Based on the Monin-Obulchov similarity theory, a scheme was developed to calculate surface roughness length. Surface roughness length over the eastern Qinghai-Tibetan Plateau during the winter season was then estimate...Based on the Monin-Obulchov similarity theory, a scheme was developed to calculate surface roughness length. Surface roughness length over the eastern Qinghai-Tibetan Plateau during the winter season was then estimated using the scheme and eddy covariance measurement data. Comparisons of estimated and measured wind speeds show that the scheme is feasible to calculate surface roughness length. The estimated roughness lengths at the measurement site during unfrozen, frozen and melted periods are 3.23x10(-3), 2.27x10(-3) and 1.92x10(-3) m, respectively. Surface roughness length demonstrates a deceasing trend with time during the winter season. Thereby, setting the roughness length to be a constant value in numerical models could lead to certain degree of simulation errors. The variation of surface roughness length may be caused by the change in land surface characteristic.展开更多
利用昆明站1991-2020年近30年逐日降水数据计算昆明雨季(5-10月)的起止时期,进一步确定昆明市雨季的长短。又基于云南省和昆明市的统计年鉴数据,使用年末总人口、城市建成区面积、城镇化率、人均GDP等城市发展因子确定昆明的城市发展进...利用昆明站1991-2020年近30年逐日降水数据计算昆明雨季(5-10月)的起止时期,进一步确定昆明市雨季的长短。又基于云南省和昆明市的统计年鉴数据,使用年末总人口、城市建成区面积、城镇化率、人均GDP等城市发展因子确定昆明的城市发展进程,将昆明市的城市发展进程划分为缓慢发展期(1991-2003年)和快速发展期(2004-2020年),进而分析比较两段时期中昆明市雨季长短的特征和差异,采用统计分析、小波分析和M-K突变检验等综合分析方法,系统分析了昆明市雨季长短的时间变化特征,并用灰色关联度分析方法分析了昆明市雨季长短与城市发展的关联性。结果表明,1991-2020年昆明市的雨季开始日呈逐渐偏晚的趋势,而雨季结束日呈逐渐偏早的趋势,总体上雨季长度呈逐渐缩短的趋势;小波系数分析结果显示,在8年以下的时间尺度上,昆明市雨季长短变化的周期不存在明显的规律性,在17年时间尺度上的周期变化明显,呈偏短-偏长-偏短-偏长-偏短的5个循环交替,2003-2008年、 2014-2017年雨季增长,1991-2002年、 2009-2012年、 2018-2020年雨季缩短,2018-2020年等值线未闭合说明还有进一步缩短的趋势。通过M-K检验表明昆明市的雨季长短在1991-2020年间出现4次突变,分别发生在2002年、 2008年、 2012年和2017年。从昆明城市发展与雨季长短的关系来看,昆明城市发展缓慢期的雨季长短的变化趋势较为平稳,而城市发展快速期2004年以后,昆明市雨季长度缩短的变化明显,并随着城市发展进程的加快其极端波动性更加明显。运用SPSS(Statistical Product and Service Solutions)软件对未来10年昆明的雨季长短进行预测,结果显示未来10年昆明雨季长短将持续偏短的趋势。在灰色关联度分辨率为0.5时,表征城市发展进程的4个因子对昆明雨季长短变化均产生不同程度影响,其关联度系数都在0.70以上,表明昆明城市发展与雨季长短显著关联性,其中影响最大的因子是年末总人口,最小为人均GDP,灰色关联度分别为0.88和0.70,属于高度关联和显著关联。对4个因子的关联系数进行排序为:年末总人口>城镇化率>城市建成区面积>人均GDP。展开更多
Lakes regulate the water and heat exchange between the ground and the atmosphere on different temporal and spatial scales. However, studies of the lake effect in the high-altitude Tibetan Plateau(TP) rarely have been ...Lakes regulate the water and heat exchange between the ground and the atmosphere on different temporal and spatial scales. However, studies of the lake effect in the high-altitude Tibetan Plateau(TP) rarely have been performed until recently, and little attention has been paid to modelling of frozen lakes. In this study, the Weather Research and Forecasting Model(WRF v. 3.6.1) is employed to conduct three numerical experiments in the Ngoring Lake Basin(the original experiment, an experiment with a tuned model, and a no-lake experiment) to investigate the influences of parameter optimization on the lake simulation and of the high-altitude lake on the regional climate. After the lake depth, the roughness lengths, and initial surface temperature are corrected in the model, the simulation of the air temperature is distinctly improved. In the experiment using a tuned model, the simulated sensible-heat flux(H) is clearly improved, especially during periods of ice melting(from late spring to early summer) and freezing(late fall). The improvement of latent-heat flux(LE) is mainly manifested by the sharp increase in the correlation coefficient between simulation and observation, whereas the improvement in the average value is small. The optimization of initial surface temperature shows the most prominent effect in the first year and distinctly weakens after a freezing period. After the lakes become grassland in the model, the daytime temperature clearly increases during the freezing and melting periods; but the nocturnal cooling appears in other stages, especially from September to October. The annual mean H increases by 6.4 times in the regions of the Ngoring Lake and the Gyaring Lake, and the LE declines by 56.2%. The sum of H and LE increases from 71.2 W/m2(with lake) to 84.6 W/m2(no lake). For the entire simulation region, the sum of H and LE also increases slightly. After the lakes are removed, the air temperature increases significantly from June to September over the area corresponding to the two lakes, and an abnormal convergence field appears; at the same time, the precipitation clearly increases over the two lakes and surrounding areas.展开更多
基金supported by the National Natural Science Foundation of China (41275016, 41405016, 41205006, 41275014, 41375077, 91537104, and 91537106)
文摘Based on the Monin-Obulchov similarity theory, a scheme was developed to calculate surface roughness length. Surface roughness length over the eastern Qinghai-Tibetan Plateau during the winter season was then estimated using the scheme and eddy covariance measurement data. Comparisons of estimated and measured wind speeds show that the scheme is feasible to calculate surface roughness length. The estimated roughness lengths at the measurement site during unfrozen, frozen and melted periods are 3.23x10(-3), 2.27x10(-3) and 1.92x10(-3) m, respectively. Surface roughness length demonstrates a deceasing trend with time during the winter season. Thereby, setting the roughness length to be a constant value in numerical models could lead to certain degree of simulation errors. The variation of surface roughness length may be caused by the change in land surface characteristic.
