This study investigated the response of the ionospheric electron temperature (T-e) over Sanya to the super geomagnetic storm of May 2024. The observations, conducted with the Sanya Incoherent Scatter Radar (SYISR; 18.3 degrees N, 109.6 degrees E, dip latitude: 12.8 degrees N) using a zenith-directed uncoded long pulse, provided the T-e from May 10 to 12, 2024. On May 11, the daytime (nighttime) T-e at 400 km increased similar to 40% (similar to 30%) relative to the quiet-time reference, and a wave-like variation of T-e was also observed. On May 12, a unique T-e increase occurred above similar to 270 km, with the T-e at 400 km increasing similar to 90% relative to the quiet-time reference and remaining increased for similar to 7 hr. Further Thermosphere Ionosphere Electrodynamics General Circulation Model (TIEGCM) simulations reproduced the observed T-e relatively well under realistic geophysical conditions. The TIEGCM simulations indicated that the decrease in the ionospheric electron density, which was associated with the unique T-e increase, was dominated by chemistry at similar to 270-380 km, while E & times; B drifts and neutral winds contributed most successively at higher altitudes. The simulations also revealed that the relative contribution of the electron-neutral cooling was comparable with that of the electron-ion cooling at 400 km and 09:00 LT on May 12, when the unique T-e increase mainly occurred.

The heaviest stable nuclei in the universe owe their existence to quantum shell structure, the grouping of protons and neutrons into discrete energy levels separated by gaps. The largest known neutron shell gap in stable nuclei, at N=126, stabilizes doubly-magic ^208Pb and is responsible for the characteristic abundance peak of heavy elements near gold and platinum produced by the rapid neutron-capture process (r-process). Whether this shell gap persists as protons are removed from lead is a question central to both nuclear structure and the modeling of heavy-element synthesis, yet it has remained unanswered due to the extraordinary difficulty of producing the relevant neutron-rich nuclei. Direct experimental knowledge in this region was essentially absent. Here we report the first precision mass measurements of ^203,204Pt and ^204,205,206Au, performed at GSI using a novel combination of Schottky and isochronous mass spectrometry in a heavy-ion storage ring. The N=126 isotones ^204Pt and ^205Au are more strongly bound than the extrapolated trend of the previously known mass surface by 403 and 464 keV, respectively, revealing an unexpectedly enhanced N=126 shell strength below doubly-magic ^208Pb. Furthermore, the proton-neutron interaction strength exhibits a hitherto unobserved bifurcation at N=126 as protons are removed from ^208Pb. Our results redefine the nuclear mass surface in the neutron-rich heavy-element region and provide direct experimental benchmarks for theoretical models whose extrapolations toward more exotic nuclei are essential for r-process nucleosynthesis calculations.

The bright band (BB), a critical zone where solid precipitation transforms into liquid precipitation, plays a significant role in radar quantitative precipitation estimation (QPE) and drop size distribution (DSD) analysis. Existing studies of the BB have been mainly conducted in low and middle altitude areas, while studies in extremely high lands are still insufficient. This study systematically investigates the bright band characteristics in the Nam Co (4718 m above sea level) area on the Tibetan Plateau (TP) through integrated analysis of X-band dual-polarization radar and Micro Rain Radar (MRR) data, focusing on four aspects: optimization of the BB identification methods, geometric characteristics, polarimetric characteristics, and convective features embedded within the BB. The dual-polarization vertical profile reflectivity (dPVPR) BB identification algorithm was optimized and applied to analyze the BB characteristics of 14 precipitation cases in 2024. The results reveal that the BB in Nam Co area exhibits distinct characteristics: compared to low-altitude areas, it occurs at a lower height above ground level (253 to 614 m), and its thickness ranging from 448 to 774 m. Moreover, this study found that Lake Nam Co significantly influences the BB characteristics. The thermal-induced local convection over Nam Co can trigger the formation of extensive graupel clusters near the BB height, which in turn forms an area with abnormally high reflectivity. These findings not only enhance the understanding of precipitation microphysical processes in high altitude areas but also provide theoretical basis for developing precise QPE algorithms for the TP.

