Nordeste Region Research Articles

Application of the PROMETHEE II method to define better strate-gies for preventing land transport accidents in the Nordeste region

One of the biggest causes of death in the world is caused by land transport accidents (ATL), involving vehicles, according to the world health organization. This article presents an application of the multicriteria methodology for ordering preventive actions in the Nordeste region of Brazil, considering traffic accidents involving fatal victims. Through the database of the Federal Highway Police on traffic accidents in the year 2018, it identified the State of Bahia that had the highest absolute number of fatalities. The PROMETHEE II method was applied to the collected data and resulted in the ordering of preventive actions that should be incorporated by decision makers. It is expected that emphasis should be placed on intensifying traffic enforcement in the State of Bahia, as in 2018, there were 83 deaths caused by speeding, representing 18% of the data collected involving fatal victims in 2018. In addition, undue overtaking and non-activation of the lighting/signalling system represented 9.6% of the deaths that occurred in 2018. Therefore, decision-makers will be able to define strategies, actions and measures to improve traffic safety.

Using Genetic Programming to Identify Characteristics of Brazilian Regions in Relation to Rural Credit Allocation

Rural credit policies have a strong impact on food production and food security. The attribution of credit policies to agricultural production is one of the main problems preventing the guarantee of agricultural expansion. In this work, we conduct family typology analysis applied to a set of research data to characterize different regions. Through genetic programming, a model was developed using user-defined terms to identify the importance and priority of each criterion used for each region. Access to credit results in economic growth and provides greater income for family farmers, as observed by the results obtained in the model for the Sul region. The Nordeste region indicates that the cost criterion is relevant, and according to previous studies, the Nordeste region has the highest number of family farming households and is also the region with the lowest economic growth. An important aspect discovered by this research is that the allocation of rural credit is not ideal. Another important aspect of the research is the challenge of capturing the degree of diversity across different regions, and the typology is limited in its ability to accurately represent all variations. Therefore, it was possible to characterize how credit is distributed across the country and the main factors that can influence access to credit.

The Globally Coherent Pattern of Autumn Monsoon Precipitation

AbstractOver most tropical land areas, the annual peak in precipitation occurs during summer, associated with the local monsoon circulation. However, in some coastal regions in the tropics the bulk of annual precipitation occurs in autumn, after the low-level summer monsoon westerlies have abated. Examples include the Nordeste region of Brazil, southeastern India and Sri Lanka, and coastal Tanzania. Unlike equatorial regions, they receive little rainfall during local spring. Such regions are present along the eastern coasts of nearly all continents, suggesting that they comprise a coherent yet previously unrecognized global phenomenon.In this study, we identify eight tropical locations that experience an “autumn monsoon” and show that this unusual seasonal cycle is generated by similar mechanisms in all of these. When these regions receive their peak rainfall, they lie poleward of the ITCZ in easterly low-level winds. The spatial structure of precipitation in these regions can be explained by their placement to the east of mountain ranges that organize moist convection on their windward sides. However, orographic forcing alone cannot explain their unique seasonal cycle: despite similarities in wind direction, surface humidity, and sea surface temperatures (SSTs) between autumn and spring, these regions receive significantly more rainfall in autumn than in spring. We show that this is due to differences in the large-scale atmospheric stability between the equinoctial seasons, which can be captured by a relative SST metric and is influenced by SSTs in the remote eastern upwelling zones of the Pacific and Atlantic Oceans.

Análise de dados aplicada às Cidades Inteligentes: reflexões sobre a Região Nordeste do Brasil

As cidades inteligentes, como aposta para a gestão urbana, têm despertado a atenção de pesquisadores e gestores públicos ao redor do mundo. Em 2020, na Região Nordeste do Brasil, 36 municípios estão categorizados como “cidades inteligentes”. Este artigo descreve os métodos usados para analisar, visualizar e discutir algumas informações sobre essas 36 cidades. A utilização de mapas temáticos permitiu demonstrar, numa perspectiva espacial, algumas características desses municípios, e sua associação ao uso de métodos de mineração de dados e a uma perspectiva teórica crítica mostrou-se útil para compreender as dinâmicas territoriais das cidades inteligentes. Ao combinar variáveis das cidades pesquisadas, a análise de componentes principais e o agrupamento hierárquico identificaram automaticamente similaridades e diferenças entre elas. Em comparação com as metrópoles e capitais incluídas neste estudo, e tomando-se como referência a REGIC 2007, os resultados mostram-se úteis para identificar as cidades com potencialidades para melhor promover e/ou abrigar dinâmicas territoriais características de cidades inteligentes, que são: Jaboatão dos Guararapes-PE, Olinda-PE, Igarassu-PE, São Lourenço da Mata-PE, Moreno-PE, Itapissuma-PE, que fazem parte da Região Metropolitana de Recife; e Parnamirim-RN, pertencente à Região Metropolitana de Natal.

