Dust storms are common in Mongolia and northern China, this is a serious threat to the ecological security and socioeconomic development of both countries and the surrounding areas. However, a complete quantitative study of the source area, affected area, and moving path of dust storm events (DSEs) in Mongolia and China is still lacking. In this study, we monitored and analyzed the spatiotemporal characteristics of the source area and affected areas of DSEs in Mongolia and China using the high-spatiotemporal-resolution images taken by the Himawari-8 satellite from March to June 2016–2020. In addition, we calculated the moving path of dusty weather using the HYSPLIT model. The results show that (1) temporality, a total of 605 DSEs occurred in the study area, with most of them occurring in April (232 DSEs), followed by May (173 DSEs). Spatially, the dust storm sources were concentrated in the arid inland areas such as the Taklimakan Desert (TK, 138 DSEs) and Badain Jaran Desert (BJ, 87 DSEs) in the western, and the Mongolian Gobi Desert (GD, 69 DSEs) in the central parts of the study area. (2) From the affected areas of the DSEs, about 60% of the DSEs in Mongolia started locally and then affected downwind China, as approximately 55% of the DSEs in the Inner Mongolia Desert Steppe and Hunshandake Sandy Land came from Mongolia. However, the DSEs in the TK located in the Tarim Basin of northwest China affected the entire study area, with only 31.3% belonging to the local dust. (3) From the moving path of the dusty weather, the dusty weather at the three meteorological stations (Dalanzadgad, Erlian, and Beijing), all located on the main transmission path of DSEs, was mainly transported from the windward area in the northwest, accounting for about 65.5% of the total path. This study provides a reliable scientific basis for disaster prevention and control, and has practical significance for protecting and improving human settlements.

Evapotranspiration (ET) plays an important role in the study of regional long-term water cycles. The water cycle in Mongolia has been seriously affected by global warming and the intensification of human activities. A significant relationship exists between climate factors and ET. In this paper, the temporal and spatial fluctuations and stability of ET in Mongolia from 2001 to 2020 were studied by using MOD16A2 ET, MOD13A2 NDVI and the climate data of ERA5-Land. ET trends were analysed by using the Breaks for Additive Season and Trend (BFAST) software package, Theil–Sen median trend analysis, Mann–Kendall method and Hurst index. The correlations between ET and temperature (Tem), precipitation (Pre), net solar radiation (Nsr), soil moisture (Swl) and human activities were determined by partial correlation analysis and a geographic detector. In the past 20 years, ET increased significantly in 49.4% of Mongolia, and NDVI also showed a significant increasing trend. BFAST detected two mutation years. ET decreased rapidly from 2006 to 2007 and increased rapidly from 2015 to 2016. In addition to winter, the meteorological factor that had a significant positive impact on ET in the east and west was Pre, whereas the impact of Tem was more obvious in central Mongolia. In winter, Tem had a great impact on ET. In the vegetation growing season, the joint action of NDVI and Pre greatly positively contributed to ET. The geographical detector showed that the influence of annual human factors on ET was weakened by changes in NDVI and Pre. In the growing season, Tem and Nsr increased nonlinearly to ET, and other natural and human factors showed bivariate enhancement. These results will help to understand the responses of ET changes to natural factors and human activities in Mongolia and provide data support for future research on ET and the water cycle.

Typical grassland is the core of the Mongolian Plateau grassland belt, and is also an important ecological barrier in the north of China. It is of great significance to explore the real-time changes in grassland climate for the prevention and control of climate disasters, and for ecological protection. In this study, the spatial and temporal variation of temperature, precipitation and maximum wind speed in typical Mongolian Plateau grassland were studied using observation data from 16 meteorological stations from 1978 to 2020, using the linear trend method, cumulative anomaly method, Mann-Kendall test, sliding t-test and Morlet wavelet analysis. The results show that: (1) The typical grassland temperature has been increasing at a rate of 0.4 °C/10a (p < 0.001) over the past 40 years, with the most significant warming in spring and summer; a sudden change from low to high temperature occurred in 1992; the annual average temperature gradually increased from northeast to southwest, with significant warming in the southwest. (2) Annual precipitation decreased slightly at a rate of −2.39 mm/10a, with the most significant decrease in summer precipitation; a sudden change from more to less precipitation occurred in 1998; spatially, precipitation decreased gradually from east to west, with significant moisture reduction in its northern part. (3) The maximum wind speed decreased significantly at a rate of −0.33m/s/10a (p < 0.001), with the most pronounced decrease in spring; the maximum wind speed changed abruptly from strong to weak around 1991; spatially, the annual average maximum wind speed decreased gradually from northwest to southeast and northeast, with the most pronounced decrease in the south and northeast. (4) The wavelet analysis shows that the typical grassland area will still be in a warm, low-rainfall and weak-wind stage in the coming years. Using the above analysis, the typical grassland climate of the Mongolian Plateau has shown a clear trend of warm and dry, weak wind in the past 40 years.

