The goal was to perform the filling,consistency and processing of the rainfall time series data from 1943 to 2013 in five regions of the state.Data were obtained from several sources(ANA,CPRM,INMET,SERLA and LIGHT),to...The goal was to perform the filling,consistency and processing of the rainfall time series data from 1943 to 2013 in five regions of the state.Data were obtained from several sources(ANA,CPRM,INMET,SERLA and LIGHT),totaling 23 stations.The time series(raw data)showed failures that were filled with data from TRMM satellite via 3B43 product,and with the climatological normal from INMET.The 3B43 product was used from 1998 to 2013 and the climatological normal over the 1947-1997 period.Data were submitted to descriptive and exploratory analysis,parametric tests(Shapiro-Wilks and Bartlett),cluster analysis(CA),and data processing(Box Cox)in the 23 stations.Descriptive analysis of the raw data consistency showed a probability of occurrence above 75%(high time variability).Through the CA,two homogeneous rainfall groups(G1 and G2)were defined.The group G1 and G2 represent 77.01%and 22.99%of the rainfall occurring in SRJ,respectively.Box Cox Processing was effective in stabilizing the normality of the residuals and homogeneity of variance of the monthly rainfall time series of the five regions of the state.Data from 3B43 product and the climatological normal can be used as an alternative source of quality data for gap filling.展开更多
Background The Cerrado is the most biodiverse savanna and maintains other biomes.Aware of its significance,this paper evaluated the Brazilian Cerrado’s climatic,environmental,and socioeconomic aspects using remote se...Background The Cerrado is the most biodiverse savanna and maintains other biomes.Aware of its significance,this paper evaluated the Brazilian Cerrado’s climatic,environmental,and socioeconomic aspects using remote sensing data and spatial statistics(correlation analysis and principal components analysis—PCA).Following the measures of sample adequacy(MSA)and Kaiser–Meyer–Olkin(KMO)tests,seventeen variables were evaluated.Results The MSA revealed that the dataset had a good quality(0.76),and nine variables were selected:elevation,evapotranspiration,active fires,Human Development Index(HDI),land use and land cover(LULC;shrubland and cropland/rainfed),rainfall(spring and autumn),and livestock.The correlation matrix indicated a positive(negative)association between HDI and autumn rainfall(HDI and active fires)with a value of 0.77(-0.55).The PCA results determined which three principal components(PC)were adequate for extracting spatial patterns,accounting for 68.02%of the total variance with respective values of 38.59%,16.89%,and 12.5%.Due to economic development and agribusiness,Cerrado’s northern(central,western,and southern)areas had negative(positive)score HDI values,as shown in PC1.Climatic(rainfall—spring and fall)and environmental(cropland/rainfed and shrubland)aspects dominated the PC2,with negative scores in northern and western portions due to the transition zone between Amazon and Cerrado biomes caused by rainfall variability.On the other hand,environmental aspects(LULC-shrubland and elevation)influenced the PC3;areas with high altitudes(>500 m)received a higher score.Conclusion Agricultural expansion substantially affected LULC,leading to deforestation-caused suppression of native vegetation.展开更多
Brazilian biomes are home to a significant portion of the world’s biodiversity,with a total of 14%of existing species and still concentrate 20%of the world’s water resources.However,changes in biomes have a direct i...Brazilian biomes are home to a significant portion of the world’s biodiversity,with a total of 14%of existing species and still concentrate 20%of the world’s water resources.However,changes in biomes have a direct impact on rainfall patterns and water recycling.Based on this,the objective was to evaluate the variability of rainfall in the four existing biomes in the Northeast Brazil(NEB)and their interaction with the ENSO climate variability mode and regional scale meteorological systems via CHELSA product.For this,monthly rainfall data were used from 1979 to 2013,with a spatial resolution of 1 km×1 km of the CHELSA product,and seasonal and annual rainfall patterns were extracted via boxplot.It was found that the rainy season in the Amazon,Caatinga and Cerrado biomes occurred