Snow can alter soil water and heat conditions, affect the phenology and reproduction of vegetation. This study explores the influence and underlying mechanism of snow variations in winter and spring on the Fractional Vegetation Cover (FVC) during the growing season in Eurasia. Winter and spring snow variations exert distinct and regional dependent impacts on growing season vegetation in Eurasia. North of 55°N, persistent snow anomalies decrease May–June vegetation coverage through albedo–driven cooling and delayed soil thawing, while south of 55°N increased snowmelt enhances soil moisture and promotes vegetation growth. By July–August, snow primarily influences vegetation through a soil moisture legacy effect, leading to a generally positive correlation between snow and FVC across Western Siberia, Eurasian Far East, Central Asia. The main December–April snow mode features a south–north dipole, which modifies surface energy distribution and drives circulation anomalies that make two key regions (central and eastern Europe and western Okhotsk Bay) warm (cold). This enhances vegetation in positive anomaly years and inhibit it in negative anomaly years. This study indicates the critical role of seasonal snow in regulating vegetation dynamics across Eurasia and provides a scientific foundation for advancing our understanding of snow–climate–ecosystem interactions.

Snow cover can significantly influence climate via modulating surface energy balance, yet its cross-seasonal impacts on Arctic temperatures remain poorly understood. Here, based on diagnostic analysis and numerical experiments, we reveal a robust linkage between reduced early spring (March-April) snow water equivalent (SWE) in northern Europe and increased May-July (MJJ) 2-m air temperature over the East Siberian-Chukchi Sea during 1951-2022. Specifically, the March-April SWE negative anomaly can persist to June and result in drier surface conditions due to reduced snowmelt. It led to elevated turbulent heat fluxes and positive geopotential height anomalies over northern Europe via snow-albedo and snow-hydrological effects during April-June. Hence, the eastward-propagating wave train enhanced over northern Europe and reaches south Siberia, causing cyclonic activity and enhanced precipitation. The resultant soil moisture increases persist into MJJ, favoring less sensible heat fluxes, upward wave activity flux, and wave train poleward propagation. Finally, an anticyclonic anomaly appears over East Siberian-Chukchi Sea, enhancing anomalous descending motion, water vapor, and downward longwave radiation, collectively raising near-surface temperatures. Moreover, numerical experiments successfully reproduce this cascade of mechanisms, confirming the physical pathway. Our study provides a new perspective for the studies of the snow-cover climate effect, especially its impacts to the Arctic temperature variability.

Variations in snow cover could have profound impacts on regional and large-scale circulations and climate anomalies. Previous studies have focused on their effects on mid- to low-latitude weather without considering the impacts on the Arctic climate. Here, we propose that the snow cover in Europe and Central Siberia is an important land factor for the early spring 2 m temperature (T2m) interannual variability in the Barents-Kara Sea (BKS). In years when there is less snow over Europe and Central Siberia, there are positive radiative forcing at the surface, which can lead to elevated surface air temperatures, contributing to upward surface sensible heat flux anomalies. Correspondingly, anomalous anticyclones appear in the mid-upper troposphere, accompanied by enhanced southwesterly winds over the northern side of Europe and southerly winds over the western side of Central Siberia, enhancing the transport of atmospheric heat and moisture to the BKS and their conservation. Such variations consequently increase the downwelling longwave radiation and T2m over the BKS. Moreover, the negative correlation between Eurasian SWE and BKS T2m can be identified by most CMIP6 models and by multi-model ensemble (MME) results. Additionally, the multidecadal fluctuations in the Eurasian SWE-Arctic T2m connection are strongly out of phase with the PDO index, which can be effectively captured in the CMIP6 MME results. Furthermore, among two different PDO- periods, the BKS T2m were influenced mainly by variation in SWE in Central Siberia during P1 (1962-1977) and, conversely, were impacted mainly by variation in SWE in Europe during P3 (1999-2012).