Unprecedented drought over tropical South America in 2016: significantly under-predicted by tropical SST

Tropical and sub-tropical South America are highly susceptible to extreme droughts. Recent events include two droughts (2005 and 2010) exceeding the 100-year return value in the Amazon and recurrent extreme droughts in the Nordeste region, with profound eco-hydrological and socioeconomic impacts. In 2015–2016, both regions were hit by another drought. Here, we show that the severity of the 2015–2016 drought ("2016 drought" hereafter) is unprecedented based on multiple precipitation products (since 1900), satellite-derived data on terrestrial water storage (since 2002) and two vegetation indices (since 2004). The ecohydrological consequences from the 2016 drought are more severe and extensive than the 2005 and 2010 droughts. Empirical relationships between rainfall and sea surface temperatures (SSTs) over the tropical Pacific and Atlantic are used to assess the role of tropical oceanic variability in the observed precipitation anomalies. Our results indicate that warmer-than-usual SSTs in the Tropical Pacific (including El Niño events) and Atlantic were the main drivers of extreme droughts in South America, but are unable to explain the severity of the 2016 observed rainfall deficits for a substantial portion of the Amazonia and Nordeste regions. This strongly suggests potential contribution of non-oceanic factors (e.g., land cover change and CO2-induced warming) to the 2016 drought.

The Causes of mortality during the Great Famine

A comparison with the Nordeste region of Brazil suggests that the Irish, despite their poverty and recurring food shortages, were in good health prior to the Great Famine. But the exceptional length of the Famine weakened their immunitary defenses and they became vulnerable to numerous infections. Yet medical knowledge at the time was not only insufficient to correctly identify the causes of death, it actually increased mortality, notably by grouping people in fever hospitals where contagion was rife.

The role of North Brazil Current transport in the paleoclimate of the Brazilian Nordeste margin and paleoceanography of the western tropical Atlantic during the late Quaternary

Reconstructions of surface paleoceanographic conditions of the western equatorial Atlantic and past climates of the adjacent Northeast Brazilian (the “Nordeste”) continental margin were undertaken by analyzing sediments from a piston core and associated gravity and box cores recovered from 3107 meter water depth at 0° 20′ N on the equatorial Brazilian continental slope. The record is dated by radiocarbon analysis and oxygen isotopic stratigraphy of planktonic foraminifers and spans from near-modern to approximately 110 Ka.High-resolution XRF analysis provides insight into the paleoclimate history of the Nordeste during the last glacial interval. Several large-amplitude and abrupt peaks are observed in the time series of Ti/Ca and are usually accompanied by peaks of Fe/K. Together these record periods of increased precipitation and intense weathering on the adjacent continent and increased terrestrial sediment discharge from Nordeste rivers into the Atlantic. Within the limits of dating accuracy, most Ti/Ca peaks correlate with Heinrich events in the North Atlantic. This record thus corroborates, and extends back in time, the previous record of Arz et al. (1998) determined on sediment cores from farther southeast along the Nordeste margin.Stable oxygen isotopic analysis and Mg/Ca paleothermometry on the near-surface-dwelling planktonic foraminiferal species Globierinoides ruber find that mean sea-surface temperature (SST) during glacial time (20–55 Ka, n=97) was 23.89±0.79°C and the mean SST during the late Holocene (0–5 Ka, n=14) was 26.89±0.33°C. SSTs were 0.5–2°C higher and inferred sea-surface salinities were lower during most of the periods of elevated Ti/Ca, thus, as observed in previous studies, the western equatorial Atlantic was warm (at least locally) and the adjacent southern tropical continent was wet at the same time that the high-latitude North Atlantic was cold.Using the SYNTRACE-CCSM3 fully coupled climate model with transient forcing for the period 22 Ka to present, we find that decreased transport of the North Brazil Current co-occurs with reduced Atlantic meridional overturning circulation, and colder-than-normal SSTs in the North Atlantic region. These simulated conditions are invariably associated with significantly increased precipitation in the Nordeste region.