between January and April,with varying intensities,except for the Atlantic Forest.Such seasonality patterns are associated with the NEB meteorological systems,with emphasis on ITCZ(all Biomes),UTCV(Amazon,Caatinga and Cerrado),Frontal Systems(extreme south of Caatinga,Cerrado and Atlantic Forest)and EWD/TWD in the(Atlantic Forest).In the inter-annual scale,the remarkable influence of ENSO was verified,mainly in the years 1983,1985,1989,1993,1998,2009 and 2012.It is noteworthy that 1985 was the wettest year of the period,with a surplus in all biomes,while the driest year differs between the Amazon(1983),Atlantic Forest and Caatinga(1993)and Cerrado(2012)biomes.The study via orbital product in NEB showed that anthropogenic processes and natural variability interfere with the forms of rain interception in the biomes and hence in rainfall patterns and water recycling in NEB.展开更多
The aims of this study were:i)to compare no-till areas in two municipalities located in different regions of Brazil,along with the influence on CO_(2)Flux and GPP,and ii)to verify the difference between environmental ...The aims of this study were:i)to compare no-till areas in two municipalities located in different regions of Brazil,along with the influence on CO_(2)Flux and GPP,and ii)to verify the difference between environmental factors followed by the trends of these variables regarding future scenarios(ARIMA time-series model number).The study was carried out in two areas with different latitudes in the municipalities of Sinop-MT and Passo Fundo-RS,both in Brazil.A time series of 19 years was performed with data acquired by remote sensing from the following satellites:i)Landsat-8(OLI and TIRS),and ii)TERRA/AQUA(MODIS).The results propound that the spectro-temporal variables are directly influenced by soil management and agricultural practices over the observation time,with a satisfactory correlation in future predictions of the variables for the next ten years,in which presented that the variation of GPP and albedo values for the two study sites would gradually increase until 2028 and the temperature remained constant between the range of its seasonality,and CO_(2)Flux tends to decrease in its seasonality,indicating a higher CO_(2) absorption.展开更多
基金The authors acknowledge the Agência Nacional deÁguas(ANA),Companhia de Pesquisa de Recursos Minerais(CPRM)Instituto Nacional de Meteorologia(INMET)+2 种基金SERLA Fundação Superintendência Estadual de Rios e Lagoas and Light Serviços de Eletricidade S/A by gently give in the data for composing the rainfall time seriesthe CAPES for granting Doctorate scholarshipThe second author thanks Brazilian National Council for Scientific and Technological Development(CNPq)for granting the Research Productivity Fellowship level 2(309681/2019-7).
文摘The goal was to perform the filling,consistency and processing of the rainfall time series data from 1943 to 2013 in five regions of the state.Data were obtained from several sources(ANA,CPRM,INMET,SERLA and LIGHT),totaling 23 stations.The time series(raw data)showed failures that were filled with data from TRMM satellite via 3B43 product,and with the climatological normal from INMET.The 3B43 product was used from 1998 to 2013 and the climatological normal over the 1947-1997 period.Data were submitted to descriptive and exploratory analysis,parametric tests(Shapiro-Wilks and Bartlett),cluster analysis(CA),and data processing(Box Cox)in the 23 stations.Descriptive analysis of the raw data consistency showed a probability of occurrence above 75%(high time variability).Through the CA,two homogeneous rainfall groups(G1 and G2)were defined.The group G1 and G2 represent 77.01%and 22.99%of the rainfall occurring in SRJ,respectively.Box Cox Processing was effective in stabilizing the normality of the residuals and homogeneity of variance of the monthly rainfall time series of the five regions of the state.Data from 3B43 product and the climatological normal can be used as an alternative source of quality data for gap filling.
基金The authors thank CNPq and CAPES(Financial Code 001)for their scholarship awardsThis article was developed during the Post-Doctorate Junior scholarship of no.161023/2019-3 granted by Brazilian National Council for Scientific and Technological Development(CNPq)at the first authorThe second author thanks CNPq for granting the Research Productivity Fellowship level 2(309681/2019-7).
