cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14282092.v1
title: Evaluation of Erosivity Extremes Caused by Precipitation in the Apodi/Mossoró-RN River Basin

description: Abstract Identifying areas with a potential risk of environmental degradation by anthropic or natural processes is important for sustainable management of natural resources, especially in the semiarid regions of northeastern Brazil. Rain erosivity is given by the Universal Soil Loss Equation (EUPS) which relates the erosive capacity of rainfall and its ability to disintegrate by the impact of the particle surface. The present study aimed to evaluate the erosion index (EI30) and to evaluate the EI30 extremes in the Apodi/Mossoró watershed through the theory of extreme values and to associate with the rainfall pattern of the region. For this, precipitation data from the Agência Nacional das águas (ANA) and the Tropical Rainfall Measuring Mission (TRMM) project were used. Among several methodologies for the selection of mathematical models that explain the extremes of erosivity, this research used the Akaike Information Criteria (AIC) and the Schwarz Bayesian Criterion (BIC), together with the correlation assessment at EI30 and the coefficient of rain (Rc). Thus, Felipe Guerra station presented the best results to generate the hydrological effect of the EI30 in the basin with TRMM data. It can be concluded that TRMM data can be of great value for the estimation of the EI30 where observational data is not available. Moreover, the EI30 follows the precipitation seasonality and was classified as moderate whose highest values occur from February to May.
DOI: 10.6084/m9.figshare.14282093
title: Influence of Tropical Disturbances on Severe weather phenomena of Stable Atmosphere Formation in Northeast Brazil

description: Abstract The main aim of this study is to analyze an impact of Tropical Disturbs (TD) in the Northern Hemisphere (NH), associated with Tropical Cyclones (TC), on adverse phenomena in Northeast Brazil (NEB) in 2013 - 2015, in order to improve the weather forecasting method in this area. Information about TC was obtained from the National Hurricane Center. Adverse phenomena were studied using METAR and SYNOP data. The synoptic analysis was based on the satellite images and maps of different variables. Reanalysis data from the European Center for Medium-Range Weather Forecasts were used. Nine TD were observed during the passage of TC. In the same period, fogs and mist with drizzle were recorded in the NEB. These phenomena were associated with the trough in the NEB created under the influence of TD in HN. The current from TD in NH converges with current from extratropical cyclone trough of the Southern Hemisphere at the high levels over the NEB. This convergence created sinking, contributed to the accumulation of moisture at the low levels and the formation of adverse phenomena. The results confirm the effect of TD in NH on the weather at the NEB and important for weather forecast in this region.
DOI: 10.6084/m9.figshare.14282096
title: A Conceptual Model of Probability for Determining Population Vulnerability to Climate

description: Abstract The population's vulnerability assessment is an analysis of the expected impacts, risk modeling, exposure, sensitivity and lack of adaptability of a specific region or sector to the effects of extreme weather events. The vulnerability encompasses a variety of concepts including sensitivity or susceptibility to harm and a lack of ability to cope and adapt. One way to analyze these very different aspects is through a stochastic process, such as conditional probability. In this article, a conceptual model is presented to assess the population's vulnerability to the climate, taking into account one of the susceptible regions of Brazil, the Northeast. The results show that the proposed indicator IVPopS presents the most vulnerable central semi-arid region, in addition to a detailed assessment in each component of the indicator. Production areas such as Petrolina-PE have high levels of risk (0,604), exposure (0,863), sensitivity (0,910), while the inability to adapt is low (0.002).
DOI: 10.6084/m9.figshare.14282093.v1
title: Influence of Tropical Disturbances on Severe weather phenomena of Stable Atmosphere Formation in Northeast Brazil

description: Abstract The main aim of this study is to analyze an impact of Tropical Disturbs (TD) in the Northern Hemisphere (NH), associated with Tropical Cyclones (TC), on adverse phenomena in Northeast Brazil (NEB) in 2013 - 2015, in order to improve the weather forecasting method in this area. Information about TC was obtained from the National Hurricane Center. Adverse phenomena were studied using METAR and SYNOP data. The synoptic analysis was based on the satellite images and maps of different variables. Reanalysis data from the European Center for Medium-Range Weather Forecasts were used. Nine TD were observed during the passage of TC. In the same period, fogs and mist with drizzle were recorded in the NEB. These phenomena were associated with the trough in the NEB created under the influence of TD in HN. The current from TD in NH converges with current from extratropical cyclone trough of the Southern Hemisphere at the high levels over the NEB. This convergence created sinking, contributed to the accumulation of moisture at the low levels and the formation of adverse phenomena. The results confirm the effect of TD in NH on the weather at the NEB and important for weather forecast in this region.
DOI: 10.6084/m9.figshare.14282098
title: Characteristics of Mesoscale Convective Complexes over Northeastern Brazil

