Meteorology

Accurate air temperature and precipitation data are fundamental for environmental and socioeconomic applications in Brazil. However, the observational network managed by the National Institute of Meteorology, suffers from spatial gaps, necessitating the use of gridded datasets. This study provides a rigorous comparative assessment of three prominent gridded products—the station-interpolated dataset of Brazilian Daily Weather Gridded Data (BR-DWGD), the satellite-gauge blended product MERGE, and the ERA5-Land Reanalysis dataset—against station data. We evaluate the performance of the institutionally supported MERGE and ERA5-Land products as viable alternatives to the interpolated dataset. Daily data for maximum temperature (Tmax), minimum temperature (Tmin), and total precipitation were selected from 1994 to 2024 and analyzed using statistical metrics. The interpolated product showed the highest fidelity to observations, especially for temperature. For precipitation, the MERGE product demonstrated the best performance, achieving higher correlation and lower error than both the interpolated dataset and the poorly performing ERA5-Land. For temperature, ERA5-Land proved to be an excellent alternative for minimum temperature, but exhibited significant regional biases for maximum temperature and a tendency to underestimate heat extremes. We conclude that MERGE is the most robust alternative for precipitation studies in Brazil. ERA5-Land is a highly reliable source for minimum temperature, but its direct use for maximum temperature requires caution.

Drought remains a phenomenal disaster of critical concerns in West Africa, particularly within the Niger River Basin, due to its insidious, multifaceted, and long-lasting nature. Its continuous severe impacts on communities, combined with the limitations of existing univariate index-based monitoring methods, worsen the challenge. This paper introduces and evaluates a Hybrid Drought Resilience Empirical Model (DREM) that integrates meteorological, agricultural, and hydrological indicators to improve their concurrent monitoring and early warning for effective decision-making in the region. Using reanalysis hydrometeorological data (1980–2016) and community vulnerability records, results show that the DREM-based composite index detects drought earlier than the Standardized Precipitation Index (SPI), with stronger alignment to soil moisture and streamflow variations. The model identifies drought onset when thresholds range from −0.26 to −1.19 over three consecutive months, depending on location, and signals drought termination when thresholds rise between −0.08 and −0.82. The study concludes that the DREM-based composite index provides a more reliable and integrated framework for early drought detection and decision-making across the Niger River Basin, and hence, has proven to be a suitable drought monitor for stakeholders in the Niger Basin which can be relied upon and trusted with high confidence.

Extratropical cyclones are the main drivers of high-energy wave events along the southern coast of Brazil, frequently producing hazardous coastal conditions. Between 2001 and 2020, we identified 51 high-impact coastal storms based on Marine Weather Warnings and ERA5 reanalysis. Events showed a clear seasonal pattern, with the highest occurrence in winter and autumn. Composite analyses revealed that these extreme events are consistently associated with strong meridional pressure gradients and southerly to southeasterly low-level winds, which establish long wind-fetch zones that favor the generation and shore-normal propagation of energetic waves. Significant wave heights typically exceeded 4 m along the entire coastline, with maxima south of 35° S. EOF analyses showed that the dominant mode of variability is a recurrent low-pressure system centered between 40 and 45° S over the southwestern Atlantic. In contrast, the second mode represents the dipole between continental high pressure and oceanic low pressure that intensifies storm-related wave generation. Case studies from 2008 and 2015 confirmed that these synoptic patterns result in prolonged hazardous sea states and coastal impacts, including bar closures at the Port of Rio Grande, totaling 355 h of inoperability. These findings provide a clear characterization of the meteoceanographic patterns associated with high-impact coastal storms in southern Brazil and offer a climatological basis for improving early warning, navigation safety, and coastal risk management.