文摘Background The Cerrado is the most biodiverse savanna and maintains other biomes.Aware of its significance,this paper evaluated the Brazilian Cerrado’s climatic,environmental,and socioeconomic aspects using remote sensing data and spatial statistics(correlation analysis and principal components analysis—PCA).Following the measures of sample adequacy(MSA)and Kaiser–Meyer–Olkin(KMO)tests,seventeen variables were evaluated.Results The MSA revealed that the dataset had a good quality(0.76),and nine variables were selected:elevation,evapotranspiration,active fires,Human Development Index(HDI),land use and land cover(LULC;shrubland and cropland/rainfed),rainfall(spring and autumn),and livestock.The correlation matrix indicated a positive(negative)association between HDI and autumn rainfall(HDI and active fires)with a value of 0.77(-0.55).The PCA results determined which three principal components(PC)were adequate for extracting spatial patterns,accounting for 68.02%of the total variance with respective values of 38.59%,16.89%,and 12.5%.Due to economic development and agribusiness,Cerrado’s northern(central,western,and southern)areas had negative(positive)score HDI values,as shown in PC1.Climatic(rainfall—spring and fall)and environmental(cropland/rainfed and shrubland)aspects dominated the PC2,with negative scores in northern and western portions due to the transition zone between Amazon and Cerrado biomes caused by rainfall variability.On the other hand,environmental aspects(LULC-shrubland and elevation)influenced the PC3;areas with high altitudes(>500 m)received a higher score.Conclusion Agricultural expansion substantially affected LULC,leading to deforestation-caused suppression of native vegetation.
基金supported by the National Council for Research and Development(CNPq)[424605/2018-0]Education Personnel Improvement Coordination(CAPES)[001]National Council for Research and Development(CNPq)[304936/2015-4].
文摘Brazilian biomes are home to a significant portion of the world’s biodiversity,with a total of 14%of existing species and still concentrate 20%of the world’s water resources.However,changes in biomes have a direct impact on rainfall patterns and water recycling.Based on this,the objective was to evaluate the variability of rainfall in the four existing biomes in the Northeast Brazil(NEB)and their interaction with the ENSO climate variability mode and regional scale meteorological systems via CHELSA product.For this,monthly rainfall data were used from 1979 to 2013,with a spatial resolution of 1 km×1 km of the CHELSA product,and seasonal and annual rainfall patterns were extracted via boxplot.It was found that the rainy season in the Amazon,Caatinga and Cerrado biomes occurred between January and April,with varying intensities,except for the Atlantic Forest.Such seasonality patterns are associated with the NEB meteorological systems,with emphasis on ITCZ(all Biomes),UTCV(Amazon,Caatinga and Cerrado),Frontal Systems(extreme south of Caatinga,Cerrado and Atlantic Forest)and EWD/TWD in the(Atlantic Forest).In the inter-annual scale,the remarkable influence of ENSO was verified,mainly in the years 1983,1985,1989,1993,1998,2009 and 2012.It is noteworthy that 1985 was the wettest year of the period,with a surplus in all biomes,while the driest year differs between the Amazon(1983),Atlantic Forest and Caatinga(1993)and Cerrado(2012)biomes.The study via orbital product in NEB showed that anthropogenic processes and natural variability interfere with the forms of rain interception in the biomes and hence in rainfall patterns and water recycling in NEB.
文摘The aims of this study were:i)to compare no-till areas in two municipalities located in different regions of Brazil,along with the influence on CO_(2)Flux and GPP,and ii)to verify the difference between environmental factors followed by the trends of these variables regarding future scenarios(ARIMA time-series model number).The study was carried out in two areas with different latitudes in the municipalities of Sinop-MT and Passo Fundo-RS,both in Brazil.A time series of 19 years was performed with data acquired by remote sensing from the following satellites:i)Landsat-8(OLI and TIRS),and ii)TERRA/AQUA(MODIS).The results propound that the spectro-temporal variables are directly influenced by soil management and agricultural practices over the observation time,with a satisfactory correlation in future predictions of the variables for the next ten years,in which presented that the variation of GPP and albedo values for the two study sites would gradually increase until 2028 and the temperature remained constant between the range of its seasonality,and CO_(2)Flux tends to decrease in its seasonality,indicating a higher CO_(2) absorption.
