cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.6084/m9.figshare.14282132.v1
title: Climate Change Scenarios for the Northeast Region of Brazil through the Statistical Downscaling Technique

description: Abstract The impact of climate change on precipitation and maximum and minimum temperatures patterns in the Northeast region of Brazil is investigated based on the mean results of four global climate models, ECHAM5-OM from Germany, HADGEM2-ES from the UK, BCM2 from Norway and the CNRM-CM3 of France, for two scenarios of greenhouse gas emissions, A1B and A2, that had their future projections regionalized for the period 2021-2080 using the statistical downscaling model. The ability of the models to simulate present climate conditions was checked for the 1961-1990 control period, presenting very satisfactory results, and validated for the period 1991-2000. The analogues method was employed to perform statistical downscaling and to find predictor-prediting relationships. The results point to a significant reduction in rainfall in the respective rainy periods of the northeastern subregions, and the highest temperatures increase in the first semester, with a tendency to decrease in large areas of the northern Northeast sector in the second semester, mainly for scenario A2. For the minimum temperatures the results show a tendency of increase in all the year with highlight for the winter months.
DOI: 10.6084/m9.figshare.14282134.v1
title: Climate Scenarios and Cotton Yield in Northeast Brazil. Part II: Simulation for 2020 to 2080

description: Abstract This paper had as its primary objective the generation of future climatic scenarios and the evaluation of impacts over the productivity of upland cotton through an agrometeorological model, when compared to the current productivity observed. A statistical downscaling was used to obtain the future series of meteorological variables needed for the calculation of productivity, obtained with an agrometeorological model appropriately calibrated for the reality of cotton in the semi-arid region of Northeast Brazil. The time series of the meteorological variables had their flaws properly completed and went through a rigorous quality control system. The future projections calculated for the climatic scenarios A1B and A2, of the models ECHAM5-OM and HadGEM2-ES were unanimous in pointing out the significant reduction in rainfall and temperature rising. The evapotranspiration, consequently, also presents an upward trend for the future horizon studied, from 2020 to 2080. As impact for the cotton crop, is predicted, for the 23 studied municipalities of the northeast semi-arid, a significant reduction in productivity, which can be reduced to approximately half of the current observed productivity.
DOI: 10.6084/m9.figshare.14282137.v1
title: Alternative Method of Agroclimatic Zoning of Maize for the State of Alagoas

description: The cultivation of corn under a rainfed regime along the state of Alagoas is deeply influenced by climate variability, especially when considering the recurring droughts affecting the entire Northeast region of Brazil. One way of minimizing the risk of losses is establishing a climate window that is optimal for the sowing time. This study resorted to an agrometeorological model of damages by water deficit to simulate the productivity in every municipality of Alagoas from 1980 to 2015. The high correlation between simulations and observations, and the low absolute mean error for reference stations validated the model. There are different windows favourable to planting, shorter in the hinterland during the month of April, between the third ten days of March and the third ten days of May in the wild, and between the first ten days of March and the second ten days of June in eastern Alagoas. On average, relative productivity losses are about 45% in “Sertão”, 40-45% in “Agreste”, and around 20% in the coast. Such results can aid the Brazilian Ministry of Agriculture, Livestock, and Supply, in the elaboration of its Agricultural Climate Risk Zoning of Crops, potentially resulting in a more considerate calendar for corn sowing in Alagoas.
DOI: 10.6084/m9.figshare.14282140
title: Impact of ENSO on Variability of the Total Ozone Column Over the Northeast Region of Brazil - Part 2: La Niña Canonical and Modoki

description: Abstract This study presents a second stage of the spatio-temporal assessment of long-term trends in ozone concentrations in Northeast Brazil (NEB) under the influence of the El Niño - South Oscillation (ENSO) with emphasis on the La Niña phase (Canonical and Modoki). The objective is to analyze the annual variation and the effects of this phenomenon in the Total Ozone Column (TOC) over the NEB, between 1997 and 2018. The data come from remote sensing, generated by the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) sensors, made available by National Aeronautics and Space Administration (NASA), and analyzed using mean, anomaly values and hovmoller diagrams. It was found that La Niña events cause, predominantly, an increase in the concentration of ozone over the NEB. During periods of action of this mode of variability, the deceleration of Brewer-Dobson circulation (CBD) is caused by the intensification of trade winds, generating ozone accumulation in the tropical region. Between the two modalities, Modoki show this effect more intensified. The highest (+6.5) and lowest (-3.0) average monthly anomaly values obtained occurred during his performance, recorded in the northern region of NEB in July and September, respectively.
DOI: 10.6084/m9.figshare.14282140.v1
title: Impact of ENSO on Variability of the Total Ozone Column Over the Northeast Region of Brazil - Part 2: La Niña Canonical and Modoki