Relationship between ocean climatic variability and rain-fed agriculture in northeast Brazil

The statistical relationship between sea-surface temperature variability over tropical oceans and the 1952 to 2000 crops of maize and beans in the state of Ceara, Brazil, was investigated. This region mainly receives precipitation from February to May. The climatic indices used were the Nino-3 for the Pacific and the dipole index for the Atlantic. In a first series of diagnostic analyses, the climatic precursor variables were examined from November to January (Years 0 to 1) for the Nino-3 in- dex and from February to April (Year 1) for the Atlantic dipole components. The agronomic variables were the planted area, annual production, yield (which showed a negative linear trend during the study period), price, and aggregate value (price/yield) for Year 1. A more robust statistical weight was obtained with the Atlantic dipole. The Pacific weight added to, or decreased, the Atlantic effect, de- pending on the sign of the index. Ocean climatic conditions that generate drought episodes in the Nordeste region of Brazil are generally associated with bad harvests. However, the reverse (i.e. wet weather episodes) does not necessarily produce good harvests. In a second series of prognostic analy- ses, a statistical model used the ocean climatic information available before the rainy season to forecast the yields of maize and beans. The model gave some relevant data in terms of yield tendencies, and was more sensitive when the climatic conditions were neutral or dry. Remarkably good yield forecasts were noted at the end of the study period. Harvests depend on complex combinations of multiple climatic criteria related, not only to quantitative, but also qualitative factors connected with the rainy season.

Effects of Twenty-First-Century Climate Change on the Amazon Rain Forest

Abstract A regional atmospheric model with 60-km resolution is asynchronously coupled with a potential vegetation model to study the implications of twenty-first-century climate change for the tropical and subtropical climate and vegetation of South America. The coupled model produces an accurate simulation of the present day climate and vegetation. Future climate is simulated by increasing atmospheric CO2 levels to 757 ppmv and imposing lateral and surface boundary conditions derived from a GCM simulation for 2081–2100 from the Canadian Climate Center GCM. The coupled regional model simulation projects a 70% reduction in the extent of the Amazon rain forest by the end of the twenty-first century and a large eastward expansion of the caatinga vegetation that is prominent in the Nordeste region of Brazil today. These changes in vegetation are related to reductions in annual mean rainfall and a modification of the seasonal cycle that are associated with a weakening of tropical circulation systems.

Improving Seasonal Forecasting in the Low Latitudes

AbstractSeasonal forecast of climate anomalies holds the prospect of improving agricultural planning and food security, particularly in the low latitudes where rainfall represents a limiting factor in agrarian production. Present-day methods are usually based on simulated precipitation as a predictor for the forthcoming rainy season. However, climate models often have low skill in predicting rainfall due to the uncertainties in physical parameterization. Here, the authors present an extended statistical model approach using three-dimensional dynamical variables from climate model experiments like temperature, geopotential height, wind components, and atmospheric moisture. A cross-validated multiple regression analysis is applied in order to fit the model output to observed seasonal precipitation during the twentieth century. This model output statistics (MOS) system is evaluated in various regions of the globe with potential predictability and compared with the conventional superensemble approach, which refers to the same variable for predictand and predictors.It is found that predictability is highest in the low latitudes. Given the remarkable spatial teleconnections in the Tropics, a large number of dynamical predictors can be determined for each region of interest. To avoid overfitting in the regression model an EOF analysis is carried out, combining predictors that are largely in-phase with each other. In addition, a bootstrap approach is used to evaluate the predictability of the statistical model. As measured by different skill scores, the MOS system reaches much higher explained variance than the superensemble approach in all considered regions. In some cases, predictability only occurs if dynamical predictor variables are taken into account, whereas the superensemble forecast fails. The best results are found for the tropical Pacific sector, the Nordeste region, Central America, and tropical Africa, amounting to 50% to 80% of total interannual variability. In general, the statistical relationships between the leading predictors and the predictand are physically interpretable and basically highlight the interplay between regional climate anomalies and the omnipresent role of El Niño–Southern Oscillation in the tropical climate system.

Theoretical framework for local PLS1 regression, and application to a rainfall data set

A new multivariate non-parametric regression method is considered, which is an extension of PLS1 regression using the multivariate local polynomial regression framework. A theoretical framework that can be used in order to study the asymptotic properties of the estimator is proposed, and the method is implemented on a real data set, made up of seasonal amounts of rainfall in the north of the Nordeste region of Brazil, to be explained by climatic variables. The performances of the three methods of PLS1 regression, multivariate local regression and local PLS1 regression are compared by means of cross-validation and the use of a validation period. All calculations have been implemented in the S-Plus package. The results confirm the good properties of local PLS1 regression.

