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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]

Due to the national nutrition crisis and the adjustment of planting structure, millet has once again become a widely planted cash crop in Northern China. However, as the climate warms in recent years, drought has occurred frequently and repeatedly in Northern China, which has seriously threatened millet production safety in this area. Therefore, it is urgent to clarify the hazard of millet drought disaster and provide reference for the formulation of millet disaster prevention and reduction measures. In this paper, combined with the water demand of millet in each growth period, Standardized Precipitation Requirement Index (SPRI) was selected to identify and quantify the drought disaster of millet. Considering the impact of different degrees of drought in different growth periods, a hazard assessment model is constructed to evaluate the hazard of millet drought disaster in Northern China under the background of climate change. The results show that: (1) SPRI can well characterize the drought of millet in Northern China. (2) In the context of climate change, millet drought in Northern China shows a trend of increasing intensity and decreasing frequency, and it is possible that millet drought will be even more severe in the future. (3) Combined with the hazard assessment model, millet drought in Northern China will still be dominated by middle hazard in the future, but the areas with high hazard will gradually increase, mainly distributed in northeast China, central and western Inner Mongolia and northern Gansu. The research results can be of great practical significance for the adjustment of agricultural production structure in the future, especially for the sustainable development of agriculture and the formulation of measures to prevent and resist agricultural disasters. [Display omitted] • We apply SPRI to identify millet drought by considering actual water demand. • Future changes of millet drought evaluated by CMIP6-GCM models. • Hazard assessment model was presented combined with disaster loss coefficient. • The areas with high hazard of millet drought will gradually increase in future. [ABSTRACT FROM AUTHOR]

Plant phenology depends largely on temperature, but temperature alone cannot explain the Northern Hemisphere shifts in the start of the growing season (SOS). The spatio–temporal distribution of SOS sensitivity to climate variability has also changed in recent years. We applied the partial least squares regression (PLSR) method to construct a standardized SOS sensitivity evaluation index and analyzed the combined effects of air temperature (Tem), water balance (Wbi), radiation (Srad), and previous year's phenology on SOS. The spatial and temporal distributions of SOS sensitivity to Northern Hemisphere climate change from 1982 to 2014 were analyzed using time windows of 33 and 15 years; the dominant biological and environmental drivers were also assessed. The results showed that the combined sensitivity of SOS to climate change (SCom) is most influenced by preseason temperature sensitivity. However, because of the asymmetric response of SOS to daytime/night temperature (Tmax/Tmin) and non-negligible moderating of Wbi and Srad on SOS, SCom was more effective in expressing the effect of climate change on SOS than any single climatic factor. Vegetation cover (or type) was the dominant factor influencing the spatial pattern of SOS sensitivity, followed by spring temperature (Tmin > Tmax), and the weakest was water balance. Forests had the highest SCom absolute values. A significant decrease in the sensitivity of some vegetation (22.2%) led to a decreasing trend in sensitivity in the Northern Hemisphere. Although temperature remains the main climatic factor driving temporal changes in SCom, the temperature effects were asymmetric between spring and winter (Tems/Temw). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. Vegetation adaptation has a greater influence on the temporal variability of SOS sensitivity relative to each climatic factor (Tems, Temw, Wbi, Srad). More moisture might mitigate the asymmetric response of SCom to spring/winter warming. This study provides a basis for vegetation phenology sensitivity assessment and prediction. [ABSTRACT FROM AUTHOR]

Examining the effects of climate change on spring maize, and its suitability under dynamic cultivation patterns, will aid strategic decision-making for future agricultural adaptation. This paper investigates the climate suitability of spring maize, based on daily data from 50 meteorological stations, and statistics on maize yield and area at the county level in Jilin Province, China, between 1986 and 2015. Based on a significant correlation between the cultivation patterns indicator ≥10 °C accumulated temperature (AAT10) and the average yield (R2 = 0.503), the yield data are used to determine suitable thresholds for meteorological factors under the dynamic cultivation pattern, and a fuzzy fitness approach is used to evaluate the climate suitability. The results showed a good agreement between suitability estimates and scaled observed yields (average d = 0.705). Moreover, good consistency between cultivation patterns, climate suitability and yield show that the late-maturing varieties of maize have gradually moved northward and eastward, and the areas of high suitability and high yield have gradually expanded eastward. In addition, drought and chilling hazard factors limit the suitability of climate resources, especially in the eastern and western regions. [ABSTRACT FROM AUTHOR]