文摘利用昆明站1991-2020年近30年逐日降水数据计算昆明雨季(5-10月)的起止时期,进一步确定昆明市雨季的长短。又基于云南省和昆明市的统计年鉴数据,使用年末总人口、城市建成区面积、城镇化率、人均GDP等城市发展因子确定昆明的城市发展进程,将昆明市的城市发展进程划分为缓慢发展期(1991-2003年)和快速发展期(2004-2020年),进而分析比较两段时期中昆明市雨季长短的特征和差异,采用统计分析、小波分析和M-K突变检验等综合分析方法,系统分析了昆明市雨季长短的时间变化特征,并用灰色关联度分析方法分析了昆明市雨季长短与城市发展的关联性。结果表明,1991-2020年昆明市的雨季开始日呈逐渐偏晚的趋势,而雨季结束日呈逐渐偏早的趋势,总体上雨季长度呈逐渐缩短的趋势;小波系数分析结果显示,在8年以下的时间尺度上,昆明市雨季长短变化的周期不存在明显的规律性,在17年时间尺度上的周期变化明显,呈偏短-偏长-偏短-偏长-偏短的5个循环交替,2003-2008年、 2014-2017年雨季增长,1991-2002年、 2009-2012年、 2018-2020年雨季缩短,2018-2020年等值线未闭合说明还有进一步缩短的趋势。通过M-K检验表明昆明市的雨季长短在1991-2020年间出现4次突变,分别发生在2002年、 2008年、 2012年和2017年。从昆明城市发展与雨季长短的关系来看,昆明城市发展缓慢期的雨季长短的变化趋势较为平稳,而城市发展快速期2004年以后,昆明市雨季长度缩短的变化明显,并随着城市发展进程的加快其极端波动性更加明显。运用SPSS(Statistical Product and Service Solutions)软件对未来10年昆明的雨季长短进行预测,结果显示未来10年昆明雨季长短将持续偏短的趋势。在灰色关联度分辨率为0.5时,表征城市发展进程的4个因子对昆明雨季长短变化均产生不同程度影响,其关联度系数都在0.70以上,表明昆明城市发展与雨季长短显著关联性,其中影响最大的因子是年末总人口,最小为人均GDP,灰色关联度分别为0.88和0.70,属于高度关联和显著关联。对4个因子的关联系数进行排序为:年末总人口>城镇化率>城市建成区面积>人均GDP。
基金supported by the National Natural Science Foundation of China (Nos. 91637107, 41605011, 41675020, 91537214 and 41775016)Sino-German Research Project (No. GZ1259)the Science and Technology Service Network Initiative of CAREERI, Chinese Academy of Sciences (No. 651671001)
文摘Lakes regulate the water and heat exchange between the ground and the atmosphere on different temporal and spatial scales. However, studies of the lake effect in the high-altitude Tibetan Plateau(TP) rarely have been performed until recently, and little attention has been paid to modelling of frozen lakes. In this study, the Weather Research and Forecasting Model(WRF v. 3.6.1) is employed to conduct three numerical experiments in the Ngoring Lake Basin(the original experiment, an experiment with a tuned model, and a no-lake experiment) to investigate the influences of parameter optimization on the lake simulation and of the high-altitude lake on the regional climate. After the lake depth, the roughness lengths, and initial surface temperature are corrected in the model, the simulation of the air temperature is distinctly improved. In the experiment using a tuned model, the simulated sensible-heat flux(H) is clearly improved, especially during periods of ice melting(from late spring to early summer) and freezing(late fall). The improvement of latent-heat flux(LE) is mainly manifested by the sharp increase in the correlation coefficient between simulation and observation, whereas the improvement in the average value is small. The optimization of initial surface temperature shows the most prominent effect in the first year and distinctly weakens after a freezing period. After the lakes become grassland in the model, the daytime temperature clearly increases during the freezing and melting periods; but the nocturnal cooling appears in other stages, especially from September to October. The annual mean H increases by 6.4 times in the regions of the Ngoring Lake and the Gyaring Lake, and the LE declines by 56.2%. The sum of H and LE increases from 71.2 W/m2(with lake) to 84.6 W/m2(no lake). For the entire simulation region, the sum of H and LE also increases slightly. After the lakes are removed, the air temperature increases significantly from June to September over the area corresponding to the two lakes, and an abnormal convergence field appears; at the same time, the precipitation clearly increases over the two lakes and surrounding areas.
