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Unraveling the distribution patterns of near-surface temperature lapse rates in the Northwestern Kunlun Mountains 被引量:1

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摘要 The near-surface temperature lapse rates for the core area of the Kunlun Mountains remain critically unresolved due to data scarcity.Here,we revealed the spatial and temporal patterns of nearsurface temperature lapse rate in the Kunlun Mountain regions based on both long-term meteorological records(1961-2017)and field surveys measured data(2012-2017).The results showed that(1)The near-surface temperature lapse rates(β;)has spatiotemporal distribution patterns on the Northwestern Kunlun Mountains(NWKM),and in complex terrain areas the complexity of the temperature-elevation relationship cannot be explained by the constant environmental temperature lapse rate(0.65℃/100 m)throughout alone.(2)Theβ;for the daily mean,minimum,and maximum temperature on the north slopes in the Kunlun mountain area are 0.41,0.47,and 0.37℃/100 m and on the Tiznafu River(TR)basin are 0.51,0.47 and 0.53℃/100 m,respectively.(3)The variations ofβ;for daily maximum and minimum temperature of the two regions exhibit similar monthly characteristics,which are lower in the winter and spring months than in other months.A greatest variability ofβ;for the daily mean,minimum,and maximum temperature appears in winter and a light variability ofβ;occurs in spring.The seasonal variability ofβ;for daily maximum temperature is greater than that for daily minimum temperature,and the seasonal variability ofβ;for daily average temperature has the smallest variability.(4)There is no significant trend of change occurred in theβ;of NWKM.(5)The spatial and temporal variations ofβ;for the NWKM are linked to the geographic differences and climate factors.The results of Grey Relational Analysis showed that theβ;distribution is mainly influenced by the wind speed and relative humidity of the NWKM.
出处 《Journal of Mountain Science》 SCIE CSCD 2022年第4期1168-1181,共14页 山地科学学报(英文)
基金 supported by the National Natural Science Foundation of China(Grant No.41901022,41807445 and 41975010) the National Key Research and Development Program of China(Grant No.2021YFE0100700)。
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