To identify the atmospheric controls of the summertime glacier surface energy balance in the Himalayas, in situ meteorological data collected at 6,523 m above sea level during May–July 2005 were obtained and analyzed. Our results showed that net shortwave radiation (103 W m⁻²) and turbulent sensible heat flux (12 W m⁻²) acted as energy sources, and net longwave radiation (−62 W m⁻²) and turbulent latent heat flux (−20 W m⁻²) represented heat sinks. Cloud cover controlled the summer surface energy balance. During the active period of the South Asian Summer Monsoon, the frequent cloud coverage increased the incoming longwave radiation more than it decreased the incident solar radiation. Intensification (weakening) of the South Asian Summer Monsoon strengthened (suppressed) surface melting. The melt energy measured during the nonmonsoon period was small due to the energy consumption associated with glacier volume warming, energy loss from sublimation, and large heat loss through net longwave radiation due to the low amount of incoming longwave radiation caused by the low cloudiness. The comparison of glacier surface energy balances on the Tibetan Plateau shows that on continental glaciers, net radiation is lower and accounts for a smaller contribution to energy sources, and the dominant energy sinks are sublimation and evaporation, rather than melting, which is the primary energy sink for maritime/subcontinental glaciers. This implies an important spatial variability in glacial sensitivity to different climatic conditions on the Tibetan Plateau.

The Qinghai–Tibet Plateau (QTP), also known as the Third Pole of the Earth, is sensitive to climate change, and it has become a hotspot area for research. As a typical natural ecosystem on the QTP, alpine wetlands are particularly sensitive to climate change. The identification of different types of alpine wetland and analysis of changes in their distributions and areas are the most direct indicators for characterizing the impact of climate change on wetlands. To understand the dynamic change process of the alpine wetlands in the QTP and their responses to climate change, the Maqu wetlands, located at the source of the Three Rivers in the eastern part of the QTP, was taken as an example; the Google Earth Engine (GEE) remote sensing cloud platform and long-term dense Landsat time series data from 1990 to 2020 were used to map the annual wetland classification and to analyze the evolution characteristics of the wetlands and their driving forces. The results revealed that (1) based on dense Landsat time series data, different alpine wetland types can be effectively distinguished, including swamp, swamp meadow, and wet meadow. (2) From 1990 to 2020, the area of the Maqu wetlands exhibited an overall fluctuating decrease, with the total area decreasing by about 23.35%, among which the swamp area decreased the most (by 27.15%). The overall type of change was from wet to dry. All of the types of wetlands were concentrated between 3400 and 3600 m above sea level, and the reduction in the wetland area was concentrated on slopes < 3°, with the greatest loss of wetland area occurring on shady slopes. (3) The driving forces of the changes in the wetlands were predominantly temperature and precipitation, and the greatest correlation was between the total wetland area and the growing season temperature. The results of this study provide valuable information for the conservation of alpine wetlands.

With the support of the Chinese National Antarctic Research Expedition, near-surface ozone (O₃) was continuously monitored at Zhongshan Station (ZOS) (69°22′12″ S, 76°21′49″ E, 18.5 m above sea level) in East Antarctica from 2008 to 2020. The seasonal and diurnal variability of near-surface O₃ at ZOS were investigated. O₃ enhancement events (OEEs) were frequently observed in the warm season (OEEs in January accounted for 23.0% of all OEEs). The OEEs at ZOS were related to the photochemical reaction processes under the influences of O₃ and solar radiation in the stratosphere and synoptic-scale air mass transport from coastal areas (Princess Elizabeth Land, Wilkes Land, and Queen Mary Land), as evidenced by the recorded wind speed, solar shortwave irradiance, and total column ozone data and the computed potential source contribution function and concentration-weighted trajectory models. The results computed by the tool Stratosphere-to-Troposphere Exchange Flux indicated that stratosphere-to-troposphere transport had no direct impact on OEEs at ZOS. Therefore, synoptic-scale air mass transport is the main cause of OEEs in Antarctica, which is consistent with previous studies. Unlike OEEs at inland Antarctic stations, which are mainly affected by air mass transport from inland plateaus, OEEs at ZOS, a coastal station, are mainly affected by air mass transport from coastal land in East Antarctica.

Introduction: As a vital component of the ecosystem of the Qinghai-Tibet Plateau, alpine wetlands coexist with their vulnerability, sensitivity, and abundant biodiversity, propelling the material cycle and energy flux of the entire plateau ecosystem. In recent decades, climate change and human activities have significantly altered the regional landscape. Monitoring and assessing changes in the alpine wetlands on the Qinghai-Tibet Plateau requires the efficient and accurate collection of long-term information.Methods: Here, we interpreted the remote sensing data of the first meander of the Yellow River of alpine wetlands from 1990 to 2020 based on Google Earth Engine (GEE) platform, using geographic information system (GIS) and landscape pattern index to analyze the spatial and temporal evolution of wetland landscape patterns, and the primary drivers of changes in wetland area were explored by GeoDetector.Results: Our result showed that most wetland areas were found in regions with gradients less than 12° and elevations between 3315 and 3600 m. From 1990 to 2010, the area of alpine wetland in the study area decreased by 25.43%. During the period between 2010 and 2020 to the 1990s, the wetland area decreased by 322.9 km². Conversion to and from grassland was the primary form of wetland transfer out and in, respectively. The overall migration of the wetland centroid in the study area was to the southwest between 1990 and 2010 and to the north between 2010 and 2020. The geometry of the wetland landscape was relatively simple, the landscape was relatively intact, and patches retained a high level of agglomeration and connectivity. However, their level of agglomeration and connectivity was disrupted. A quantitative analysis of the factor detector in GeoDetector revealed that the DEM, slope, and evaporation were the most important driving factors influencing the change of wetland area, with socioeconomic development also influencing changes in the wetland area to a lesser extent.Discussion: Using interaction detectors, it was discovered that the interaction of various driving factors could better explain the long-term variations in wetland areas, with a greater degree of explanation than that of each driving factor alone.