The dynamic changes in vegetation significantly impact the sustainability, safety, and stability of ecosystems in the source region of the Yellow River. However, the spatiotemporal patterns and driving factors of these changes remain unclear. The MODIS NDVI dataset (1998–2018), together with climatic records from meteorological stations and socio-economic statistics, was collected to investigate the spatiotemporal characteristics of vegetation coverage in the study area. For the analysis, we employed linear trend analysis to assess long-term changes, Pearson correlation analysis to examine the relationships between vegetation dynamics and climatic as well as anthropogenic factors, and t-tests to evaluate the statistical significance of the results. The results indicated the following: (1) From 1998 to 2018, vegetation in the source region of the Yellow River generally exhibited an increasing trend, with 92.7% of the area showed improvement, while only 7.3% experienced degradation. The greatest vegetation increase occurred in areas with elevations of 3250–3750 m, whereas vegetation decline was mainly concentrated in regions with elevations of 5250–6250 m. (2) Seasonal differences in vegetation trends were observed, with significant increases in spring, summer, and winter, and a non-significant decrease in autumn. Vegetation degradation in summer and autumn remains a concern, primarily in southeastern and lower-elevation areas, affecting 25% and 27% of the total area, respectively. The maximum annual average NDVI was 0.70, occurring in 2018, while the minimum value was 0.59, observed in 2003. (3) Strong correlations were observed between vegetation dynamics and climatic variables, with temperature and precipitation showing significant positive correlations with vegetation (r = 0.66 and 0.60, respectively; p < 0.01, t-test), suggesting that increases in temperature and precipitation serve as primary drivers for vegetation improvement. (4) Anthropogenic factors, particularly overgrazing and rapid population growth (both human and livestock), were identified as major contributors to the degradation of low-altitude alpine grasslands during summer and autumn periods, with notable impacts observed in counties with higher livestock density and population growth, indicating that for each unit increase in population trend, the NDVI trend decreases by an average of 0.0001. The findings of this research are expected to inform the design and implementation of targeted ecological conservation and restoration strategies in the source region of the Yellow River, such as optimizing land-use planning, guiding reforestation and grassland management efforts, and establishing region-specific policies to mitigate the impacts of climate change and human activities on vegetation ecosystems.

With the transformation of the rural economy and the increasing national emphasis on forest resources, forestry management plays an increasingly important role in promoting household income growth and sustainable rural development. This study, based on a field survey of 1043 micro-level household data collected in Guizhou Province, China, empirically analyzes the impact of participation in forestry management on household income, income structure, and income inequality, as well as its underlying mechanisms. Using endogenous switching models, quantile regression models, and mediation effect models, the study reveals the following findings: First, participation in forestry management significantly enhances household income. Second, the impact of participation in forestry management on income structure varies, significantly increasing both forestry and non-forestry income, with the effect on forestry income being particularly pronounced. Third, participation in forestry management significantly alleviates income inequality, especially for low-income households. Fourth, forestry management indirectly increases household income and non-forestry income by promoting forest-based employment. Forest-based employment acts as a partial mediator in the effect of forestry management on household income and a full mediator in the increase in non-forestry income. The contribution of this study lies in its multidimensional approach to revealing the comprehensive impact of participation in forestry management on rural household income, providing important policy insights for increasing household income and achieving sustainable rural development.

Climate change adaptation in ecologically sensitive agriculture remains underexplored, especially regarding whether farmers’ climate perceptions translate into ecological production behaviors (EPBs). Using survey data from 730 tea farmers in China’s Wuyi Mountains National Park, this study examines how general and extreme climate change perceptions relate to EPB adoption. Employing Ordered Probit models and Karlson-Holm-Breen (KHB) mediation analysis, we estimate perception–behavior associations and test indirect effects through information-seeking and policy participation, alongside moderation by ecosystem service cognition and ecological production benefit cognition. The results indicate that both general and extreme climate perceptions are positively associated with EPB adoption (β = 0.406 and 0.626, p < 0.01), with extreme perceptions showing significantly stronger effects. Climate perceptions influence EPB adoption across all dimensions (green production, ecological management, and market-based practices). Information-seeking and policy participation function as complementary mediating pathways (combined indirect effects = 0.101 and 0.117), linking climate perceptions to ecological actions. Moreover, higher ecosystem service cognition and ecological production benefit cognition strengthen the perception–behavior relationships across multiple EPB dimensions. Overall, the findings suggest that climate change perceptions are an important driver of farmers’ ecological production choices in high-ecological-value contexts. Interpreted alongside existing adaptation strategies, EPB may enhance resilience by leveraging ecosystem functions while aligning with market incentives for ecological products. These results underscore the value of policies that improve access to ecological training and market information and support demonstration programs that facilitate experiential learning.

