The rainfall regime is a critical factor in the Yucatan Peninsula, as the spatial and multiannual variability of rainfall is a major concern, particularly for crops. Variability in the rainy season was examined considering the onset and demise of the annual rainy season, the total rain volume, the rainfall season duration and the intense precipitation events recorded in meteorological stations (1978–2020). We analysed individual time series and calculated the long‐term trend. Additionally, we explored the relationship between each summer rainfall characteristic and several oceanographic indices using multivariate techniques. We also developed a Trans‐Isthmic Index from the relationship between the El Niño–Southern Oscillation and the Atlantic Multidecadal Oscillation. This index allows for determining the effect of the overall influence of the ocean on climate. The timeseries analysis revealed a high interannual variability and long‐term positive trends concerning the duration of the rainy season with earlier onset and later demise, and the total rainfall volume and also a positive trend for the occurrence of heavy precipitation suggesting a shift in intra‐annual patterns. Spatially, the analysis revealed clusters of stations with a similar variation, probably related to the AMO, NIÑO3.4 or TII indices. The spatial pattern was confirmed by analysing CHIRPS gridded precipitation data. Our results show that wetter conditions are associated with lower temperatures in the equatorial Pacific and warmer conditions in the Atlantic.

Tropical cyclones are one of the most dangerous natural phenomena. These extreme events involve various hazards, such as strong winds, severe precipitation, storm surge, flooding, and landslides. In Mexico, tropical cyclones are the most frequent natural threats and have a high cost to affected populations. This research aimed to characterise the spatial and temporal changes in risk associated with hurricane winds on the Yucatan Peninsula. This effort included a comprehensive analysis of three integral risk components (hazard, vulnerability, and exposure) for three distinct time intervals (1950–2000, 1950–2010, and 1950–2020). This analytical process was executed utilising a fine-resolution hexagonal grid. Hazard was estimated by calculating the probabilities of occurrence of winds related to various hurricane categories after estimating wind fields from the International Best Track Archive for Climate Stewardship (IBTrACS) data with a parametric model. Vulnerability was approximated by constructing indicators with sociodemographic data from the National Population and Housing Census issued by Mexico’s National Institute of Statistics and Geography. With these indicators, a factor analysis was performed, and a weighted index was constructed. Finally, exposure was estimated from population density. Each of these indices was aggregated at the hexagonal level, allowing the calculation of the risk associated with hurricane-force wind. The results showed high-risk levels associated with high-hazard levels, e.g. in coastal areas such as the Riviera Maya. Similarly, high-risk levels are related to high marginalisation, i.e. vulnerability, in the northeastern zone of the Yucatan Peninsula. The increased frequency of tropical cyclones combined with high population densities has recently led to higher risk levels in this region of Mexico.

The main climatic indices used for the determination of pre-summer drought severity were developed for temperate zones with very different climatic conditions from those found in the tropical climate zones, particularly with respect to seasonal rainfall variations. The temporal evolution of pre-summer drought leads the authors to compute the indices for each year over a defined period according to the climatic normals of each meteorological station and to consider the months inside the dry episode differently, according to the law of emptying the water reserves. As a function of this, standardized drought indices are proposed for the evaluation of the pre-summer drought in tropical zone. Two new indices were tested: one developed from precipitation and the other also considering temperature. These indices were validated by correlation with Advanced very-high-resolution radiometer (AVHRR) normalized difference vegetation index (NDVI) time series and used to identify the most severe drought conditions in the Yucatan Peninsula. The comparison between the indices and their temporal variations highlighted the importance of temperature in the most critical events and left indications of the impact of global warming on the phenomenon.

Major hurricanes are a critical hazard for North and Central America. The present study investigated the trends of occurrence, affectation, and intensity of major hurricanes in the North Atlantic and Northeast Pacific Oceans using GIS applications to the IBTrACS database. The study period ranged from 1970 to 2021. Tropical cyclones were sampled using a grid composed of 3.5° hexagonal cells; in addition, trends were obtained to assess the effect of long-term variability from natural phenomena and climate change. Critical factors influencing these trends at the oceanic scale and for each hexagon were determined using multivariate and multiscale analysis by the application of stepwise analysis and the related ANOVA. The integrated variables related to atmospheric and oceanographic oscillations and patterns, i.e., spatial variables resampled with the same analysis unit and climate indices. Our results indicated marked spatial areas with significant trends in occurrence and intensity. Additionally, there was evidence of linear changes in the number of major hurricanes and an increase in the maximum annual speed of +1.61 m s⁻¹ in the North Atlantic basin and +1.75 m·s⁻¹ in the Northeast Pacific, reported for a 10-year period. In terms of occurrence, there were increases of 19% and 5%, respectively, which may be related to ocean warming and natural variability associated with oceanic and atmospheric circulation.

The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020, and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made out. The results show different common social vulnerability driving factors in the 3 analyzed years, with root causes that have not been addressed since the beginning of the century. Likewise, a wider gap between Mexico’s most and least vulnerable populations is identified. The changes in spatial patterns respond to different historical situations, such as migration, urbanization, and increased population. Also, poverty, ethnicity, and marginalization factors located in very particular regions in Mexico have remained relatively the same in the last 20 twenty years. These situations have strongly influenced the spatial–temporal distribution of vulnerability in the country. The role of social vulnerability in the disaster risk to extreme events such as thunderstorms, hailstorms, and tornadoes in Mexico is fundamental to understanding changes in disaster distribution at the national level, and it is the first step to generating improvements in integrated risk management.

Estimation of the recession constant for soil moisture can assist in soil and water management. This article estimates soil moisture recession velocity from satellite data, thereby taking advantage of extensive data coverage in a metric that is more commonly used with point data for rivers. Retrieval from satellites of the surface soil moisture has produced global coverage of multiannual time series data, thereby allowing the application of techniques that require long time series of daily data. We applied two techniques from river hydrology to soil moisture data from the advanced scatterometer aboard the meteorological operational satellite: (1) baseflow separation; and (2) master recession curve (MRC) with the correlation method. The former filtered the data and extracted those for the base soil moisture (BSM), which is considered the water that circulates in the soil by capillarity. The latter technique allowed the estimation of recession constants by the extraction of continuously decreasing BSM segments. The use of MRC for a large range of BSM provides a recession constant representative of all the moisture decrease for each pixel, thereby permitting the identification of drought-sensitive zones. The recession constant, a metric that had not been used for soil moisture, allowed us to determine potential temporal evolution of drought in the Yucatan peninsula. Government agencies could use the approach applied in this study to improve water management and drought prevention.