description: Abstract This study presents a second stage of the spatio-temporal assessment of long-term trends in ozone concentrations in Northeast Brazil (NEB) under the influence of the El Niño - South Oscillation (ENSO) with emphasis on the La Niña phase (Canonical and Modoki). The objective is to analyze the annual variation and the effects of this phenomenon in the Total Ozone Column (TOC) over the NEB, between 1997 and 2018. The data come from remote sensing, generated by the Total Ozone Mapping Spectrometer (TOMS) and Ozone Monitoring Instrument (OMI) sensors, made available by National Aeronautics and Space Administration (NASA), and analyzed using mean, anomaly values and hovmoller diagrams. It was found that La Niña events cause, predominantly, an increase in the concentration of ozone over the NEB. During periods of action of this mode of variability, the deceleration of Brewer-Dobson circulation (CBD) is caused by the intensification of trade winds, generating ozone accumulation in the tropical region. Between the two modalities, Modoki show this effect more intensified. The highest (+6.5) and lowest (-3.0) average monthly anomaly values obtained occurred during his performance, recorded in the northern region of NEB in July and September, respectively.
DOI: 10.6084/m9.figshare.14282141
title: Monthly Streamflow Forecast in the Xingu River Basin - Eastern Amazon

description: Abstract Empirical rainfall-streamflow models have been increasingly used in recent decades, due to the unavailability of input data from conceptual models, and the reliability, speed, and less complexity of these models. In this context, the Principal Component Regression technique (PCR) to simulate the monthly average streamflow of eight river stations in the Xingu River Basin (XRB) was applied, which belongs to the large Amazon basin. The XRB has the Belo Monte hydroelectric plant, as well as important areas of environmental preservation. The degree of relationship between rainfall and streamflow, input and response of the rainfall-streamflow model based on PCR is shows in the research and the respective degrees of lag with predictive efficiency. The PCR showed good results in the simulation of the monthly streamflow in all the selected stations, characterizing well the dynamics of the time series with excellent results in the dry periods (May to October) and a tendency to slightly underestimate in the rainy periods (November to April). These results, using the rainfall observed for streamflow simulation in the XRB, allow us to conclude that a good climate forecasting system for seasonal rainfall can infer an important predictive degree for streamflow up to three months in advance.
DOI: 10.6084/m9.figshare.14282141.v1
title: Monthly Streamflow Forecast in the Xingu River Basin - Eastern Amazon

description: Abstract Empirical rainfall-streamflow models have been increasingly used in recent decades, due to the unavailability of input data from conceptual models, and the reliability, speed, and less complexity of these models. In this context, the Principal Component Regression technique (PCR) to simulate the monthly average streamflow of eight river stations in the Xingu River Basin (XRB) was applied, which belongs to the large Amazon basin. The XRB has the Belo Monte hydroelectric plant, as well as important areas of environmental preservation. The degree of relationship between rainfall and streamflow, input and response of the rainfall-streamflow model based on PCR is shows in the research and the respective degrees of lag with predictive efficiency. The PCR showed good results in the simulation of the monthly streamflow in all the selected stations, characterizing well the dynamics of the time series with excellent results in the dry periods (May to October) and a tendency to slightly underestimate in the rainy periods (November to April). These results, using the rainfall observed for streamflow simulation in the XRB, allow us to conclude that a good climate forecasting system for seasonal rainfall can infer an important predictive degree for streamflow up to three months in advance.
DOI: 10.6084/m9.figshare.14282143
title: Spatial-Temporal of Fire Foci in the Metropolitan Region of Maceió