description: Abstract The main purpose of this study was to analyze the Mesoscale Convective Complexes (MCC) physical characteristics over the Northeastern Brazil between 2008 to 2017. To create a short-term weather forecast, understanding and detailing of these systems is necessary. This is of great importance for the population, since MCC often cause adverse phenomena leading to socio-economic losses for the whole society. The MCC identification and all calculations of their physical characteristics were performed with the aid of an MCC automatic analysis and detection algorithm, based on the standards proposed by Maddox. METEOSAT satellites Infrared enhanced images were used for the processing algorithm. Sixty-five MCCs occurred mainly in the autumn and summer seasons were identified. MCC development started between late evening and early morning (between 00-03 UTC). An interval of approximately four hours was observed between genesis and maximum development, when MCC reach maximum extension area. The average coverage area of these MCCs was 120,000 km2, the largest of the reported cases had a total area of about 427,926 km2.
DOI: 10.6084/m9.figshare.14282098.v1
title: Characteristics of Mesoscale Convective Complexes over Northeastern Brazil

description: Abstract The main purpose of this study was to analyze the Mesoscale Convective Complexes (MCC) physical characteristics over the Northeastern Brazil between 2008 to 2017. To create a short-term weather forecast, understanding and detailing of these systems is necessary. This is of great importance for the population, since MCC often cause adverse phenomena leading to socio-economic losses for the whole society. The MCC identification and all calculations of their physical characteristics were performed with the aid of an MCC automatic analysis and detection algorithm, based on the standards proposed by Maddox. METEOSAT satellites Infrared enhanced images were used for the processing algorithm. Sixty-five MCCs occurred mainly in the autumn and summer seasons were identified. MCC development started between late evening and early morning (between 00-03 UTC). An interval of approximately four hours was observed between genesis and maximum development, when MCC reach maximum extension area. The average coverage area of these MCCs was 120,000 km2, the largest of the reported cases had a total area of about 427,926 km2.
DOI: 10.6084/m9.figshare.14282101
title: Nutrients Load Estimation in a Regulated Streamflow Estuary: The São Francisco Estuary (NE/Brazil)

description: Abstract This study aimed to estimate the nutrients concentration variability in the São Francisco estuary from observed data during the summer and winter seasons of 2014 and to assess the influence of outflow discharges, circulation and precipitation on nutrients fluxes exchange. The marginal difference in the streamflow (1,160 m3/s - summer; 1,260 m3/s - winter) reflected the small role of the river discharge on the variability of the nutrients load. The increase in the sediments load from February (13189.70 T/month) to July (36088.56 T/month) revealed that high precipitation (153.6 mm - winter; 37.6 mm - summer) and internal circulation might have contributed to enhancing the sediment budge towards the estuary mouth. The strong current velocity in July (~0.9 m/s) revealed more potential to export estuarine waters towards the coast when compared to ~0.7 m/s (February). The concentrations and nutrients load were higher during the winter season led by phosphate (3.70 μgL-1) and NID (83.64 μg L-1), against (1.38 μgL-1 and 30.70 μgL-1 - summer), except for silicates with 4.20 mgL-1 (summer) and 3.59 mgL-1 (winter). Despite the active control of outflows, the internal circulation, followed by local precipitation, are considered the main mechanisms behind the increased nutrients load within the estuary.
DOI: 10.6084/m9.figshare.14282101.v1
title: Nutrients Load Estimation in a Regulated Streamflow Estuary: The São Francisco Estuary (NE/Brazil)

