Surface Processes Research Articles

Spatiotemporal variations of surface albedo in Central Asia and its influencing factors and confirmatory path analysis during the 21st century

Surface albedo (SA) is crucial for understanding land surface processes and climate simulation. This study analyzed SA changes and its influencing factors in Central Asia from 2001 to 2020, with projections 2025 to 2100. Factors analyzed included snow cover fraction, fractional vegetation cover, soil moisture, average state climate indices (temperature and precipitation), and extreme climate indices (heatwave indices and extreme precipitation indices). Pearson correlation coefficient, geographical convergent cross mapping, and geographical detector were used to quantify the correlation, causal relationship strength, and impact degree between SA and the influencing factors. To address multicollinearity, ridge regression (RR), geographically weighted ridge regression (GWRR), and piecewise structural equation modeling (pSEM) were combined to construct RR-pSEM and GWRR-pSEM models. Results indicated that SA in Central Asia increased from 2001 to 2010 and decreased from 2011 to 2020, with a projected future decline. There is a strong correlation and significant causality between SA and each factor. Snow cover fraction was identified as the most critical factor influencing SA. Average temperature and precipitation had a greater impact on SA than extreme climate indices, with a 1 °C temperature increase corresponding to a 0.004 decrease in SA. This study enhances understanding of SA changes under climate change, and provides a methodological framework for analyzing complex systems with multicollinearity. The proposed models offer valuable tools for studying interrelated factors in Earth system science.

Surface Mechanical Property Prediction and Process Optimization of 18CrNiMo7-6 Carburized Steel Stator Guide Based on Radial Basis Function Neural Network and NSGA-II Algorithm

The carburizing process is a key technology that affects the mechanical properties of the surface of the hydraulic motor stator guide rail, and the related process parameters have an important influence on surface hardness, the thickness of the carburized layer, and the deformation of the guide rail. However, at present, the relationship between the carburizing process parameters and the surface mechanical properties of the target is not clear. This paper proposes a “hardness prediction and process parameter optimization” method. Firstly, a finite element model is established, with carburizing time, temperature, and carbon potential as the three input factors; the optimal Latin hypercubic experimental design and sensitivity analysis are applied. Secondly, surface hardness, carburized layer thickness, and deformation are taken as the output values, and an RBF neural network is used to construct the prediction model. The results show that the RBF neural network can be accurately used for the prediction of surface hardness, the thickness of the carburized layer, and deformation, and for the optimization of process parameters. The optimized parameters of surface hardness and the thickness of the carburized layer were increased by 4.2% and 5.1%, respectively, and the deformation amount was reduced to 0.31 mm, achieving the goal of optimal design.

Pre‐Vegetation Mixed (Wave‐Tide) Energy Trangressive Nearshore Sedimentation: Evidence From the Proterozoic Passive Margin Sequence of NW Himalaya, India

ABSTRACTThe coupled evolution of the Earth's atmosphere–biosphere system through time has caused irreversible changes in the geodynamics as well as surface processes and sedimentation patterns. One such significant change took place in sedimentation in the Palaeozoic (i.e., Silurian) by the appearance of vascular vegetation. While the impact of evolving vegetation on the terrestrial fluvial environment has been relatively well documented, vegetation‐induced effects down the system in marginal or nearshore marine settings have undergone little study. The Meso‐ to Neoproterozoic Rautgara Formation exposed in the Himalayan Orogenic Belt of NW India, offers a chance to study a well‐preserved fluvial–marine transition to nearshore sedimentation before the appearance of vascular vegetation. A detailed sedimentological analysis identifies six genetically linked facies associations (FA) probably deposited in barrier, back‐barrier, and subtidal deltaic environments. Contrary to the other transgressive barrier models (where beach‐barrier overlie the back barrier environments), in the present case, wave‐dominated barrier deposits mostly occupy the basal part of the stratigraphy. In the middle stratigraphic level, back‐barrier deposits lack thick mud flats and show a dominance of sandstone over mudstone. Stacked subtidal sand bar facies association represents the top part of the sequence. Two sequence stratigraphic surfaces, that is, subaerial unconformity and maximum flooding surface, have been identified and the whole succession is interpreted in terms of HST and TST. Barrier and back‐barrier sediments are deposited during HST and TST, respectively. Subtidal deltaic system developed in late TST. The lack of frequent interbedding between the barrier and back‐barrier facies indicates negligible landward migration of the barrier and demonstrates system stability. The barrier system might have resulted from vertical aggradations akin to modern vegetated systems. The study portrays that sandy barrier systems are common in the Proterozoic. Vegetation and thick mud flats are not always essential for the stability of a barrier‐beach system.

