Análise do desempenho dos índices climáticos na execução do monitoramento das chuvas no Estado da Paraíba.

Abstract

This study investigates the relationship between the variability of climate indices and agricultural productivity in the state of Paraíba, with an emphasis on analyzing the performance of climate indices for monitoring rainfall and identifying climate patterns of extreme precipitation. The state of Paraíba, characterized by its climate diversity, faces challenges in water management and agricultural production, making climate monitoring essential to ensure the efficiency of local agriculture. Initially, the research explores the application of different climate indices, such as the Standardized Precipitation Index (SPI) and the Drought Severity Index (DSI), to assess the effectiveness of monitoring rainfall in the state. The analysis of these indices allows identifying variations in the temporal and spatial distribution of rainfall, essential for diagnosing dry and rainy periods. In addition, the study addresses the patterns of extreme precipitation, focusing on events of intense rainfall and prolonged droughts, which have become more frequent due to climate change. Identifying these patterns is crucial for developing adaptation strategies, such as choosing more resistant varieties and adopting management practices that increase crop resilience. Finally, the research investigates the relationships between climate variability and agricultural productivity, seeking to understand how climate indices can be used to predict the productivity of crops, such as grains and fruits, in different regions of the state. Statistical analysis of the correlations between climate indices and productivity reveals the sensitivity of crops to climate variations and provides support for agricultural planning, aiming to mitigate the negative impacts of climate variability. The study contributes to the development of an integrated approach to climate monitoring, allowing rural producers in Paraíba to make more informed decisions, optimize production and reduce the risks associated with climate change.