Desenvolvimento de Atividades Convectivas Sobre a Região Nordeste do Brasil, Organizada Pela Extremidade Frontal

Veber, Maicon Eirólico; Fedorova, Natalia; Levit, Vladimir

doi:10.1590/0102-77863550071

Cited by 4 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ceará has seven mesoregions (Figure 10), due to the dismemberment of the municipalities bordering the capital, which formed the Metropolitana de Fortaleza mesoregion (Figure 10b). Throughout the state, the wettest period is the JFMAMJ semester, influenced by systems such as upper tropospheric cyclonic vortices (UTCV), which peak between January and February [44], ITCZ between February and April [45], remnants of easterly wave disturbances (EWD) in May and June [46], in addition to the interaction between larger-scale phenomena, such as frontal systems that induce the formation of mesoscale convective complexes [47,48]. However, as in the entire northern sector of the NEB, there is great interannual variability and poor spatial-temporal distribution of rainfall in the growing season, reflecting in years with higher and lower production.…”

Section: Results By State-cearámentioning

confidence: 99%

Predictive Potential of Maize Yield in the Mesoregions of Northeast Brazil

Silva,

Peixoto,

Costa

et al. 2024

AgriEngineering

View full text Add to dashboard Cite

Most of the northeastern region of Brazil (NEB) has a maize production system based on family farming, with no technological advances and totally dependent on the natural rainfall regime, which is concentrated in 4 to 5 months in most parts of the region. This means that the productivity of this crop is low in the NEB. In the northern mesoregions of the NEB, rainfall is concentrated between January and June, in the east of the NEB from April to September, and in the west of the NEB from October to March. The growing season takes place during these semesters. With this in mind, our objective was to develop a model based on canonical correlation analysis (CCA) to predict corn production in the mesoregions of the NEB between 1981 and 2010, using accumulated precipitation per semester as the predictor variable and predicting the observed production in kg/ha. Our results showed that the CCA model presented higher correlations between observed and simulated production than that obtained simply from the direct relationship between accumulated rainfall and production. The other two metrics used, RMSE and NRMSE, showed that, on average, in most mesoregions, the simulation error was around 200 kg/ha, but the accuracy was predominantly moderate, around 29% in most mesoregions, with values below 20% in six mesoregions, indicative of better model accuracy, and above 50% in two mesoregions, indicative of low accuracy. In addition, we investigated how the different combinations between two modes of climate variability with a direct influence on precipitation in the NEB impacted production in these 30 years, with the combination of El Niño and a positive Atlantic dipole being the most damaging to harvests, while years when La Niña and a negative Atlantic dipole acted together were the most favorable. Despite the satisfactory results and the practical applicability of the model developed, it should be noted that the use of only one predictor, rainfall, is a limiting factor for better model simulations since other meteorological variables and non-climatic factors have a significant impact on crops. However, the simplicity of the model and the promising results could help agricultural managers make decisions in all the states that make up the NEB.

show abstract

Section: Results By State-cearámentioning

confidence: 99%

Predictive Potential of Maize Yield in the Mesoregions of Northeast Brazil

Silva,

Peixoto,

Costa

et al. 2024

AgriEngineering

View full text Add to dashboard Cite

show abstract

Análise sinótica e termodinâmica dos complexos convectivos de mesoescala no nordeste brasileiro em 2017

Arruda Lyra,

Santiago,

Gonçalves Nobre

2024

Rev. Bras. Geog. Fis.

View full text Add to dashboard Cite

O objetivo deste trabalho foi analisar as características sinóticas e termodinâmicas dos Complexos Convectivos de Mesoescala (CCM) do Nordeste Brasileiro em 2017. As análises foram feitas utilizando dados de reanálise global ERA-Interim e imagens do satélite GOES-13. Os CCM desenvolveram-se durante o verão em decorrência da influência da Zona de Convergência Intertropical. Além disso, os eventos que se formaram em regiões próximas à costa apresentaram maior fluxo de umidade, o que possibilitou se intensificarem ainda mais. Para os casos onde os CCM se desenvolveram através dos Vórtices Ciclônicos de Altos Níveis, os valores de vorticidade mostraram-se majoritariamente positivos em baixos, médios e altos níveis. A advecção de temperatura para maioria dos casos foi negativa. Este fator demonstrou consideravel importância, pois o contraste térmico gerado pela advecção de ar frio em uma região relativamente mais quente contribui para geração de gradientes térmicos mais intensos que proporcionaram a formação dos CCM.

show abstract

Performance Assessment of Different Precipitation Databases (Gridded Analyses and Reanalyses) for the New Brazilian Agricultural Frontier: SEALBA

Silva

et al. 2022

Water

View full text Add to dashboard Cite

Since the early 2000s, Brazil has been one of the world’s leading grain producers, with agribusiness accounting for around 28% of the Brazilian GDP in 2021. Substantial investments in research, coupled with the expansion of arable areas, owed to the advent of new agriculture frontiers, led the country to become the world’s greatest producer of soybean. One of the newest agricultural frontiers to be emerging in Brazil is the one known as SEALBA, an acronym that refers to the three Brazilian states whose areas it is comprised of—Sergipe, Alagoas, and Bahia—all located in the Northeast region of the country. It is an extensive area with a favorable climate for the production of grains, including soybeans, with a rainy season that takes place in autumn/winter, unlike the Brazilian regions that are currently the main producers of these kinds of crops, in which the rainfall regime has the wet period concentrated in spring/summer. Considering that precipitation is the main determinant climatic factor for crops, the scarcity of weather stations in the SEALBA region poses an obstacle to an accurate evaluation of the actual feasibility of the region to a given crop. Therefore, the aim of this work was to carry out an assessment of the performance of four different precipitation databases of alternative sources to observations: two from gridded analyses, MERGE and CHIRPS, and the other two from ECMWF reanalyses, ERA5, and ERA5Land, and by comparing them to observational records from stations along the region. The analysis was based on a comparison with data from seven weather stations located in SEALBA, in the period 2001–2020, through three dexterity indices: the mean absolute error (MAE), the root mean squared errors (RMSE), and the coefficient of Pearson’s correlation (r), showing that the gridded analyzes performed better than the reanalyses, with MERGE showing the highest correlations and the lowest errors (global average r between stations of 0.96, followed by CHIRPS with 0.85, ERA5Land with 0.83, and ERA5 with 0.70; average MAE 14.3 mm, followed by CHIRPS with 21.3 mm, ERA5Land with 42.1 mm and ERA5 with 50.1 mm; average RMSE between stations of 24.6 mm, followed by CHIRPS with 50.8 mm, ERA5Land with 62.3 mm and ERA5 with 71.4 mm). Since all databases provide up-to-date data, our findings indicate that, for any research that needs a complete daily precipitation dataset for the SEALBA region, preference should be given to use the data in the following order of priority: MERGE, CHIRPS, ERA5Land, and ERA5.

show abstract

Desenvolvimento de Atividades Convectivas Sobre a Região Nordeste do Brasil, Organizada Pela Extremidade Frontal

Cited by 4 publications

References 4 publications

Predictive Potential of Maize Yield in the Mesoregions of Northeast Brazil

Predictive Potential of Maize Yield in the Mesoregions of Northeast Brazil

Análise sinótica e termodinâmica dos complexos convectivos de mesoescala no nordeste brasileiro em 2017

Performance Assessment of Different Precipitation Databases (Gridded Analyses and Reanalyses) for the New Brazilian Agricultural Frontier: SEALBA

Contact Info

Product

Resources

About