Performance of the ECMWF in air temperature and precipitation estimates in the Brazilian Amazon

Moraes, José Reinaldo da Silva Cabral de; Rolim, Glauco de Souza; Martorano, Lucieta Guerreiro; Aparecido, Lucas Eduardo de Oliveira; Bispo, Rafael Carlos; Valeriano, Taynara Tuany Borges; Esteves, João Trevizoli

doi:10.1007/s00704-020-03231-2

Cited by 7 publications

(9 citation statements)

References 53 publications

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“…Na Figura 1 localiza-se a área de estudo, a partir da base de dados utilizada por Martorano et al (2017); Martorano (2020) e Moraes et al (2020). Nota-se que os meses de maior oferta pluvial em Santarém concentram-se de dezembro a maio, contabilizando-se cerca de 80% da pluviosidade anual, sendo o mês de março o mais chuvoso com média de 348,9 mm.…”

Section: Localização E Condições Climáticas Da áRea De Estudounclassified

“…E se tratando da região amazônica que possui um clima tropical quente e úmido, mas é preciso entender que existem mecanismos que modulam a circulação em decorrência de processos no sistema oceano-continente-atmosfera. Mudanças no regime das termoclinas, ou seja, as variações térmicas entre as camadas superficiais e as camadas profundas nas águas do Pacífico Tropical Sul, denominada de Oscilação Sul (ENOS), causam anomalias na temperatura da superfície do mar tornando-as mais quentes (El Niño) e mais frias (La Niña) por mais de cinco meses (Jahfer et al 2020;Moraes et al 2020), ocasionando condições extremas no regime de chuvas (Loureiro et al 2014) refletindo em perdas na agricultura brasileira.…”

Section: Introductionunclassified

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Uma Aplicação na Geociência da Termografia Infravermelho para Diagnosticar Padrões Térmico-Hídricos em Solos com Culturas Irrigadas por Potes de Argila no Oeste do Pará, Amazônia

et al. 2021

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The objective of this study is to demonstrate the use of infrared thermography in a geoscience context to diagnose thermal and hydrological patterns in soils with crops irrigated using clay pots in western Pará, Amazonia. The thermographic images were obtained in a technological reference unit (URT) installed as part of the IrrigaPote project in the community of Lavras, western Pará. Images were taken in the field and thermal patterns were analyzed for the following targets: T1: Acerola (Malpighia emarginata) trees with leaf litter covering the soil; T2: Acerola trees with no leaf litter covering the soil; T3: Soil with litter cover; T4: Soil with no litter cover, and T5: a backyard agroforest with a large tree over 100 years old with litter covering the soil. The data were stratified into extreme and average values and thermal amplitude, and soil humidity was measured. The near infrared thermography diagnosis and the thermograms were analyzed using the program Flir Tools (6.3v). The thermal targets were randomly selected, with 10 targets for each of the five (05) treatments, for a total of 50 samples. Descriptive statistics were done using a 5% significance level. There were significant differences between exposed soil (T4=61.0°C) and soil covered by litter (T3=43.8°C). The soil shaded by acerola had an average temperature of (T1=33.6°C) and that of the soil shaded but with litter and outside the URT was higher (T2=32.7°C), demonstrating the effects of soil moisture due to irrigation with the clay pots. The lowest temperatures (T5=30.3°C) were found for the large, old tree with the soil covered by litter on the property of the rural producer. The thermal regulation provided by the irrigation using clay pots is in agreement with the Sustainable Development Objectives (SDO), principally SDO 2 with respect to provision of food production during the entire year, and SDO 6, 9 and 12 due to the reuse of rainfall in an agricultural setting, which promotes responsible production, and finally with SDO 13 as a strategy for thermal regulation to mitigate the effects of climate change. Infrared thermography has great potential to be applied to different areas of geoscience.

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Section: Localização E Condições Climáticas Da áRea De Estudounclassified

Section: Introductionunclassified

Uma Aplicação na Geociência da Termografia Infravermelho para Diagnosticar Padrões Térmico-Hídricos em Solos com Culturas Irrigadas por Potes de Argila no Oeste do Pará, Amazônia

et al. 2021

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“…Rainfall is is one of the most important processes of the hydrological cycle (Alvares et al, 2013), considering that its distribution and spatial variability is the most effective component in the regionalization of climatic conditions and also in vegetation growth (Javari, 2017). Rainfall is the most difficult meteorological element to model (Moraes et al, 2020;Chahine, 1992) and for this reason, it requires more efficient prevision methodologies which allow the inference of a value that represents the rainfall of the area of interest (di Piazza et al, 2011;Javari, 2016).…”

Section: Introductionmentioning

confidence: 99%

Spatial Interpolation Techniques to Map Rainfall in Southeast Brazil

Aparecido

Moraes

Lima

et al. 2022

Rev. bras. meteorol.

