Assessing the performance of two gridded weather data for sugarcane crop simulations with a process-based model in Center-South Brazil

Dias, Henrique Boriolo; Sentelhas, Paulo César

doi:10.1007/s00484-021-02145-6

Cited by 16 publications

(4 citation statements)

References 57 publications

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“…The overall performance of NASA POWER data in estimating the mean temperature is satisfactory, while rainfall is considered a reasonable performance. The results are aligned with the findings in the study by Dias et al, in which the performance of NASA POWER is evaluated in a same tropical climate country, Brazil [16].…”

Section: Resultssupporting

confidence: 89%

Assessment of NASA POWER for Climate Change Analysis using the De Martonne Climate Index in Northern Peninsular Malaysia

Bandira,

Tan,

Teh

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Global warming is threatening human population, one of which is the frequent climate disasters, i.e., floods and drought, which affect the global food security. However, the assessment of regional climatic changes is constrained by the lack of high-quality long-term climate data. Taking the Northern Region of Peninsular Malaysia as the study area, this paper aims to assess the performance of NASA POWER in estimating annual and seasonal variability of the climate variables via De Martonne climate indices from 1985 to 2021. The findings shows that NASA POWER performed satisfactory in estimating both mean temperature and rainfall over the northern Peninsular Malaysia. The NASA POWER project performs the best in Bayan Lepas station with C = 0.70 for annual mean temperature while for annual rainfall is at the Ipoh station with C = 0.50. The annual De Martonne climate index shows that the study area is dominated by wet climate conditions, since the index classify the climate as “very humid” to “extremely humid”. The De Martonne climate indes is calculated from both data source is very similar. Therefore, NASA POWER data is useful in climate studies, while the knowledge of climate variability is beneficial for climate change mitigation and adaptation plans, particularly for agriculture.

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Section: Resultssupporting

confidence: 89%

Assessment of NASA POWER for Climate Change Analysis using the De Martonne Climate Index in Northern Peninsular Malaysia

Bandira,

Tan,

Teh

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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“…This allows researchers to test whether the gridded interpolations or observed data are better for their purposes. For example, Dias and Sentelhas (2021) tested the use of previous BR-DWGD and NASA grid (http://power.larc.nasa.gov) to simulate sugarcane yield comparing to yield simulated with high-quality measured weather data. They observed that replacing gridded pr by observed pr show better agreement with the simulations using high-quality measured weather data.…”

Section: Discussionmentioning

confidence: 99%

New improved Brazilian daily weather gridded data (1961–2020)

Xavier

Scanlon

King

et al. 2022

Intl Journal of Climatology

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The demand for meteorological gridded datasets has increased within the last few years to inform studies such those in climate, weather, and agriculture.These studies require those data to be readily usable in standard formats with continuous spatial and temporal coverage. Since 2016, Brazil has a daily gridded meteorological data set with spatial resolution of 0.25 × 0.25 from January 1, 1980 to December 31, 2013 which was well received by the community. The main objective of this work is to improve the Brazilian meteorological data set. We do this by increasing the resolution of the minimum and maximum temperature (Tmax and Tmin) gridded interpolations from 0.25 × 0.25 to 0.1 × 0.1 by incorporating data on topographic relief, and increasing the time period covered (January 1, 1961-July 31, 2020). Besides Tmax and Tmin, we also gridded precipitation (pr), solar radiation (Rs), wind speed (u2), and relative humidity (RH) using observed data from 11,473 rain gauges and 1,252 weather stations. By means of ranked cross-validation statistics, we selected the best interpolation among inverse distance weighting and angular distance weighting methods. We determined that interpolations for Tmax and Tmin are improved by using the elevation of a query point, that accounts for topographic relief, and a temperature lapse rate. Even though this new version has ≈25 years more data relative to the previous one, statistics from crossvalidation were similar. To allow researchers to assess the performance of the interpolation relative to station data in the area, we provide two types of gridded controls.

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“…There is an ongoing effort in ETo modeling for large areas, such as Brazil. Xavier et al (2016) applied ETo prediction by interpolation and supported several climate studies nationally (Dias and Sentelhas, 2021;Santos et al, 2021). However, interpolation can be problematic in studies of large areas due to spatial dependence requirements (Oliver and Webster, 1990), and variables strictly related to ETo can be neglected.…”

Section: Introductionmentioning

confidence: 92%

Mapping the effects of climate change on reference evapotranspiration in future scenarios in the Brazilian Semiarid Region - South America

Silva

Souza

Silva

et al. 2023

Rev. Bras. Geog. Fis.

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Brazil has the world's most populous semi-arid region and climate change represents significant ecological and socioeconomic challenges for this area. To better understand the impact of these changes, it is crucial to analyze the dynamics of climate variables and evapotranspiration (ETo), a critical climate variable. This study aimed to model ETo rates considering climate change scenarios in the Brazilian Semi-arid region (BSR). The modeling was based on tests of five machine learning algorithms: Bayesian Regularized Neural Networks (BRNN), Cubist, Earth, Linear Regression (LM), and Random Forest (RF). A dataset with 20 covariates was used to represent the current scenario. In the future prediction, covariates from two shared socio-economic pathways were used (SSPs 126 and 585). The best statistical performance was achieved by Cubist (R² = 0.98 and RMSE = 0.08 mm day-¹ in the holdout-test). The current daily average ETo is 4.77 mm day-¹, while in future scenarios, it can increase by 3.56% in SSP 126 and 15.51% in SSP 585. ETo rates are expected to expand territorially; ranges from > 0.60 mm day-¹ should increase 8% in SSP 126 and 40% in SSP 585. The applied model suggests that ETo may increase in future scenarios in the BSR, which could affect biodiversity levels and intensify social conflicts.

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Assessing the performance of two gridded weather data for sugarcane crop simulations with a process-based model in Center-South Brazil

Cited by 16 publications

References 57 publications

Assessment of NASA POWER for Climate Change Analysis using the De Martonne Climate Index in Northern Peninsular Malaysia

Assessment of NASA POWER for Climate Change Analysis using the De Martonne Climate Index in Northern Peninsular Malaysia

New improved Brazilian daily weather gridded data (1961–2020)

Mapping the effects of climate change on reference evapotranspiration in future scenarios in the Brazilian Semiarid Region - South America

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