Rainfall-related natural disasters in the Northeast of Brazil as a response to ocean-atmosphere interaction

Silva, Bruce Kelly N.; Amorim, Ana Cleide Bezerra; Silva, Claudio M. S.; Lúcio, Paulo Sérgio; Barbosa, Lara M.

doi:10.1007/s00704-019-02930-9

Cited by 11 publications

(6 citation statements)

References 36 publications

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“…The region is characterized by long periods of drought (Hastenrath and Heller, 1977;Moura and Shukla, 1981;Marengo et al, 2017;Silva et al, 2019), the occurrence of extreme precipitation events (Oliveira et al, 2017; Da , all-seasonal variability of the precipitation field (Valadão et al, 2017) and high seasonal and interannual variability of rainfall (Moura and Shukla, 1981;Zhou and Lau, 2001;Oliveira et al, 2017). Annual cumulative rainfall is less than 500 mm in semi-arid regions, greater than 1,500 mm in coastal regions and between 1,000 and 1,200 mm in the north of NEB (Kousky and Chug, 1978;Rao et al, 2016).…”

Section: Study Areamentioning

confidence: 99%

“…In addition, it is influenced by the interannual variability of Pacific Ocean temperature, associated with the El Niño Southern Oscillation (Ropelewski and Halpert, 1987;Marengo et al, 2017), and to the interannual variability of Atlantic Ocean temperatures (Bombardi et al, 2014;Rodrigues et al, 2015). Low-frequency variability is modulated by the action of the Atlantic and Pacific oceans (Andreoli and Kayano, 2007;Moura et al, 2009;Silva et al, 2019).…”

Section: Study Areamentioning

confidence: 99%

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Spatial distribution of the level of return of extreme precipitation events in Northeast Brazil

Rodrigues

Gonçalves

Spyrides

et al. 2020

Intl Journal of Climatology

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This study aimed to estimate levels of return of extreme daily precipitation events, associating them with natural disasters in Northeast Brazil (NEB), a region characterized by different climatic conditions and low rates of social and economic development. For this, generalized Pareto distribution (GPD) models were adjusted to the daily extreme precipitation data estimated by the Tropical Rainfall Measuring Mission (TRMM) 3B42 product of the multisatellite precipitation analysis for a period of 16 years (2000-2015). In addition, the estimates of the GPD model were compared using two data sources, TRMM and pluviometer. The investigation showed that the results of the GPD model estimated by means of the extreme data from the rain gauge and the TRMM were statistically the same, with 95% confidence. Thus, using the data referring to the 2,082 grid points of the TRMM, it was possible to map the spatial distribution of the estimates of the levels of return of extreme precipitation to the return periods of 2, 5 and 10 years, per seasonal period. In general, the results indicated that the intensity of expected extreme precipitation depends on the seasonal period and the place of occurrence of precipitation. The eastern NEB stood out as the region where the highest intensities of extreme precipitation are expected. Extreme precipitation values of up to 178 mm are expected in 2 years. The areas where natural disasters occurred in the years 2016, 2017 and 2018 are similar to those in which the highest rainfall intensities are expected. The results of this study can allow the evaluation of the spatial distribution of risks related to extreme precipitation events, and therefore, support the planning of regional public policies and environmental management for the prevention of natural disasters in NEB. K E Y W O R D S diaries precipitation, generalized Pareto distribution, natural disaster, TRMM 1 | INTRODUCTION Extreme weather events are one of the main topics studied related to climate change. Future projections released by the Intergovernmental Panel on Climate Change (IPCC) show that these events will become increasingly frequent and intense in several regions of the world, including in areas of Northeast Brazil (NEB; Du et al., 2019). Extreme weather events can cause waves of heat and cold, floods, landslides, droughts and more.

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Section: Study Areamentioning

confidence: 99%

Section: Study Areamentioning

confidence: 99%

Spatial distribution of the level of return of extreme precipitation events in Northeast Brazil

Rodrigues

Gonçalves

Spyrides

et al. 2020

Intl Journal of Climatology

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“…Droughts have been reported in NEB since the colonial period [3,11,12]. Historically, the States of Ceará, Rio Grande do Norte, Paraiba, and Pernambuco are concentrated drought hotspots [13]. Drought hazards have caused massive migration and significant population death, such as the drought of 1877-1879, with human drought-related deaths estimated to be around 500,000 persons in Ceará State alone [12].…”

Section: Introductionmentioning

confidence: 99%

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

Filho

Martins

et al. 2020

Water

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The 2012–2018 drought was such an extreme event in the drought-prone area of Northeast Brazil that it triggered a discussion about proactive drought management. This paper aims at understanding the causes and consequences of this event and analyzes its frequency. A consecutive sequence of sea surface temperature anomalies in the Pacific and Atlantic Oceans, at both the decadal and interannual scales, led to this severe and persistent drought. Drought duration and severity were analyzed using run theory at the hydrographic region scale as decision-makers understand impact analysis better at this scale. Copula functions were used to properly model drought joint characteristics as they presented different marginal distributions and an asymmetric behavior. The 2012–2018 drought in Ceará State had the highest mean bivariate return period ever recorded, estimated at 240 years. Considering drought duration and severity simultaneously at the level of the hydrographic regions improves risk assessment. This result advances our understanding of exceptional events. In this sense, the present work proposes the use of this analysis as a tool for proactive drought planning.

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“…This pattern of vegetation variability was expected for these regions, as they are composed of biomes that respond rapidly to local rainfall. Among them, the Brazilian Cerrado and Caatinga stand out [2,49,57,58], and the Dry Chaco is present in Bolivia, Paraguay, and Argentina [23].…”

Section: New Vegetation Climatologymentioning

confidence: 99%

A New Climatology of Vegetation and Land Cover Information for South America

Alves,

Gonçalves,

Ávila

et al. 2024

Sustainability

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Accurate information on vegetation and land cover is crucial for numerical forecasting models in South America. This data aids in generating more realistic forecasts, serving as a tool for decision-making to reduce environmental impacts. Regular updates are necessary to ensure the data remains representative of local conditions. In this study, we assessed the suitability of ‘Catchment Land Surface Models-Fortuna 2.5’ (CLSM), Noah, and Weather Research and Forecasting (WRF) for the region. The evaluation revealed significant changes in the distribution of land cover classes. Consequently, it is crucial to adjust this parameter during model initialization. The new land cover classifications demonstrated an overall accuracy greater than 80%, providing an improved alternative. Concerning vegetation information, outdated climatic series for Leaf Area Index (LAI) and Greenness Vegetation Fraction (GVF) were observed, with notable differences between series, especially for LAI. While some land covers exhibited good performance for GVF, the Forest class showed limitations. In conclusion, updating this information in models across South America is essential to minimize errors and enhance forecast accuracy.

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Rainfall-related natural disasters in the Northeast of Brazil as a response to ocean-atmosphere interaction

Cited by 11 publications

References 36 publications

Spatial distribution of the level of return of extreme precipitation events in Northeast Brazil

Spatial distribution of the level of return of extreme precipitation events in Northeast Brazil

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

A New Climatology of Vegetation and Land Cover Information for South America

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