Abstract On the basis of observations from Sanya incoherent scatter radar (SYISR), we investigated the vertical structures of multiple medium‐scale traveling ionospheric disturbances (MSTIDs) over low latitudes on December 28, 2022. Nine MSTIDs were observed to occur continuously during the night (17:18–00:18 LT) at 150–250 km altitude. These MSTIDs are generated by gravity waves (GWs) propagating from the lower atmosphere. Among them, five GWs exhibit periods of 34–49 min and horizontal phase velocities of 148–324 m/s, while the remaining four displayed periods of 17–22 min and horizontal phase velocities of 134–276 m/s. 8 of 9 GWs propagated northwestward with azimuths of 289°–339°, whereas one 4th GW propagated northeastward at an azimuth of 59°. Three‐dimensional reconstructions of the multiple MSTIDs reveal phase fronts that initially appeared at higher altitudes and subsequently at lower altitudes, which is consistent with the phase progression of upward‐propagating GWs. All GWs exhibit downward vertical phase velocities of 91–265 m/s and amplitudes of ∼3%–9%. The vertical and horizontal wavelengths of these GWs increased with altitude, whereas the periods and amplitudes initially increased with altitude, peaked near the bottom of the F layer, and then decreased. This altitudinal variation reflects the dissipative filtering of upward‐propagating GWs through viscosity and thermal conduction. Ray‐tracing results suggest that the nine MSTIDs likely originated from secondary waves, which were excited by primary waves generated by deep convection.

Sedimentary organic carbon (SeOC) plays a critical role in carbon (C) sequestration in riparian zones, yet its accumulation and stability are influenced by complex hydrodynamic processes such as flooding and erosional sorting. However, it remains poorly understood as to how varying flooding intensities (the relative duration of submergence caused by water level fluctuations) across different elevations and in turn the size sorting processes perturb the sources, composition and stability of SeOC. Sediments were collected across the riparian zone of the Three Gorges Reservoir from three flooding intensities: strong, intermediate, and weak corresponded to the elevation intervals of 145-155 m, 155-165 m, and 165-175 m. The sediments were subsequently fractionated into four size classes according to their settling velocities to determine size-specific SeOC content, chemical compositions, thermal stability and delta 13C signature. The results indicated that, the proportion of the 63-250 mu m fractions at weak and intermediate flooding intensity was 39.8%-51.1% and 5.9%-15.9% lower, respectively, than that with strong flooding intensity. The delta 13C signatures and the contribution of soil-derived C decreased but the SeOC thermal stability and the contribution of C3 plant and phytoplankton increased with stronger flooding intensity. In addition, the TG-T50 values (the temperature resulting in 50% of organic matter loss) were positively related to the C--C/C--O ratios, but negatively associated with the C-H/C--O ratios. The accumulation of fine sediment particles with greater SeOC stability at stronger flooding intensity highlights the decisive role of flooding regimes in determining the sources, chemical composition and thermal variations of SeOC across different elevations. Thus, accurate quantification of SeOC dynamics in riparian zones necessitates consideration of both flooding perturbations and erosional size fractionation.

Given the vast expanses of bare soil and sparse grassland in the central and western Tibetan Plateau (CWTP), the duration of precipitation serves as a critical control on key hydrological and geomorphological responses, such as runoff generation, soil erosion, and sediment transport. This study analyzes the spatial distribution of precipitation events with different durations (short-duration, medium-duration, and long-duration) across the Tibetan Plateau (TP). To explore the differences in precipitation duration between the central-western and eastern TP, we utilize hourly precipitation data from a newly established cross-sectional rainfall observation network (53 gauges) on the CWTP and the China Meteorological Administration observation (145 gauges) on the eastern TP for comparison. The main conclusions are as follows: First, short-duration (1-3 h) precipitation events contribute more than 50% of the total rainfall in the CWTP. In contrast, short-duration events contribute less than 30% in the eastern TP, where medium- and long-duration precipitation events dominate. Second, the reanalysis data ECMWF reanalysis 5 and the high-resolution atmospheric simulation data high asia refined analysis version 2 tend to systematically underestimate (overestimate) the contribution of short-duration (long-duration) precipitation events. Specifically, they exhibit mean biases of 23% and 19% for short-duration precipitation, and 34% and 20% for long-duration precipitation, respectively. Third, the satellite remote sensing precipitation data integrated multisatellite retrievals perform well in estimating the contribution of precipitation events, with biases mostly within 30% . By comparing the original and gauge-calibrated satellite datasets, the results show that calibration with coarse temporal resolutions (daily or monthly) does not necessarily improve the identification of short-duration precipitation events. Our results not only enhance the understanding of precipitation characteristics and processes over the TP, but also provide valuable guidance for hydrological modeling and the evaluation and improvement of satellite-based precipitation data.

