Situated at middle-to-high latitudes with limited thermal resources, Northeast China is the primary maize-producing region in China. It is also one of the regions most significantly impacted by climate change. Given the persistent impact of climate change, it is crucial to elucidate the effects of the varying thermal conditions and low temperatures for different sowing dates on the growth, development, and grain maturity of spring maize. To ensure secure maize production and disaster prevention, choosing the optimal sowing time for spring maize holds significant implications for the judicious utilization of climatic resources, risk mitigation, and the provision of meteorological guidance. Moreover, it can serve as a technical reference for relevant departments to conduct climate evaluation, disaster monitoring, prediction, and assessment, as well as impact analysis of corn production safety. Additionally, it can provide meteorological evidence to ensure food security and promote the sustainable development of modern agriculture. An interval sowing experiment of spring maize was conducted in Harbin in the north of Northeast China. Two varieties were used in the experiment. Four sowing dates were set, and the interval between adjacent sowing dates was 10 days. The local perennial sowing time, 5 May, was set as the second sowing date, with one date set later and two dates set earlier. During the experiment, the growth process, grain dry matter, seed moisture content, yield components, and temperature of spring maize were observed. The impact of temperature conditions on maize growth and yield formation was analyzed in this paper through mathematical statistics, which further led to the establishment of a monitoring and evaluation model for assessing the effect of thermal conditions and temperature on maize. The results showed that the growth rate of spring maize was closely related to temperature. When the average temperature, minimum temperature, and maximum temperature increased by 1 °C, the average emergence rate increased by 1.05%, 0.99%, and 1.07%, respectively, and the average vegetative growth rate increased by 0.16%, 0.16%, and 0.09%, respectively. The change rate of ≥10 °C active accumulated temperature was significantly correlated with the change rate of the dry weight of the grain kernel, which conformed to the quadratic equation of one variable. The temperature influence coefficients of different sowing dates varied from 1.0% to 1.7%. The relationship between the accumulated values of 10 ℃ active accumulated temperature and the grain moisture content of spring maize was a logarithmic function. From 10 to 50 days after anthesis, the effect of temperature can explain about 95% of the change in grain moisture content. After physiological maturity, the effect of thermal conditions can only explain 56–83%. The temperature influence coefficient ranges from 1.3% to 13.8%. Comparatively speaking, the second sowing date is the most suitable sowing date. Early sowing is prone to encounter low temperatures, resulting in underutilization of the early heat, while late sowing is prone to less heat. Both conditions are not conducive to better improve the yield of spring maize.

In the context of global warming, a key scientific question for the sustainable development of the Arctic tourism industry is whether the region’s climate is becoming more suitable for tourism. Based on the ERA5-HEAT (Human thErmAl comforT) dataset from the European Center for Medium-range Weather Forecasts (ECMWF), this study used statistical methods such as climatic tendency rate and RAPS to analyze the spatial-temporal changes in Arctic summer climate comfort zones from 1979 to 2019 and to explore the influence of changes in climate comfort on Arctic tourism. The results showed the following: (1) With the increase in the Arctic summer temperature, the universal thermal climate index (UTCI) rose significantly from 1979 to 2019 at a rate of 0.457 °C/10a. There was an abrupt change in 2001, when the climate comfort changed from “colder” to “cool”, and the climate comfort has remained cool over the past decade (2010–2019). (2) With the increase in Arctic summer temperatures, the area assessed as “comfortable” increased significantly from 1979 to 2019 at a rate of 2.114 × 10⁵ km²/10a. Compared with the comfortable area in the 1980s, the comfortable area increased by 6.353 × 10⁵ km² over the past 10 years and expanded to high-latitude and high-altitude areas, mainly in Kola Peninsula, Putorana Plateau, and Verkhoyansk Mountains in Russia, as well as the Brooks Mountains in Alaska. (3) With the increase in Arctic summer temperatures, the number of days rated comfortable on 30% of the grid increased significantly from 1979 to 2019 (maximum increase: 31 days). The spatial range of the area with a low level of comfortable days narrowed and the spatial range of the area with a high level of such days expanded. The area with 60–70 comfortable days increased the most (4.57 × 10⁵ km²). The results of this study suggest that global warming exerts a significant influence on the Arctic summer climate comfort level and provides favorable conditions for further development of regional tourism resources.