description: Abstract This study aimed to estimate the nutrients concentration variability in the São Francisco estuary from observed data during the summer and winter seasons of 2014 and to assess the influence of outflow discharges, circulation and precipitation on nutrients fluxes exchange. The marginal difference in the streamflow (1,160 m3/s - summer; 1,260 m3/s - winter) reflected the small role of the river discharge on the variability of the nutrients load. The increase in the sediments load from February (13189.70 T/month) to July (36088.56 T/month) revealed that high precipitation (153.6 mm - winter; 37.6 mm - summer) and internal circulation might have contributed to enhancing the sediment budge towards the estuary mouth. The strong current velocity in July (~0.9 m/s) revealed more potential to export estuarine waters towards the coast when compared to ~0.7 m/s (February). The concentrations and nutrients load were higher during the winter season led by phosphate (3.70 μgL-1) and NID (83.64 μg L-1), against (1.38 μgL-1 and 30.70 μgL-1 - summer), except for silicates with 4.20 mgL-1 (summer) and 3.59 mgL-1 (winter). Despite the active control of outflows, the internal circulation, followed by local precipitation, are considered the main mechanisms behind the increased nutrients load within the estuary.
DOI: 10.6084/m9.figshare.14282102
title: Climate Scenarios and Cotton Yield in Northeast Brazil. Part I: Calibration and Validation of the Agrometeorological Model

description: Abstract This research aimed to calibrate and validate an agrometeorological model of penalization for water deficit applied to the herbaceous cotton culture in 23 municipalities in the Northeast region. The results showed different scenarios, with yield varying from extremely low, with an annual average of less than 500 kg/ha, to extremely high, with an annual average of more than 3500 kg/ha. The calibration process of the agrometeorological model took into account the level of maximum technological productivity, estimated from a statistical adjustment based on the data series of the actual observed yield, allowing satisfactory simulations of the values made available by IBGE. In municipalities with very low yield up to 500 kg/ha, the average observed (AOY) and simulated (ASY) yield was 333 and 361 kg/ha with mean absolute error (MAE) of ± 56 kg/ha, for municipalities with yield between 500 and 1000 kg/ha, the AOY and ASY was 774 and 814 kg/ha with MEA of ± 172 kg/ha, in the municipalities with median yield between 1000 and 2000 kg/ha, the AOY and ASY was 1358 and 1400 kg/ha with MAE of ± 198 kg/ha, and in municipalities with high yield, above 2000 kg/ha, the AOY and ASY was 3233 and 3357 kg/ha with MAE of ± 319 kg/ha, respectively.
DOI: 10.6084/m9.figshare.14282105
title: Dynamic Downscaling Using the RegCM Model for Different Initializations Using CFSv2 Data

description: Abstract The main objective of this study was to evaluate the regional climate forecasts of precipitation over Brazil during the winter season of 2018 through the RegCM4.7 model. It was used with different initializations, both spatial and in five specific areas. To emit alerts of possible below/above climate normal anomalies is necessary the verification these model abilities in predicting precipitation. The RegCM4.7 model was used with Global Climate Forecast System Version 2 global model data. The forecast quality was evaluated qualitatively and quantitatively, comparing its results with Climate Prediction Center (CPC) analysis data. The RegCM4.7 model was able to predict precipitation consistently a few months in advance for the june, july and august quarter (JJA), with minor mistakes over the northeastern and southeastern Brazil. However, the biggest errors were identified over the northern and southern regions. Prediction correlations were less than 0.8 during every experiments and subdomains, except for the Northeast region that presented the highest correlation values. In general, it stands out that RegCM4.7 was able to predict the spatial distribution of precipitation in advance over every domain, but with a tendency to underestimate what was observed.
DOI: 10.6084/m9.figshare.14282102.v1
title: Climate Scenarios and Cotton Yield in Northeast Brazil. Part I: Calibration and Validation of the Agrometeorological Model