Previous observations have demonstrated that rocket exhaust can trigger ionospheric electron density holes and cause electron temperature enhancements during launches. Using high-precision measurements from the Sanya incoherent scatter radar, we discovered a previously overlooked decrease in electron temperature. We report a daytime event and a nighttime event. During daytime, the electron temperature first decreased sharply by similar to 650 K within 5.5 min, then increased by similar to 1000 K before gradually recovering over similar to 1 hr. Multi-beam observations indicated that this cooling was localized near the rocket trajectory, much narrower than the accompanying electron density depletion. Moreover, the ion temperature increased by 550 K. The nighttime electron and ion temperatures decreased by similar to 450 and similar to 150 K, respectively, without subsequent electron temperature increase. Analysis indicated that these temperature perturbations resulted from the initial expansion cooling following the exhaust injection and the subsequent hole formation, which disrupted the thermal equilibrium in the ionosphere.

Sporadic E (Es) layer plays essential role in ionosphere-atmosphere coupling. Theoretical simulations show that the atmospheric gravity waves (GWs) in the lower thermosphere are the main modulatory source on Es dynamics at small spatial scales and short periods. Based on Sanya Incoherent Scatter Radar, direct observational evidence for the mesoscale GW modulations on low-latitude Es layer is firstly obtained by four-dimensional electron density with extreme fine resolutions of 37.5 m in range and 50 s in time. The wave-like horizontal structures, with similar to 10 min period and similar to 55 km wavelength, indicate the typical features of mesoscale GWs. Our results confirm that, interacting with the background tidal winds, the upward propagating GWs modulate the horizontal structures and drift velocity of Es layers at different altitudes with increasing amplitude to cause the rapid oscillations in range.

Real-time broadband communication (RTBC) scenarios, such as cloud virtual reality and 8K live streaming, further raise the criteria of the performance triangle, requiring video bitrates exceeding 30 Mbps, tail delay below 50 ms, and fairness guarantees for multi-user concurrent access. Based on our testing and analysis, existing RTBC-oriented rate control solutions, including end-to-end algorithms and network-assisted algorithms, fail to simultaneously satisfy all performance metrics. The native dynamic delay and physical-layer resource allocation strategy inherent to the 5G radio access network (RAN) are the key reasons. These solutions lack adaptation to the 5G architecture, leading to reduced decision performance. This paper proposes Choir, an innovative collaborative solution mainly deployed on 5G base stations that deeply integrates 5G radio characteristics and video streaming traffic patterns to guide efficient sender-side rate control. Extensive simulation and testbed evaluations demonstrate Choir's significant performance in achieving high average bitrate, low tail delay, and inter-flow fairness across different 5G network scenarios.

Monitoring species-level vegetation dynamics within mountainous riparian zones is challenging due to hydrological variability, intricate terrain, and fragmented vegetation corridors, which amplify mixed-pixel effects. Consequently, sub-meter imagery is conventionally deemed necessary, yet high costs and limited availability constrain continuous monitoring under such dynamic conditions. This study evaluates the feasibility of using meter-scale satellite imagery (PlanetScope) for species-level monitoring in these dynamic environments. Specifically, we investigate whether dominant species coverage (CDS) can be accurately mapped by combining multiple machine learning models. To mitigate the pronounced temporal variability driven by fluctuating water levels, we further assess the efficacy of a multi-temporal integration (MTI) strategy to stabilize these species-level vegetation signals. Results indicate that single-date predictions are highly sensitive to acquisition timing, with R2 varying from 0.53 to 0.90 due to meteorological conditions, water-level fluctuations, and phenology. In contrast, the MTI strategy markedly enhanced prediction accuracy and temporal consistency by integrating multi-date predictions. For the best-performing model, MTI increased the R2 to 0.91 and reduced the RMSE to 0.09, with initially lower-performing models exhibiting greater relative improvements after integration. Overall, the results demonstrate that meter-scale satellite imagery, when integrated with frequent temporal sampling, can yield reliable species-level data in narrow and heterogeneous riparian environments, which have traditionally been thought to necessitate sub-meter resolution. This underscores the practical applicability of meter-scale data for ecological monitoring in complex riparian systems.

