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Droughts are complex natural phenomena that influence society's development in different aspects; therefore, monitoring their behavior and future trends is a useful task to assist the management of natural resources. In addition, the use of satellite-estimated rainfall data emerges as a promising tool to monitor these phenomena in large spatial domains. The Tropical Rainfall Measuring Mission (TRMM) products have been validated in several studies and stand out among the available products. Therefore, this work seeks to evaluate TRMM-estimated rainfall data's performance for monitoring the behavior and spatiotemporal trends of meteorological droughts over Paraíba State, based on the standardized precipitation index (SPI) from 1998 to 2017. Then, 78 rain gauge-measured and 187 TRMM-estimated rainfall time series were used, and trends of drought behavior, duration, and severity at eight time scales were evaluated using the Mann–Kendall and Sen tests. The results show that the TRMM-estimated rainfall data accurately captured the pattern of recent extreme rainfall events that occurred over Paraíba State. Drought events tend to be drier, longer-lasting, and more severe in most of the state. The greatest inconsistencies between the results obtained from rain gauge-measured and TRMM-estimated rainfall data are concentrated in the area closest to the coast. Furthermore, long-term drought trends are more pronounced than short-term drought, and the TRMM-estimated rainfall data correctly identified this pattern. Thus, TRMM-estimated rainfall data are a valuable source of data for identifying drought behavior and trends over much of the region. [ABSTRACT FROM AUTHOR]

Drought is a natural phenomenon that originates from the absence of precipitation over a certain period and is capable of causing damage to societal development. With the advent of orbital remote sensing, rainfall estimates from satellites have appeared as viable alternatives to monitor natural hazards in ungauged basins and complex areas of the world; however, the accuracies of these orbital products still need to be verified. Thus, this work aims to evaluate the performance of Tropical Rainfall Measuring Mission (TRMM) satellite rainfall estimates in monitoring the spatiotemporal behavior of droughts at multiple temporal scales over Paraíba State based on the standardized precipitation index (SPI) over 20 years (1998–2017). For this purpose, rainfall data from 78 rain gauges and 187 equally spaced TRMM cell grids throughout the region are used, and accuracy analyses are performed at the single-gauge level and in four mesoregions at eight different time scales based on 11 statistical metrics calculations divided into three different categories. The results show that in the mesoregions close to the coast, the satellite-based product is less accurate in capturing the drought behavior regardless of the evaluated statistical metrics. At the temporal scale, the TRMM is more accurate in identifying the pattern of medium-term droughts; however, there is considerable spatial variation in the accuracy of the product depending on the performance index. Therefore, it is concluded that rainfall estimates from the TRMM satellite are a valuable source of data to identify drought behavior in a large part of Paraíba State at different time scales, and further multidisciplinary studies should be conducted to monitor these phenomena more accurately based on satellite data. [ABSTRACT FROM AUTHOR]

Drought events are mainly associated with alterations in ocean-atmosphere patterns, leading to abnormally dry conditions due to reduced precipitation. This study aims to enhance the understanding of the spatiotemporal relationship of atmospheric teleconnections associated with droughts in the Brazilian Legal Amazon (BLA), based on the Rainfall Anomaly Index (RAI), utilizing 1675 precipitation grid points from the Global Precipitation Climatology Centre (GPCC) for the period 1970–2019. The results revealed that Principal Component Analysis (PCA) and cluster analysis of RAI demonstrated significant climatic variability, with 15 components explaining 68% of the total variance and identifying two homogeneous regions closely aligning with observed conditions. Atmospheric teleconnections showed substantial variation in spatial and temporal extent in extreme drought events in the years 2005, 2010, 2015–2016, and 2019 in the BLA. The findings indicate that on an interannual scale, the dominant teleconnections in the BLA are the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Tropical North Atlantic (TNA), Pacific North American (PNA) pattern, and Atlantic Meridional Overturning Circulation (AMOC). In contrast, on a decadal scale, the Pacific Decadal Oscillation (PDO), Southern Oscillation Index (SOI), Oceanic Niño Index (ONI), and Tropical South Atlantic (TSA) prevail. Our results provide valuable insights into the nature of drought events in the Amazon, including strategies for the early detection of their intensity and affected areas, demonstrating that atmospheric teleconnections significantly influence both interannual and decadal periods. These influences are concentrated on specific temporal scales and during particular years. Conclusively, this study underscores the critical role of atmospheric teleconnections in shaping drought dynamics in the BLA, offering a foundation for predictive models and mitigation strategies to combat climate-induced challenges in the region. [Display omitted] • Identified key teleconnections affecting Brazilian Legal Amazon (BLA) droughts. • Used 1675 grid points to map Rainfall Anomaly Index (RAI) variability. • Principal Component Analysis (PCA) and Cluster analysis reveal climate patterns. • Highlights Atlantic Multidecadal Oscillation (AMO), NAO's role in Amazon droughts. • Proposes early detection strategies for drought. [ABSTRACT FROM AUTHOR]