South American climate during the Last Glacial Maximum: Delayed onset of the South American monsoon

The climate of the Last Glacial Maximum (LGM) over South America is simulated using a regional climate model with 60‐km resolution, providing a simulation that is superior to those available from global models that do not resolve the topography and regional‐scale features of the South American climate realistically. LGM conditions on SST, insolation, vegetation, and reduced atmospheric CO2 on the South American climate are imposed together and individually. Remote influences are not included. Annual rainfall is 25–35% lower in the LGM than in the present day simulation throughout the Amazon basin. A primary cause is a 2–3 month delay in the onset of the rainy season, so that the dry season is about twice as long as in the present day. The delayed onset occurs because the low‐level inflow from the tropical Atlantic onto the South American continent is drier than in the present day simulation due to reduced evaporation from cooler surface waters, and this slows the springtime buildup of moist static energy that is needed to initiate convection. Once the monsoon begins in the Southern Hemisphere, LGM rainfall rates are similar to those in the present day. In the Northern Hemisphere, however, rainfall is lower throughout the (shortened) rainy season. Regional‐scale structure includes slight precipitation increases in the Nordeste region of Brazil and along the eastern foothills of the Andes, and a region in the center of the Amazon basin that does not experience annual drying. In the Andes Mountains, the signal is complicated, with regions of significant rainfall increases adjacent to regions with reduced precipitation.

Ethnopsychiatrie : la culture au service de la santé

Antonio Mourâo Cavalcante - Ethnopsychiatry: culture comes to the aid of health. The Author takes a case history as a basis for developing a discussion where he emphasizes the psychiatric and cultural aspects of a situation. This is a typical ethnopsychiatric approach, which goes back to the work of Georges Devereux and Tobie Nathan. The psychiatric elements the case presents suggest a depression. The cultural aspects, closely linked to the realities of life in the Nordeste region of Brazil, reflect the world of rural traditional, steeped in religious beliefs and struggles for power. The scenario is typical of ancient Brazil which, through the aging patient, shows the decline, even the progressive disappearance, of that world, now suffused with modernity and social pluralism.

Influence of Surface Processes over Africa on the Atlantic Marine ITCZ and South American Precipitation

Abstract Previous studies show that the climatological precipitation over South America, particularly the Nordeste region, is influenced by the presence of the African continent. Here the influence of African topography and surface wetness on the Atlantic marine ITCZ (AMI) and South American precipitation are investigated. Cross-equatorial flow over the Atlantic Ocean introduced by north–south asymmetry in surface conditions over Africa shifts the AMI in the direction of the flow. African topography, for example, introduces an anomalous high over the southern Atlantic Ocean and a low to the north. This results in a northward migration of the AMI and dry conditions over the Nordeste region. The implications of this process on variability are then studied by analyzing the response of the AMI to soil moisture anomalies over tropical Africa. Northerly flow induced by equatorially asymmetric perturbations in soil moisture over northern tropical Africa shifts the AMI southward, increasing the climatological precipitation over northeastern South America. Flow associated with an equatorially symmetric perturbation in soil moisture, however, has a very weak cross-equatorial component and very weak influence on the AMI and South American precipitation. The sensitivity of the AMI to soil moisture perturbations over certain regions of Africa can possibly improve the skill of prediction.

The drought of the century in the Amazon Basin: an analysis of the regional variation of rainfall in South America in 1926

The most severe drought in tropical South America during the 20th century occurred in 1926. This extreme El Nino year is further documented anecdotally, in an update of the river stage observations at Manaus, and in annual rainfall records. The annual rainfall anomaly is an east-west dipole over tropical South America, with drought to the west over the Amazon basin whose discharge is documented at Manaus, and with a surplus to the east and including the Nordeste region of Brazil. Speculations about a role for aerosol in aggravating the drought are discussed.

The Africa–South America Intercontinental Teleconnection

Abstract The influence of heating over Africa on the South American precipitation climatology, and the influence of South America on Africa, is examined through the application of GCM simulations with idealized boundary conditions and perpetual solstice (January and July) conditions. The presence of Africa is associated with a pronounced (up to 4 mm day−1) decrease in precipitation in Brazil's Nordeste region during austral summer. Low-level moisture divergence and dry-air advection associated with the downbranch of a Walker circulation induced by heating over southern Africa is amplified over the Nordeste due to the response of the land surface. The response is much smaller during austral winter due to differences in the heat source over Africa and a reduced sensitivity in the surface heat balance over tropical South America. Forcing from South America in January shifts the position of the South Indian convergence zone (SICZ) to the southwest over southern Africa in association with the formation of the ...