Topography plays a fundamental role in shaping vegetation distribution, community structure, and ecosystem functioning. This influence remains significant in hydrologically complex environments, particularly in reservoir drawdown zones (RDZs). However, how topographic factors drive spatial heterogeneity in vegetation across different levels of hydrological disturbance remains insufficiently understood. Clarifying these relationships is essential for interpreting ecological processes and informing vegetation restoration strategies in RDZs. This study selected three mid-channel bars (MCBs) within the Three Gorges Reservoir Region, each located in a distinct hydrological zone—namely, the fluctuating backwater zone, the transition zone between the fluctuating and permanent backwater zones, and the permanent backwater zone—to represent a gradient of hydrological disturbance. Using a combination of the geographic detector and geographically weighted regression models, we quantified the effects of elevation, slope, and aspect on the spatial distribution of vegetation vigor, measured by the Enhanced Vegetation Index (EVI), and analyzed their regional variations. The results showed that: 1) EVI varied significantly among hydrological disturbance zones, with vegetation vigor highest in the permanent backwater zone and lowest in the fluctuating backwater zone. 2) Elevation was the primary factor explaining EVI spatial variation; however, its interactions with slope and aspect produced nonlinear enhancement effects, intensifying the topographic control on vegetation distribution. 3) While elevation dominated overall, slope and aspect exhibited zone-specific regulatory roles: slope notably restricted vegetation recovery in steep areas, and aspect enhanced vegetation vigor in less-disturbed zones by improving local microclimatic conditions. Moreover, the influence of slope and aspect varied across disturbance zones, with aspect playing a stronger role in the permanent backwater zone, and slope exerting greater limiting effects in the fluctuating backwater zone. Although the study was conducted within a single reservoir system, the inclusion of multiple MCBs across distinct hydrological disturbance regimes, coupled with multi-year validation, supports the broader applicability of the findings to other RDZs with similar hydro-topographic conditions. These findings advance our understanding of how topographic factors shape vegetation spatial patterns under varying hydrological regimes and offer valuable insights for ecological restoration in RDZs.

The Tibetan Plateau(TP) plays a key role in both Asian and global climates. TP is one of the regions with the largest precipitation deviations in numerical models. The biases in precipitation simulations over the TP are closely related to its distinctive convective processes and complex topographic effects. This study uses the Weather Research and Forecasting(WRF)model to conduct a two-month simulation over the TP during the summer of 2019, aiming to investigate the combined impact of a cumulus scheme with optimized entrainment process and a turbulent orographic form drag(TOFD) scheme on cloud and precipitation simulations. The results show that the optimized cumulus scheme reduces the wet bias, while the TOFD scheme adjusts the spatial distribution of precipitation simulation, bringing it closer to the observations, especially by reducing the wet bias on the southern slope of the TP. The optimized cumulus scheme increases the simulated convective entrainment rate, leading to reduced convective cloud depth, convective precipitation frequency, and convective precipitation intensity, thereby decreasing the amount of convective precipitation. The TOFD scheme reduces precipitation on the southern slope of the TP by weakening moisture transport toward the TP, wind speed, vertical velocity, and cloud physical processes. The combined use of the two schemes integrates their advantages and jointly improves the accuracy of precipitation simulation over the TP. The results reduce the bias in summer precipitation simulations over the TP and provide a reliable scientific reference for weather and climate research, as well as precipitation forecasting in this region.