description: Abstract This work evaluated the burnings and fires in the Maceió Metropolitan Region (MMR) via Fire Foci (FF) data available in BQueimadas for the period 1999 to 2019. The FF time series was submitted to descriptive and multivariate statistical analysis (Cluster Analysis - CA) together with the Vegetation Health Index (VHI) applied to the fire foci in the municipalities of MMR. Based on the hierarchical grouping, three homogeneous groups (G1, G2 and G3) of FF were identified and the municipality of Atalaia was not grouped (NA). Groups G1 (145.5 ± 7.77 FF) and G2 (28.5 ± 44 FF) presented similarities regarding the seasonality of the foci. While Group G3 (91 ± 7.07 FF), which includes the capital Maceió, presented irregular distribution spatially. All the variability of the FF is associated with the agricultural activities in the MMR. But also, the negligence of atheism of flammable material on the vegetation propitiates an increase of fires and burns, mainly in the sugarcane harvest.
DOI: 10.6084/m9.figshare.14282143.v1
title: Spatial-Temporal of Fire Foci in the Metropolitan Region of Maceió

description: Abstract This work evaluated the burnings and fires in the Maceió Metropolitan Region (MMR) via Fire Foci (FF) data available in BQueimadas for the period 1999 to 2019. The FF time series was submitted to descriptive and multivariate statistical analysis (Cluster Analysis - CA) together with the Vegetation Health Index (VHI) applied to the fire foci in the municipalities of MMR. Based on the hierarchical grouping, three homogeneous groups (G1, G2 and G3) of FF were identified and the municipality of Atalaia was not grouped (NA). Groups G1 (145.5 ± 7.77 FF) and G2 (28.5 ± 44 FF) presented similarities regarding the seasonality of the foci. While Group G3 (91 ± 7.07 FF), which includes the capital Maceió, presented irregular distribution spatially. All the variability of the FF is associated with the agricultural activities in the MMR. But also, the negligence of atheism of flammable material on the vegetation propitiates an increase of fires and burns, mainly in the sugarcane harvest.
DOI: 10.6084/m9.figshare.14282144
title: Heat and Freshness Islands Analysis Using Digital Image Processing - Case Study City of São Paulo/SP

description: Abstract Brazilian cities have been growing in a disorderly manner and undergoing a disturbed anthropogenic process, which severely transforms the local atmosphere, influencing the quality of life of society. The purpose of this research is to analyze the temperature variation through the use of remote sensing, seeking to identify heat and freshness islands, their origins and the space-behavioral variation, having as study area the Municipality of São Paulo, a large city with population density of 7,398.26 inhabitants/km2 and more than 12,000,000 inhabitants. We opted to use Landsat 5 satellite images and SEBAL algorithm methodology for surface temperature calculation. The results show that the surface temperature variation has been increasing over the years, the city of São Paulo, the presence of large industrial zones, the disordered urban growth, the presence of soil sealing through asphalt coating, are some of the factors that contribute to the emergence of heat islands. It was also evidenced the presence of freshness zones, most of them in wooded areas, which contributes to reducing the temperature and improving the living conditions of the population.
DOI: 10.6084/m9.figshare.14282144.v1
title: Heat and Freshness Islands Analysis Using Digital Image Processing - Case Study City of São Paulo/SP

description: Abstract Brazilian cities have been growing in a disorderly manner and undergoing a disturbed anthropogenic process, which severely transforms the local atmosphere, influencing the quality of life of society. The purpose of this research is to analyze the temperature variation through the use of remote sensing, seeking to identify heat and freshness islands, their origins and the space-behavioral variation, having as study area the Municipality of São Paulo, a large city with population density of 7,398.26 inhabitants/km2 and more than 12,000,000 inhabitants. We opted to use Landsat 5 satellite images and SEBAL algorithm methodology for surface temperature calculation. The results show that the surface temperature variation has been increasing over the years, the city of São Paulo, the presence of large industrial zones, the disordered urban growth, the presence of soil sealing through asphalt coating, are some of the factors that contribute to the emergence of heat islands. It was also evidenced the presence of freshness zones, most of them in wooded areas, which contributes to reducing the temperature and improving the living conditions of the population.
DOI: 10.6084/m9.figshare.14282147
title: Influence of Climatic Changes on Agricultural Land Suitability Potential for Wheat Cultivation in the Guarapuava Microregion, Southern Brazil