This study analyzed temperature and yield data from 34 meteorological stations in Heilongjiang Province during 1961–2020. Four climate averages (P₁, P₂, P₃, and P₄) were determined based on their respective time distributions (1961–1990, 1971–2000, 1981–2010, and 1991–2020). The national standard temperature anomaly index was used to identify delayed chilling damage in rice cultivation compared to these climate averages. Climate tendency rate analysis, Mann–Kendall detection, and linear regression methods were employed to examine the relationship between temperature anomaly and rice yield from May to September. The results showed that there were noticeable differences in recognizing delayed chilling damage across different climate averages from 1961 to 2020. The average duration of chilling damage under P₁, P₂, P₃, and P₄ was, respectively, estimated as 8.5 years, 13.3 years, 21.4 years, and 30.9 years, with severe cold damage accounting for a significant portion (68.2–76.0%) of the total chilling damage period. The occurrence of severe cold damage increased significantly over time while light and moderate cold damage did not show a clear increasing or decreasing trend. Based on the test results, P₃ was found to be the most suitable climate average for identifying delayed chilling damage in rice cultivation from 1961 to 2020. Moreover, the incidence of chilling damage revealed declining trend over time. There was a high incidence of chilling damage in the 1960s and 1970s, followed by a decrease from the 1980s to the mid 1990s, and finally a low-incidence period after the mid-1990s. Spatially, the western regions experienced greater occurrence of chilling damage than the eastern regions. Additionally, there was a highly significant positive correlation (p < 0.01) between temperature anomalies from May to September and relative meteorological yield of rice. As temperature anomalies decreased during this period, there was an observed downward trend in relative meteorological yield of rice, indicating that delayed cold injury had a negative impact on rice production.

Agro-meteorological disasters are a significant cause of crop yield reduction. Northeast China is a major base for commodity grain production and is also highly sensitive to climate change. Early frost is one of the most significant meteorological disasters in Northeast China. The typical weather system serves as the primary meteorological cause of the occurrence of early frost. The Northeast Cold Vortex is a cyclonic system of certain intensity located in Northeast China, which has the potential to induce severe weather conditions such as extreme low temperatures and intense convection. Despite extensive research on the first occurrence of frost in Northeast China, the evolutionary characteristics under the combined influence of climate change and the Northeast Cold Vortex remain unclear. This limitation hinders the development of effective monitoring and early warning systems for early frost, as well as the formulation of disaster prevention and mitigation plans for crop production. Therefore, this study aims to objectively document the occurrence of early frost in maize crops in Northeast China from 1961 to 2021 under the influence of the Northeast Cold Vortex. It seeks to unveil the climatic characteristics and evolutionary patterns of early frost events in maize crops within this region, considering the impact of the Northeast Cold Vortex. Additionally, it endeavors to analyze the factors contributing to varying degrees of early frost caused by the Northeast Cold Vortex. The results showed that the occurrence of both early frost and frost influenced by the Northeast Cold Vortex exhibited a declining trend. Furthermore, there was also a decreasing proportion of initial frost attributed to the Northeast Cold Vortex, with a decline rate of 2% per decade, indicating a diminishing dominance of initial frost caused by this weather system. The onset date for the early frost under the influence of the Northeast Cold Vortex progressively advanced from southeast to northwest, occurring 4 days earlier than during the period from 1961 to 1990 between 1991 and 2021. While early frost displayed an increasing spatial distribution from southeast to northwest, it is noteworthy that the majority concentration of the Northeast Cold Vortex was observed in central regions, highlighting its predominant role in causing early frost in Northeast China.

This study focuses on the four typical agrometeorological disasters in cold regions that frequently occur during the flowering period of spring maize in Northeast China, namely low temperature, drought, waterlogging, and insufficient sunlight. By using meteorological data, spring maize growth period, yield, and yield composition, and integrating statistical analysis and machine learning techniques, the Compound Stress Occurrence Index of low temperature, insufficient sunlight, drought and waterlogging during the Spring maize flowering reriod in Cold Regions (MCSI) was defined and constructed, using the bald tip rate as a characteristic parameter. The relationship among disaster-causing factors, yield composition, and yield were established hierarchically, the entire compound disaster process was analyzed, revealing the impact mechanism of the compound stress on maize yield. Relevant evaluation models were established and threshold indicators were divided. The results indicated that the critical threshold values of the compound disaster indicators of light, moderate and severe levels during the spring maize flowering period in cold regions are [0.31, 0.42), [0.42, 0.52), and [0.52, 0.76], respectively, and the yield loss rates are [0.4%, 3.5%), [3.5%, 7%), and [7%, 17.5%], respectively. The verification results of 446 samples showed that the average proportion of stations with consistent or a one-level difference in yield loss grades is 88.3%. It indicated that this index was capable of evaluating the yield loss caused by compound disasters relatively well. The research findings can enrich the monitoring, early warning and assessment approaches of agrometeorological disasters in the high latitudes at the technical level, providing meteorological references for ensuring the safe production of spring maize in Northeast China and regional disaster reduction and efficiency enhancement.