Search Results (30)

The Complementary Relationship (CR) principle of evapotranspiration provides an efficient approach for estimating actual evapotranspiration (ET_a), owing to its simplified computation and effectiveness in utilizing meteorological factors. Accurate estimation of actual evapotranspiration (ET_a) is crucial for understanding surface energy and water cycles, especially in permafrost regions. This study aims to evaluate the applicability of two Complementary Relationship (CR)-based methods—Bouchet’s in 1963 and Brutsaert’s in 2015—for estimating ETa on the Qinghai–Tibetan Plateau (QTP), using observations from Eddy Covariance (EC) systems. The potential evapotranspiration (ET_p) was calculated using the Penman equation with two wind functions: the Rome wind function and the Monin–Obukhov Similarity Theory (MOST). The comparison revealed that Bouchet’s method underestimated ET_a during frozen soil periods and overestimated it during thawed periods. In contrast, Brutsaert’s method combined with the MOST yielded the lowest RMSE values (0.67–0.70 mm/day) and the highest correlation coefficients (r > 0.85), indicating superior performance. Sensitivity analysis showed that net radiation (Rn) had the strongest influence on ET_a, with a daily sensitivity coefficient of up to 1.35. This study highlights the improved accuracy and reliability of Brutsaert’s CR method in cold alpine environments, underscoring the importance of considering freeze–thaw dynamics in ET modeling. Future research should incorporate seasonal calibration of key parameters (e.g., ε) to further reduce uncertainty. Full article

Gonghe Basin is an important frontier of resource and energy development and environmental protection on the Qinghai–Tibetan Plateau and upper sections of the Yellow River. As a characteristic ecotone, this area exhibits complex and diverse ecosystem types while demonstrating marked ecological vulnerability. The response of ecosystem services (ESs) to human activities (HAs) is directly related to the sustainable construction of an ecological civilization highland and the decision-making and implementation of high-quality development. However, this response relationship is unclear in the Gonghe Basin. Based on remote sensing data, land use, meteorological, soil, and digital elevation model data, the current research determined the human activity intensity (HAI) in the Gonghe Basin by reclassifying HAs and modifying the intensity coefficient. Employing the InVEST model and bivariate spatial autocorrelation methods, the spatiotemporal evolution characteristics of HAI and ESs and responses of ESs to HAs in Gonghe Basin from 2000 to 2020 were quantitatively analyzed. The results demonstrate that: From 2000 to 2020, the HAI in the Gonghe Basin mainly reflected low-intensity HA, although the spatial range of HAI continued to expand. Single plantation and town construction activities exhibited high-intensity areas that spread along the northwest-southeast axis; composite activities such as tourism services and energy development showed medium-intensity areas of local growth, while the environmental supervision activity maintained a low-intensity wide-area distribution pattern. Over the past two decades, the four key ESs of water yield, soil conservation, carbon sequestration, and habitat quality exhibited distinct yet interconnected characteristics. From 2000 to 2020, HAs were significantly negatively correlated with ESs in Gonghe Basin. The spatial aggregation of HAs and ESs was mainly low-high and high-low, while the aggregation of HAs and individual services differed. These findings offer valuable insights for balancing and coordinating socio-economic development with resource exploitation in Gonghe Basin. Full article

Temperate glaciers in the Kangri Karpo region of the southeastern Qinghai–Tibet Plateau (QTP) have experienced significant ablation in recent decades, increasing the risk of glacier-related hazards and impacting regional water resources. However, the spatial and temporal pattern of mass loss in these glaciers remains inadequately quantified. In this study, we used ASTER L1A stereo images to construct a high-resolution elevation time series and provide a comprehensive spatial–temporal assessment of glacier elevation change from 2000 to 2024. The results indicate that almost all glaciers have experienced rapid ablation, with an average surface elevation decrease of −18.35 ± 5.13 m, corresponding to a rate of −0.76 ± 0.21 m yr⁻¹. Glaciers in the region were divided into the northern and southern basins, with average rates of −0.79 ± 0.17 m yr⁻¹ and −0.72 ± 0.13 m yr⁻¹, respectively. A notable difference in acceleration trends between the two basins was observed, with the elevation rate increasing from −0.78 ± 0.17m yr⁻¹ to −1.04 ± 0.17 m yr⁻¹ and from −0.52 ± 0.13 m yr⁻¹ to −0.92 ± 0.13 m yr⁻¹, respectively. The seasonal cycle was identified in glacier surface elevation change, with an accumulation period from November to March followed by a prolonged ablation period. The seasonal amplitude decreased with elevation, with higher elevations exhibiting longer accumulation periods and less ablation. Correlation analysis with meteorological data indicated that higher summer temperatures and increased summer rainfall intensify elevation loss, while increased spring snowfall may reduce ablation. Our analysis highlights distinct variations in glacier elevation changes across different locations, elevations, and climatic conditions in the Kangri Karpo region, providing valuable insights into glacier responses to environmental changes on the Tibetan Plateau. Full article

