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Analysis of precipitation characteristics during the vegetation growth season in the Urumqi River Basin in arid region of northwest China
XING Hongyan, HE Qing, PU Zongchao, WANG Guosheng, JIN Chen
Journal of Arid Meteorology    2023, 41 (1): 34-42.   DOI: 10.11755/j.issn.1006-7639(2023)-01-0034
Abstract356)   HTML13)    PDF(pc) (12685KB)(756)       Save

Based on the daily precipitation data of 7 national meteorological stations and 20 automatic meteorological stations in the Urumqi River Basin during the vegetation growth season from May to September) from 2013 to 2021, the variation characteristics of precipitation, precipitation days, precipitation with different levels and their contribution rates to total precipitation with altitude are analyzed. It is expected to provide some references for water resources utilization, eco-environmental treatment and protection in the basin. The results show that both precipitation and precipitation days in the Urumqi River Basin presented a fluctuating and increasing trend with elevation at a rate of 17.4 mm·(100 m)-1 and 2.85 d·(100 m)-1, respectively, and the dependence on altitude changed from weak to strong with an altitude of about 1 000 m as a boundary. The high precipitation zones appear in the elevation about 1 200 m and 2 000 m and show a rule of gradual rise from the lower mountain area to the mid-alpine zone and then fall back. The high values of precipitation days are stability and always in the mid-alpine zone (above 1 800 m). The monthly variation characteristics of precipitation days and precipitation in the vegetation growth season are in good agreement, and both are increasing with elevation. In areas below 2 200 m, precipitation in June and precipitation days in July increased most significantly with elevation at a rate of 4.8 mm·(100 m)-1 and 0.72 d·(100 m)-1, and in September the increasing rate of both are 1.1 mm·(100 m)-1 and 0.37 d·(100 m)-1, respectively. The occurring times of light moderate and heavy rainfall in the growth season of vegetation is strongly altitude-dependent and the contribution rate of precipitation with different levels is not significantly correlated with altitude.

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Research on Snow Surface Temperature Forecast Modelover the Xiaohaituo Mountain Area, Beijing
LI Chen, WU Jin, GUO Wenli, JIN Chenxi, QI Chen
Journal of Arid Meteorology    2021, 39 (4): 687-696.  
Abstract279)      PDF(pc) (5414KB)(1374)       Save

Abstract: Based on the hourly meteorological observations at Erhaituo station with high altitude and Changchonggou station with low altitude in the Xiaohaituo mountain area of Yanqing, Beijing from October 2019 to March 2020, the characteristics of snow surface temperature and its correlation with meteorological factors were analyzed. The forecast models of snow surface temperature of two stations were established and tested by using neural networks and stepwise regression methods. The results are as follows: (1) The hourly variation of snow surface temperature during snow cover period in the Xiaohaituo mountain area was obviously stronger than that of air temperature, air temperature and total solar radiation were positively correlated with snow surface temperature and were the main factors causing the change of snow surface temperature. (2) The performance of snow surface temperature forecast model based on neural network method was superior to the one based on stepwise regression method, the model forecast effect at low altitude station was better than that at high altitude station, and the model forecast effect in the daytime was better than that during nighttime. (3) The model established by distinguishing daytime and nighttime was more suitable for the low altitude station.


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