The largest glacier area outside the Arctic and Antarctic is found on the Tibetan Plateau and its surrounding regions (TP) (Xu et al., 2009). These glaciers are located at the headwaters of many prominent Asian rivers (e.g., Ganges, Indus, Brahmaputra, and Yangtze), which supply water for billions of people living downstream (

Using automatic weather station and reanalysis data (ERA5) from 2011 at Panda-1 Station, situated in the katabatic region of Princess Elizabeth Land, East Antarctica, the surface energy balance was calculated using a surface temperature iteration method, and the characteristics of each energy component were analyzed. Downward shortwave and longwave radiation were the two primary energy sources during summer days with seasonal means of 346 and 142 W m −2 . The turbulent fluxes of sensible and latent heat flux represent smaller heat sources. In the annual mean, reflected shortwave radiation exceeds the upward longwave radiation with a seasonal average values of −287 W m −2 . During winter, the shortwave radiation is small, and the main energy input and output terms of the surface energy balance are downward and upward longwave radiation, with seasonal average values of 149 and −159 W m −2 , respectively. The combination of high wind speed and a large near-surface humidity gradient during summer resulted in significant frost depositional events. The total surface frost deposition for the whole year was 24 kg m −2 , which accounted for 61% of the total accumulation (averaged over 10 years). When a high-pressure ridge blocks cyclones and deflects fronts of low-pressure systems to inland East Antarctica during winter, this has a significant impact on the surface energy balance at Panda 1 automatic weather station, with daily sensible and latent heat fluxes increasing by as much as 25 and 12 W m −2 , respectively. These results still contain uncertainties as we only address a single year, when interannual variability may be considerable, and we do not consider drifting snow sublimation.

Abstract. This paper introduces a unique multiyear dataset and the monitoring capability of the PANDA automatic weather station network which includes eleven automatic weather stations (AWS) across Prydz Bay-Amery Ice Shelf-dome area from the coast to the summit of the East Antarctica ice sheet. The ~1460 km transect from Zhongshan to Panda S station follows roughly along ~77° E longitude and covers all geographic and climatic units of East Antarctica. Initial inland observation, near the coast, started in the 1996/1997 austral summer. All AWSs in this network measure air temperature, relative humidity, air pressure, wind speed and wind direction at 1-hour intervals, and some of them can also measure firn temperature and shortwave/longwave radiation. Data are relayed in near real-time via the ARGOS system. Data quality is generally very reliable and the data have been used widely. In this paper, we firstly present a detailed overview of the AWSs, including the sensor characteristics, installation procedure, data quality control protocol, and the basic analysis of each variable. We then give an example of a short-term atmospheric event that shows the monitoring capacity of the network. This dataset, which is publicly available, is planned to be updated on a near-real time and should be valuable for climate change estimation, extreme weather events diagnosis, data assimilation, weather forecasting, etc. The dataset is available at https://doi.org/10.11888/Atmos.tpdc.272721 (Ding et al., 2022).

Under the effect of global warming, more precipitation will shift to rainfall in cryospheric regions. Considering the influence of the precipitation type on surface energy and mass cycles, it is important to determine the specific precipitation features and to classify the precipitation type in key areas correctly. We analyzed the monthly distribution, variations in each precipitation type’s annual days, and trends based on daily precipitation and air temperature observations from six tripolar stations. The results indicated that snow dominated the precipitation type at Zhongshan station (69.4°S, 76.4°E) throughout the year, while the Greatwall station (62.2°S, 59.0°W) exhibited a relatively diverse precipitation type distribution and significant seasonal cycles. Compared to the Greatwall station, every precipitation type was less frequently encountered at the Barrow (71.3°N, 156.8°W), Coral Harbour (64.2°N, 83.4°W), Linzhi (29.6°N, 94.5°E), and Maqu stations (34°N, 102.1°E), in which all the sites demonstrated classical reverse seasonal variation. A consistent trend across the years was found regarding the trends of the different precipitation types, except at the Greatwall and Coral Harbour stations. Due to snow/rain conditions partly converting into sleet conditions, which may be related to air temperature changes and synoptic atmospheric activities, inconsistent increasing trends of the sleet days were observed compared to the snow/rain days. Furthermore, a hyperbolic parameterized model was also fitted to determine the air temperature threshold of precipitation type transitions in this paper. According to the threshold comparison results, a warm bias in the temperature threshold was found at the warm stations. We also proposed that high relative humidity and low freezing levels were the likely reasons for the ERA5 reanalysis datasets. Finally, this paper’s fitted parameterized model was proven to perform better than the ERA5 reanalysis datasets through validation. This preliminary research provides observational evidence and possible interpretation of the mechanism of precipitation type changes in tripolar areas.

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