An Evaluation of the Predictability of Austral Summer Season Precipitation over South America

Abstract In this study predictability of austral summer seasonal precipitation over South America is investigated using a 12-yr set of a 3.5-month range (seasonal) and a 17-yr range (continuous multiannual) five-member ensemble integrations of the Center for Ocean–Land–Atmosphere Studies (COLA) atmospheric general circulation model (AGCM). These integrations were performed with prescribed observed sea surface temperature (SST); therefore, skill attained represents an estimate of the upper bound of the skill achievable by COLA AGCM with predicted SST. The seasonal runs outperform the multiannual model integrations both in deterministic and probabilistic skill. The simulation of the January–February–March (JFM) seasonal climatology of precipitation is vastly superior in the seasonal runs except over the Nordeste region where the multiannual runs show a marginal improvement. The teleconnection of the ensemble mean JFM precipitation over tropical South America with global contemporaneous observed sea surface ...

Dynamic Downscaling of Seasonal Simulations over South America

In this paper multiple atmospheric global circulation model (AGCM) integrations at T42 spectral truncation and prescribed sea surface temperature were used to drive regional spectral model (RSM) simulations at 80-km resolution for the austral summer season (January–February–March). Relative to the AGCM, the RSM improves the ensemble mean simulation of precipitation and the lower- and upper-level tropospheric circulation over both tropical and subtropical South America and the neighboring ocean basins. It is also seen that the RSM exacerbates the dry bias over the northern tip of South America and the Nordeste region, and perpetuates the erroneous split intertropical convergence zone (ITCZ) over both the Pacific and Atlantic Ocean basins from the AGCM. The RSM at 80-km horizontal resolution is able to reasonably resolve the Altiplano plateau. This led to an improvement in the mean precipitation over the plateau. The improved resolution orography in the RSM did not substantially change the predictability of the precipitation, surface fluxes, or upper- and lower-level winds in the vicinity of the Andes Mountains from the AGCM. In spite of identical convective and land surface parameterization schemes, the diagnostic quantities, such as precipitation and surface fluxes, show significant differences in the intramodel variability over oceans and certain parts of the Amazon River basin (ARB). However, the prognostic variables of the models exhibit relatively similar model noise structures and magnitude. This suggests that the model physics are in large part responsible for the divergence of the solutions in the two models. However, the surface temperature and fluxes from the land surface scheme of the model [Simplified Simple Biosphere scheme (SSiB)] display comparable intramodel variability, except over certain parts of ARB in the two models. This suggests a certain resilience of predictability in SSiB (over the chosen domain of study) to variations in horizontal resolution. It is seen in this study that the summer precipitation over tropical and subtropical South America is highly unpredictable in both models.

A new approach in space‐time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three‐way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Regional simulation of interannual variability over South America

Three regional climate simulations covering the austral summer season during three contrasting phases of the El Niño‐Southern Oscillation cycle were conducted with the Regional Spectral Model (RSM) developed at the National Centers for Environmental Prediction (NCEP). The simulated interannual variability of precipitation over the Amazon River Basin, the Intertropical Convergence Zone, the Pacific and Atlantic Ocean basins, and extratropical South America compare reasonably well with observations. The RSM optimally filters the peturbations about a time‐varying base field, thereby enhancing the information content of the global NCEP reanalysis. The model is better than the reanalysis in reproducing the observed interannual variability of outgoing longwave radiation at both high frequencies (3–30 days) and intraseasonal (30–60 days) scales. The low‐level jet shows a peak in its speed in 1998 and a minimum in the 1999 simulations. The lag correlation of the jet index with convection over various areas in continental South America indicates that the jet induces precipitation over the Pampas region downstream. A detailed moisture budget was conducted over various subregions. This budget reveals that moisture flux convergence determines most of the interannual variability of precipitation over the Amazon Basin, the Atlantic Intertropical Convergence Zone, and the Nordeste region of Brazil. However, both surface evaporation and surface moisture flux convergence were found to be critical in determining the interannual variability of precipitation over the southern Pampas, Gran Chaco area, and the South Atlantic Convergence Zone.