Spatial downscaling of SMAP soil moisture to high resolution using machine learning over China’s Loess Plateau

Soil moisture (SM) is a critical physical parameter in land surface processes that affects the atmospheric and hydrological cycles. Soil Moisture Active Passive (SMAP) mission produces high-quality global SM data, but its low spatial resolution limits the applications at a regional or local scale. In this study, we developed a novel method to select optimal factors from 34 candidate downscaling factors for each month using three machine learning methods (Back Propagation Neural Network (BPNN), Support Vector Machine (SVM) and Random Forest (RF)) to produce monthly time series SM products at a spatial resolution of 1 km for the entire Loess Plateau in China from 2015 to 2023. 11 in-situ SM measurements distributed in Loess Plateau and precipitation data were used to evaluate the downscaling performances of the three machine learning approaches. The results show that the spatial trends of the three downscaled SM were essentially the same as the SMAP SM, with similar spatial patterns, and all three downscaled SM can provide more spatial information and texture features than SMAP SM. Among the three types of downscaled SM, the RF downscaled SM reached the highest R (0.654) and the smallest unbiased Root Mean Square Error (ubRMSE) (0.044 m3m−3), better than the BPNN and SVM downscaled SM, and most closely matched the in-situ measurements. The dynamics of SM were successfully captured by RF downscaled SM, which exhibited strong temporal consistency with the in-situ SM and responded well to precipitation events, with significant increases in SM values in the month of high precipitation and subsequent months. In conclusion, the RF model has the best downscaling effect and it can be used to provide high spatial resolution SM data for applications at a regional or local scale across the Loess Plateau.

Large-scale medieval urbanism traced by UAV-lidar in highland Central Asia.

Aerial light detection and ranging (lidar) has emerged as a powerful technology for mapping urban archaeological landscapes, especially where dense vegetation obscures site visibility1,2. More recently, uncrewed aerial vehicle/drone lidar scanning has markedly improved the resolution of three-dimensional point clouds, allowing for the detection of slight traces of structural features at centimetres of detail across large archaeological sites, a method particularly useful in areas such as mountains, where rapid deposition and erosion irregularly bury and expose archaeological remains3. Here we present the results of uncrewed aerial vehicle-lidar surveys in Central Asia, conducted at two recently discovered archaeological sites in southeastern Uzbekistan: Tashbulak and Tugunbulak. Situated at around 2,000-2,200 m above sea level, these sites illustrate a newly documented geography of large, high-altitude urban centres positioned along the mountainous crossroads of Asia's medieval Silk Routes (6th-11th centuryCE (Common Era)4,5. Although hidden by centuries of surface processes, our pairing of very-high-resolution surface modelling with semiautomated feature detection produces a detailed plan of monumental fortifications and architecture spanning 120 ha at Tugunbulak, thereby demonstrating one of the largest highland urban constellations in premodern Central Asia. Documentation of extensive urban infrastructure and technological production among medieval communities in Central Asia's mountains-a crucial nexus for Silk Road trade networks6-provides a new perspective on the participation of highland populations in the economic, political and social formation of medieval Eurasia.

Scraper Point Attitude Optimization in the Scraping Process of Aviation Composite Curved Surface

Aiming at the interference problem between the tool and the surface during the contact between the blade position and the composite material during the off-line programming scraping process of aviation composite parts, the contact effect of the blade during the scraping process of the composite surface is discussed, and a rotation projection attitude optimization strategy is proposed. Firstly, by constructing the mathematical model of the contact between the scraper and the surface, the geometric properties of the scraper and its contact on the surface are analyzed. Then, the non-uniform rational B-spline (NURBS) surface is used to reconstruct the surface, and the position information of the local area of the contact point is obtained to obtain the normal direction and curvature. In order to evaluate the contact effect of the scraper, an objective function is defined to minimize the contact error between the scraper linear trajectory and its projection on the surface, thereby quantifying the contact accuracy. By comparing the position and attitude of the scraper before and after optimization, the effectiveness of the proposed optimization method is verified. The optimized scraper posture significantly improves the contact accuracy with the composite surface, better adapts to the geometric characteristics of the complex surface, and ensures the efficiency and consistency of the scraping process. The research results provide a new perspective and method for the future development of automatic scraping process, and also provide an effective solution and technical means for other industries in the application scenario of curved scraping.

