observation data obtained in a mesoscale convective system are compared to Weather Research and Forecasting(WRF)model simulations using four microphysics schemes(Morrison,WSM6,P3,SBM)with different complexities.The ma...observation data obtained in a mesoscale convective system are compared to Weather Research and Forecasting(WRF)model simulations using four microphysics schemes(Morrison,WSM6,P3,SBM)with different complexities.The main purpose of this paper is to assess the performance of the microphysics ensemble in terms of cloud microphysical properties.Results show that although the vertical distributions of liquid water content(LWC)and ice water content(IWC)simulated by the four members are quite different in the convective cloud region,they are relatively uniform in the stratiform cloud region.Overall,the results of the Morrison scheme are very similar to the ensemble average,and both of them are closer to the observations compared to the other schemes.Besides,the authors also note that all members still overpredict the LWC by a factor of 2–8 in some regions,resulting in large deviation between the observation and ensemble average.展开更多
The cognition of low-carbon tourism among tourists is closely related to education level.In this study,the degree of coordination of low-carbon cognition with different educational levels is assessed by the coupling m...The cognition of low-carbon tourism among tourists is closely related to education level.In this study,the degree of coordination of low-carbon cognition with different educational levels is assessed by the coupling model in Wutai Mountain,and the effect of each factor on low-carbon cognition is analyzed by the geographical detector.The results show that:(1)The six cognition aspects of low-carbon tourism gradually transition from the level of intermediate coordination to good coordination with the advancement of the education level.Both the low-level and lower-level tourists belong to the lag type of low-carbon visiting cognition,and the higher-level tourists belong to the lag type of low-carbon shopping cognition,while the high-level tourists show the lag type of low-carbon food cognition.(2)According to the individual factors and interactive effects in the geographical detector,each impacting factor has a decisive effect on tourists’cognition of low-carbon tourism,and the effect of any two factors after interaction shows either a double-factor or nonlinear enhancement.The findings of this study provide valuable practical implications for helping tourism destinations to educate tourists and improve their low-carbon tourism options.At the same time,this study will provide theoretical standards for measuring tourists’cognition of low-carbon tourism,so as to enrich and improve the theoretical research related to low-carbon tourism.展开更多
基金supported by the National Key R&D Program of Chinagrant number 2018YFC1507900the Demonstration Project of Artificial Precipitation Enhancement and Hail Suppression Operation Technology at the Eastern Side of the Taihang Mountains grant number hbrywcsy-2017-2sponsored by the National Natural Science Foundation of China grant numbers 41530427 and 41875172。
文摘observation data obtained in a mesoscale convective system are compared to Weather Research and Forecasting(WRF)model simulations using four microphysics schemes(Morrison,WSM6,P3,SBM)with different complexities.The main purpose of this paper is to assess the performance of the microphysics ensemble in terms of cloud microphysical properties.Results show that although the vertical distributions of liquid water content(LWC)and ice water content(IWC)simulated by the four members are quite different in the convective cloud region,they are relatively uniform in the stratiform cloud region.Overall,the results of the Morrison scheme are very similar to the ensemble average,and both of them are closer to the observations compared to the other schemes.Besides,the authors also note that all members still overpredict the LWC by a factor of 2–8 in some regions,resulting in large deviation between the observation and ensemble average.
基金Supported by Program for the Philosophy and Social Sciences Research of Higher Learning Institutions of Shanxi(2023W064)。
文摘The cognition of low-carbon tourism among tourists is closely related to education level.In this study,the degree of coordination of low-carbon cognition with different educational levels is assessed by the coupling model in Wutai Mountain,and the effect of each factor on low-carbon cognition is analyzed by the geographical detector.The results show that:(1)The six cognition aspects of low-carbon tourism gradually transition from the level of intermediate coordination to good coordination with the advancement of the education level.Both the low-level and lower-level tourists belong to the lag type of low-carbon visiting cognition,and the higher-level tourists belong to the lag type of low-carbon shopping cognition,while the high-level tourists show the lag type of low-carbon food cognition.(2)According to the individual factors and interactive effects in the geographical detector,each impacting factor has a decisive effect on tourists’cognition of low-carbon tourism,and the effect of any two factors after interaction shows either a double-factor or nonlinear enhancement.The findings of this study provide valuable practical implications for helping tourism destinations to educate tourists and improve their low-carbon tourism options.At the same time,this study will provide theoretical standards for measuring tourists’cognition of low-carbon tourism,so as to enrich and improve the theoretical research related to low-carbon tourism.