This study applies the Multilayer Perceptron (MLP) and Random Forest (RF) models, utilizing remote sensing and ground-based net primary productivity (NPP) data from 1992 to 2020, along with meteorological data and soil properties, to model the NPP in the alpine grassland and alpine meadow ecosystems of the Qinghai-Tibetan Plateau (TP) and assess their sensitivity to climate change. As a vital ecological barrier, the TP’s grassland ecosystems are critical for understanding the impacts of climate change. However, sensitivity analysis of the NPP in the TP grasslands has been limited, which this study aims to address by focusing on the effects of maximum temperature, solar radiation, and wind speed on the NPP. The results show that the MLP model outperforms the RF model in prediction accuracy (R² = 0.98, RMSE = 16.24 g C·m⁻²·a⁻¹, MAE = 9.04 g C·m⁻²·a⁻¹). NPP responses to climate factors are diverse: linear with temperature and nonlinear with solar radiation and wind speed. Under multi-factor scenarios, the NPP in both alpine meadow and alpine grassland exhibit nonlinear trends, with a higher sensitivity to changes in all three factors than to single- or two-factor changes. Spatial distribution analysis revealed that the NPP in alpine meadows was more sensitive to climate change in the southern regions, while alpine grassland showed greater sensitivity in the central regions. This study, using machine learning models and sensitivity analysis, sheds light on the complex response of the NPP in the TP grasslands to climate change, offering valuable insights for carbon cycle research in cold ecosystems and regional climate adaptation management. Full article

Grasslands have been increasingly impacted by human activities, gradually becoming one of the most threatened ecosystems globally. Advanced geographic information technology and remote sensing techniques allow for a fresh perspective on studying the response of the grassland degradation index ($GDI$) to climate change. This study utilized remote sensing image data of grasslands to calculate the vegetation coverage and derive the $GDI$ for five grassland regions of China from 2001 to 2019. The results indicate that the national degradation status of grasslands remained at a level of mild degradation. The increasing trend of the $GDI$ in some regions was effectively inhibited by regional climate change, especially in the Northeastern and Northern Plain–Mountain–Hill Grassland regions, where the $GDI$ showed a continuous decreasing trend. $GDI$ was strongly correlated with atmospheric pressure, precipitation, temperature, and wind speed. In the arid northern region, the increasing precipitation and decreasing temperatures predominantly contributed to the depressed $GDI$. In the Qinghai–Tibetan Plateau Grassland region, the instability of the $GDI$ is attributed to fluctuating atmospheric pressure, with a correlation coefficient ranging from 0.5 to 0.8. Our findings underscore the importance of meteorological factors to evaluate and forecast grassland ecosystem stability. This understanding is vital for developing informed conservation and management strategies to address current and future climate challenges. Full article

The risk analysis and assessment of snow disasters are essential foundational tasks in natural disaster management and profoundly impact the scientific and precise formulation of disaster prevention, preparedness, and mitigation strategies. Employing the theory and methodology of snow disaster assessment, this research focuses on historical and potential snow disasters in the Qinghai–Tibetan Plateau (QTP) Region. Utilizing a long-time-series snow depth remote sensing dataset, we extracted six assessment indicators for historical snow disaster risk factors and potential snow disaster risk factors. We determined the weights of these six assessment indicators using the entropy weight method. Subsequently, we established a snow disaster assessment model to evaluate the grade distribution of snow disasters in the study area. This method can effectively solve the problem of the sparse data distribution of meteorological stations and reflect degrees of snow disaster risk on a large spatial scale. The findings reveal that areas with a relatively high snow disaster risk are primarily concentrated in the western part of the Ali Region, the central part of Chamdo, and near the border in Southern Xizang. Additionally, regions with a high frequency of snow disasters are predominantly located at the junction of Nagchu, Chamdo, and Nyingchi in the eastern part of Xizang. These results contribute valuable insights into the risk assessment of snow disasters and facilitate the development of effective strategies for disaster management in the region. Full article