This work analyzed the intraseasonal variability of non-migrating tides DE3 and gravity wave momentum fluxes (GWMF) in the mesosphere and lower thermosphere (MLT) region and discussed the possible connection with the tropospheric MJO. Based on the joint observations of the TIMED-TIDI satellite and the 120°E meridian meteor radar chain, we revealed a significant broad-band intra-seasonal signal in the DE3 amplitude around the equator with a clear seasonal dependence. The intraseasonal variability of DE3 in zonal winds (DE3-U) has a strong amplitude in boreal winter, up to 1-2 times the seasonal average, while the variability is usually within 20% during other seasons. The response of MLT DE3 tides to the MJO in different seasons was further discussed together with the MJO activity index. The results suggested that the DE3-U in boreal winter generally has a larger amplitude during MJO phases 4–6 (~10%–40%), while the amplitude is smaller for other MJO phases (~−10%–−40%). As for the GWMF estimation, the 12-year continuous observation of the Mohe meteor radar (53.5°N, 122.3°E) was analyzed. The results showed that intraseasonal GWMF variability is also prominent during boreal winter. Composite analysis for DJF season according to MJO phases revealed that the zonal GMWFs notably increased in MJO P4 by ~2–4 m2/s2, and a Monte Carlo test was designed to examine the statistical significance. The response in zonal winds differs from the GMWF response by two MJO phases (i.e., 1/2π). Additionally, time-lagged composites revealed the strengthened westward GWMF occurred ~25–35 days after MJO P4, coincident with the MJO impact on the polar vortex as previous works revealed. Overall, this work emphasized that the tropical sources (MJO) impress the intraseasonal signal from the troposphere to the MLT region, either tropics or extratropics.

Lake thermal stratification is of great importance to hydrodynamics and transport of nutrients, oxygen, and primary production, which influence limnology and local climate. The thermal regime of the lakes over Tibetan Plateau (TP) was summarized as follow. During summer, solar radiation unevenly heats the water column in the vertical direction, resulting in a stratified thermal structure. The stratification dissipates in October, after which time a more uniform vertical distribution of temperature is observed. This occurs because the increased temperature gradient between the air and lake surface, combined with strong winds, drives considerable energy transfer from the lakes to the overlying air, and leads to a rapid decrease in surface water temperature. This result increases in density of the upper layers and then drives vertical convection that deepens the mixed layer. When the lakes have been completely frozen, the vertical water circulation stops; weak thermal stratification then develops and persists during winter. However, lake water near the surface warms rapidly, and rest water layer does not change much when lakes are covered with ice. When the lake ice disappears, wind-driven turbulence develops and promotes lake vertical mixing. Due to sparse observation, the lake modeling was an alternative method to simulate the seasonal lake thermal change induced by local climate change. Using lake model, the seasonal variation and magnitude of water temperature at different layers were reproduced fundamentally. The interaction heat flux and water exchange with overlying air also were simulated with reasonable error. Both the simulation and observation have shown that the thermal characteristic and ice phenology has altered: warming water and shorter ice duration, impacted by climate change. Meanwhile, the future projection of thermal response of lakes over TP to climate change shows that remarkable water temperature increase and winter ice loss which indicates less mixing frequent and shifting mixing regime. The Lake mixing events can channel the epilimnion and hypolimnion and release large amounts of potent greenhouse gases into the upper surface layer and the atmosphere in autumn, making lakes generally being considered as a weak net carbon source. The epilimnion depth show significant implications on the algal distribution, photosynthesis rates and establishing food web basis. Thus, the seasonal variations of thermal stratification and mixing in lakes can influence the aerobic life, prevent anoxia and impact on local climate and it is one of the most important factors in limnology and climate change.

Real-time communication (RTC) applications, such as virtual reality and video conferencing, impose stringent ultra-low latency requirements, making efficient video rate control a critical challenge in 5G networks. In scenarios where wireless link conditions fluctuate rapidly, ensuring latency performance while maintaining high bandwidth utilization poses a significant difficulty for existing congestion control algorithms. Conventional schemes primarily rely on end-host measurements and reactive adjustments, which often suffer from delayed responses to network dynamics, leading to elevated tail latency and inefficient bandwidth usage. To address these limitations, this paper proposes PIKA, a deployable link-assisted congestion control mechanism specifically designed for realtime video streaming over 5G networks. PIKA exploits bandwidth and queue state information collected at the base station to compute congestion signals in real time. These signals are embedded into packet headers within the 5G core network and subsequently parsed by the receiver, which feeds the information back to the sender via ACKs. Based on this feedback, the sender performs fine-grained bitrate adjustments, enabling timely adaptation to network dynamics. Experimental results demonstrate that PIKA outperforms both conventional congestion control protocols and emerging RTC-oriented approaches in 5G edge environments, achieving superior performance in terms of end-to-end latency and average bitrate.

