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High winds are a type of catastrophic weather characterized by wind speeds over 10.8 m·s−1, occurring in all seasons, and have become more frequent, impacting crop growth, agricultural production and quality of life. It is crucial to understand the spatial and temporal distribution patterns of high winds, as well as their speed and other characteristics, for logical planning of agricultural production and the creation of disaster resilience measures. This study applied the climate tendency, accumulative anomalies, theory of run, Mann–Kendall trend and Theil–Sen median to analyse the spatial and temporal distribution characteristics of the average wind speed and high wind days in Jilin Province, the probability of occurrence of high winds of various magnitudes in different eras, and the gale concentration degree (GCD) throughout Jilin Province for a total of 40 years from 1982 to 2021. The average wind speed and number of high wind days in Jilin Province have decreased over the past 40 years, and this trend has slowed over time. The average GCD in Jilin Province has shown an increasing trend over the last 40 years, with the average GCD being highest in Liouhe and lowest in Linjiang. In general, level six high winds were the main wind hazard level in Jilin Province, with the highest frequency occurring in different seasons and decades. In addition, the occurrence of high wind days is affected by global climate change and different underlying surfaces, which leads to maize and yield reduction. Research on the spatiotemporal distribution of high winds can provide important suggestions for the prevention and management of high wind disasters. [ABSTRACT FROM AUTHOR]

As the climate warms, the impact of drought on plants has increased. We aimed to construct a comprehensive drought index (CDI), coupling soil-vegetation-atmosphere drought and heat conditions based on multi-source information, and to combine it with static and dynamic drought hazard evaluation models to analyze the spatial and temporal distribution characteristics of agricultural drought disasters and hazards during the growing season (May to September) in Northeast China (NEC). The results demonstrated that the CDI could combine the benefits of meteorology (standardized precipitation evapotranspiration index, SPEI), vegetation (vegetation health index, VHI), and soil (standardized soil moisture condition index, SMCI) indices. This was performed using a relative weighting method based on the remote sensing data of solar-induced chlorophyll fluorescence (SIF) to determine the weights of SPEI, VHI, and SMCI. The CDI for drought monitoring has the advantages of broad spatial range, long time range, and high accuracy, and can effectively reflect agricultural drought; the growing season in NEC showed a trend of becoming drier during 1982–2020. However, the trends of the drought index, the impact range of drought events, and the hazard of agricultural drought all turned around 2000. The drought hazard was highly significant (p < 0.001) and decreased from 2000 to 2020. The frequency of drought disasters was the highest, and the hazard was the greatest in May. The best level of climatic yield anomalies in maize were explained by drought hazard in August (R2 = 0.28). In the center and western portions of the study area, farmland and grassland areas were where higher levels of hazard were most commonly seen. The dynamic hazard index is significantly correlated with climatic yield anomalies and can reflect the actual impact of drought on crop yield. The study results serve as a scientific foundation for drought risk assessment and management, agricultural planning, and the formulation of drought adaptation policies, as well as for ensuring food security in China. [ABSTRACT FROM AUTHOR]