This study investigated the convective weather features, precipitation microphysical characteristics, and water vapour transport characteristics associated with a southwest vortex precipitation event that occurred on the eastern edge of the Qinghai–Tibet Plateau, coinciding with a southwest vortex event, from 15 to 16 July 2021, using conventional observations of raindrop spectra, ERA5 reanalysis data, CMORPH precipitation data, and the HYSPLIT_v4 backward trajectory model. The findings aim to provide theoretical insights for improving the forecasting and numerical simulations of southwest vortex precipitation events. The findings revealed that the precipitation event induced by the southwestern vortex at Emeishan Station on 15–16 July 2021 was characterised by high rainfall intensity and significant precipitation accumulation. The raindrop spectrum exhibited a broad distribution with a notable bimodal structure. Both the Sichuan Basin and the Tibetan Plateau were dominated by the South Asian high pressure at higher altitudes, while a pronounced low-pressure system developed at mid and low altitudes within the basin, establishing a meteorological context marked by upper-level divergence and lower-level convergence. Throughout the event, notable vertical uplift velocities were recorded across the Sichuan Basin and Tibetan Plateau, along with distinct positive vorticity zones in the lower and middle strata of the Sichuan Basin, indicating that the atmosphere was in a state of thermal instability. The majority of moisture was in the mid and lower troposphere with evident convergence movements, which played a crucial role in the southwest vortex’s development. WRF numerical simulations of the Emeishan precipitation event more accurately modelled the weather conditions for this precipitation but tended to overestimate the level of precipitation. It was observed that the region around Emei Mountain primarily received moisture influx from the southern Bay of Bengal and the South China Sea, with moisture transport chiefly originating from the Sichuan Basin and in a south-westward trajectory. Full article

Accurately estimating daily mean land surface temperature (LST) is crucial for studying the urban heat island effect, land–atmosphere energy exchange, and global climate change. However, limited research has been conducted on average surface temperature estimation, particularly in high-altitude regions like the Qinghai–Tibet Plateau with extensive cloud cover. In this study, we propose the Reanalysis Data and Thermal Infrared Remote Sensing Data Merging-Diurnal Temperature Cycle (RTM-DTC) model specifically for the Qinghai–Tibet Plateau, successfully estimating mean LST using the model. We apply the RTM method to reconstruct LST under cloud cover from the MODIS LST product and calculate the average temperature using the DTC model. Validation with in situ measurements from seven meteorological stations on the Tibetan Plateau yielded daily scale RMSEs ranging from 1.81 K to 2.021 K and monthly scale RMSEs ranging from 1.77 K to 2.0 K, with an average RMSE of 1.91 K. These results demonstrate the adaptability of the RTM-DTC model and its ability to depict the annual variation curve of the mean surface temperature, and provide further research on RTM-DTC as a valuable approach. Full article

The Tibet Plateau of Qinghai supports complex vegetation types that are ecologically fragile and sensitive to climatic factors. Therefore, it is important to understand the changes in vegetation and the factors responsible for these changes and to maintain the ecosystem balance and promote sustainable development in the region. Therefore, this paper is based on annual SPOT/VEG NDVI (Normalized Difference Vegetation Index) data, land use data, topographic data, temperature data, and precipitation data from 1999 to 2019. The spatiotemporal variation in the NDVI over the Tibetan Plateau in the last 21 years and its response to different driving factors were investigated by using the Theil–Sen slope method, Mann–Kendall test, partial correlation analysis, and geographical detector method. The results showed that (1) the vegetation coverage on the Qinghai–Tibet Plateau showed an increasing trend from 1999 to 2019, with increases in approximately 67.00% of the plateau area. (2) The spatial differences in vegetation coverage were large; notably, low-density vegetation areas decreased obviously, moderate-density vegetation areas accounted for approximately 50% of the total area, high-density vegetation areas were the least common, and the overall growth rate was significant. (3) The NDVI was positively correlated with temperature and precipitation, and a positive correlation was observed in more than 66% of the region. (4) The order of the influence of single driving factors on the NDVI was as follows: precipitation > soil type > altitude > temperature > gradient > slope > population density > GDP. (5) The combined effect of the factors was significantly higher than that of single driving factors, with a notable nonlinear influence. The interactions between meteorological factors, such as precipitation, and topographic factors, such as altitude, were important, with a q-value over 0.79. The results of this study provide some methodological support for the ecological conservation of the Tibetan Plateau, and at the same time establish a scientific and reasonable strategy for vegetation restoration. Full article