description: Abstract Evidence that global climate change will occur as a result of increased concentrations of greenhouse gases has been increasingly consistent and accepted by the international scientific community. This study aimed to evaluate climate change estimates in the Guarapuava microregion in the state of Paraná, analyzing the impacts on the wheat crop, using modeling for future scenarios and comparing with a base scenario of the past. Mathematical adequacy models were adjusted using Multiple Criteria Analysis (MCA) and Analytical Hierarchy Process (AHP), with the purpose of evaluating the possible impacts of climate changes on wheat crop, using the climatic scenarios RCP4.5 and RCP8.5 (IPCC) for the calculation of the Land suitability potential in the Guarapuava-PR microregion. The results indicate that the factor of greatest impact for the reduction of the agricultural aptitude index of the wheat in the next 30 years is the projection of increase of the average monthly temperature by approximately 1.5 to 2 °C during the development cycle of the crop in the field.
DOI: 10.6084/m9.figshare.14282147.v1
title: Influence of Climatic Changes on Agricultural Land Suitability Potential for Wheat Cultivation in the Guarapuava Microregion, Southern Brazil

description: Abstract Evidence that global climate change will occur as a result of increased concentrations of greenhouse gases has been increasingly consistent and accepted by the international scientific community. This study aimed to evaluate climate change estimates in the Guarapuava microregion in the state of Paraná, analyzing the impacts on the wheat crop, using modeling for future scenarios and comparing with a base scenario of the past. Mathematical adequacy models were adjusted using Multiple Criteria Analysis (MCA) and Analytical Hierarchy Process (AHP), with the purpose of evaluating the possible impacts of climate changes on wheat crop, using the climatic scenarios RCP4.5 and RCP8.5 (IPCC) for the calculation of the Land suitability potential in the Guarapuava-PR microregion. The results indicate that the factor of greatest impact for the reduction of the agricultural aptitude index of the wheat in the next 30 years is the projection of increase of the average monthly temperature by approximately 1.5 to 2 °C during the development cycle of the crop in the field.
DOI: 10.6084/m9.figshare.14282149
title: Electrical Activity Associated with Hurricane Otto (2016) in the Caribbean Sea and in the Central American Dry Corridor

description: Abstract Otto (2016) is the first hurricane in the documented tropical cyclone history to have directly reached Costa Rica. This work analyses the electrical discharges (ED) associated with Otto in November 2016 during its trajectory from the Caribbean to the Pacific, using data from the World Wide Lightning Location Network; which constitutes a pioneering research in the Central America region. Otto ED captured very well Ottoos intensification and degradation phases, which as a variable could be parametrized in numerical models to improve the knowledge and evolution of these systems. Otto presented three ED peaks during each one of the categories it attained; the last one during hurricane category 3 (Saffir-Simpson scale) just prior to make landfall between Costa Rica and Nicaragua. The region with most ED moved from the near center of the system to its external region in pace with the hurricane intensification. When Otto reached category 3, the maxima of ED was observed in Otto's external bands (250-300 km). During Otto's evolution ED maximum were observed to be related to cloud top temperatures of less than -70 °C.
DOI: 10.6084/m9.figshare.14282149.v1
title: Electrical Activity Associated with Hurricane Otto (2016) in the Caribbean Sea and in the Central American Dry Corridor

description: Abstract Otto (2016) is the first hurricane in the documented tropical cyclone history to have directly reached Costa Rica. This work analyses the electrical discharges (ED) associated with Otto in November 2016 during its trajectory from the Caribbean to the Pacific, using data from the World Wide Lightning Location Network; which constitutes a pioneering research in the Central America region. Otto ED captured very well Ottoos intensification and degradation phases, which as a variable could be parametrized in numerical models to improve the knowledge and evolution of these systems. Otto presented three ED peaks during each one of the categories it attained; the last one during hurricane category 3 (Saffir-Simpson scale) just prior to make landfall between Costa Rica and Nicaragua. The region with most ED moved from the near center of the system to its external region in pace with the hurricane intensification. When Otto reached category 3, the maxima of ED was observed in Otto's external bands (250-300 km). During Otto's evolution ED maximum were observed to be related to cloud top temperatures of less than -70 °C.
DOI: 10.6084/m9.figshare.14282152
title: Wind Speed Forecast Comparison Using WRF Model and Artificial Neural Network

