Qiang Zhang’s research while affiliated with Beijing Normal University and other places

The Yarlung Zsangbo Grand Canyon (YGC) in the eastern Himalaya is one of the deepest canyons in the world. Satellite precipitation products should be assessed and calibrated before their applications in this remote mountain area. A new rain gauge network was installed in the YGC in November 2018, since then the network observation data was utilized to calibrate the Integrated Multi-satellite Retrieval for Global Precipitation Measurements V06 Final Run product (IMERG-F). The evaluation demonstrated that the IMERG-F data reasonably captured the observed seasonal and diurnal variations in the precipitation but with much weaker seasonal and diurnal variations compared with the gauge data. The IMERG-F overestimated/underestimated the hourly light/heavy precipitation frequency, leading to a significant underestimation of daily and monthly rainfall amounts. The rainfall produced by the two layers of cloud in the mountainous region cannot be captured by the IMERG-F algorithm, which causes the underestimation of total rainfall. To address this issue, we applied a cumulative distribution function (CDF) calibration, which successfully reduced the mean bias of hourly and monthly rainfall for IMERG-F from −0.11 mm/hour and −95.0 mm/month, to 0.03 mm/hour and −5.2 mm/month. The mean biases of the daily light, moderate, and heavy rainfall decreased from −0.93, −1.02, and 4.71 to 0.13, −0.13 and 3.24 mm/day respectively. The CDF method can effectively correct the underestimation bias in IMERG-F. This study has implications for the application of satellite rainfall products to global mountain areas.

This study employs the meshfree Smoothed Particle Hydrodynamics (SPH) method to simulate the fluid–solid coupling process of gear meshing rotation with lubricating oil or oil jet lubrication fluids, considering the heat-transfer process under preset initial temperature conditions. While traditional grid methods face challenges in simulating the dynamic interaction between gear-meshing rotation and lubricating fluids, such as time-dependent contact in fluid–solid coupling and heat transfer, difficulties in handling meshing gaps, and the complexity of dynamic mesh setup, our approach leverages the unique advantages of meshless methods. In the established fluid–solid–heat coupling model, gears are considered as rigid bodies, and both fluids and gears are discretized into SPH particles, achieving fluid–solid coupling through the interaction between fluid particles and solid SPH particles. The model considers three cooling scenarios: oil pool cooling, oil jet cooling, and combined cooling. Simulation results show that oil pool cooling is more effective than oil jet cooling, but oil jet cooling can achieve localized spot cooling. The model exhibits good computational stability and efficiency in simulating the fluid–solid coupling and heat-transfer processes of gear rotation, oil jetting, and oil pool fluids. This study provides an effective numerical simulation method for gear lubrication cooling and has significant application potential for simulating complex scenarios such as gear operation and oil pool sloshing in coal mining machine arms. Compared to previous SPH work, this study couples a thermodynamic model in the simulation, thus enabling the modeling of fluid–thermal–solid coupled processes.

Lake areas across the Tibet Plateau have been taken as the major indicator of water resources changes. However, drivers behind spatiotemporal variations of lake areas over the Tibet Plateau have remained obscure. Selin Co Lake is the largest lake in the Qinghai–Tibet Plateau. Here, we delineate the Selin Co Lake area changes during the period of 1988–2023 based on Landsat remote sensing data. We also delved into causes behind the Selin Co Lake area changes from perspectives of glacier changes and tracing water vapor sources. We identified the persistently increasing lake area of Selin Co Lake. The Selin Co Lake area reached 2462.59 km² in 2023. We delineated the basin of Selin Co Lake and found a generally decreasing tendency of the main glaciers within the Selin Co basin. Specifically, the loss in the Geladandong Glacier area is 17.39 km² in total and the loss in the Jiagang Glacier area is 76.42 km². We found that the melting glaciers and precipitation within the Selin Co basin are the prime drivers behind the increasing the Selin Co Lake area. In the Selin Co basin, approximately 89.12% of the evaporation source of precipitation is propagated external to the Selin Co basin by the westerlies and the Indian monsoon. The internal hydrological circulation rate is 10.88%, while 30.61% of the moisture transportation is sourced from the ocean, and 69.39% is from the continental land. The moisture transportation from the ocean evaporation shows a significant increasing trend, which may contribute to the continued expansion of the Selin Co Lake area.

Introduction Global warming has led to an increase in the frequency and intensity of extreme weather events. In Hainan Province, a key tropical agricultural region in China, extreme temperatures significantly affect crop yields, quality, and the sustainability of the agricultural economy. Understanding the temporal and spatial patterns of extreme temperature events in Hainan Province is crucial for formulating effective strategies for mitigating meteorological disasters and safeguarding agricultural productivity. Methods This study uses observational data from 21 meteorological stations in Hainan Province from 1980 to 2022. Eight extreme temperature indices were calculated using the RClimDex model. Temporal and spatial characteristics of extreme temperature events were analyzed through linear fitting, Mann-Kendall mutation tests, Morlet wavelet analysis, and principal component analysis. Results The results reveal that extreme temperature events in Hainan Province show an overall increasing trend over time. Spatially, most stations exhibit a similar increasing trend in extreme temperature events. Two indices, Maximum Daily Temperature of the Year (TXx) and Number of Days with Lowest Temperature >20°C (TR20), display upward mutations, particularly between 2000 and 2011. Additionally, cyclical patterns in extreme temperature indices include short (4 years), medium (8–14 years), and long (16–20 years) oscillatory cycles. Discussion The study highlights that the primary drivers of temperature variations in Hainan Province are warm temperature indicators, with significant changes in daily maximum temperatures playing a key role. These findings emphasize the need for further investigation into the long-term effects of temperature variations on agricultural production and suggest potential pathways for disaster mitigation and adaptation strategies in the region.

The Yarlung Tsangbo Grand Canyon (YGC) is located in the southeastern Tibetan Plateau and often experiences heavy precipitation, which can cause flooding and landslides. The scarcity of meteorological observations in the YGC limits our understanding of the mechanisms behind heavy precipitation in this region. In this study, we conducted 1-km numerical simulations of six heavy precipitation events to uncover their common mechanisms. The effectiveness of both cumulus parameterization and orographic drag schemes was evaluated. The results indicated that the multiscale Kain-Fritsch scheme (MSKF) outperformed the no cumulus scheme (NO_CU) in at least four out of six events. Further evaluations of four precipitation intensities during the six events also revealed that MSKF has reduced overestimation of light precipitation (Mean Absolute Error, MAE, was decreased by 15.4%), and underestimation of moderate and heavy precipitation by NO_CU. In mountainous regions, including orographic turbulent drag is crucial for accurately simulating heavy precipitation. Thus, a Turbulence Orographic Form Drag scheme (TOFD), which precisely simulates the influence of orographic drag on local circulation, was used to further enhance the accuracy of heavy precipitation simulations. The MSKF plus TOFD model configuration shows more improvements than MSKF at hourly scale for the six heavy precipitation events in the YGC region. The improvements were mainly attributed to the implementation of TOFD. Therefore, the MSKF plus TOFD model configuration is recommended for predicting disastrous weather events in the YGC region.