Duzheng Ye (Tu-cheng Yeh) was an active member of Rossby’s Chicago School, one of the founders of modern meteorology in China since the 1950s, and a pioneer of global change science in China and over the world. His achievements have been central to the development of atmospheric and climate dynamics and global change studies in China, and many of them remain to be fundamental in the context of global climate change. In this review, his lifelong research career is divided into five periods: (1) the preparatory period (1935–1944); (2) the Chicago period (1945–1950); (3) the period of breaking ground (1950–1966); (4) the period of transition (1972–1983); and (5) the period of global change (1984–2013). The evolution of Yeh’s main achievements is described in the context of the historical background of both China and the world. These well-known achievements included the theory of energy dispersion in the atmosphere, the general circulation of the atmosphere (GCA) over East Asia and the globe, Qinghai–Tibetan Plateau meteorology, the scale-dependence theory of geostrophic adaptation (adjustment), and his pioneering ideas on global change. Special emphases are put on some of Yeh’s investigations that were well ahead of his time, such as his investigations on trade inversion, the GCA as an internally consistent whole, abrupt seasonal changes in the GCA, the physical mechanism of atmospheric blocking, and orderly human activities. Full article

Many extreme meteorological events are closely related to the strength of land–atmosphere interactions. In this study, the heat exchange regime between the shallow soil layer and the atmosphere over the Qinghai–Tibetan Plateau (QTP) was investigated using a reanalysis dataset. The analysis was conducted using a simple metric ΔT, defined as the difference between the temperatures of the shallow soil and the air. First, the performance of 4 widely used reanalysis data products (GLDAS-Noah, NCEP-R2, ERA5 and ERA5-land) in estimating ΔT on the QTP at soil depths of 0~7 or 0~10 cm was evaluated during the baseline period (1981–2010); the ERA5-land product was selected for subsequent analysis, because it yielded a better performance in estimating the annual and seasonal ΔT and finer spatial resolution than the other datasets. Using the soil temperature at depths of 0~7 cm and the air temperature at 2 m above the ground, as provided by the ERA5-Land reanalysis dataset, the entire QTP was found to be dominated by a positive ΔT both annually and seasonally during the baseline period, with large differences in the spatial distribution of the seasonal values of ΔT. From 1950 to 2021, the QTP experienced a significant decreasing trend in the annual ΔT at a rate of −0.07 °C/decade, and obvious decreases have also been detected at the seasonal level (except in spring). In the southern and northeastern parts of the QTP, rapid rates of decrease in the annual ΔT were detected, and the areas with significantly decreasing trends in ΔT were found to increase in size gradually from summer, through autumn, to winter. This study provides a holistic view of the spatiotemporal variations in ΔT on the QTP, and the findings can improve our understanding of the land–atmosphere thermal interactions in this region and provide important information pertaining to regional ecological diversity, hydrology, agricultural activity and infrastructural stability. Full article

Characterizing extreme precipitation precisely is crucial for predicting vegetation response to drought or storms. However, current precipitation generators in vegetation models do not simulate the occurrence and amount of extreme precipitation well. This study examined the effects of extreme precipitation on the skewness, kurtosis, and skewness–kurtosis interaction of annual precipitation distribution. The examination was based on theoretical calculations and monitoring data from 78 meteorological stations on the Qinghai–Tibetan Plateau (QTP). The results showed that extreme precipitation generally increased the skewness and kurtosis of annual precipitation distribution. A higher mean annual precipitation amplified the effects of precipitation extremes on promoting skewness and kurtosis in normal distribution scenarios. In contrast, these effects tended to be saturated for scenarios of higher mean annual precipitation in probability-based distributions. A reduction of dry days in a year markedly intensified the interaction of the skewness and the kurtosis, while the skewness–kurtosis interaction weakened with decreased maximum daily precipitation in a year. Moreover, the effect of extreme precipitation on the skewness–kurtosis interaction was stronger in arid or low-altitude areas. This study illustrates the fact that considering the skewness and kurtosis of annual precipitation distributions will be very helpful for simulating extreme precipitation on the QTP in the future. This will allow us to better understand the impact of climate change on alpine plants. Full article

