Abstract
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.
Highlights
As an important weather phenomenon, precipitation affects the energy and mass cycles in nature via its different types
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
We proposed that high relative humidity and low freezing levels were the likely reasons for the ERA5 reanalysis datasets
Summary
As an important weather phenomenon, precipitation affects the energy and mass cycles in nature via its different types (snow, rain, and sleet). Many studies have addressed the precipitation features of mainly middle to high-latitude regions (Bourgouin, 2000; Dai, 2001; Sims and Liu, 2015). To better identify the precipitation type, many studies have proposed relatively accurate parameterized models (Hux et al, 2001; Thériault et al, 2012; Ikeda et al, 2013). By using weather reports from land stations and ships, Liu (2008) calculated the conditional probability of snow precipitation as a function of the surface air temperature and found that a 50% probability occurred at an air temperature of approximately 2°C. In similar work by Dai (2008), who proposed a hyperbolic tangent parameterized model, the temperature thresholds over land areas (1.2°C) and oceans (1.9°C) were obtained based on observational records from 1977 to 2007
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