description: Abstract This research aimed to calibrate and validate an agrometeorological model of penalization for water deficit applied to the herbaceous cotton culture in 23 municipalities in the Northeast region. The results showed different scenarios, with yield varying from extremely low, with an annual average of less than 500 kg/ha, to extremely high, with an annual average of more than 3500 kg/ha. The calibration process of the agrometeorological model took into account the level of maximum technological productivity, estimated from a statistical adjustment based on the data series of the actual observed yield, allowing satisfactory simulations of the values made available by IBGE. In municipalities with very low yield up to 500 kg/ha, the average observed (AOY) and simulated (ASY) yield was 333 and 361 kg/ha with mean absolute error (MAE) of ± 56 kg/ha, for municipalities with yield between 500 and 1000 kg/ha, the AOY and ASY was 774 and 814 kg/ha with MEA of ± 172 kg/ha, in the municipalities with median yield between 1000 and 2000 kg/ha, the AOY and ASY was 1358 and 1400 kg/ha with MAE of ± 198 kg/ha, and in municipalities with high yield, above 2000 kg/ha, the AOY and ASY was 3233 and 3357 kg/ha with MAE of ± 319 kg/ha, respectively.
DOI: 10.6084/m9.figshare.14282105.v1
title: Dynamic Downscaling Using the RegCM Model for Different Initializations Using CFSv2 Data

description: Abstract The main objective of this study was to evaluate the regional climate forecasts of precipitation over Brazil during the winter season of 2018 through the RegCM4.7 model. It was used with different initializations, both spatial and in five specific areas. To emit alerts of possible below/above climate normal anomalies is necessary the verification these model abilities in predicting precipitation. The RegCM4.7 model was used with Global Climate Forecast System Version 2 global model data. The forecast quality was evaluated qualitatively and quantitatively, comparing its results with Climate Prediction Center (CPC) analysis data. The RegCM4.7 model was able to predict precipitation consistently a few months in advance for the june, july and august quarter (JJA), with minor mistakes over the northeastern and southeastern Brazil. However, the biggest errors were identified over the northern and southern regions. Prediction correlations were less than 0.8 during every experiments and subdomains, except for the Northeast region that presented the highest correlation values. In general, it stands out that RegCM4.7 was able to predict the spatial distribution of precipitation in advance over every domain, but with a tendency to underestimate what was observed.
DOI: 10.6084/m9.figshare.14282107
title: Erosivity Estimation and Spatialization in Climatic Mesoregions in the State of Alagoas

description: Abstract The lack of rainfall data in Alagoas, similar in many regions of the country, makes them use regression equations obtained in other regions of Brazil to calculate the R factor of the Universal Soil Loss Equation. The study aims to: i) define an equation to estimate rainfall erosivity based on the EI30 index and the rain coefficient Rc, ii) validate the data imputation method for rain and erosivity and iii) spatially estimate erosivity in rainy, dry and transition periods to Alagoas. Monthly rainfall data from 54 stations in the period (1960-2016) were used. The equation used showed a significant correlation between the observed and estimated data, according to the coefficients r (93%), R2 (87%) and RMSE (775.2 MJ.mm.ha−1.h−1). The Ordinary Kriging was the best spatial interpolator. The monthly isoerosivity showed that the highest EI30 rates occurred between April and July, a period coinciding with the rainy season in the state. In annual erosivity, the largest records are located in eastern Alagoas, close to the coast. Highlight for the stations Satuba, Maceió, São Luiz do Quitunde and Flexeiras, categorized between moderate and strong. These results will assist in planning conservation practices, especially in areas of vulnerability.
DOI: 10.6084/m9.figshare.14282107.v1
title: Erosivity Estimation and Spatialization in Climatic Mesoregions in the State of Alagoas

description: Abstract The lack of rainfall data in Alagoas, similar in many regions of the country, makes them use regression equations obtained in other regions of Brazil to calculate the R factor of the Universal Soil Loss Equation. The study aims to: i) define an equation to estimate rainfall erosivity based on the EI30 index and the rain coefficient Rc, ii) validate the data imputation method for rain and erosivity and iii) spatially estimate erosivity in rainy, dry and transition periods to Alagoas. Monthly rainfall data from 54 stations in the period (1960-2016) were used. The equation used showed a significant correlation between the observed and estimated data, according to the coefficients r (93%), R2 (87%) and RMSE (775.2 MJ.mm.ha−1.h−1). The Ordinary Kriging was the best spatial interpolator. The monthly isoerosivity showed that the highest EI30 rates occurred between April and July, a period coinciding with the rainy season in the state. In annual erosivity, the largest records are located in eastern Alagoas, close to the coast. Highlight for the stations Satuba, Maceió, São Luiz do Quitunde and Flexeiras, categorized between moderate and strong. These results will assist in planning conservation practices, especially in areas of vulnerability.
DOI: 10.6084/m9.figshare.14282110.v1
title: Impact of Climate Change on Sugarcane Yield in Maceió