The phenological parameters estimated from different data may vary, especially in response to climatic factors. Therefore, we estimated the start of the growing season (SOS) and the end of the growing season (EOS) based on sunlight-induced chlorophyll fluorescence (SIF), the normalized difference vegetation index (NDVI) and the near-infrared reflectance of vegetation (NIRv). The SIF, NDVI and NIRv breakpoints were detected, and the trends and change-points of phenological parameters based on these data were analyzed. The correlations between the phenological parameters and snow-related factors, precipitation, temperature, soil moisture and population density were also analyzed. The results showed that SIF and NIRv could identify breakpoints early. SIF could estimate the latest SOS and the earliest EOS. NDVI could estimate the earliest SOS and the latest EOS. The change-points of SOS_SIF were mostly concentrated from 2001 to 2003, and those of SOS_NDVI and SOS_NIRv occurred later. The change-points of EOS_SIF and EOS_NIRv were mostly concentrated from 2001 to 2007, and those of EOS_SIF occurred later. Differently from the weak correlation with SOS_SIF, SOS_NDVI and SOS_NIRv were significantly correlated with snow-related factors. The correlation between the meteorological factors in the summer and autumn and EOS_SIF was the most significant. The population density showed the highest degree of interpretation for SOS_NIRv and EOS_NDVI. The results reveal the differences and potentials of different remote-sensing parameters in estimating phenological indicators, which is helpful for better understanding the dynamic changes in phenology and the response to changes in various influencing factors.

Sand and dust storms (SDSs) are particularly concerning natural disasters in East Asia. At present, there is still a lack of comprehensive knowledge of the characteristics of the cross-border SDSs between Mongolia and Northern China and the associated weather systems. This study identifies and documents the spring cross-border SDSs between Mongolia and Northern China based on the MODIS AOD map and Himawari-8/9 dust RGB images and analyzes the corresponding weather system types. A total of 76 spring cross-border SDSs were identified during 2000–2023, accounting for 55.1% of the total SDSs in both countries. The vast majority of the cross-border SDSs (86.8%) were related to Mongolian cyclones (MCs). Among them, 53.9% of the cross-border SDSs were mainly driven by Mongolian cyclones alone, and 32.9% were driven by the combination of MCs and cold highs (MC-CH type). Significant differences in the horizontal distribution of the SDSs were observed for different weather types. MCs alone trigger SDSs in the southern halves of the MCs, so the horizontal extent of the SDSs is consistent with that of MCs but larger than that associated with cold fronts. For the MC-CH type, strong winds in the southern flanks of MCs and their rear cold highs jointly drive a large-scale zonally extensive SDS belt. In recent years, particularly in 2021 and 2023, the strong cross-border SDSs have been dominated by the MC–CH type. This study provides a reference for the forecasting and early identification of cross-border SDS disasters.

Aeolian processes in temperate grasslands (TGs) are unique because the plant growth–decay cycle, soil water, and land-use interactions affect the seasonal and inter-annual changes in dust events. Land-use types in Inner Mongolian TGs are unique (settled grazing and grass mowing) compared with those in Mongolian TGs. Since 2003, land use has been controlled by grassland protection legislation, which is intended to prevent desertification and dust storms. In this study, we used process-based ecosystem (DAYCENT) and statistical modeling, along with dust event observations from March to June of 1981–2015, to (1) identify critical land surface factors controlling dust emissions (vegetation components, live grass, standing dead grass, litter, and soil moisture) at typical and desert steppe sites in Inner Mongolia and (2) estimate the impact of controlled land-use legislation on dust events. The DAYCENT model realistically simulated the dynamics of the observed vegetation components and soil moisture in 2005–2015. At both sites, similar significant correlations were obtained between spring dust events and wind speed or a combination of all surface factors that retained anomalies (memory) from the preceding year. Among the surface factors, vegetation was a critical factor that suppressed dust in Inner Mongolian TGs, similar to that in Mongolian TGs. In the desert steppe, standing dead grass had the strongest memory and was significantly correlated with dust events, whereas no significant correlations were observed in the typical steppe. This suggests that, in a typical steppe region, heavy grazing and mowing result in few dead grasses, thereby inhibiting the prevention of dust events. Moreover, the simulations of dust events under controlled (light grazing) and uncontrolled (heavy grazing) land-use conditions demonstrated that the grassland protection legislation reduced the occurrence of dust events in typical and desert steppe sites by 25 and 40%, respectively, since 2003.