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The prediction, as well as the estimation of precipitation, is one of the challenges of the scientific community in the world, due to the high spatial and seasonal variability of this meteorological element. For this purpose, methodologies that allow the accurate interpolation of these elements have fundamental importance. Thus, we seek to evaluate the efficiency of the interpolation methods in the mapping of rainfall and compare it with multiple linear regression in tropical regions. The interpolation methods studied were inverse distance weighted (IDW) and Kriging. Monthly meteorological data rainfall from 1961 to 1990 was obtained from 1505 rainfall stations in the Southeast region of Brazil, provided by the National Institute of Meteorology. The comparison between the interpolated data and the real precipitation data of the surface meteorological stations was performed through the following analyzes: accuracy, presicion and tendency. The mean PYEAR, for summer, autumn, winter, and spring are 596 mm seasons−1 (s= ±118 mm), 254 mm seasons−1 (s= ±52 mm), 114 mm seasons−1 (s= ±54 mm) and 393 (s= ± 58 mm) mm seasons−1, respectively. The Kriging highlight accuracy slightly high in relation to IDW. Since the MAPEKRIGING was of 2% while the MAPEIDW was of 3%. The IDW and Kriging methods were accurate and, with low trends in precipitation estimation. While multiple linear regression showed low accuracy when compared with interpolation methods. Despite the lower accuracy the regression linear is more practical and easy to use, as it estimates the rain with only altitude, latitude and longitude, input variables that commonly known input variables. The largest errors in estimating the spatial distribution of precipitation occurred in Winter for all interpolation methods.

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“…Climate is defined as the grouping of atmospheric dispositions, providing the characterization of a region (WMO345w, 2008;Werndl, 2016), influencing several economic, social, and environmental activities (Palinkas and Wong, 2020;Tol, 2018), especially the agribusiness. All stages of agricultural development suffer from climate interference (Schauberger et al, 2017;Syed et al, 2022), providing higher or lower crop yields (De Moraes et al, 2020;Yu et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Estimation of Air Temperature Using Climate Factors in Brazilian Sugarcane Regions

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Aparecido

Lorençone

et al. 2022

Rev. bras. meteorol.

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This study aimed to estimate the minimum and maximum monthly air temperatures in the sugarcane regions of Brazil. A 30-year historical series (1988-2018) of maximum (Tmax) and minimum (Tmin) air temperatures from the NASA/POWER platform was used for 62 locations that produce sugarcane in Brazil. Multiple linear regression was used for data modeling, in which the dependent variables were Tmin and Tmax and the independent variables were latitude, longitude, and altitude. The comparison between estimation models and the real data was performed using the statistical indices MAPE (accuracy) and adjusted coefficient of determination (R2adj) (precision). The lowest MAPE values of the models for estimating the minimum air temperature occurred mainly in the North during February, March, and January. Also, the most accurate models for estimating the maximum air temperature occurred in the Southeast region during January, February, and March. The MAPE and R2adj values showed accuracy and precision in the models for estimating both the maximum and minimum temperatures, indicating that the equations can be used to estimate temperatures in sugarcane areas. The Tmin estimation model for the Southeast region in July shows the best performance, with a MAPE value of 1.28 and an R2adj of 0.94. The Tmax model of the North region for September presents higher precision and accuracy, with values of 1.28 and 0.96, respectively.

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Performance of the ECMWF in air temperature and precipitation estimates in the Brazilian Amazon

Cited by 7 publications

References 53 publications

Uma Aplicação na Geociência da Termografia Infravermelho para Diagnosticar Padrões Térmico-Hídricos em Solos com Culturas Irrigadas por Potes de Argila no Oeste do Pará, Amazônia

Uma Aplicação na Geociência da Termografia Infravermelho para Diagnosticar Padrões Térmico-Hídricos em Solos com Culturas Irrigadas por Potes de Argila no Oeste do Pará, Amazônia

Spatial Interpolation Techniques to Map Rainfall in Southeast Brazil

Estimation of Air Temperature Using Climate Factors in Brazilian Sugarcane Regions

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