Effects of Frequency on the Performance of Ultrasonic Vibration Assisted Chemical Mechanical Polishing for Sapphire

Abstract Sapphire (Al2O3) is renowned for its exceptional properties, yet its unique natural presents a surface processing challenge. To enhance the polishing quality and efficiency, the sapphire ultrasonic vibration assisted chemical mechanical polishing (UV-CMP) has been proposed. This paper employs computational fluid dynamics (CFD) simulation and polishing experiments to investigate the action and mechanism of ultrasonic frequency on sapphire UV-CMP. The CFD simulation reveals that an increase in frequency can effectively elevate the fluid velocity, pressure, and cavitation. The enhancement in pressure, Z-direction, and resultant velocity has a positive impact on the cutting ability and utilization rate of nano-abrasives. A high frequency can enhance the physical fields of slurry, but it suppresses the growth of cavitation bubbles, and is detrimental to the number and size of abrasive particles. The best processing performance of sapphire UV-CMP is obtained at 40 kHz due to coordinated physicochemical interactions. X-ray photoelectron spectroscpy proves the product of solid-solid chemical reaction between nano-SiO2 and sapphire is softer Al2Si2O7 instead of Al2SiO5, which is beneficial to the material removal. This article provides theoretical and practical guidance for sapphire UV-CMP.

Exploring Topography Downscaling Methods for Hyper‐Resolution Land Surface Modeling

AbstractHyper‐resolution land surface modeling provides an unprecedented opportunity to simulate locally relevant water and energy cycles. However, the available meteorological forcing data is often insufficient to fulfill the requirements of hyper‐resolution modeling. Here, we developed a comprehensive downscaling framework based on topography‐adjusted methods and automated machine learning (AutoML). With this framework, a 90 m and hourly atmospheric forcing data set was developed from ERA5 data at a 0.25° resolution, and the Common Land Model (CoLM) was then forced with the developed forcing data over two complex terrain regions (the Heihe River Basin and Upper Colorado River Basin). We systematically evaluated the downscaled forcing and the CoLM outputs against both in situ observations and gridded data. The ground‐based validation results suggested consistent improvements for all downscaled forcing variables with mean RMSE improved by 6.362%–95.86%. The downscaled forcings, which incorporated detailed topographic features, offered improved magnitude estimates, achieving a comparable level of performance to that of regional reanalysis forcing data. The downscaled forcing driving the CoLM model showed comparable or better skills in simulating water and energy fluxes, as verified by in situ validations. The hyper‐resolution simulations provided a detailed and more reasonable description of land surface processes and attained similar spatial patterns and magnitudes with high‐resolution land surface data, especially over highly elevated areas. Additionally, this study highlighted the benefits of using mountain radiation theory‐based shortwave radiation downscaling models and AutoML‐assisted precipitation downscaling models. These findings emphasized the significance of integrating topography‐based downscaling methods for hillslope‐scale simulations.

Pixel-level Terrain Processing of the Martian Surface from Moderate Resolution Images of Tianwen-1

The moderate-resolution camera (MoRIC) of the Tianwen-1 orbiter, China’s first Mars exploration mission, is a frame-imaging scheme color camera. However, generating a precise digital elevation model (DEM) from these images faces challenges due to the presence of featureless and repetitive regions on the Martian surface. Traditional photogrammetric methods often struggle to achieve pixel-level resolution in these areas. To address this, we employ a shape from shading (SFS) algorithm that leverages shading patterns to reconstruct fine-scale terrain details, optimizing photogrammetric initial DEM. This paper presents a novel global bisection search algorithm, based on the Pearson correlation coefficient to determine the smoothing parameter, a crucial element in the SFS process. Comparisons with higher-resolution data from the Mars Express high-resolution stereo camera and Mars Reconnaissance Orbiter CTX images validate our approach, highlighting the potential of SFS to significantly enhance the scientific value of Tianwen-1 MoRIC data by generating high-resolution, three-dimensional maps of Mars.