Snow is considered a climate indicator. The Qinghai-Tibet Plateau (QTP) is covered largely with typical alpine snow, influencing the local water-heat balance and the surrounding regional climate. However, there are large uncertainties in land surface snow data. A comprehensive, quantitative multimetric evaluation is an urgent need. In this study, five snow datasets are comprehensively evaluated on the basis of station-observed snow depth data. The temporal and spatial variations in snow depth over the QTP from 1979 to 2022 are analysed, and a new indicator is proposed to represent the overall snow variation on the QTP in a more reasonable way. The main conclusions are as follows: (1) In terms of snow depth on the QTP, the China Long Time Series Snow Depth dataset (CLSD) has the best performance, followed by ERA5-Land and NOAA (V3). The bias of the Northern Hemisphere Long Time Series Day-by-Day Snow Depth dataset (NHSD) is small compared with the observation. (2) The first EOF mode of snow depth on the QTP, in annual, autumn, winter and spring, shows a reversal spatial distribution between the main area of QTP and the northwestern Hengduan Mountains. The main area of QTP in snow depth has a decreasing trend, and the northwestern Hengduan Mountains in snow depth has an increasing trend. (3) After detrending, the main characteristic of EOF mode in snow depth on the QTP is consistent variations throughout the region. The variation indicator of snow depth on the QTP (QTPSDI) reflects the variation of the snow depth over the overall plateau. The QTPSDI has a significant 2-7 year periodicity. Therefore, we emphasise that the selection of accurate and applicable snow data is as important as the reasonable representation of snow cover variations.

There are teleconnections between snow water equivalent (SWE) and sea surface temperatures (SSTs). Mainly on the basis of ERA5, ERA5-land, HadISST datasets, the characteristics of the interdecadal responses of Eurasian SWE in winter and spring to Northern Hemisphere sea surface temperatures (NHSSTs) in winter are investigated. From 1951 to 2021, a "west-east" SWE dipole pattern persisting from winter to spring was detected over Eurasia. Two main modes of the response of SWE in winter and spring to changes in NHSSTs in winter were identified. The first mode results in opposite variations in SWE in Europe and central Eurasia. When the North Atlantic and Northwest Pacific SSTs increase in winter, anomalies in atmospheric circulation, integrated vapour transport (IVT) and ground conditions are conducive to increases in winter and spring SWE over Europe. Because of the decreases in IVT and precipitation, the SWE in central Eurasia decreases in winter and spring. The second mode describes a significant reverse change between the SWE over Eurasia and the Northeast Pacific SSTs, and the North Atlantic SST is in tripole mode. This mode has a quasi-16-year period. When winter SSTs increase in the Northeast Pacific, the troughs and ridges in Eurasia weaken, and anomalies in air temperature and precipitation lead to a decrease in SWE in winter and spring.

Biological soil crust (biocrust) is regarded as a self-organizing principle, and widely distributes in the Tibetan Plateau, which is a crucial ecological security area of China and water towel of Asia. Unfolding biocrust distribution in the region is critical to maintain ecosystem functions and services therein. However, we know little about explicit distribution of biocrust in the Tibet Plateau. To that end, this study combined field survey, reference compiling and random forest algorithm to explore the spatial distribution of biocrusts on Tibetan Plateau and the associated driving factors. A total of 203 data points had been collected. We found that the biocrusts cover up to 20% of the soil surface in the Tibetan Plateau and mainly cover the Qaidam Basin and the northern Tibetan Plateau, but less in the Qiangtang Plateau and the southeastern Tibetan Plateau.The dominating factors affecting biocrust distribution are soil clay content, altitude, average temperature of the hottest season, pH, and soil organic carbon content. Specifically, biocrust acclimatization is positively affected by lower soil clay content and elevation, hotter quarter temperatures (especially greater than 8°C), and greater pH, while negatively affected by higher soil organic carbon content. Overall, this study sheds light on biocrust distribution in the Tibetan Plateau, and will significantly expand our understandings of biocrusts.

