Kunstmann ◽  
K. Stan ◽  
M. M. Sohrabi ◽  
...  
Keyword(s):  
Extreme Events ◽  
Precipitation Extreme ◽  
Climate Variations ◽  
Temperature And Precipitation

scholarly journals Potential of GPM IMERG Precipitation Estimates to Monitor Natural Disaster Triggers in Urban Areas: The Case of Rio de Janeiro, Brazil

2020 ◽  
Vol 12 (24) ◽  
pp. 4095
Author(s):  
Augusto Getirana ◽  
Dalia Kirschbaum ◽  
Felipe Mandarino ◽  
Marta Ottoni ◽  
Sana Khan ◽  
...  
Keyword(s):  
Natural Disaster ◽  
Extreme Events ◽  
Land Surface ◽  
Urban Areas ◽  
Rio De Janeiro ◽  
Temporal Dynamics ◽  
Extreme Rainfall ◽  
Surface Model ◽  
The City ◽  
Rainfall Estimates

Extreme rainfall can be a catastrophic trigger for natural disaster events at urban scales. However, there remains large uncertainties as to how satellite precipitation can identify these triggers at a city scale. The objective of this study is to evaluate the potential of satellite-based rainfall estimates to monitor natural disaster triggers in urban areas. Rainfall estimates from the Global Precipitation Measurement (GPM) mission are evaluated over the city of Rio de Janeiro, Brazil, where urban floods and landslides occur periodically as a result of extreme rainfall events. Two rainfall products derived from the Integrated Multi-satellite Retrievals for GPM (IMERG), the IMERG Early and IMERG Final products, are integrated into the Noah Multi-Parameterization (Noah-MP) land surface model in order to simulate the spatial and temporal dynamics of two key hydrometeorological disaster triggers across the city over the wet seasons during 2001–2019. Here, total runoff (TR) and rootzone soil moisture (RZSM) are considered as flood and landslide triggers, respectively. Ground-based observations at 33 pluviometric stations are interpolated, and the resulting rainfall fields are used in an in-situ precipitation-based simulation, considered as the reference for evaluating the IMERG-driven simulations. The evaluation is performed during the wet seasons (November-April), when average rainfall over the city is 4.4 mm/day. Results show that IMERG products show low spatial variability at the city scale, generally overestimate rainfall rates by 12–35%, and impacts on TR and RZSM vary spatially mostly as a function of land cover and soil types. Results based on statistical and categorical metrics show that IMERG skill in detecting extreme events is moderate, with IMERG Final performing slightly better for most metrics. By analyzing two recent storms, we observe that IMERG detects mostly hourly extreme events, but underestimates rainfall rates, resulting in underestimated TR and RZSM. An evaluation of normalized time series using percentiles shows that both satellite products have significantly improved skill in detecting extreme events when compared to the evaluation using absolute values, indicating that IMERG precipitation could be potentially used as a predictor for natural disasters in urban areas.

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