On the Stationarity of the Global Spatial Dependency of Heat Risk on Drought

AbstractLand surface processes such as the soil moisture—air temperature coupling influence compound climate anomalies like heatwaves and droughts, yet the spatial and temporal variability of the coupling strength is still understudied. We assess global land exposure to concurrent heat waves and drought since the 1980s. We found that drought significantly shapes the spatial distribution of the risk of heat waves. We show that the portion of global land experiencing drought‐conditioned heat anomalies more than tripled in less than 3 decades. However, using such traditional heat waves indicators, the level of spatial coupling between heat waves and drought seems to decline. Conversely, time‐dependent approaches accounting for the baseline climate change offer a more stable perspective. We conclude that tailoring hazard definitions to specific processes and impacts is crucial. Early warning systems can play a prominent role in mitigating the impacts of global warming to society.

Root zone in the Earth system

Abstract. The root zone is a vital part of the Earth system and a key element in hydrology, ecology, agronomy, and land surface processes. However, its definition varies across disciplines, creating barriers to interdisciplinary understanding. Moreover, characterizing the root zone is challenging due to a lack of consensus on definitions, estimation methods, and their merits and limitations. This opinion paper provides a holistic definition of the root zone from a hydrology perspective, including its moisture storage, deficit, and storage capacity. We demonstrate that the root zone plays a critical role in the biosphere, pedosphere, rhizosphere, lithosphere, atmosphere, and cryosphere of the Earth system. We underscore the limitations of the traditional reductionist approach in modelling this complex and dynamic zone and advocate for a shift towards a holistic, ecosystem-centred approach. We argue that a holistic approach offers a more systematic, simple, dynamic, scalable, and observable way to describe and predict the role of the root zone in Earth system science.

Modeling of surface generation and process experiments for grinding Ti-6Al-4V with small-scale grinding tool with regular array structure

Modeling of surface generation and process experiments for grinding Ti-6Al-4V with small-scale grinding tool with regular array structure

Effect of Initial Surface Morphology and Laser Parameters on the Laser Polishing of Stainless Steel Manufactured by Laser Powder Bed Fusion.

The topological characteristics of the down-skin surfaces for as-built components by laser powder bed fusion (LPBF) are particularly representative, while the study on the improvement of the surface quality of these surfaces remains largely unexplored. Herein, the laser polishing of LPBF-built components with different inclination angles was systematically investigated with an emphasis on the down-skin surfaces. Our result shows that the topography of the top surface is independent of the inclination angle, and the surface topography of the down-skin surface is dominated by additional angle-dependent surface characteristics. It also indicates that the surface roughness can be reduced sharply when increasing the laser power from 40 W to 60 W, and the reduction slows down when further increasing the laser power while decreasing the scanning speed leads to a progressive improvement of the surface morphology. Moreover, a second-order regression model was established to evaluate the influence of the initial surface morphology and polishing parameters on the polished surface roughness and to achieve surface roughness optimization. Therefore, our established methodology can be readily applied to surface morphology manipulation and process optimization for laser polishing of widely used metals and alloys fabricated by the additive manufacturing process.

Size effects and optimization during laser directed energy deposition on high thermal conductivity copper alloys

High-copper alloy/nickel-based high-temperature alloy bimetallic structures are widely utilized in critical components, such as thrust chambers of liquid rocket engines, water cooling circuits for fusion reactor deflectors, and electromagnetic railguns. Among various methods for fabricating Cu/Ni bimetallic structures, laser directed energy deposition (LDED) is considered one of the most promising techniques for depositing nickel-based high-temperature alloys onto high-copper alloy surfaces. In the LDED fabrication process, substrates with uneven thicknesses are a common. The process is characterized by its multi-parameter, high-sensitivity, and non-equilibrium solidification characteristics. Consequently, variations in substrate size can significantly affect molten pool morphology and fabrication stability. This study examines the size effect of a single track of LDED Inconel 718 (In718) on a CuCr0.8 high-copper alloy substrate. The results indicate a pronounced size effect when using a high thermal conductivity CuCr0.8 substrate, particularly regarding substrate thickness. By reducing the thermal conductivity of the CuCr0.8 substrate, the size effect is mitigated, improving the process adaptability of LDED. These findings provide valuable data for the laser processing of surfaces with uneven thickness and high thermal conductivity. They are expected to support the fabrication of variable thrust liquid rocket engines and advance the field of interplanetary exploration.