Facilitating the sustained and stable growth of farmers’ income is crucial for achieving sustainable development in forest regions. As an emerging driving force, the digital economy has demonstrated substantial potential in enhancing farmers’ income and promoting regional economic prosperity in forest areas. Based on survey data from 1043 households across 10 counties in Guizhou Province, China, this study empirically examined the direct and indirect effects of digital economy participation on income growth among farmers in forest regions. The findings revealed that, first, participation in the digital economy significantly contributed to income growth for these households. This effect remained robust across various estimation methods, restricted sample tests, and when replacing dependent variables. Second, forestry management and its diversification played a mediating role in the relationship between digital economy participation and farmers’ income. Participation in the digital economy indirectly influenced income growth by fostering forestry management activities and their diversification. Third, the heterogeneity analysis indicated that digital economy participation had a significant positive impact on the income growth of pure farming households, part-time farming households, and households that had previously escaped poverty. This discovery underscored the unique role of the digital economy in alleviating poverty and preventing its recurrence. The conclusions of this study provide essential theoretical and practical guidance for empowering forestry development through the digital economy and advancing the digital transformation of the forestry industry. More critically, this research presents a novel pathway for the deep integration of the digital economy with forestry, jointly fostering income growth for farmers in forest regions, which holds significant implications for achieving rural sustainable development.

Cold surges(CSs)often occur in the mid-latitude regions of the Northern Hemisphere and have enormous effects on socioeconomic development.We report that the occurrences of CSs and persistent CSs(PCSs)have rebounded since the 1990s,but the trends related to the frequencies of strong CSs(SCSs)and extreme CSs(ECSs)changed from increasing to decreasing after 2000.The highest-ranked model ensemble approach was used to project the occurrences of various CSs under the SSP1-2.6,SSP2-4.5,and SSP5-8.5 scenarios.The frequencies of the total CSs show overall decreasing trends.However,under the SSP1-2.6 scenario,slight increasing trends are noted for SCSs and ECSs in China.Atmospheric circulations that are characterized by an anomalous anticyclonic circulation with a significantly positive 500-hPa geopotential height(Z500)anomaly at high latitudes along with significant negative anomalies in China were favorable for cold air intrusions into China.In addition,the frequencies of all CS types under the SPP5-8.5 scenario greatly decreased in the long term(2071-2100),a finding which is thought to be related to negative SST anomalies in the central and western North Pacific,differences in sea level pressure(SLP)between high-and mid-latitude regions,and a weaker East Asian trough.In terms of ECSs,the decreasing trends observed during the historical period were maintained until 2024 under the SSP1-2.6 scenario.Compared to the SSP1-2.6 scenario,the Z500 pattern showed a trend of strengthened ridges over the Ural region and northern East Asia and weakened troughs over Siberia(60°-90°E)under the SSP2-4.5 and SSP5-8.5 scenarios,contributing to the shift to increasing trends of ECSs after 2014.

Understanding the response of the ecological well–being to ecosystem services of urban green space is imperative for urban ecosystem conservation and management. However, few studies have focused on the response process and spatial relationship of ecological well–being to ecosystem services of urban green space in mega cities, while residents’ demand and evaluation of ecological well–being have not been fully considered. In this study, the ecological well–being evaluation index system was developed through integrating subjective and objective indicators. Using the main urban area of Beijing as an example, our results indicate that from 2015 to 2023, the ecological well–being has been continuously increasing. Moreover, this study indicated that the coupling and coordination degree between ecological well–being and ecosystem services of urban green space still need to be improved. In addition, three modes of spatial relationship were identified in this study: high coordination area, moderate coordination area, and low coordination area. The finding extracted from these spatial relationship models should provide references for urban green space planning to maintain sustainable urban ecosystem conservation and management.

Snow is an indicator of climate change. Its variation can affect surface energy, water balance, and atmospheric circulation, providing important feedback on climate change. There is a lack of assessment of the spatial characteristics of multi-source snow data in Eurasia, and these data exhibit high spatial variability and other differences. Therefore, using data obtained from the Global Historical Climatology Network Daily (GHCND) from 1980 to 2018, snow depth information from ERA5, MERRA2, and GlobSnow is assessed in this study. The spatiotemporal variation characteristics and the primary spatial modes of seasonal variations in snow depth are analyzed. The results show that the snow depth, according to GlobSnow data, is closer to that of the measured site data, while the ERA5_Land and MERRA2 data are overestimated. The annual variations in snow depth are consistent with seasonal variations in winter and spring, with an increasing trend in the mountains of Central Asia and Siberia and a decreasing trend in most of the rest of Eurasia. The dominant patterns of snow depth in late autumn, winter, and spring are all north–south dipole patterns, and there is overall consistency in summer.