description: Abstract In this study, a statistical downscaling model (SDSM) based on the analogous methodology was used to project future patterns of precipitation and temperature in the city of Maceió, east coast of northeastern Brazil (9.7° S; 35.7° W; 64.5m), and to evaluate its impacts on sugar cane yield. Historical observed data were used for downscaling precipitation and temperature using different global climate models (CanESM2, CNRM-CM5, IPSL-CM5A-MR, GFDL-ESM2M, MIROC-ESM, MPI-ESM-MR, and NorESM1-M) in relation to the reference period (1961-1990), and then for future scenarios from 2021 to 2080. The data were analysed in a ten days period, the same time step as the agrometeorological model used for culture. Contrary to what was expected, the combination of reduced rainfall and increased evapotranspiration in future scenarios did not decrease the estimate of yield, with an increase forecast. This effect can be attributed to the fact that the reduction in predicted rainfall, which was more pronounced in the rainy season, was not decisive for the decrease in yield, since in most MCGs there is a forecast of increased rainfall in the dry period from September to December, which is crucial for the initial growth of the crop, which has a planting schedule from the first ten-day period of September.
DOI: 10.6084/m9.figshare.14282110
title: Impact of Climate Change on Sugarcane Yield in Maceió

description: Abstract In this study, a statistical downscaling model (SDSM) based on the analogous methodology was used to project future patterns of precipitation and temperature in the city of Maceió, east coast of northeastern Brazil (9.7° S; 35.7° W; 64.5m), and to evaluate its impacts on sugar cane yield. Historical observed data were used for downscaling precipitation and temperature using different global climate models (CanESM2, CNRM-CM5, IPSL-CM5A-MR, GFDL-ESM2M, MIROC-ESM, MPI-ESM-MR, and NorESM1-M) in relation to the reference period (1961-1990), and then for future scenarios from 2021 to 2080. The data were analysed in a ten days period, the same time step as the agrometeorological model used for culture. Contrary to what was expected, the combination of reduced rainfall and increased evapotranspiration in future scenarios did not decrease the estimate of yield, with an increase forecast. This effect can be attributed to the fact that the reduction in predicted rainfall, which was more pronounced in the rainy season, was not decisive for the decrease in yield, since in most MCGs there is a forecast of increased rainfall in the dry period from September to December, which is crucial for the initial growth of the crop, which has a planting schedule from the first ten-day period of September.
DOI: 10.6084/m9.figshare.14282117
title: Applicability of the MACD Technical Indicator to the Predictability of the Annual Average Flow of Paraná River

description: Abstract This article assesses the applicability and effectiveness of the statistical tool “Convergence and Divergence of Moving Averages” (MACD) to the predictability of the average annual flow of the Paraná River measured in the city of Corrientes-Argentina, with a time span of 100 years. This technique is widely used in the financial market for forecasting trends and reversals in commodities and stock prices. Given the versatile nature of this technique, its parameters were easily adapted to be implemented in this study. The periods assigned to the exponential moving averages (EMA), an inherent parameter of the oscillator, allude to astronomical cycles that produce effects on the climatological variable in the addressed timescale, namely, the Schwabe Solar Cycle, with a periodicity of 11.2 years, the Lunar Nodal Cycle, of 18.6 years, and the Apsidal Lunar Cycle, of 8.85 years. There is a growing scientific understanding that such astronomical cyclical parameters do influence the terrestrial climate, especially via the modulation of ocean-atmospheric oscillations of global scale, such as the Pacific Decadal Oscillation (ODP) and El Niño-Oscilação Sul (ENOS), which are known to be related to the variable in study, which, in turn, is responsive to the rainfall conditions that supply water to two of the most important rivers in the La Plata basin: Paraná and Uruguay. Specific properties of MACD obtained considerable performance in predicting trends of increase/decrease in several periods of that centennial data series of river flow. The use of MACD for other climate variables, such as rainfall, Sea Level Pressure and Sea Surface Temperature, is highly encouraged, in order to consummate it as an additional tool to improve confidence in climate prediction.