Synergetic effect of hybrid surface treatment on the mechanical properties of adhesively bonded AA2024-T3 joints

ABSTRACT Improving the surface properties of AA2024-T3 aluminium alloys is crucial for achieving durable and sustainable joints. For this purpose, AA2024-T3 alloys were first sandblasted at 4, 5 and 6 bar pressures using aluminium oxide and glass sphere abrasives. Then, the sandblasted samples were subjected to the chemical surface treatment resulting in a hybrid surface process. The surface properties of sandblasted and hybrid surface-treated AA2024-T3 alloys were characterised by 3D image analysis, contact angle and roughness measurement. Additionally, single-lap joints were fabricated using adhesives with low and high viscosity. The effect of changes in the viscosity of adhesives and the surface properties of the AA2024-T3 on the mechanical properties of the joints has been analysed in detail. It was found that both sandblasting and hybrid surface treatments applied to AA2024-T3 alloys caused significant improvement in the mechanical properties of the joints. AA2024-T3 alloys, which were chemically surface treated after being sandblasted with glass spheres at 6 bar pressure, were joined using low and high viscosity adhesives, and the failure load of these joints increased by approximately 110% and 68%, respectively, compared to untreated samples. In the case of aluminium oxide usage, the increase rates were determined to be 93% and 43%.

STUDY ON THE PROPERTIES OF DIAMOND FILMS ON CEMENTED CARBIDE SUBSTRATES BY SURFACE IMPLANTATION PRETREATMENT PROCESS

The deposition of diamond films on tungsten carbide-based tools can greatly improve the life and performance of cutting tools. However, the deposition of diamond coatings on cemented carbide (WC-Co) suffers from poor film-base bond strength. In this paper, diamond coatings were deposited of phytocrystalline metal micropowders (pure, Nb, Ti, Ta) pretreatment method and the properties of diamond films were analyzed by energy spectrometry (EDS), scanning electron microscopy (SEM), Raman spectroscopy and bonding strength test of diamond films. The results show that through the experiment of the pretreatment process of surface implanted crystal metal micropowder, the best implanted crystal metal micropowder was obtained, the surface quality of implanted crystal titanium (Ti) coating was improved, the diamond Raman peaks were sharp and the indentation cracks had a crack diameter of 389 [Formula: see text]m, which is small and has the highest bond strength. The pretreatment process of phytocrystalline diamond micropowder can deposit high-performance diamond coatings and improve the bonding strength between the coating and the substrate film base.

Quantification of the Contribution of Heterogeneous Surface Processes to Pollutant Abatement during Heterogeneous Catalytic Ozonation.

Heterogeneous surface processes such as adsorption and oxidation with surface-adsorbed reactive oxygen species (ROSad, e.g., adsorbed oxygen atom (*Oad) and hydroxyl radicals (•OHad)) have been suggested to play an important role in pollutant abatement during heterogeneous catalytic ozonation (HCO). However, to date, there is no reliable method to quantitatively evaluate the contribution of heterogeneous surface processes to pollutant abatement (fS) during HCO. In this study, we developed a method by combining probe compound-based experiments with kinetic modeling to distinguish heterogeneous surface processes from homogeneous bulk reactions with aqueous O3 and ROS (•OH and superoxide radicals (O2•-) in the abatement of various pollutants (e.g., atrazine, ibuprofen, tetrachloroethylene, and perfluorooctanoic acid) during HCO with reduced graphene oxide. The results show that the pollutants that have a low affinity for the rGO surface (e.g., ibuprofen and tetrachloroethylene) were essentially abated by homogeneous bulk reactions, while the contribution of heterogeneous surface processes was negligible (fS < 5%). In contrast, heterogeneous surface processes played an important or even dominant role in the abatement of pollutants that have a high surface affinity (e.g., fS = 32-82% for atrazine and perfluorooctanoic acid). This study is a critical first step in quantitatively evaluating the role of heterogeneous surface processes for pollutant abatement during HCO, which is crucial to understanding the mechanism of HCO and designing catalysts for effective pollutant abatement.

A global–land snow scheme (GLASS) v1.0 for the GFDL Earth System Model: formulation and evaluation at instrumented sites

