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As the highest and most extensive plateau on earth, the Tibetan Plateau has strong thermo-dynamic effect, which not only affects regional climate around the plateau but also temperature and precipitation patterns of itself. However, due to scattered meteorological stations, its spatial precipitation pattern and, especially, the mechanism behind are poorly understood. The availability of spatially consistent satellite-derived precipitation data makes it possible to get accurate precipitation pattern in the plateau, which could help quantitatively explore the effect and mechanism of mass elevation effect on precipitation pattern. This paper made full use of TMPA 3B43 V7 monthly precipitation data to track the trajectory of precipitation and identified four routes (east, southeast, south, west directions) along which moisture-laden air masses move into the plateau. We made the assumption that precipitation pattern is the result interplay of these four moisture-laden air masses transportation routes against the distances from moisture sources and the topographic barriers along the routes. To do so, we developed a multivariate linear regression model with the spatial distribution of annual mean precipitation as the dependent variable and the topographical barriers to these four moisture sources as independent variables. The result shows that our model could explain about 70% of spatial variation of mean annual precipitation pattern in the plateau; the regression analysis also shows that the southeast moisture source (the Bay of Bengal) contributes the most (32.56%) to the rainfall pattern of the plateau; the east and the south sources have nearly the same contribution, 23.59% and 23.48%, respectively; while the west source contributes the least, only 20.37%. The findings of this study can greatly improve our understanding of mass elevation effect on spatial precipitation pattern.

Alpine treeline, as a prominent ecological boundary between forested mountain slopes and alpine meadow/shrub, is highly complex in altitudinal distribution and sensitive to warming climate. Great efforts have been made to explore their distribution patterns and ecological mechanisms that determine these patterns for more than 100 years, and quite a number of geographical and ecophysiological models have been developed to correlate treeline altitude with latitude or a latitude related temperature. However, on a global scale, all of these models have great difficulties to accurately predict treeline elevation due to the extreme diversity of treeline site conditions. One of the major reasons is that “mass elevation effect” (MEE) has not been quantified globally and related with global treeline elevations although it has been observed and its effect on treeline elevations in the Eurasian continent and Northern Hemisphere recognized. In this study, we collected and compiled a total of 594 treeline sites all over the world from literatures, and explored how MEE affects global treeline elevation by developing a ternary linear regression model with intra-mountain base elevation (IMBE, as a proxy of MEE), latitude and continentality as independent variables. The results indicated that IMBE, latitude and continentality together could explain 92% of global treeline elevation variability, and that IMBE contributes the most (52.2%), latitude the second (40%) and continentality the least (7.8%) to the altitudinal distribution of global treelines. In the Northern Hemisphere, the three factors’ contributions amount to 50.4%, 45.9% and 3.7% respectively; in the south hemisphere, their contributions are 38.3%, 53%, and 8.7%, respectively. This indicates that MEE, virtually the heating effect of macro-landforms, is actually the most significant factor for the altitudinal distribution of treelines across the globe, and that latitude is relatively more significant for treeline elevation in the Southern Hemisphere probably due to fewer macro-landforms there.

Slope aspect has significant effect on the development and distribution of montane forest, especially in arid and semiarid regions. This paper, using SPOT5 images and 1:50,000 DEM, digitally extracts and analyzes the spatial information of montane coniferous forest (mainly Qinghai spruce), and thereby explores how the upper and lower limits and the altitudinal range of coniferous forest vary and how the area of coniferous forest is related with annual insolation with all aspects in the Helan Mountains. The results show that: 1) In the eastern flank, the lower limit of coniferous forest is between 1,600 m and 2,000 m a.s.l., and the upper limit between 2,800 m and 3,000 m a.s.l.; in the western flank, the lower limit of coniferous forest is between 2,000 m and 2,300 m a.s.l., and the upper limit between 2,800 m and 3,100 m a.s.l. 2) The altitudinal ranges of coniferous forest are 806~1,435 m, 438~1,140 m for eastern flank and western flank, respectively. 3) The area of coniferous forest takes on a normal distribution with aspect, and it has a close relationship with annual insolation. This distribution model developed in this paper quantitatively reveals the significant effect of slope aspect on the distribution of coniferous forest in arid and semi-arid land.