Under the dual pressures of climate change and human activities, the restrictions imposed by conservation policies, along with the increasing overlap between wildlife protected areas (PAs) and community living areas, have intensified the contradictions and conflicts between PAs and surrounding communities. Effective governance of such conflicts is particularly crucial to reconciling the contradictions between conservation and development. This study takes the Mikumi–Selous areas in Tanzania, Africa, as a case study. Through questionnaires and semi-structured interviews, it explores the current state of conflicts between PAs and communities in the study area and summarizes conflict governance measures. Moreover, this research focuses on identifying various factors that influence the conservation willingness and action of community residents, further validating the relationships between residents’ household characteristics, conservation costs and benefits, conservation cognition, willingness, and behaviors through empirical analysis methods. The results indicate that residents’ conservation cognition significantly positively impacts their conservation willingness and behaviors, while conservation willingness also positively affects their conservation behaviors. Additionally, it was found that conservation costs inhibit residents’ conservation willingness and behaviors. This study primarily explores, from a community governance perspective, the participation willingness and behaviors of core stakeholders in conflict governance, emphasizing the critical role of community involvement in achieving biodiversity conservation and coordinated community development and providing a new perspective for alleviating conservation and development issues.

Humans and elephants inevitably encounter competition over resources in the elephant habitat. Due to different social development conditions, there may be differences in how humans and elephants coexist in different regions, mainly reflected in the attitude toward elephant conservation and the ability to cope with conflicts. By comparing human-elephant conflicts in different regions, it helps to explore the long-term coexistence path between humans and elephants. This paper selects the Xishuangbanna National Nature Reserve in China, the habitat of Asian elephants (Elephas maximus), and the Nyerere-Selous-Mikumi region in Tanzania, the habitat of African steppe elephants (Loxodonta africana), as the study area, and assesses the current situation of human-elephant conflict in the study area through semi-structured interviews and questionnaires, to understand the residents' perception of the conflict and the willingness of residents to protect elephants, and empirically analyze the factors affecting the residents' willingness to protect. The results showed that the types of human-elephant conflicts in the Xishuangbanna (China) and the surrounding areas of the Nyerere-Selous-Mikumi ecosystem in Tanzania were similar, and the respondents in the Xishuangbanna region (China) suffered more losses but had a stronger willingness to protect elephants. Besides, residents that are less impacted by conflict, have higher household incomes and more diversified livelihood sources are likely to have a stronger willingness to protect the elephant. This study emphasizes the role of socioeconomic development and governance capacity enhancement in mitigating human-elephant conflict, providing a richer perspective on the governance of human-elephant conflict.

Promoting the development of eco-industries plays a significant role in achieving the harmonious symbiosis between economic growth and environmental protection as well as enhancing the comprehensive effectiveness of ecological and economic benefits. Due to their unique nature, cooperatives may play a crucial role in facilitating the integration between farmers and the development of eco-industries. To investigate whether cooperatives possess the capacity to enhance the income-generating effects for farmers involved in eco-industries, this study selected the Crested Ibis National Nature Reserve (CINNR), a representative area for eco-industry development, as the research site. Data were gathered through face-to-face interviews, and this research empirically analyzed the impact of cooperatives on the income-generating effect of farmers using endogenous switching regression (ESR). The findings are threefold. First, cooperatives indeed enhance the income-generating effects for farmers engaged in eco-industries. Second, variables such as the distribution of agroforestry materials, premium capacity, soil quality, and status of village cadres have a positive impact on farmers joining cooperatives, whereas punishment initiatives discourage their participation. Third, for farmers who have joined cooperatives, factors such as the distribution of agroforestry materials, premium capacity, low-cost conservation initiatives, land area, status of village cadres, the proportion of labor force, technical training, soil quality, and land area positively affect their income from eco-industries. Conversely, punishment initiatives, age, and land location negatively impact their income. The results of this study provide new ideas for farmers to participate in the development of eco-industries, new evidence showing co-operatives can improve farmers’ income, and new directions for coordinating conflicts between conservation and development in protected areas.