The impact of environmental constraints on permafrost distribution and characteristics of the remote western Qinghai-Tibetan Plateau (QTP) were seldom reported. Using augmented Noah land surface model, this study aims to elaborate the permafrost characteristics and their relationship with key environmental constraints in the Gaize, a transitional area with mosaic distribution of permafrost and seasonally frozen ground in the western QTP. There were two soil parameter schemes, two thermal roughness schemes, and three vegetation parameter schemes with optimal minimum stomatal resistance established using MODIS NDVI, turbulent flux, and field survey data. Forcing data were extracted from the China Meteorological Forcing Dataset (CMFD) and downscaled to 5 km × 5 km resolution. Results show that the error of simulated mean annual ground temperatures (MAGT) were less than 1.0 °C for nine boreholes. The Kappa coefficiency between three types of permafrost and three types of vegetation is 0.654, which indicates the close relationship between the presence of certain vegetation types and the occurrence of certain permafrost types in the Gaize. Permafrost distribution and characteristics of the Gaize are jointly influenced by both altitude and vegetation. The relationship of permafrost with environmental constraints over the Gaize is significantly different from that of the West Kunlun, a western, predominantly permafrost-distributed area. Full article

Soil moisture dynamics play an active role in ecological and hydrological processes. Although the variation of the soil water moisture of multiple ecosystems have been well-documented, few studies have focused on soil hydrological properties by using a drying and weighing method in a long time series basis in the Qinghai-Tibet Plateau (QTP). In this study, 13 year (2008–2020) time-series observational soil moisture data and environmental factors were analyzed in a humid alpine Kobresia meadow on the Northern Qinghai–Tibetan Plateau. The results showed no significant upward trend in soil water content during the 2008–2020 period. In the growth season (May–October), the soil water content showed a trend of decreasing firstly, then increasing, and finally, decreasing. Correlation analysis revealed that five meteorology factors (temperature, humidity, net radiation, dew point temperature, and vapor pressure) and a biomass element (above-ground biomass) had a significant effect on the soil moisture, and air temperature impacted the soil water variation negatively in 0–50 cm, indicating that global warming would reduce soil moisture. Humidity and net radiation made a difference on shallow soil (0–10 cm), while dew point temperature and vapor pressure played a role on the deep soil (30–50 cm). Above-ground biomass only effected 30–50 cm soil moisture variation, and underground biomass had little effect on the soil moisture variation. This indirectly indicated that below-ground biomass is not limited by soil moisture. These results provide new insights for the rational allocation of water resources and management of vegetation in alpine meadows, in the context of climate change. Full article

The Tibetan Plateau (TP) is an important water source in Asia, and precipitation and evaporation patterns at different geographical and temporal scales play a significant role in managing water resource distribution. Based on quality control data from 87 meteorological stations, this study analyzed the spatial and temporal evolution patterns of precipitation and pan evaporation (Epan) on the TP in 1966–2016 using the Mann–Kendall test, the moving t-test, wavelet analysis, Sen’s slope method, and correlation analysis. The results revealed that the average mean temperature in the TP area increased by about 2.1 °C during the study period, and precipitation steadily increased at an average rate of 8.2 mm/10a, with summer and autumn precipitation making up about 80% of the year. In contrast, Epan showed an overall decreasing trend at a decline rate of 20.8 mm/10a, with spring and summer Epan values making up about 67% of the year. The time series of the precipitation and Epan within the TP region clearly exhibit nonstationary features. Precipitation is more concentrated in the southeast than in the northwest, while Epan is mostly concentrated in the southwest and northeast of the plateau around the Qaidam Basin. The “evaporation paradox” phenomenon was common in the TP region for about 40 years (1960s–1990s) and gradually faded in the 21st century. In addition, we introduced a standardized precipitation evaporation index (SPEI) to investigate the differences and relationships between precipitation and Epan time series over the past 50 years. The findings indicate that the southern Qinghai was dominated by an arid trend, while the central and southeast TP remained wet. Droughts and floods coexist in the eastern Qinghai and southern Tibet areas with high population concentrations, and the risk of both is rising as the inhomogeneity of precipitation distribution in the TP region will increase in the future. This study can be used as a reference for managing water resources and predicting regional drought and flood risk. Full article