In northern China, the transition zone affected by summer monsoon and its neighboring areas frequently experience drought events. Especially since the twenty-first century, the number of major drought events in this region has significantly increased, making it a notable drought-prone area known as the northern drought-prone belt (NDPB). Till now, major drought events in this area have profoundly impacted China’s historical progress and socioeconomic development. In fact, similar drought-prone belts are common in other monsoon transition zones globally, making it highly relevant and scientifically valuable to study the major drought issues in this region. Therefore, we discuss the major drought issues in the NDPB for the first time, comprehensively analyze the basic characteristics of the NDPB, systematically review the main stages of drought research in northern China, and identify scientific challenges currently faced in major drought research in the NDPB. Based on this and in line with the current forefront of Earth system science research, we outline five research directions and their basic approaches, including scientific experimental research focusing on major droughts in the NDPB, the impact of multifactor atmospheric circulation interactions on major drought formation, mechanisms promoting major drought development through the land–atmosphere coupling, the synergistic mechanisms of the atmospheric circulation and land–atmosphere coupling on major droughts, and fine monitoring technology and prediction methods for the full-chain progression of major droughts that have multifactor collaborative impacts. This research work holds significant scientific reference value for promoting innovative breakthroughs in the theory of major drought formation and monitoring and prediction techniques in northern China. Significance Statement: Since the twenty-first century, the northern China drought-prone belt has seen a significant increase in severe and extreme drought events. However, there has never been a dedicated discussion on the major drought issues in this unique region. Our manuscript is the first to propose the scientific concept of the northern China drought-prone belt. By understanding the basic characteristics of this region’s climate and environment and identifying the main scientific challenges encountered in major drought research, we suggest several key research directions and fundamental approaches. This work offers new insights into future in-depth studies on mechanisms behind major drought occurrences in northern China and methods for their monitoring and prediction.

Accurately obtaining the spatial distribution of soil moisture and its variability are the basis for the land-atmosphere interaction study. We investigated the fidelity of four satellite-based soil moisture products (AMSR2, CCI, SMAP, and SMOS) using in situ observation during the period 2019–2020. The spatial distribution and variability of different soil moisture products in northern China were analyzed for different seasons and climate zones. The satellite products showed the best performance of summer soil moisture with the bias and uncertainty of the three products (CCI, SMAP, and SMOS) being less than 0.041 and 0.097, whereas soil moisture showed a large bias in winter. For all seasons, AMSR2 and CCI demonstrated a positive bias whereas SMAP and SMOS showed a negative bias. CCI product had little bias in spring, summer, and fall in northern China, while SMAP and SMOS had the smallest bias in winter. For different climate zones, CCI product performed better in describing the temporal variability of soil moisture in arid climate zones with the correlation coefficients > 0.50 for most areas, while AMSR2 product provided a similar spatial distribution. In the eastern monsoon region, the soil moisture from SMAP and SMOS was found to have a large bias, whereas the bias in CCI product was small. Four products failed to reproduce the observed soil moisture characteristics in the transitional zones affected by the summer monsoon, with a positive bias found in AMSR2 and CCI and the largest biases in SMAP and SMOS products. We also suggest several reasons for the bias and error in the satellite soil moisture products. These results have important implications for soil moisture studies over midlatitude regions.

Due to the complex terrain, sparse precipitation observation sites, and uneven distribution of precipitation in the northeastern slope of the Qinghai–Tibet Plateau, it is necessary to establish a precipitation estimation method with strong applicability. In this study, the precipitation observation data from meteorological stations in the northeast slope of the Qinghai–Tibet Plateau and 11 geographical and topographic factors related to precipitation distribution were used to analyze the main factors affecting precipitation distribution. Based on the above, a multivariate linear regression precipitation estimation model was established. The results revealed that precipitation is negatively related to latitude and elevation, but positively related to longitude and slope for stations with an elevation below 1700 m. Meanwhile, precipitation shows positive correlations with both latitude and longitude, and negative correlations with elevation for stations with elevations above 1700 m. The established multivariate regression precipitation estimating model performs better at estimating the mean annual precipitation in autumn, summer, and spring, and is less accurate in winter. In contrast, the multivariate regression mode combined with the residual error correction method can effectively improve the precipitation forecast ability. The model is applicable to the unique natural geographical features of the northeast slope of the Qinghai–Tibet Plateau. The research results are of great significance for analyzing the temporal and spatial distribution pattern of precipitation in complex terrain areas.

Northern China is an ecologically fragile region, making it highly significant for studying the temporal and spatial variations of vegetation cover and their driving factors. In this study, we analyze the temporal and spatial variations of vegetation cover in northern China from 2001 to 2022 by using a kernel normalized difference vegetation index (kNDVI) dataset, and quantify the contributions of influencing factors by random forest. The results indicate that the spatial distribution of kNDVI in northern China follows a pattern of "low in the west and high in the east," with a gradual increase from west to east. The average kNDVI value for the study area is 0.144. Vegetation cover in northern China exhibits a fluctuating upward trend, with the northern Loess Plateau showing the highest rate of increase at 0.0032 per year and Southern Xinjiang and the Hexi Corridor showing the lowest rate of increase at 0.0003 per year. The average lag period of vegetation response to precipitation across different climate regions ranges from 0.5 to 2.2 months, while the average lag period for vegetation response to temperature ranges from 0.3 to 1.5 months. The response time of vegetation to precipitation is faster than that to temperature in the western arid zone, while in the transition zone influenced by the summer monsoon, vegetation responds more quickly to temperature than to precipitation. In the monsoon zone, the response times to precipitation and temperature are relatively similar. Precipitation is the dominant factor driving changes in vegetation cover, with an average contribution of 67.9%, although the contribution of kNDVI driving factors varies across different regions. This study provides valuable insights for guiding the restoration and sustainable development of ecosystems in northern China.