Do Gridded Weather Datasets Provide High-Quality Data for Agroclimatic Research in Citrus Production in Brazil?

Author(s)

Rasera, Julia Boscariol ; da Silva, Roberto Fray ; Piedade, Sonia ; Mourao Filho, Francisco de Assis Alves ; Delbem, Alexandre Claudio Botazzo ; Saraiva, Antonio Mauro ; Sentelhas, Paulo Cesar ; Marques, Patricia Angelica Alves

• Document type: Journal article
• Source: AGRIENGINEERING; v. 5, n. 2, p. 17-pg., 2023-06-01.

Abstract

Agrometeorological models are great tools for predicting yields and improving decision-making. High-quality climatic data are essential for using these models. However, most developing countries have low-quality data with low frequency and spatial coverage. In this case, two main options are available: gathering more data in situ, which is expensive, or using gridded data, obtained from several sources. The main objective here was to evaluate the quality of two gridded climatic databases for filling gaps of real weather stations in the context of developing agrometeorological models. Therefore, a comparative analysis of gridded database and INMET data (precipitation and air temperature) was conducted using an agrometeorological model for sweet orange yield estimation. Both gridded databases had high determination and concordance coefficients for maximum and minimum temperatures. However, higher errors and lower confidence coefficients were observed for precipitation data due to their high dispersion. BR-DWGD indicated more accurate results and correlations in all scenarios evaluated in relation to NasaPower, pointing out that BR-DWGD may be better at filling gaps and providing inputs to simulate attainable yield in the Brazilian citrus belt. Nevertheless, due to the BR-DWGD database's geographical and temporal limitations, NasaPower is still an alternative in some cases. Additionally, when using NasaPower, it is recommended to use a measured precipitation source to improve prediction quality. (AU)

• FAPESP's process: 19/07665-4 - Center for Artificial Intelligence
• Grantee: Fabio Gagliardi Cozman
• Support Opportunities: Research Grants - Research Program in eScience and Data Science - Research Centers in Engineering Program
• FAPESP's process: 22/06804-3 - Development and evaluation of a simulation model to estimate the productivity of sweet oranges (Citrus sinensis L.)
• Grantee: Júlia Boscariol Rasera
• Support Opportunities: Scholarships in Brazil - Doctorate