Protected areas (PAs) are key areas for biodiversity conservation, and at the saµe tiµe they are also ecologically fragile areas. Therefore, proµoting farµers around PAs to practice pro−environµental behaviors (PEBs) in agroforestry production, resource utilization and biodiversity conservation is an effective way to help rural revitalization, and it is also an inevitable choice to protect the ecological environµent. Also a critical topic in global studies on environµental issues. This paper aiµed to deterµine whether the behavioral choices of farµers around PAs in China were influenced by social preferences. This study used factor analysis to categorize PEBs into both public and private spheres. A coµbination of cluster saµpling and randoµ saµpling was used to deterµine the respondents in each village. Additionally an intercept regression µodel was used to estiµate the effect of social preferences on different doµains of PEBs of farµers in the PAs. And further subgroup analysis was done for different age and different incoµe. The results show that (i) altruistic preferences, institutional trust, and interpersonal trust proµote the iµpleµentation of PEBs in both the public and private spheres, and that altruistic preferences and institutional trust have a stronger influence on PEBs in the private sphere. (ii) Froµ the perspective of incoµe disparity, altruistic preferences and institutional trust have µore significant incentive effects on the PEBs of households in the higher−incoµe group, and interpersonal trust has a stronger proµotional effect on the PEBs of faµilies in the lower−incoµe group. (iii) Froµ the perspective of generational differences, altruistic preference and institutional trust have a µore pronounced incentive effect on the PEBs of faµilies in the younger age group, and interpersonal trust has a stronger proµotional effect on the PEBs of faµilies in the older age group. Therefore, good social norµs should be established to stiµulate the altruistic culture of “love” and “benevolence” to precisely strengthen the awareness and responsibility of farµers to ensure environµental protection and biodiversity conservation.

Existing land surface models still have large error in the simulation of surface albedo. At present, introducing the influence of meteorological factors into the albedo parameterization scheme is an effective way to improve the albedo simulation. However, the improvement of the vegetation canopy surface albedo parameterization scheme is still insufficient. Therefore, based on the radiation and meteorological observation data during 1 November 2015-30 April 2018 from a land-atmosphere interaction observation tower in a typical secondary evergreen broadleaved forest in Southern China, this study firstly analyzed the influencing factors of canopy surface albedo. It was found that the solar elevation angle and air relative humidity are two key factors influencing the canopy surface albedo, and the impact of the solar elevation angle on canopy surface albedo is not exactly the same on diurnal and seasonal scales. Then, two new canopy surface albedo parameterization schemes of additive form and multiplicative form were proposed and introduced into CLM5 model for single point simulation. Results show that the adoption of newly developed canopy surface albedo parameterization schemes can improve the simulation of diurnal and seasonal variations of albedo and reduce the overestimation of the simulation of near-infrared radiation albedo and visible radiation albedo in the CLM5 model, then significantly reduce the root mean square errors of reflected solar radiation and net radiation simulation. Surface albedo is an important factor affecting the heat exchange between land and atmosphere, and is critical for weather forecasting and regional climate modeling. At present, even in some complex land surface models, the canopy surface albedo parameterization scheme only considers the variation of leaf and stem index and the cosine of the solar zenith angle over time but does not take into account the effect of meteorological factors. In this study, two newly developed canopy albedo schemes that take into account the effects of solar elevation angle and air relative humidity were developed, and then introduced into the CLM5 model for single point simulation. The results show that the new canopy albedo scheme can indeed improve the simulation skills of the reflected solar radiation. The results emphasize the important influence of meteorological factors on the surface albedo, and the findings may provide a base to further develop and improve the CLM5 model. Two new canopy surface albedo schemes considering the influence of solar elevation angle and air relative humidity are proposedThe new canopy surface albedo schemes can reduce the canopy surface albedo of evergreen broad-leaved forest overestimated by CLM5 model

Study region: The arid area of Northwest China. Study focus: This study aims to explore the lagged effects of snow on extreme precipitation and the associated mechanisms by using composite analysis and extracting significant areas. Due to the complex terrain of the study area, we have explored the response of soil temperature, soil moisture, and various energy changes in different sub-regions, these explorations are conducted in conjunction with the study of lagged effects of snow on extreme precipitation and provide a reference for future climate prediction. New hydrological insights for the region: The response pathways of soil and energy are explored during the impact of snow on extreme precipitation in different significant areas. Latent heat flux is the main energy source, but sensible heat flux and effective radiation can also become the local dominant energy sources due to the influence of many environmental factors. Differences in the paths of influence in different regions will result in different atmospheric circulation anomalies. When the low-value system appears, it is more likely to cause extreme precipitation.