description: Abstract The aim of this work is to improve wind speed forecasting, using the atmospheric mesoscale model Weather Research and Forecasting (WRF) and Artificial Neural Network (ANN) nonlinear auto regressive (with external input - NARX and without external input - NAR). The accuracy of the predictions was measured with observed data (OBS) measured every 10 min in an anemometric tower 50 m high, located in Craíbas (dry region of Alagoas State). The univariate statistics indicated that the forecasting represented well the wind temporal evolution in the studied period (April 2015). The average, maximum and minimum OBS speeds were 5.26 m.s−1, 12,29 m.s−1 and 0,01 m.s−1. Predictions ranged from 5.18 m.s−1 to 5.41 m.s−1 for the average, 11.58 m.s−1 to 13.92 m.s−1 for the maximum and 0.01 m.s−1 to 0.36 m.s−1 for the minimum. On the bivariate analysis, the statistical metrics used resulted in the following: Mean Error (ME) from -0.31 m.s−1 to 0.04 m.s−1; The root mean square error (RMSE) from 1.14 m.s−1 to 1.27 m.s−1; Mean Absolute Percentage Error (MAPE) from 22 to 23%; Correlation coefficient from 0.63 to 0.72. These results, despite considering a short period of data, indicate the potential for applying ANN and WRF in forecasting wind speed.
DOI: 10.6084/m9.figshare.14282152.v1
title: Wind Speed Forecast Comparison Using WRF Model and Artificial Neural Network

description: Abstract The aim of this work is to improve wind speed forecasting, using the atmospheric mesoscale model Weather Research and Forecasting (WRF) and Artificial Neural Network (ANN) nonlinear auto regressive (with external input - NARX and without external input - NAR). The accuracy of the predictions was measured with observed data (OBS) measured every 10 min in an anemometric tower 50 m high, located in Craíbas (dry region of Alagoas State). The univariate statistics indicated that the forecasting represented well the wind temporal evolution in the studied period (April 2015). The average, maximum and minimum OBS speeds were 5.26 m.s−1, 12,29 m.s−1 and 0,01 m.s−1. Predictions ranged from 5.18 m.s−1 to 5.41 m.s−1 for the average, 11.58 m.s−1 to 13.92 m.s−1 for the maximum and 0.01 m.s−1 to 0.36 m.s−1 for the minimum. On the bivariate analysis, the statistical metrics used resulted in the following: Mean Error (ME) from -0.31 m.s−1 to 0.04 m.s−1; The root mean square error (RMSE) from 1.14 m.s−1 to 1.27 m.s−1; Mean Absolute Percentage Error (MAPE) from 22 to 23%; Correlation coefficient from 0.63 to 0.72. These results, despite considering a short period of data, indicate the potential for applying ANN and WRF in forecasting wind speed.
DOI: 10.6084/m9.figshare.14282155
title: Foehn-like Wind in the Mountains of Southeastern Brazil as Seen by the Eta Model Simulation

description: Abstract The present study gives evidence of the occurrence of foehn-like wind on the eastern slopes of the mountains at Southeastern Brazil. A particular case was detected based on observational evidence on 4 July 2015 near the city of Cruzeiro, state of Sao Paulo, on the Serra da Mantiqueira mountains. Results obtained from numerical simulations are consistent with the foehn wind occurrence deducted from the analysis of regional patterns and time series of selected meteorological parameters.
DOI: 10.6084/m9.figshare.14282155.v1
title: Foehn-like Wind in the Mountains of Southeastern Brazil as Seen by the Eta Model Simulation

description: Abstract The present study gives evidence of the occurrence of foehn-like wind on the eastern slopes of the mountains at Southeastern Brazil. A particular case was detected based on observational evidence on 4 July 2015 near the city of Cruzeiro, state of Sao Paulo, on the Serra da Mantiqueira mountains. Results obtained from numerical simulations are consistent with the foehn wind occurrence deducted from the analysis of regional patterns and time series of selected meteorological parameters.