Due to global warming, it is necessary to study the influence of extreme climate and concurrent events on crop growth. The study area was the Songliao Plain, where drought events frequently occur. First, the daily meteorological data of 14 meteorological stations from 1981 to 2016 were collected to analyze the temporal and spatial changes in the crop water surplus and deficit index, extreme growing degree-days, and heat stress intensity during different growth stages of maize. Second, the cloud model was used to describe the fuzziness of concurrent events (simultaneous drought and heat), and mutual mapping between qualitative and quantitative data was undertaken. The fuzzy certainty degree of the influence of different degrees of concurrent events on maize was calculated. Third, the copula function was used to describe the randomness of concurrent extreme events and calculate the joint probability distribution and return period. An assessment method was proposed for concurrent events from the perspective of system uncertainty. Finally, we analyzed the relationship between concurrent events and maize yield, which showed different degrees of water deficit and warming trends during each growth period. Crops were most affected by extreme weather during the reproductive growth period (RGP). During the vegetative growth period (VGP), the temperature increase was higher than in other periods, especially in the high-latitude region. The frequency of mild concurrent events was higher during the VGP and RGP. During the vegetative and reproductive period, the average occurrence probability of mild, moderate, and severe concurrent events was 21.9%, 1.7%, and 0.35%, respectively, whereas during the RGP, it was 23.1%, 8.2%, and 0.12%, respectively. The present study provides a meaningful reference for a better understanding of the occurrence laws of drought, heat, and concurrent events during crop growth periods and how to optimize the agricultural management of maize. • Cloud model qualitative and quantitative mapping of drought and heat events. • Copula function was used to describe the randomness of concurrent extreme events. • Vegetative growth periods (VGP) and reproductive growth periods (RGP) were modelled. [ABSTRACT FROM AUTHOR]

• Overall, climate warming is beneficial to sugarcane distribution. • There is a risk of drought in the main sugarcane producing areas. • The cropland fragmentation is significant in sugarcane climate suitable area. • The sugar industry has faced challenges seriously in recent years under global warming and human factors. Guangxi is the primary producer of sugarcane in China and provides a highly suitable habitat for sugarcane growth. However, its distribution range has changed significantly in recent years due to climate change as well as human factors. Without extensive knowledge of the changing trends in suitable sugarcane planting areas, efforts to improve its productivity in Guangxi may be insufficient. In this study, the interdecadal change in sugarcane distribution in Guangxi in response to climate change from 1960 to 2019 was estimated using the MaxEnt model and the landscape pattern of land use in the suitable sugarcane area was analyzed. In addition, we discuss the effects of global warming on sugarcane production in the sustainable development of the sugar industry in Guangxi. Our results indicate: (1) from 1960 to 2019, approximately 65% of Guangxi Province could grow sugarcane. Chongzuo City, Nanning City and Parts of Baise City, are highly suitable areas, and unsuitable areas are mainly concentrated in the north. In general, sugarcane climate suitability extended further in low-altitude areas, and then extended to high- altitude areas. However, from the 2000s to the 2010s, climate suitability showed a decreasing trend, decreasing from 16.036 × 106 ha to 15.4985 × 106 ha (2) The order of land use area in the suitable sugarcane climate range was as follows: woodland > cropland > grassland > construction land > water. With the increase in climate suitability, the distribution of cultivated land expanded. From 1980 to 2005, cropland in suitable areas showed a fragmentation trend. By 2010, the cropland patches disappeared after fragmentation. (3) Due to landscape constraints, infertile soil, and labor costs, the sugar industry faces various challenges. The evaluation of climate suitability could provide a theoretical reference for a planting layout of sugarcane, and landscape pattern analysis of suitable sugarcane climate areas is conducive to the integration of small pieces of land into large ones, making mechanization possible. Overall, strict layout and management measures are required in sugarcane planting areas. [ABSTRACT FROM AUTHOR]