Abstract. Snowpacks modulate water storage over extended land regions and at the same time play a central role in the surface albedo feedback, impacting the climate system energy balance. Despite the complexity of snow processes and their importance for both land hydrology and global climate, several state-of-the-art land surface models and Earth System Models still employ relatively simple descriptions of the snowpack dynamics. In this study we present a newly-developed snow scheme tailored to the Geophysical Fluid Dynamics Laboratory (GFDL) land model version 4.1. This new snowpack model, named GLASS (Global LAnd–Snow Scheme), includes a refined and dynamical vertical-layering snow structure that allows us to track the temporal evolution of snow grain properties in each snow layer, while at the same time limiting the model computational expense, as is necessary for a model suited to global-scale climate simulations. In GLASS, the evolution of snow grain size and shape is explicitly resolved, with implications for predicted bulk snow properties, as they directly impact snow depth, snow thermal conductivity, and optical properties. Here we describe the physical processes in GLASS and their implementation, as well as the interactions with other surface processes and the land–atmosphere coupling in the GFDL Earth System Model. The performance of GLASS is tested over 10 experimental sites, where in situ observations allow for a comprehensive model evaluation. We find that when compared to the current GFDL snow model, GLASS improves predictions of seasonal snow water equivalent, primarily as a consequence of improved snow albedo. The simulated soil temperature under the snowpack also improves by about 1.5 K on average across the sites, while a negative bias of about 1 K in snow surface temperature is observed.

Water-Polymer Slide Electrification in Polyethylene Films Coated with Amphiphilic Compounds and Its Connection to Surface Properties Dependent on Water-Polymer Interactions.

Slide electrification experiments were performed on low-density polyethylene films (PE) and PE sprayed with five amphiphilic compounds, including antistatic and slip additives. Drops of aqueous solutions were delivered on the films and after sliding spontaneously acquired a net electrical charge (Qdrop), which is dependent on the pH and ionic strength. The slide electrification was detected in pristine PE films and those with five additives. An acid-base equilibrium model, based on the adsorption of hydroxides and protons on surface sites, accounted for the dependence of Qdrop on pH, allowing recovery of the acid-base equilibrium constants and the density of adsorption sites. The model was modified to account for ionic strength effects through activity factors. The surface conductivity, wettability, and friction coefficients were strongly modified by the additives. However, the observed trends are different from those observed in slide electrification, which better correlated with zeta potential determinations. This suggests that the interaction mechanisms among surface water, the considered additives, and the polymer, which are involved in slide electrification and the generation of zeta potential, are different from those associated with other surface processes involving surface water. Although additives are required for changing surface resistivity, friction coefficients, and wettability, the generation of sliding electrical charges in polyethylene is a spontaneous and highly effective process. For one specific additive, a simultaneous decrease in friction coefficients, zeta potential, and Qdrop was observed, assigned to the blockade of hydroxide adsorption sites and water repulsion by the compound.

Characteristics and Driving Factors of Energy Balance over Different Underlying Surfaces in the Qinghai Plateau

The study of the surface energy balance characteristics of different ecosystems in the Qinghai Plateau is of great significance for a deeper understanding of land surface processes, the water cycle, and global climate change. This study aims to compare the seasonal variations in energy balance and partitioning of four typical ecosystems on the Qinghai Plateau—swamp meadows, subalpine mountain meadows, alpine shrublands, and alpine deserts. Mantel analysis and path analysis were used to explore the regulatory mechanisms of meteorological elements on energy fluxes and the Bowen ratio (β). The results showed the following: (1) Net radiation (Rn), sensible heat flux (H), and latent heat flux (LE) all exhibited a single-peak pattern of change, and the energy partitioning was closely related to the hydrothermal conditions. Swamp meadows and subalpine mountain meadows were dominated by LE throughout the year and the growing season, while H dominated in the non-growing season. Meanwhile, alpine shrublands and alpine deserts were dominated by H throughout the year. (2) β reflected the characteristics of turbulent fluxes variations and the moisture level of the underlying surface. Swamp meadows and subalpine mountain meadows were relatively moist, with the value of β all being less than 1. Alpine shrublands and deserts were comparatively arid, with the values of β all exceeding 1. The energy closure rate ranged from 48% to 90%, with better energy closure conditions observed during the growing season compared to the non-growing season. (3) Meteorological factors collectively regulated the variations in energy fluxes and its partitioning, with H and LE being primarily influenced by Rn, relative humidity (RH), and soil moisture (Ms). β was significantly affected by RH, Ms, and the saturated vapor pressure deficit (VPD). The sensitivity of the ecosystems to changes in fluxes increased with decreasing moisture, especially in alpine deserts, with Ms, VPD and RH being the most affected. Swamp meadows were significantly associated with air temperature (Ta), soil temperature (Ts), and wind speed; subalpine mountain meadows with Ta and Ts; and alpine shrublands with Ta. These results provided a basis for further analyses of the energy balance characteristics and partitioning differences of different ecosystems on the Qinghai Plateau.