Recently, the Third Pole(TP) region has experienced rapid environmental changes. Meteorological data are essential for hydrometeorological and ecological applications but still have large uncertainties on the TP owing to the heterogeneous land surface, complex terrain, and sparse weather stations. In this study, a long-term(1979–2020) high-resolution(1/30°) meteorological forcing dataset for the TP(TPMFD) was developed, as a sister to the widely used China Meteorological Forcing Dataset(CMFD). The TPMFD comprises seven components necessary for driving land surface models. We have previously contributed precipitation and downward shortwave radiation data for the TPMFD, and this study presents the development of five other components and focuses on validations for all components. Specifically, 2-meter air temperature, 2-meter specific humidity, 10-meter wind speed, and surface air pressure were generated by combining the fifth-generation atmospheric reanalysis for European Center for Medium-Range Weather Forecasts(ERA5), a short-term high-resolution atmospheric simulation, and in situ observations, and the downward longwave radiation was calculated using semi-physical parameterization. Both cross-validation and independent-validation demonstrated that most variables in the developed dataset outperformed those in widely used reanalysis datasets, including ERA5, ERA5-Land, and the Global Land Data Assimilation System(GLDAS). This dataset is expected to be beneficial for climate analyses and modeling applications of land-surface processes on the TP.

A noticeable wet bias persists over the Tibetan Plateau (TP) during summer in both global and regional climate models, despite numerous advancements and ongoing efforts to lower it. This study investigates the performance of the Gaussian Probability Density Function (GPDF) cloud fraction scheme in the Weather Research and Forecasting (WRF) model over the TP during July and August 2018. The evaluation reveals that the GPDF scheme mitigates the wet bias over the TP in simulations at two resolutions (0.1° and 0.05°), with a significant reduction in the bias. This scheme also reduces the overestimation of downward surface shortwave radiation, indicating an improvement in cloud simulations. We propose that the GPDF scheme alleviates the wet bias through both local moisture process and dynamic process. Specifically, an increase in cloud water/ice content leads to a reduction in surface net radiation and subsequent decrease in surface sensible heat flux and evapotranspiration. This diminished surface heating lessens the thermal effect of the TP, causing a weakened monsoon circulation and decreased moisture flux convergence over the TP. Both the decreases in local evapotranspiration and remote moisture flux convergence contribute to the alleviation of the wet bias, and the latter plays a dominant role, contributing to approximately 70% of the precipitation decrease.

Reliable low-latency media streaming is increasingly critical for delivering seamless interactive and immersive services. To meet this need, the IETF and 3GPP have introduced the Low Latency, Low Loss, Scalable Throughput (L4S) architecture, which mitigates queuing delays in IP traffic and supports latency-sensitive applications. This paper focuses on real-time video streaming and proposes an enhanced framework, Enhanced L4S (EL4S), which integrates a link load factor feedback mechanism to more accurately reflect real-time network conditions. We design and implement a cross-layer end-side transmission control algorithm based on EL4S to improve real-time video performance over 5G networks. In this design, EL4S encodes link load information into packets at the 5G core and uses ACK-based feedback to inform the sender about current network states. At the sender, a dynamic bitrate adaptation algorithm adjusts the transmission rate in response to the reported link load factor, balancing throughput and delay while avoiding network congestion. This adaptive mechanism enables precise, frame-level control over video encoding rates and transmission behavior. Extensive experimental evaluations demonstrate that EL4S achieves high link utilization and low latency, significantly outperforming existing baseline algorithms. Overall, EL4S provides an efficient and deployable solution for achieving low-latency, high-quality real-time streaming in dynamic 5G networks.